I take this seriously; we’ve all lost loved ones to this condition. The best check on my reasoning would be an objective measure of the health of American democracy. There are several “democracy indices” that purport to do this, but they have a mixed reputation. My impression is that most current accusations of bias are relatively weak - I agree with Claude’s analysis here - but they rely enough on “expert” opinion that I don’t expect them to convince a skeptic.

The newest entrant in this space - Metaculus Democracy Threat Index - works differently, and deserves a closer look.

Metaculus is a prediction site - like a prediction market, except that no money changes hands. People can record their guesses for how future events will turn out, which get aggregated by an algorithm (currently just a recency-weighted median, although they’ve done fanicer things in the past).

Their Democracy Threat Index is a collection of 153 questions relevant to US democracy. For example:

This question says there’s a 3.5% chance that a political party will keep an opponent off the ballot in a state election in 2026. You can see that 86 people have made forecasts about this. When probabilities like this go up on the 153 questions, the index gets higher.

This has some advantages over traditional democracy index design. It’s transparent: you can see all the questions and how they fit together. It’s crowdsourced, so there’s limited opportunity for ideologues or biased experts to put their fingers on the scale. It does a good job limiting itself to things which naturally seem democracy-related, resisting the pressure to add “and they support my preferred policy” to the definition of democracy.

But the biggest change is that Metaculus leverages modern forecasting science (popularly called “superforecasting” - although I think the people with that trademark would be unhappy to hear me use it this way). Does this help?

We care most about questions like “Did they cancel elections?” or “Did they murder protesters?” But these are coarse binary outcomes - when someone wants to know if democracy is “under threat”, they want to know when there’s increased chance of these things happening, even though they haven’t happened yet. As a forecasting platform, Metaculus can distinguish not just between “keeps elections” vs. “cancels elections”, but between 10% chance of cancelling the next elections vs. 50% chance. This both lets them focus on the big questions (rather than the small questions that are most likely to differ between one mildly-concerning regime and another) and give finer-grained estimates (a 10% vs. 50% chance of elections getting cancelled, rather than just ‘not cancelled yet’).

What are the remaining risks/biases?

• Susceptibility to crowd attack: If a hundred Democrats join Metaculus and give maximally pessimistic answers to all democracy-related questions, would that make Trump look worse? Currently Metaculus has near-perfect security through obscurity - nobody cares about this index enough to attack it. I asked them what happened if that changed, and they said they had good security, and that medians are naturally more secure than means to this kind of threat. I’m still disappointed to have to rely on the security of one centralized site.

These problems could be solved by transitioning from Metaculus to a true prediction market. Prediction markets’ main advantage over Metaculus-style forecasting engines is resilience to attack (because new bettors are incentivized to come take the attacker’s money). Unfortunately right now Metaculus is focusing on being a responsible academic institution, and prediction markets are focusing on attracting sports-gambling-obsessed degens, so we’ll have to settle for the former.

That still leaves one possible source of risk:

• Susceptibility to question selector bias: Who decides which questions get added to the Index? Right now, it’s a “nonpartisan group” called Bright Line Watch. Are they really nonpartisan? You can see some discussion here, but even if we trust them, it’s disappointing that the question of trust has to come up at all, given the otherwise-trustless design.

I thought about this most when seeing the question about whether government departments will change policy in response to bribes, which mentions as a possible bribe vector an “expenditure to a cryptocurrency” - for example, some high official creates a crypto token, and the would-be-bribe-giver buys into it. Democrats and Republicans are corrupt in different ways, and privileging memecoin buyers is so far a uniquely Republican form of corruption. If they’d missed that vector, the bribery question would have been biased toward finding corruption in Democrats (who so far haven’t use memecoins as much). But how chould we prove that they didn’t include that vector specifically because they searched very hard for Republican-coded forms of bribery and made sure to include them, while thinking less hard about Democrat-coded forms? Are they allowed to use their judgment and say that there seem to be more things like this on one side of the aisle than the other?

Maybe it would be safer to stick to really obvious questions like “will they cancel elections?” But even this might be subjective - maybe Republicans are more likely to cancel elections, but Democrats are more likely to censor speech. Is censoring speech as much of a “threat to democracy” as canceling elections? Hard to say.

As far as I can tell, questions like these make it hard to conclude anything from the index’s “historical backfilling”:

That is: the index was started in 2025. The 2021-2022 and 2023-2024 data points come from retrospectively checking how many of the questions they invented in 2025 had already happened by 2021-2022 etc. There are many reasons it could be fewer besides declining democracy. For example, it might have been boring to start with questions that had already happened. Conversely, it could be especially exciting to consider new (as of 2025) threats to democracy like memecoin corruption.

On the other hand, as far as I can tell the third and fourth data points - the squares - are pretty believable. These represent forecasters’ opinions when the index was first formed, and their forecasts about what will be true two years later. They seem to expect that democracy as measured by these questions won’t get any worse over the remainder of Trump’s term - which I find reassuring.

Here’s another interesting graph:

The expected index level for 2027-2028 over time. We see that concerns about democracy peaked in November/December 2025, when the expected value of the index was 47%. Then they started declining in mid-December, and are currently stable at 39%. What changed? Maybe the results of various November special elections (both the elections going without a hitch, and Trump’s preferred candidates losing), or the failure of a grand jury to indict Trump opponent Letitia James in a trial widely perceived as politicized. I respect this graph for telling me a non-obvious thing (the level of predicted threat to democracy decreased in December 2025) that makes some sense in retrospect.

As time goes on, the Index will become more valuable insofar as it gets further from any possibility of biasing the questions. That is: any biases in the question set are the biases of 2025, when (for example) Republicans are more into memecoin-based corruption than Democrats. But as time goes on, the biases will drift - the biases of 2035 will be correlated <1 with the biases of 2025 (for example, Democrats might take up memecoin-based corruption, or Republicans might drop it) and as long as the question set is stable, biased question-selectors can’t optimize it for the most up-to-date biases.

Suppose that the 2028 election is Newsom vs. Vance, and that each party claims the other’s nominee will destroy democracy. We could have a conditional prediction market - what will the Democracy Index be in 2032 conditional on Vance/Newsom getting elected? Or we could just watch how the Democracy Index responds to shocks in election outcome percentages: for example, if Newsom has a bad debate and his chances drop 5% on Polymarket, does that drive the Democracy Index up or down?

What would we need to make this really work? My wish list looks like:

• Duplicates of some of these questions on Polymarket and Kalshi, as a backup against attacks on Metaculus.

• More thought put into the questions, including a policy on how new questions will (or won’t) be added.

• More forecasters, and existing forecasters adjusting their guesses more often. There’s now $10,000 in prize money on the line, so consider participating!

Isn’t this crazy? Whole-body screening can save lives by detecting serious diseases like cancer. The experts counterargue that it finds so many false positives - minor zit-like imperfections that would never have caused problems, but which cost patients time, money, anxiety, and side effect burden to investigate - that it ends up net negative. But isn’t this just a problem of setting thresholds correctly? Can’t you commit to only investigating the most obviously bad things, then ignore the rest?

This seemed like an interesting problem to investigate in more depth, so I’ve tried to get numbers. These are rough estimates loosely based on parameters extracted from unsatisfactory studies1 - please don’t take them seriously as exact values, just as right-order-of-magnitude estimates. We’ll focus on whole-body MRIs, since this is a well-studied existing technology, then speculate later on how the results might generalize to whole-body ultrasound.

For every 1,000 seemingly-healthy people who get whole-body screening MRIs:

• 680 look fine and no follow-up is needed.

• 300 have mildly concerning findings. They’re told to follow-up with specialists, get further tests, or come back for more imaging later.

• 20 have extremely concerning findings and get immediate biopsies (surgeries to collect tissue samples from the area).

• Of those 20 people who got biopsies, 10 turn out to really have some serious disease. This is usually cancer, and for simplicity we’ll focus entirely on cancer going forward.

• Of those 10 cancer patients, 4 end up living longer and healthier lives because their cancer was detected early. The other six either have such slow-growing cancers that they would never have noticed before dying of something else, or such deadly cancers that detecting them early doesn’t help, or would have been found by standard screening so soon afterward that the extra screening didn’t buy meaningfully more time.

• Meanwhile, the 300 people who followed up with specialists and got extra tests will spend some number of years seeing more doctors and getting more tests and waiting and seeing, and eventually for 4 of them this will result in detecting some dangerous condition in a way that causes them to live longer and healthier lives.

So in total, 8 of the 1,000 people have benefited. The average benefit among those 8 people is 4 quality-adjusted life-years, so the total benefit from the scans is ~32 QALYs.

What’s the total cost?

• The original 1,000 scans cost about $2K each, and each takes about 3 hours of patient time (one hour for the scan itself, but we add two hours for driving, waiting, arranging the appointment, etc).

• The 300 patients who follow up each cost about another $2K in extra scans, tests, and doctor visits, and let’s say this takes them each ten hours (probably over the course of several years; some of what they’re doing is waiting and seeing whether the anomaly gets bigger vs. goes away). Rare and minor side effects of the testing might contribute -0.005 QALYS per person.

• Additionally, these people are anxious. 29% of them report “moderate” or “severe” distress. It’s easy to trivialize this and round it off to meaningless, but it’s doesn’t feel trivial when it’s happening to you or a loved one. In my day job as a psychiatrist, I sometimes encounter patients having mental breakdowns (the polite term is “adjustment disorder”) over potential cancers that they’ll have to wait six months to retest. The literature quantifies this as an average cost of 0.01 QALYs per uncertain test result.

• The 20 biopsies each cost about $5K and take about 10 hours. Biopsies are pretty minor as surgeries go, but there’s always some risk of post-surgical complication, and in the end these probably cost 0.04 QALYs each. Add the extra 0.01 for anxiety, and it’s a total of 0.05.

• We’ll very optimistically assume that there’s no extra cost to being diagnosed with a cancer that doesn’t require extra early treatment. The doctor says “You have cancer, but it’s a very slow cancer that will take thirty years to harm you, and you’re eighty years old, so this doesn’t matter. Just be chill.” This doesn’t always work in real life, but we’re trying to imagine a best-case scenario.

• We’ll very optimistically assume that after enough tests, the smartest doctors can distinguish cancers that should be treated and cancers that shouldn’t be treated with 100% accuracy, or at least that the number of cancers caught according to the above statistics is at some threshold where falsely identifying a cancer as treatable is rare.

• We’ll assume that the extra cost of treating the treatable cancers is zero. Why assume this? Because if we didn’t detect the cancer early, we would have detected it later, and still had to treat it, and the cost of treating small early cancers is probably no worse - and likely better - than the cost of treating large late cancers (even though treating the latter is less likely to work). So zero is actually close to an upper bound!

So total costs are $2.7 million, 6,200 hours of patient time, and 5 QALYs.

32 QALYS ←→ $2.7 million + 6,200 hours + 5 QALYS
27 QALYS ←→ $2.7 million + 6,200 hours
25 QALYs ←→ $2.7 million
$108,000 per QALY

So, converting everything to the same units, whole-body screening costs $108,000 to save one quality-adjusted life year. Usually in health economics, $100,000 per year of healthy life saved is considered the bar for a good cost-effective intervention (though other sources say $150,000). So this is somewhere around the bar, not unambiguously good or bad.

Could we improve this number by refusing to follow up on ambiguous results?

I think these numbers assume that we’re already being pretty rational in ordering followup. We’re following up on the 300 cases with minor findings because that genuinely discovers 4 extra cancers, in a way that’s more cost-effective than the original round of screening. If doctors irrationally followed up on truly minor results, then that would make the cost-benefit ratio worse.

What if you’re personally rich and $2,000 means nothing to you?

In this situation, wouldn’t the benefits obviously outweigh the costs? The majority of the costs in the analysis above were financial, but this hypothetical rich person can ignore them.

This should be surprising, since every statement I’ve seen about the costs of whole-body screening downplays the financial angle and says that disadvantage is in anxiety, follow-up, and side effects from additional testing. Let’s double-check it.

This individual is buying a 1/125 chance of gaining 4 QALYs (=0.03 QALYs in expectation) at a cost of $0 (money is meaningless to him!), 3 hours of his time, plus a 1/3 chance of -0.015 QALYs of anxiety and testing side effects and 10 additional hours of medical appointments, plus a 1/50 chance of -0.05 QALYs from a biopsy plus another 10 hours of medical appointments. Now the calculus is 0.03 QALYs benefits vs. 0.006 QALYs + 6.2 hours costs = 0.024 QALYs benefit vs. 6.2 hours costs.

0.024 quality-adjusted life-years = 210 quality-adjusted life-hours. Even if you assume that half of those are spent sleeping or doing meaningless work, sacrificing 6.2 good hours to gain 105 good hours is a great trade.

It seems like the rich person who doesn’t care about money should do this!

Wait, can we really compare life-hours spent in medical treatment to life-hours gained from avoiding fatal diseases?

When I think about this harder, there’s something suspicious here.

Suppose there was a medical procedure which had a 5% chance of catching a disease which, if undetected, would have taken four years off your lifespan. On average, getting this scan would add ~900 good hours to your life. So a rational person should be willing to spend 899 hours scanning for this procedure (since in expectation they would benefit.)

But 899 hours of scans would look like going to your doctor’s office for one hour every weekday for three years! And in real life, only ~half of people bother to go to regular checkups, which takes one hour per year and probably have effects nearly this big. If any real person went to their doctor for an hour daily for years to decrease their risk of cancer by 5%, we would call them an insane hypochondriac! And there are dozens of things the average person could do for an hour a day to vastly increase their health (like exercise, or cook nutritious food), and most people don’t bother.

But maybe this is irrational? Sure, most people would hate going to the doctor every day, but if people are willing - even excited - to get whole-body MRIs, then it seems like we should let them, since this is more rational than the irrational normal human behavior we’re comparing it to. Granting that people have weird cognitive biases, it seems counterproductive to communicate the efficacy of whole body MRI by translating it into a domain where they have a bias, then telling them to avoid the whole body MRI because their bias makes them avoid the other thing.

So maybe the correct guidance is something like “The cost-benefit calculation for this whole-body MRI is worse than for many other good things which you don’t do. You’re not doing those other good things because you’re an idiot. However, that same idiocy has led you to believe that you’re somehow getting a leg up on the medical cartel’s evil conspiracy by getting a whole-body MRI, and that’s made you actively delighted about improving your health in this one specific case. So even though by your usual idiotic values you shouldn’t, in reality you should, so go ahead.”

What problems did our previous spherical cow analysis leave out?

The cost-benefit analysis above looks pretty good, at least for certain types of rich people. Why might we be reluctant to trust it?

First, it uses many statistics that I called “order-of-magnitude estimates”, and any of them could be off by an order of magnitude.

Second, it assumes that cancer is the only disease. There’s probably some extra benefit from finding non-cancer diseases (and maybe some extra cost from finding non-cancer false positives).

Third, it assumes that doctors do a good job. A few years ago, my aunt had some concerning symptoms and got a scan. The scan showed she probably had cancer. The doctor inexplicably ignored it for several months and she died. RIP. The doctors in studies usually do a better job than random other doctors, because they’re somehow linked to the sorts of prestigious and thoughtful institutions that conduct research, plus they know they’re being watched. But if you get a doctor more like my aunt’s, you’ll pay the same costs in money, time, and side effect burden, but get zero benefit.

Fourth, it assumes that the average person’s response to being told that they have a slow-growing cancer which will won’t hurt them is “Thank you for this information; as a perfectly rational agent, I will now proceed to never worry about this again.” But in fact, many people become extremely distressed, nocebo-effect themselves into psychosomatic symptoms, and maybe doctor-shop until they find someone willing to give them counterproductive chemotherapy. If even a few patients do this, it quickly erodes our life-years-gained calculation.

Fifth, it assumes that when all the most accurate tests are done and all the best doctors have been consulted, it’s at least possible to distinguish the cancers that should be treated from the slow growing ones that won’t hurt them. This isn’t always true, and sometimes people will be completely rational and still make the wrong choice. We can get this number arbitrarily low by setting stricter and stricter thresholds for which cancers we treat, but the stricter we go, the lower we drive number of true positives caught, until eventually our 32 QALYs gained number becomes a large overestimate. This decreases the benefits some amount, but I don’t have a good sense of how big an effect it is.

Sixth, it assumes that the population you care about is comparable to the study population which I got these numbers from. The median age in these studies is early 50s. If you’re younger than that, you’re less likely to have real disease, so your benefits are lower; if you’re older than that, the opposite is true. But also, these studies focus on people who chose to get full-body MRIs. These people might be sicker than you (maybe they chose to get them because something was bothering them, even if it wasn’t serious enough that their doctor ordered normal screening). Or they might be less sick than you (because they’re rich, or because they care enough about their health to get unusual tests, which probably means they care about their health in other ways like eating healthy and exercising). The second effect probably predominates over the first, so for a fixed age population-wide screening might work better than these studies suggest.

Seventh, it assumes current levels of technology and medical wisdom. If we implemented a national population screening program, it might encourage people to get better screening technology, and it would produce data that doctors could use to more wisely decide which findings to pursue vs. ignore. On the other hand, if we implemented a national screening program, then the quality of the marginal doctor working on whole-body screening might decrease (since we would need to devote far more doctors to this field).

Eighth, it assumes that I accurately calculated the cost of false positives in money, time, and side effects from additional testing. I got these numbers from AIs that estimated them from studies, but aside from the known dangers of both AIs and studies, they collapse a large amount of variation into one headline statistic, and they feel low to me.

Ninth, this is assuming you only get screened once. But most people who go for whole-body screening go every year. The cost-benefit calculation for multiple screens is worse than for one screen, because the first screen detects all the problems you’ve accumulated over your whole life, and the second only detects the new problems you’ve accumulated over the past year (but the second still costs just as much time and money as the first). On the other hand, this also decreases side effect burden from the second (fewer new anomalies to provide false positives) and takes away some side effect burden from the first (instead of following up with a specialist, you might be able to follow up by getting your regularly-scheduled next yearly scan.)

Tenth, there are probably dozens of unknown unknowns of approximately this magnitude.

Depending on which of these factors end up mattering in real life, they could push the cost-benefit calculation from where it is now (around the edge of usefulness) to anywhere from fantastically useful to horribly counterproductive. In the past when doctors have come up with clever cost-benefit analyses like the one in this post, these sorts of known unknowns and unknown unknowns have predominated, and the real effects have been much different from the expected effects - usually much worse. So doctors try to err on the side of being conservative and not doing anything until preliminary studies show that it helps.

But if the calculations above are right, and only ~8 people out of 1,000 benefit, then it would be hard for high-quality studies to measure the effect. You’d probably need hundreds of thousands of participants to find a signal. Instead, we only have meta-analyses of low-quality studies measuring secondary endpoints (eg cancers detected) like this one. But secondary endpoints are notorious for failing to generalize to the things we really care about (like lives saved).

So since the cost-benefit analysis is merely on the edge of being worthwhile, and there are no good studies showing that the assumptions in the cost-benefit analysis are remotely true, and in the absence of good studies doctors err on the side of caution, they currently recommend against whole-body MRI screening. But for the specific scenario of a rich person who doesn’t care about money, who is willing to accept rational over intuitive models of the value of time, and who feels confident that they can avoid excessive anxiety over false positives, there’s a case - not a fully evidence-backed one, but still a case - that they might be mildly net positive.

What about Midjourney’s proposed full-body ultrasound scanner?

Hard to say, because it’s untested new technology and they don’t report many firm numbers about how good it is. But trying to speculate from what we know:

First, the potential benefit is lower. Unless the Midjourney team managed to solve other currently-unsolved problems with ultrasound along the way, it would only be able to detect about half the number of cancers that an MRI could. You could even make a case that this flips its existence to net negative - it would depend on the open consumer-behavior-question of whether whole-body ultrasound would substitute for whole-body MRI (i.e. people who would previously have gotten the MRI would get the ultrasound instead) or add to it (i.e. people who previously would have gotten neither would get the ultrasound). If the former, total number of cancers detected would go down!

Second, the scans might take less time. I don’t think this shifts the numerical cost-benefit analysis much, because the majority of the time for both procedures is driving to the testing center, waiting in the waiting room, etc. If people really hate being in the scary MRI machine for an hour, it could increase the number of people who got the test, but that wouldn’t change the per person cost-benefit ratio.

Third, it might cost less. Midjourney claims that it will, but this hinges on optimistic assumptions (they are so successful that they can manufacture them at massive scale). Since our previous calculation found that financial cost was the biggest negative of whole-body MRIs, this could potentially be decisive and flip the sign to positive even by standard cost-effectiveness numbers.

Fourth, Midjourney is leaning on the hope that people will get this scan yearly or even multiple times per year; this is where some of the benefits of scale come from. But this decreases the efficacy per scan for the reasons mentioned above. And if you don’t do this, you lose some of the scale and the price probably goes up.

Fifth, it might have a different false positive rate. I don’t know if this would be higher or lower. Some people say it would definitely be lower, because surely the combination of massive data + AI could solve everything. I don’t agree. First, these screens will start out with less data than MRI, because they’re a new technology and MRIs have already been done tens of millions of times. Second, ultrasound starts out weaker than MRI and they have to overcome this limitation. Third, even if a billion results would give you enough training data to make this better than MRI, you have to convince a billion people to do a thing which is currently worse than the alternatives to get there. Fourth, at some point you brush up against fundamental limits of the technology. Ultrasound can determine the size, shape, density, and location of things in the body. But sometimes harmless things have the same size, shape, density, and location as dangerous things, and even after you’ve wrung as much information as possible out of those parameters, you’re still not sure. Mr. X is 5’8, overweight, and lives in Chicago. Is he a terrorist? Would it help if I told you his height to five decimal places?

(“But if you get multiple scans at different times, you can see how fast it’s growing!” Okay, Mr. X gained three pounds since last year, ready to answer now?)

So I don’t think a mature version of this technology shows signs of obviously being better or worse than existing whole-body screening MRIs. If you’re excited, it should be for economic, regulatory, or cultural reasons. Maybe they can scale up faster! Maybe they can deploy Silicon Valley levels of capital and ambition against other barely-related unsolved imaging problems! Maybe they can short-circuit the existing medical authorities in ways that existing MRI companies have somehow failed to do, and successfully deliver the message that rich people who don’t care about money or time and who are immune to anxiety and won’t make irrational decisions might benefit!

Any of these would be a more grounded hope than “of course more data will always be good and worth it”.

I’m a rich person who doesn’t care about time or money, and is immune to anxiety, and won’t make irrational decisions. Should I get a whole-body screening MRI?

Seems plausible, but I worry that the set of people who think they fall into this category is bigger than the set of people who really do.

Allow me to go into arrogant condescending doctor mode for a second: I see a lot of people saying they’re sure that they would never be so foolish as to get a procedure that most experts think is unnecessary - or if they did, they’d only do it after extensively reading the research, or at least after discussing the evidence with their favorite AI. They say this in the process of explaining why they’re definitely going to use the Midjourney scanner, a procedure that most experts think is unnecessary. Most of them didn’t read any radiology papers or ask any AIs before deciding to join Team Whole-Body Ultrasound.

Your problem is that your threat model is an uneducated ninety-year old woman collapsing on her fainting couch and hysterically saying “Dearie me! A disease? I must get all possible medical treatment forthwith!” This is maybe a small part of the threat model - although I know some of these women and they’re often cannier than you expect.

But another part of the threat model is some very smart rich person whose boutique concierge doctor (paid per procedure!) will convince him that he’s scoring a point against the evil medical cartel by getting this exciting new contrarian high-tech surgery. Or that your favorite integrative longevity wellness influencer says on his podcast that he got the procedure and his biomarkers went up, and if it makes a biomarker go up then it’s got to be good! Or that your executive personalized medicine screening panel tells you that as a twice-exceptional neurodivergent person with the MTHFR mutation, you can’t rely on generic recommendations made for the average patient, but they will help you sculpt your own bespoke treatment plan including all the latest breakthroughs that ordinary doctors are too low-IQ and uncreative to know about. One of them is by a buzzy AI startup! It uses rays! If a procedure uses rays, and you still don’t get it, doesn’t that kind of make you an anti-tech decel? Seems problematic!

If you think you’re the exception, prenuvo.com, I bet they’d love to have you.

1: The Future of Life Foundation, which unconvincingly denies being part of our conspiracy, asks me to signal-boost their Epistemic Case Study Competition. Prizes up to $50K for finding “the best workflows and methodologies for using AI to produce reliable, trustworthy knowledge bases, grounded in real-world cases”. If you have a difficult controversial question (”is eating eggs healthy?”) what set of AI tools, prompts, pipelines, human interventions, etc can you combine to be most likely to get a correct answer? Deadline July 19, learn more here.

2: More ACX grantee results: Eli Elster describes his research on psilocybin use in Lesotho.

3: New York primary election is this Tuesday. The central Manhattan congressional primary has somehow turned into a proxy war between different Silicon Valley AI factions. ACX supports the pro-safety faction, and so continues to urge readers to vote for Alex Bores.

4: Thanks to everyone who voted for Book Review finalists. I’ll try to have results by next Open Thread.

Midjourney is an AI image model. If you’ve ever used Nano Banana or asked GPT to draw you a picture, it’s like that, except from a medium-sized startup instead of a tech giant.

Earlier today, they announced a pivot to medical scanners. The new MidJourney Scanner, which they describe as “a bold new kind of machine to reimagine the foundations of healthcare and our relationships to our bodies”, will be a tank of water surrounded by a ring of ultrasound scanners. The patient goes into the tank, the scanners emit ultrasound from all angles, and then some fancy AI reconstructs the echoes into a 3D picture of the body. The result is ultrasound tomography: the same sort of rich data as a CT or MRI, but done via ultrasound, with no harmful radiation, in twenty seconds.

This is cool, and it’s great to be ambitious, but I think the narrative among the SF AI crowd has escaped its basis in the medical facts, so I want to throw a bit of cold water on it. I’m a psychiatrist, which is about as far as you can get from radiology while still being a doctor, so this is speculation only, and you can ignore it if you find an actual radiologist or ultrasonographer with opinions. Still, my take is that this scanner isn’t useful for most current serious medical applications. It could potentially be used to pioneer a new class of low-risk screening applications, but it’s unclear whether these are good, and depends a lot on what other future technology gets invented in parallel.

Why can’t this immediately replace existing medical image modalities like normal ultrasound, CT, or MRI?

Ultrasound is great, but it can’t penetrate bone or air. Many things doctors want to look at involve bone or air in some way. For example, the brain is behind the skull, which is a bone. The bowels are full of air. The lungs are super full of air. This limits ultrasound to the remainder - especially parts of the digestive, endocrine, and vascular systems, and superficial tissue like fat and muscle.

(it’s actually worse than this. Normal ultrasound can be used to image certain organs like the heart or prostate, but only via the technician carefully angling the probe. Midjourney hasn’t given details, but most likely their Scanner won’t be able to match this level of precision, so the heart, prostate, and some other usually-ultrasound-compatible organs will be outside its reach.)

Most MRIs or CTs involve one of the organs ultrasound can’t reach (this would be one reason doctors might do an MRI or CT, instead of just using ultrasound). In other cases, you don’t know what organ you’re looking for, and you want to be able to see everything (for example, if you’re scanning for cancer metastases, you can’t leave the brain and bowels out of the scan!) So this technology can’t replace most MRI or CT.

What about replacing ordinary ultrasound? One of the big advantages of ordinary ultrasound is that it’s a cheap machine you can keep on a cart and connect to a patient who’s lying in a hospital bed. Even though it might work better to put the patient in a giant water-filled tank surrounded by hundreds of ultrasound machines, if you tell your hospital orderlies “please transport this frail 90-year old to my giant water-filled tank, and lower them in slowly” they will stab you with your own scalpel. So this would need to be much better than ordinary ultrasound to capture even a fraction of these use cases. But ordinary ultrasound is already pretty good, this technology is untested, and it will be hard for it to be that much better.

Aren’t there a few edge cases that are poorly-served by existing modalities and ordinary ultrasound? Yes - the classic one is certain types of breast cancer, which don’t show up well on mammography against dense breast tissue, and require too much of a search for ordinary ultrasound. It’s a perfect match for this technology, which is why ordinary medical device companies have already created an ultrasound tomography scanner for the breast and it’s used regularly in medical practice. It’s not quite as neat as the MidJourney Scanner - the patient just lies on a weird-shaped table in a position that puts their breasts in a pool of water, instead of submerging the whole body, and you get correspondingly less coverage - but it works fine for the rare case where this technology actually fills a gap.

There are probably other edge cases I don’t know about, but they weren’t important enough for normal medical device companies - who absolutely know about this technology and have thought about it a long time - to invent devices for it.

Couldn’t this technology enable new, non-specific-diagnostic uses for healthy people?

This is where Midjourney seems to be going. Aware that this doesn’t fill a specific diagnostic hole (and would probably be annoying to get past the FDA), they’re imagining something where healthy people go for one of these scans regularly (let’s say once a year). The scanner can produce an image of the whole body, and if there’s anything abnormal (for example, a tumor), they can send them to the regular medical system to get it investigated and treated. You could even have a longitudinal series - this anomaly was tiny on the last scan a year ago, but now it’s bigger, so it’s suspicious for cancer and needs to be investigated immediately.

Here the question is - why is this better than regular whole-body screening MRI scans, a technology which currently exists?

We can certainly think of the opposite - reasons why the screening MRIs are better. Screening MRIs can view the whole body, including the brain, lungs, heart, and interior of the bowels. They have higher resolution. They’re a real technology that exists now, rather than a cool idea by an AI art company. They cost about $2,000, which is cheap by the standards of the US medical system.

So why don’t people get yearly whole-body MRI screenings? Some people do - companies like this provide them, and some rich people who can pay $2,000 out of pocket consume them. But the medical consensus currently recommends against them because they’re more likely to produce dangerous false positives than helpful true positives, and studies have failed to demonstrate benefit.

(a “false positive” in this context isn’t the scanner hallucinating something that isn’t here. It’s the scanner finding some sort of boring abnormality that doesn’t matter - like a zit but inside your organs - and then making everyone panic that it’s cancer, and causing unnecessary tests, surgeries, etc).

Let’s grant that, in fact, these scans produce a lot of false positives, and that a lot of harm is done by unnecessary tests and biopsies and treatments for these false positives. Still, can’t you just adjust the detection threshold until it only fires for extremely obviously bad findings that are definitely worth investigating? This question has bothered me for a long time, and I’ve never been able to get a perfectly clear answer from the medical literature. Here are the mediocre answers I can sort of vaguely see:

• “Obviously bad” is a medical judgment, not a radiological one. Radiology can tell you when something is very big, or very fast-growing, but sometimes there are harmless large fast-growing things. What clinches a decision of “important to investigate further” are questions like age, smoker status, family history, etc. But if you’re an old person who smokes and has a family history of cancer, your doctor is already recommending some kind of lung scan, and this is the opposite of telling all healthy people to get screened all the time.

• In practice, most problems start producing symptoms before the threshold where they’re so clearly bad on imaging that you should extremely obviously investigate them.

• If you actually set the standard for further investigation high enough, it would trigger so rarely that people wouldn’t want these scans for other reasons, like inconvenience and cost.

• Smart technocrats can set the threshold for investigation wherever they please, but a patient who learns that they have a large mass in their brain isn’t going to accept “no” for an answer, and is either going to get it investigated or else spend the next several years freaking out, which has health costs of its own. And malpractice-suit-wary doctors are going to think about how it will sound in a court case to say “yeah, I knew he had a giant mass in his brain, but it was 0.1mm short of the threshold where we bother checking what’s going on, so I did nothing”. So in practice, patients will demand further investigation, and doctors will agree. And the sort of rich, agentic, ultra-health-conscious people who will pay $2000 for a screening MRI their doctor recommends against are exactly the types of people who would be most likely to fall into this error mode.

So although pushy rich people occasionally get boutique clinics to give them these screening MRIs, normal doctors and the legitimate system are against them. Whether or not you agree with this perspective, I assume they would approach the idea of screening whole-body ultrasounds the same way (ie recommend against them). So this would basically be serving the same population of pushy rich people who are already getting the screening MRIs, which are better. So what does this buy you?

One possible answer is convenience. Midjourney claims these ultrasounds could be much faster and more comfortable than an MRI (which involves ~60 minutes in a giant scary metal tube that sometimes kills you if you forget to take off your jewelery).

Another answer is cost. Currently, the Midjourney Scanner is entirely experimental; its prototype is no doubt very expensive, like all prototypes. But the sorts of sensors and chips that make up the Midjourney Scanner have better cost scaling curves than the sorts of giant magnets that make up MRIs. So if this ever became exactly as common as MRIs, it would probably be much cheaper.

This, then, is the strongest argument for the whole-body scanning proposition: you could serve the same pushy rich people who get whole-body MRI scans now against their doctors’ recommendations, but they could do it in a nice spa instead of a giant scary metal tube, and it could be cheaper. And that could unlock a whole new demographic of different pushy rich people who then would be willing to try it.

Couldn’t this technology become more useful in the future?

Yes. I think the best way to think of this is as a bet that future technology develops in a way that allows new possibilities for diagnostic ultrasound - or, even better, an attempt to gather the training data / interest / investment that will make this happen.

For example, if you get lots of high-quality ultrasound data (perhaps because you incorporated your ultrasound scanner into a spa and billed it as something that billions of people should be using every year), maybe you could train a really good AI on that data and do better than any existing radiologist in learning to interpret it and figure out what’s dangerous. Then you wouldn’t have to worry about the studies failing to find benefits from existing whole-body screening.

Or - a commenter informs me of Full Waveform Inversion Imaging Of The Human Brain, which argues that bone only makes ultrasound imaging very difficult, not impossible. It scatters the waves in complicated ways, but with enough math, you could reconstruct what’s going on. How much math? Enough that nobody has ever done it for a real human skull. It would take absolutely gargantuan amounts of compute. But it’s fine! The world economy is in the process of re-centering around creating gargantuan amounts of compute! In the glorious AI future, when a halo of space-based data centers has turned Earth into a miniature Saturn, we can get as many brain ultrasounds as we want!

So the best case for the Midjourney Scanner is that they’re trying to pre-emptively jostle themselves into a position where they can benefit from upcoming AI revolutions. If AI drives the cost of sensor electronics to near zero, and gets so good at radiology that it can cleanly separate true positives from incidentalomas, and becomes so good at wave dynamics that it can overcome previously insurmountable problems around imaging through bone, then probably a company that already has a chain of spas fitted with giant rings of ultrasound scanners will be in a great place to benefit from the subsequent medical revolutions.

All that I can say against this plan is that you need to believe AI will benefit ultrasound tomography in particular. By the time the AI revolution has solved all the problems that stand in the way of the Midjourney Scanner, might it also have beefed up normal MRI, or normal ultrasound, or enabled some kind of entirely new scanning modality, or cured cancer so thoroughly that we don’t need yearly cancer screening?

If you think that no - it will most likely benefit ultrasound in particular - then Midjourney’s bet looks a lot better.

Appendix: Highlights From The Comments On Twitter

I mentioned this on Twitter and got some great responses.

The responses from real radiologists were universally negative. Here are some examples:

When I pressed him for details, Dr. Harris kindly gave a longer explanation:

The trivial reason is that due to the limitations of physics ultrasound will always be less capable at resolving anatomy than MRI or x-ray-based methods that we already have

The more fundamental reason is that all of these applications of technology to screening for anatomic abnormalities rest on a flawed assumption that detecting an abnormality indicating cancer earlier necessarily leads to better outcomes from earlier treatment. This is not, however, a dogma that we can just assume, but rather a hypothesis that must be tested for each type of cancer we wish to improve the survival for. The current imaging based screenings we do, whether for breast, colon, prostate, or lung all have robust literature that at least supports the idea that earlier detection leading to earlier intervention improves outcomes. In the case of prostate, it’s still being argued about quite vociferously and I’m not taking a particular position on that myself. But all of these screening regimes depend not just on modality, but the exact protocol you use to enroll and screen the patients in addition to the treatments that are available and how well they work at what stage.

To the lay person, it seems obvious that finding a cancer on imaging earlier is always better, but in many cases, it’s not only not better it can be worse! Especially on a population basis when you account for medical misadventures that may ensue from unnecessary or earlier or futile treatment.

Finally, this guy is a former president of the Society of Skeletal Radiology:

But I also got responses from non-radiologists, who were more optimistic:

Like I said above, I’ve never been able to fully get my head around the argument against screening and setting a very high threshold for action. Michael’s temperature-taking analogy is a good one. But I don’t think this can be the whole story, because even when entrepreneurs set up their own full-body MRI clinics that don’t cost the system anything, the medical system recommends against using them.

Several people thought that no, surely there has to be some way to make this useful, especially if you could take multiple scans over a long time period:

I think a good intuition pump here is the skin. Weird stuff is always happening on your skin - zits, pimples, warts, but also occasionally melanoma. If you couldn’t see your skin, and had to observe it through some kind of medical imaging, a doctor might be able to tell you “There’s some kind of little bump on your elbow”. Then you wouldn’t know if it was a zit, pimple, wart, or melanoma. But since cancer is very scary, you might say “Oh no! There’s a mass on my skin! Maybe it’s melanoma! And it grew since the last scan! You need to do a skin biopsy immediately!” And then you would have to get surgery for a pimple or a spider bite or something.

Using this intuition pump, I don’t think Paul’s argument stands. Most pimples come after birth! Even if you got a skin scan every month and could compare the current skin scan to the previous one, you’d still be at high risk of fretting over pimples and demanding biopsies for them.

All of your organs are constantly growing little pimple-like things that don’t matter. Depending on the location and type, we call these cysts, polyps, fibroids, lipomas, adenomas, hamartomas, etc. We are bad at distinguishing these from dangerous tumors - and so far the studies show that when we try to do it in the entire population on a mass scale, we cause more problems than we solve. That could change in the future! But it’s a separate bet from whether ultrasound tomography will be good or not, and the ultrasound tomography won’t be very useful unless we solve this problem too.

Andrew knows a lot about sports and metabolic medicine, so I take his opinion here very seriously. A DEXA scan is complicated way of arranging x-rays which is specialized for measuring things like density. Its most common use is measuring bone density in osteoporosis. The Midjourney Scanner probably won’t help with that, because some bones are behind other bones or air.

But its second most common use is measuring “body composition”, the relative amount of fat and muscle. Some high-powered athletes use this to make sure they have exactly the amount of muscle they want, and some people on very precise diets use it to make sure they’re losing exactly the amount of fat they want. And then as usual, there’s a long tail of rich people who don’t know exactly why they’re using it, but their boutique rich-person clinics upsell them on it and give them very precise information on their body parameters which they then proceed to ignore. Between these three categories, it’s a 9-10 digit dollar industry.

The Midjourney Scanner would be a good replacement for DEXA scans - there might be a little fat hidden behind air pockets, but it can still give you a pretty good idea. I don’t know whether it has better or worse resolution, but it might be better, and it would save people (a tiny bit of) radiation.

On the other hand, Big Business has done a great job with DEXA scans. The cost has been driven down to ~$50, and you can do them in a van in the parking lot of your gym (or in front of your house if you make it worth their while). The advantage of the Midjourney Scanner over MRI - all you have to do is go to a spa! - here becomes a disadvantage - you mean I have to go all the way to the spa?

So this is a possible application, but it depends on branding and on outcompeting some pretty cut-throat existing businesses.

This is an interesting take. If you could guarantee that the diagnostician would be perfectly rational (because it’s an AI) and perfectly immune to patient pressure (because it’s an AI), would that switch the sign of primary imaging-based screening from negative to positive?

There are many cases in medicine of some computer system outperforming doctors at some specific diagnostic task. But because of the way regulation works, usually the final decision about whether or not to trust the computer system gets put back in the hands of doctors, who then reintroduce some of the biases the system was intended to prevent. So thus far there have been limited gains from this kind of thing.

In 1917, three children in Fatima, Portugal claimed to have seen the Virgin Mary. They promised she would perform a miracle on a certain day in October. Nearly 100,000 pilgrims arrived, hoping to see whatever happened, and nearly all report that the sun turned pale, changed color, and spun around.

Many other writers have investigated the children and their visions, but I was fixated on this sun miracle. Despite popular discussion of “mass hallucinations”, this is AFAICT the only example of tens thousands of people all saying they witnessed the same impossible thing, at the same time. I got kind of obsessed with this; you can read my preliminary investigations in this, this, and this post.

One of the first things I found was that there were many other sun miracles - at least ten! - similar to Fatima. Most were associated with Marian apparitions, but one was at a Buddhist temple. Bigfoot only gets sighted by lone hikers; ghosts are only ever in the corner of your eye; UFOs are just blurs in the sky. Of all the countries and outposts in the vast empire of the unexplained, it’s only this one phenomenon - the spinning, multicolored sun - that regularly gets seen by thousands of people at once, in broad daylight.

Speaking of “regularly”, there’s one spot where it continues even today. Fifty years ago, the Virgin Mary appeared to six children in Medjugorje, Bosnia. Now those children are well past middle-age, but she continues to come. Three of them report that she’s appeared less frequently as the years go by, but the others still see her every day at 6:40 sharp. Travelers to Medjugorje, especially those passing through around 6:40, report a slew of miracles, including the spinning sun. Certainly this is true of those whose hearts are pure. But even the atheists get lucky sometimes.

I was shocked never to have heard about this before. There’s a place you can just go, and have a decent chance of seeing a real miracle? People take vacations to the Bahamas for the beaches, when they could go instead to Medjugorje and see the natural law of the universe get violated in real time? Seems crazy!

So in early April, I and my extremely-accommodating, long-suffering wife flew to Dubrovnik, rented a car, and drove down a series of windy mountain roads toward the Bosnian border, hoping for a miracle.

The Sands Of Time Were Falling, From Your Finger And Your Thumb

Our story begins at 6:40 on June 24, 1981, at the very beginning of the slow-motion collapse of Yugoslav communism. Two teenage girls walking in the countryside suddenly perceived a glowing woman on a nearby hill, but were too scared to approach. The next night, a group of villagers came to investigate. Most of them saw nothing, but six children - including the two original visionaries - saw the woman again. Compelled by a force they couldn’t understand, they ran up the hill at a speed later determined to be impossibly fast, then fell to their knees on the rocky ground.

“Be not afraid,” said the figure, was now clearly visible as a girl about their own age. She introduced herself as the Virgin Mary, and said she had chosen this town for a special role in her project of bringing peace to the world. “Give us a sign,” pled one of the children. The Virgin suggested they check the time, a suggestion so bizarre that they instead remained transfixed on her. She said1 that she would give them ten secrets to keep until the appointed time. In addition, each would play their own special role bringing her message to a different demographic: Vicka and Jackov to the sick, Ivan to the young, Ivanka to families, Marija to the souls in Purgatory, and Mirjana to the unbelievers. Then she vanished, promising to return at 6:40 the next night.

Mirjana, the girl charged with ministering to the unbelievers, was the first to finally check the time, and found that her watch had reversed. Not in the sense of “it was running backward”, but in the sense of:

And as part of her ministry to the unbelievers, it was Mirjana who wrote the definitive book about the apparitions:

As an unbeliever, I was happy to have it, and it’s my source for the rest of this story.

The next few weeks were a whirlwind demonstration of both the best and worst of humanity. Thousands of pilgrims descended on Medjugorje, begging for scraps of information, miracle cures, or word about the fate of dead relatives. The visionaries tried their best to relay the flood of requests to the Virgin during their daily meetings; she answered some requests and denied others, without obvious pattern. The children’s families and the local priests tried to shield the children from getting totally overwhelmed, from angry unbelievers, and from angry Christians who thought this was a scam and a blasphemy against the Virgin’s name.

The Communists interpreted the whole thing as a threat and decided to move against it. They didn’t want the PR blowback of persecuting innocent pure-hearted children, so they focused on the surrounding village - blocking the roads, arresting the priests, posting guards over the hillside where the apparitions occurred. None of it worked: desperate pilgrims walked around the roadblocks, the revival continued apace without any clergy, and it turned out that although the Virgin had first appeared on that spot of hillside she was equally happy to show up elsewhere.

After a few weeks of this, the Communists decided that okay, fine, they would persecute innocent pure-hearted children, and they whisked the six visionaries off to terrifying interrogations at various police stations, jails, and mental hospitals (though the government never worked up the nerve to actually imprison them). “Confess your deception immediately, or we’ll lock you up and throw away the key!” the bad cop would say. Then the good cop: “Just tell us who it was who put these silly notions into your head, and this can all be papered over without any trouble.”

Mirjana goes more into her own personal story. Her parents lived in Sarajevo; she had been in Medjugorje visiting an aunt and uncle. The authorities carted her back to Sarajevo and told her to not to return to Medjugorje if she knew what was good for her and her family. The Virgin continued to visit her in Sarajevo, even while the rest of her life fell apart. The Communists arranged for her to be expelled from school, and she had to go to a remedial school for the worst and most hopeless students (needless to say, she ministered to the teenage criminals and prostitutes with perfect Christian grace and love). Then, hoping to starve her out, they began making arrangements to fire her parents. The family considered their options, and decided on a sham divorce. They had a “fight” where Mirjana’s father “demanded” she recant, “leaving” her and her mother alone and penniless when she refused. As a result, he was allowed to keep his job - and used it to pass money under the table to Mirjana and her now-single mother. The Communists never did figure out why she wasn’t starving, and failed to come up with any more schemes to force her compliance.

Even as she dealt with these practical crises, she struggled with a more spiritual one: the Virgin Mary is so much more beautiful and glorious than any part of earthly existence that, after seeing her, it becomes hard to appreciate ordinary life. Mirjana described whiling away the hours, listlessly waiting for her 6:40 visitation. After a few years, the Virgin Mary declared their work together mostly finished, switching their daily schedule to an annual one, and the visionary fell into a deep depression. Her parents, her friends, and the Virgin Mary all got concerned for her, urging her to try to bring spirituality and religion into her ordinary life by praying and doing good deeds. This worked a medium amount, and she was able to go on living in between visitations, though always with a sense of loss and longing.

If you can’t beat ‘em, join ‘em. Eventually the Communists decided that the role of Medjugorje in the global revolution was as a revenue-generating tourist trap, and they relaxed restrictions on the site. Mirjana was allowed to return. She reintegrated into the village, married, and had children, thinking to live a normal life. It wouldn’t happen. The flood of pilgrims grew to a torrent. The quiet farmland got dotted with hotels. The Pope sent them his shoes2. Catholic groups across Europe, America, and beyond begged her to do tours and give speeches.

When the war came to Bosnia, Mirjana and her family suffered just like everyone else (maybe not exactly like everyone else; she claims that when the Serbian Air Force tried to bomb Medjugorje, they were turned away by a mysterious and unseasonal mist). But because of the village’s newfound wealth and foreign connections (plus or minus divine protection), it became a shelter for refugees and a hub for foreign aid. With the Queen of Heaven’s guidance, the visionaries tried their best to help. Medjugorje soon had a Mary-themed orphanage, a Mary-themed drug abuse recovery community, and a Mary-themed anti-hunger charity (I donated a small amount to offset the sacrilege of writing this post).

By war’s end, Medjugorje was even more famous and holy than at its beginning. In the 21st century, the Vatican finally gave it the coveted desgination of nihil obstat, a sort of middle-ground where they would neither confirm nor condemn the possibility that a miracle had occurred there. Today, said Mirjana, Medjugorje is one of the great centers of world pilgrimage, a place where cripples are healed and unbelievers return to the faith, a place where the Divine seems to hide behind every corner…

If You’re Squeezed For Information, That’s When You’ve Got To Play It Dumb

Immediately upon entering Medjugorje, I turned a corner, and there she was - the Virgin Mary!

Then I turned another corner, and - lo! - I saw her again!

And again!3

In fact, there were thousands of her! And scores of saints, plethoras of Popes, arrays of angels, crews of Christs, multitudes of mangers, and enough holy water to re-wild the Aral Sea.

It turns out that Mirjana’s book is slightly dated. Medjugorje is no longer a sleepy village filled with pure-hearted peasants and an aura of sacredness. Now it’s a giant Virgin-Mary-themed Disneyland, 90% souvenir shops by weight. Whatever isn’t souvenir shops is, all called things like Hotel Grace, or Villa Regina…

…or named after angels:

…or Popes:

Is there anywhere suitable for a Californian atheist like me?

Perfect4.

My plan was to interview the residents and pilgrims. I knew that many people who came to Medjugorje saw sun miracles, but how many? The reports were numerous enough that I could believe it was almost everyone. Or it could be selection effects, and it’s only one in a thousand, or one in ten thousand.

And what was the pattern? If the spinning sun was real, we might expect shopkeepers who had been there ten years to have seen it 520x as often as pilgrims who spent a week. But if it was a hallucination, triggered by excessive religious enthusiasm, maybe the pilgrims would see it multiple times during their week, and the shopkeepers not at all. Nobody had previously collected statistics on this, so, fancy journalist’s notebook under my arm, I resolved to be the first. My destination: the great square in front of St. James’ Church, where travelers gathered to listen to the Mass being broadcast via loudspeakers in all the languages of the world.

There’s nowhere like a pilgrimage site for people-watching. Yes, there were the expected nuns, priests, and elderly women with the light of faith shining in their eyes. But there were so many other kinds of people. A busload of Asian tourists, snapping pictures with their camera. A man with the most-rabbinical looking beard I have ever seen, wearing flowing black robes and a blue baseball cap. A woman in a dress lower-cut than I would usually associated with churches, covered in enough cosmetics to turn heads at Mar-a-Lago. Mothers desperately trying to redirect herds of five or six children each. A ten-year old in a Ghostbusters t-shirt, which under the circumstances I considered slightly offensive.

Unwilling to interrupt people imbibing the holy atmosphere, I stood at a path leading away from the church, notebook in hand, and accosted passers-by, asking for their experiences. Here’s what I learned:

• People hate being accosted by someone with a notebook asking if they have a few minutes to answer some questions.

• Bosnians hate it even more than the ordinary cross-cultural background of hating this.

• Some of them will say that they don’t speak English, even though in other situations basically everyone in the town speaks English just fine.

• Some of them will literally refuse to acknowledge my existence.

• Of the various pilgrim ethnicities, the Irish earn a exception, living up to their reputation for friendliness, except dontcha know they were all late for some very important religious event and didn’t have time to talk right now although they would definitely help me later.

I tried several other locations (a bench in a quiet part of town, a little plaza in front of a store) with no better luck. Eventually I resorted to buying little trinkets from souvenir shops to see if the shopkeepers would talk to me (this worked once). I cannot describe how much I hated this. I am introverted and socially awkward. Cold approaches to dozens of people who are annoyed by my existence is a torture worthy of Purgatory. Still, I endured, and after several hours, I had a few reports:

• Two Romanian brothers, in Medjugorje for two days, reported that they had seen nothing. But they said that their grandmother had been to Medjugorje nine times, and on the ninth, she saw a vision of the Virgin Mary in a cloud (they specified on further questioning that it was definitely a cloud and not the sun).

• One shopkeeper who had lived in Medjugorje for twenty years reported that she used to have her shop at the bottom of the holy hill where the Virgin had first appeared. Once she saw a disabled woman drag herself up on crutches, then come down unassisted, walking as easily and gracefully as anyone else, and her whole party reported she hadn’t been able to walk like that in years, and it was a miracle. She had never seen anything unusual in the sun.

• A hotel clerk who had been working there six months hadn’t seen anything unusual, although she had talked to a hotel guest who said they had witnessed some sort of miraculous healing. They had heard vague rumors that there were sun miracles in Medjugorje, but didn’t know anyone who had seen one.

The whole process was so discouraging that I wrote off the entire gather-statistics-about-Medjugorje project off as a loss. That left the second half of my plan. I was going to stare at the sun for a somewhat inadvisable length of time and see what happened.

When You Know That You’ve Been Taken, When You’re Begging For A Crumb

Having returned to my hotel room in defeat, I spent the night finishing My Heart Will Triumph and trying to figure out what to make of it.

The first step was to learn the other side of the story, and the Medjugorje Wikipedia article served admirably. It was clearly written by a hostile unbeliever, and focuses on the visionaries’ material success. The religious-speakers-circuit has been very good to them. Most - all? - of them now own tourism-related properties in Medjugorje. Most - all? - are millionaires (the article, gloriously petty, lists the locations of their various mansions and villas). One of them married a former Miss Massachusetts.

This is awkward, but only updated me slightly. To a first approximation, everyone who was in Medjugorje in 1981 must have gotten rich off tourism - a quick count of the number of hotels per square kilometer makes it clear that this required no special shadiness. Mirjana writes about how she struggled with the decision to become a nun vs. get married and live a normal life, and how the Virgin Mary’s advice helped her pick the latter. All of these people have happy families and lovely children, and there’s no shame in honest wealth. Let he who would never marry Miss Massachusetts if the option were available throw the first stone.

More problematic is the heresy. Decades of daily visitation from the Virgin gave her the opportunity to say a lot of stuff. In particular, she said some beautiful-sounding things about God loving all religions equally, which happen to be extremely contrary to the position of the Catholic Church (they think God loves Catholicism more). Those with more theological knowledge can review the whole list of supposed missteps here.

And: in 1956, a bedridden Italian woman claimed that Jesus and Mary appeared to her regularly and gave her vast amounts of information about their earthly lives. She collected these into an epic called The Poem Of The Man-God, a sort of latter-day gospel narrative dictated directly by Christ. One of the Medjugorje visionaries, Marija Pavlović Lunetti, asked the Virgin Mary whether it was legit, and the Virgin said that it “could be read . . . it makes for good reading”. Bad answer! The Church has said the Poem is super-heretical (and the historical scholars have their own concerns, like references to screwdrivers, vanilla, prickly pear cacti, and other things not known for their presence in first-century Judaea). Accordingly, the Virgin’s apparent endorsement of it as a fun yarn "scandalized Catholic theologians”.

Also counted as a mark against Pavlović Lunetti: one of the priests who helped the children during those first few apparitions in 1981, Father Tomislav Vlašić, later fell off the deep end. He founded a sect called “Church Of Jesus Christ Of The Whole Universe”, with fringe beliefs and (wait for it) sex scandals. Through it, Pavlović Lunetti stood by him, joined his weird commune, and said he was an okay guy. Vlašić claimed the “okay guy” message came directly from the Virgin; when he was later revealed not to be so okay after all, Pavlović Lunetti claimed it did not - it had been her own personal mistake (and the Virgin Mary had simply never mentioned that she was making a horrible mistake?)

Against all of these objections, what positive evidence do we have for the visions?

Mirjana once claimed to have physical proof - a reversed watch, something which it should have been impossible for a teenage girl to obtain without an expert watch-maker in on the conspiracy. But the authorities stole it from her during one of the interrogations. She never got it back.

Later in her book, she mentions a different physical artifact. When she worried about forgetting the secrets (or dying before they came to pass), the Virgin handed her a physical piece of parchment with the secrets written upon it. She was afraid that random houseguests would stumble across it and learn contraband information about the future, but when the feared event happened, the two interlopers only reported random boring text - one, a grocery list, the other a short and boring poem. Mirjana seems not to realize that a parchment which shows different things to different people would itself constitute miraculous proof of God’s existence, and never mentions this again. If anyone should happen to meet her, this is the thing I want to ask about most.

Speaking of the secrets, they, too, are supposed to eventually provide proof of the visions. Mirjana will not reveal them, but she tells us the instructions she is given. Each secret describes a future event. Three days before the event happens, she is to announce it to the world. In case she dies before the last secret is revealed, she is allowed to share them with one priest, who will carry out this task in her stead. Otherwise, she gives us two clues. First, the third secret involves a sign that will take place on the hill near Medjugorje where she first saw the Virgin, and which will serve as undeniable proof of the faith. Second, the secrets are pretty scary, and people will be very unhappy about them, but in the end they will be part of the divine plan, and we should have no fear.

My main thought about these secrets is - Mirjana is currently 61 years old. The average female life expectancy in Bosnia is 81. Although Mirjana mentioned worrying that she might die before the secrets are revealed, she seems to treat this as a remote chance worth warding against (eg the chance that we all might die in a car accident or something), not as a likely outcome. That means the secrets must refer to a time sometime in the next twenty years or so. As clock ticks and the years go by, the chance that Mirjana’s prophecy is true decreases accordingly. On the other hand, my beliefs tell me that we are in for some pretty crazy stuff in the next twenty years, and I can’t fault anyone else whose beliefs imply the same.

Aside from these poor tokens, our only evidence is the case presented by Mirjana herself:

In the early days, I was deeply hurt whenever someone accused me of making everything up. I always wanted to ask them, “Why would I invent such a lie? What would I gain by lying? I would have to be an extremely troubled person to lie about such things, especially during communist times. Before the apparitions, I had a beautiful life. I lived with parents who cherished me, and I went to one of the best schools in Sarajevo. Why would I want to turn my life upside down? Why bring turmoil and agony into an otherwise pleasant situation? Only an unstable person would do that. But I was not the only one; there were six of us, including a ten-year-old boy who much preferred playing soccer over praying.”

By Mirjana’s telling, before June 1981 the six visionaries weren’t especially religious. They barely knew each other; they’d crossed paths before, it was impossible to do otherwise in such a small village, but they were hardly close friends. Then, when the whole village went to the base of hill to investigate the previous day’s reports, those six children all immediately broke out of the crowd, ran up the hill, fell to their knees at the same spot, and would spend the rest of their lives saying that they saw the Virgin Mary.

All six continued to see apparitions throughout their lives. All six faced brutal questioning, threats, and retaliation from the Communists without changing their story in the slightest. All six would speak to fellow Christians, the media, and curious tourists about their past and present visions without sounding the least bit uncomfortable. All six would submit to experiments by various scientists and psychologists interested in their experience5, which would always return results of “idk, they seem to be in some sort of weird trance”.

I’m not sure what to make of this. In case anyone in the exhaustively-categorizing-spiritual-experiences branch of our conspiracy wants to try their hand, I present a suggestive passage in which Mirjana describes her experience of seeing the Virgin:

Towards the end of every month [when the apparitions were happening monthly], I begin to pray and fast more intesely, which helps me feel closer to the Blessed Mother. An enormous excitement builds in my heart. I get little sleep on the night before the apparition. I toss and turn in bed. Anticipation steals my breath and makes me feel like I’m suffocating. But when I pray, I feel as if God gives me strength, as if He whispers to me ‘You can do it’ and only then am I able to wait patiently until morning […]

In the past, I only knew that she’d appear to me at some time on the 2nd. But these days, I know that Our Lady always appears to me a little before 9 AM6. I usually spend the first part of the morning praying in my living room. By then, I can feel the love building in my heart - I can feel the moment drawing near - but it’s not yet time…

By [a little after 8], I’m beginning to experience the feeling of Heaven, and I can sense Our Lady’s presence and hear her faint voice in my heart. That’s when I’m able to encourage myself.

I can do it, I think. See, she does love me. I’m not such a sinner that she won’t come.

But as my consciousness drifts farther into Heaven, I comprehend less of what’s going on around me. For example, I invited an American friend to come with me to the Blue Cross [a literal cross on the hill in Medjugorje] for one of the recent apparitions. When we met in front of my house that morning, I greeted him and asked him how he’d been, but he did not reply…finally, he politely said “Mirjana, I’m sorry, but I don’t speak Italian.” Of course. I knew he spoke English, but my thoughts were so jumbled before the apparition that I even forgot what language I was speaking. Some people even get offended when they tell me something and I do not respond, but it’s difficult to explain that I’m already halfway in another world […]

The volunteers escort me down the street [to the Blue Cross site where Mirjana has her visions in public for pilgrims] and I stop to greet people if I feel compelled to do so. At this point, my heart is bursting with love for everyone I see on my way. Usually when we reach the base of the hill, the crowd of pilgrims is so large that it blocks the entire street…Italian people are known to be blessed with passionate temperaments, and some of them think it’s necessary to touch me, as if I’m some kind of saint or miracle worker. One time, I even caught a woman trying to cut off a lock of my hair as a keepsake.

When I was on my way to one apparition, a disturbed woman in the crowd grabbed my arm so forcefully that it dislocated my shoulder. Intense pain shot through my entire body, and I cried as I held my injured arm with my other hand. When I finally reached the Blue Cross, I was in agony and my body trembled. I prayed in silence, Blessed Mother, please come quickly. I can’t withstand this pain much longer. When Our Lady appeared, the throbbing instantly vanished. In Heaven, there is no pain. There is only love…

As I kneel on the fat rock, facing the Blue Cross, I feel like I’m losing my breath. My heart is awash with a maelstrom of emotions…I would probably hyperventilate or pass out if not for the calming effects of prayer. The feeling builds to a crescendo. I put my hand over my chest as if to prevent my heart from jumping out. I gasp for air. Suddenly it’s as if someone flips a switch - the world disappears, and I’m encompassed in a great, unending blueness. Our Lady is before me in the middle of it all. Every pain and fear disappears. I’m comforted. I’m loved. I’m complete…I’m not aware of anyone or anything around me. I’m not even on the hill anymore. Everything is concealed by the blueness, which itself is difficult to describe. I might compare it to the color of the sky on a cloudless day in springtime, but it’s really nothing like the sky. In fact, it’s more than just a color. It’s like a place and a feeling at the same time. It totally envelops me and Our Lady…

I see her like I see anyone else - as a tangible, physical being, in no way transparent or spectral. Her beauty, however, is clearly not of this world, and when she speaks, it’s like music from Heaven. But her voice is more than a sound…I hear her voice with my ears but also with my heart - with my entire being. One time, an acoustic engineer came from New York with the goal of identifying what Our Lady’s voice was like. He brought recordings of many different types of voices. With headphones on my earts, I listened to all of them, but nothing came close.

Our Lady usually gives me a message halfway into the apparition…sometimes I get concerned that I won’t be able to memorize the message, especially if she says some words I never personally use, and I’ve even asked her “Will I be able to remember all this?” She responds with a gentle smile, as if to say I needn’t worry. When she gives me the message, she doesn’t always speak in the same continuous way that I dictate it later. Instead, she connects certain parts of the message with what has happened and what is supposed to happen in the future. I cannot share specific details about this yet, but, for example, if Our Lady’s message asks us to forgive, then she might explain to me that if we do not forgive, then this or that will happen…

She usually concludes by saying “Pray, pray, pray” and then she rises slowly into the blueness, almost as if being vacuumed away….Our Lady rises just a short distance before she disappears, and the blueness immediately recedes with her. Suddenly back among the pilgrims, I’m assaulted by a cacophony of sound, as if people are shouting in my ears and blasting harsh noises through a megaphone. In reality thought, everyone is quietly praying. Even a whisper sounds like a scream in the moments after I leave the peace of Heaven.

Someone helps me to my feet and I sit on a nearby stone bench. I feel completely broken, lifeless, and I need a moment to readjust. Sometimes I can’t stop crying. I’ve just experienced a brief moment of love in its purest form and lost it just as quickly. To know Heaven and live on Earth is more painful than anyone can imagine….

As soon as I reach my house after coming down, I go to my room. I pray. I cry. I ask God to help me understand why I have to stay on Earth. Through this prayer, I begin to feel God gently nudging me forward…I cannot yet go with Our Lady and she cannot stay here with me. Finally, after two or three days, I have enough strength to face life as a typical person - at least until I taste Paradise again next month.

I’ll wait for the spiritual-experience-categorization experts before I weigh in on this myself, but I did find the level of detail in this description compelling, along with the unexpectedness of some of its twists and turns. Still, one wishes she had kept the watch, or was more willing to show the parchment. For now, this is all we have to go on: one woman’s very compelling book, and several thousand sightings of a spinning, many-colored sun.

Let’s Do Something Crazy, Something Absolutely Wrong

This section is a love letter to my wife.

Family and childcare responsibilities let us take one good vacation per year. When I told her I wanted to spend it on a Bosnian village, her first reaction was “Sure, sounds like it’ll be a good story for your blog.”

It was only later that she started getting worried. “If you see the miracle, you’re not going to convert to Catholicism, are you?”

“What?” I said. “Of course you’ve got to convert if you see a miracle!”

“No you don’t!” said my wife, just as vocally, and proceeded to list the usual atheist concerns with Catholicism. Many of its stories seem false. The idea of an eternal Hell is morally outrageous. It has various regressive opinions on gender and sexuality.

I agreed these were all strong concerns, which was why I wasn’t currently a Catholic - but come on, if you see a miracle then all that goes out the window. Not, like, if after fasting and purging and otherwise working yourself up into a weird state you manage to spot some slightly trippy hallucinations in the sky. But if, on a totally normal day, you see the sun unambiguously change colors and whirl around like a top, of course you’ve got to convert, right?

My wife raised the very valid point that I already knew that hundreds of people had seen exactly this. I had read their testimonies, even created a spreadsheet comparing all their various observations for use in my posts on the topic. Probably not all of these people were lying. So they must have hallucinated it. But they said it was all perfectly clear and vivid and utterly convincing, not just some vague trippy effect skirting the edges of normality. So if I also hallucinated something that was perfect and clear and vivid and utterly convincing, that would raise the testimony count from ~500 to ~501, which barely matters. Either I should be Catholic already, or else seeing a miracle, however clear, should do nothing for me.

I didn’t like this conclusion. I am, not to toot my own horn, an expert at not hallucinating. I’ve experimented with various forms of woo, alternative medicine, and occultism, and I’ve always seen and felt precisely nothing. One time I was called up to a stage hypnotist’s show, and everyone else was spinning in circles or honking like geese, and I just stood there awkwardly and eventually asked if I could go back to my seat. On hallucinogenic drugs, I can get some pretty crazy delusions, but I never see anything. Who knows what the mental integrity of those previous five hundred witnesses was like? If I saw it with my own stress-tested eyes, surely that had to add something.

My wife approached the topic from the opposite direction. When she was little, her parents made her go to bed long before she was tired. She would lie awake all evening with nothing better to do than experiment with the exact contour of her thoughts. Later, she would learn these experiments were meditation, and that over her childhood she had logged enough hours to make the most serene monk go green with envy. Now, every so often, I’ll read about some crazy qualia self-experimenter on the Internet, and I’ll hit her with something like “Did you know a guy on r/streamentry says that if you take DMT and mescaline at the same time and then lie in a sensory deprivation tank for nine hours, conscious experience will turn into a torus?”. And my wife will answer with something like “Oh yeah, that one’s fun, but you don’t need DMT or mescaline, you can just turn conscious experience into a cylinder and then loop it around so the ends connect.” I never have the slightest idea what she’s talking about when our conversations stray into this zone, but it doesn’t matter - she long ago realized that everyone in California who talks about meditation either joins a cult or starts one, and she responded by ascribing no seriousness at all to any of her experiences and refusing to discuss them except with her husband and a few close friends. I can go months completely forgetting that she’s like this. But then I’ll say something like “Surely you couldn’t hallucinate a miracle!”, and she will list the one hundred different mental states she knows of where miracle-hallucination is natural and common, and tell me which miracles she has hallucinated in each of them.

There followed one of the longest and most stressful arguments of our marriage, in which I futilely insisted that I was as anti-Catholic as the best of them but that you had to convert if you saw a miracle, and she (one of the most practical people I know!) insisted that she had already converted religions once to marry me, and she was not going to do it again, and she was not going to go to Mass every Sunday, and she was definitely not going to wear that headscarf-shawl thing that some Catholic women wear. Eventually, we agreed only that we table the discussion until we went to Medjugorje, saw whatever we saw, and determined whether there was even anything to fight about.

I mention this to confess that I had divided loyalties. I said above that I was hoping for a miracle, but that’s not quite right. My utility function was non-monotonic over different miracle sizes. I wanted either one that was so big it was impossible to doubt, one that was so small I could laugh it off, or none at all. Just don’t, I prayed to God, send a medium-sized miracle.

When You’ve Got To Go On Waiting, For The Miracle To Come

The traditional pilgrimage to Medjugorje has three parts.

First, you climb Cross Mountain, a big mountain with a concrete cross on the top. I did it my first evening in town. It was foolhardy to start so late, but I was antsy and wanted to get started. By the time I reached the summit, the sun had long since set. The stars blazed unusually bright, but no more so than could be attributed to the altitude and relative lack of light pollution. I got slightly lost on my way down, only to be “rescued” by two pilgrims who were so excited at the opportunity to aid a fellow Christian that I didn’t have the heart to tell them I was mostly fine and an unbeliever. They told me this was their second time climbing Cross Mountain. The first time, they’d done it barefoot, as penitence for their sins.

Second, you climb Apparition Hill, the site where the Virgin first appeared almost five decades earlier. This is the nexus for strange occurrences at Medjugorje, and the only tourist attraction I’ve ever been to whose TripAdvisor rating (4.7 stars) is biased by people who saw miracles there:

I went up around noon of my second day. The top was pretty and peaceful, and the throngs of pilgrims praying before the statue of the Virgin impressed me with their obvious joy and faith. But the midday sun was as bright and as motionless as ever, and my brief glances won me nothing but a slight headache.

Third, you pray at St. James Church. My wife had finally recovered from the cold she’d gotten on the flight in, so the two of us headed over late afternoon, hoping to make it before the 6:40 mark when miracles are most common. The church itself was full (and besides, had no line of sight to the sun), but loudspeakers blasted the prayers to a lovely park in the back. Nearer the church, a crowd sat and worshipped. Further away, other couples lounged on the grass, half-listening to the prayers and music. A few small children played ball beside an “ABSOLUTELY NO BALL GAMES” sign.

I was glad to have my wife with me, both for the obvious reasons and for one clandestine one. In many of the stories out of Medjugorje, one person in a group had seen the spinning sun first, then pointed it out, and then everyone in the group had seen it. This didn’t really fit the hallucination theory, unless the hallucination was somehow contagious, maybe through mass suggestion. The obvious experiment was for me to shout, at a random moment, “LOOK! THERE IT IS! THE MIRACLE!” and see whether other people agreed or not. I was too much of a coward to do this in a random crowd. But I could do it to my wife.

The problem was, my wife knew me really well, and I didn’t think I could lie to her successfully. Also, I hated lying, even lying for a good cause when I knew I would be forgiven afterwards. Also, we were still in a sort of awkward truce over the question of whether you had to convert if you saw a miracle, and I was scared of opening that wound.

Also, it was 6:30. The miracle most often happened at 6:40. If I did it before then, we would both be in a kind of bad mood and maybe when the miracle was actually supposed to arrive we would be poisoned against it. But if I waited much after 6:40, the sun might be too low on the horizon to be clearly visible. I fretted over this for about ten minutes, then resolved that I would try it at 6:35. I steeled myself up. I rehearsed the exact sequence of events I was going to try. I would grab her by the shoulder. I would point at the sun. I would say “LOOK! THERE IT IS! THE MIRACLE!” I would let her look for ten seconds before admitting my deception. We would laugh about it afterward. Nothing would go wrong.

At 6:33, my wife grabbed me by the shoulder, pointed at the sun, and said “LOOK! THERE IT IS! THE MIRACLE!”

I knew my wife really well, and I didn’t think she could lie to me successfully. And she didn’t look like someone who was lying. She was staring straight at the evening sun, as intensely as I’d ever seen her do anything. “Do you see it?” she asked. “It isn’t bright anymore! It just looks like a disc! It’s stopped being painful to stare at!”

There was no contagion, no suggestion effect. The sun looked totally normal to me. It was too bright to look at directly for more than a few seconds, even though my wife was doing exactly that.

“It’s changing color!” said my wife. “And sort of pulsing, or strobing, or . . . something! Wow! You’re not seeing this?”

I looked harder. I wouldn’t describe myself as seeing any kind of miracle. The sun was partly behind some thin clouds. The clouds made the disc slightly less bright than usual, but were themselves very bright - so much so that the afterimages from the sun bled into the afterimages from the clouds in an odd, almost violent way. I wouldn’t have noticed it was strange on my own, let alone called it a miracle, but maybe now that she’d mentioned it . . .

“Oh, there it goes,” she said, after about thirty seconds. “It’s back to normal.” And then “Oh, wow, I’m really crying right now.” She hadn’t thought the sun had been bright, but her tear ducts apparently disagreed. Then “Oh, I have a big white spot in the center of my vision right now, I sure hope this isn’t permanent.” A few months earlier, I’d read through all the ophthalmology journal articles I could find that mentioned sun-staring at Medjugorje and was now something of an expert; given that she’d only stared for thirty seconds around sunset, I assured her that the spot would disappear in a few minutes, which turned out to be the case.

“That was pretty cool!” she told me, once the immediate afterimage-related crisis had passed. Those were her exact words, “pretty cool”. On our way back to the hotel, she passed a church with unusual roof tiles, which she also dubbed “pretty cool”.

Like I said, one of the most practical people I’ve ever met.

The Maestro Says It’s Mozart, But It Sounds Like Bubblegum

We didn’t convert to Catholicism, but we did spend a while comparing notes and trying to figure out what had happened. In retrospect, it was great luck that my wife saw the miracle so much more intensely than I did - it gave us different perspectives that let us sort of triangulate what was going on.

Here’s our working theory for what happens when people see the miracle.

Step 1: Sun within a narrow range of unusual dimness, surrounded by clouds in a narrow range of unusual brightness.

The sun has to be so dim that it’s possible to stare at it without immediately flinching, turning away, or going blind - but also so bright that it’s still able to produce strong afterimages and eventually do damage.

Is it possible for it to be this dim and this bright simultaneously? I think there’s a narrow band around 10,000 nits of brightness where this is possible, especially if the sun is surrounded by very bright clouds. When the sun is surrounded by bright clouds, it appears dimmer than it is, because your eyes estimate brightness through contrast with the surroundings.

(I think the reason my wife’s experience was so much more impressive than mine was that her vision snapped the bright sun against bright clouds to “both sun and clouds are dim” and mine snapped them to “both sun and clouds are bright”, due to some kind of perceptual idiosyncrasy.)

In this band, someone primed to expect a miracle will look at the sun, see that it looks “dim” or “pale”, and notice that it’s possible to gaze at it without feeling pain. This will be surprising enough that they’ll keep staring, precipitating the rest of the miracle.

Looking back over past reports of the miracle, I think there are two ways you can get this:

1. The sun shining through a tiny window of light cirrus clouds, in the middle of a sky of dark rainclouds, in a moisture-filled sky, anytime between midday and sunset. All of the most dramatic examples of large crowds seeing the miracle have happened in these conditions.

2. The sun shining through light cirrostratus clouds, around sunset. Many of the Medjugorje reports, including ours, happened in these conditions.

Step 2: Afterimage superimposed upon sun

In fact, the sun is still bright enough to produce an unexpectedly strong afterimage, which is superimposed directly over the sun itself. Like all afterimages, these cycle between yellow, blue, and pink as different receptors come on- and offline. But absent normal brightness cues, you don’t naturally interpret them as afterimages. You just see the sun flashing yellow, blue, and pink.

Step 3: Drift and microsaccades cause a fiery, multicolored halo

At first, the afterimage is exactly superimposed upon the sun. But the eyes are constantly making tiny random involuntary movements. One type of movement, microsaccades, is a deliberate attempt to prevent photoreceptor fatigue that usually happens a few times per second. Another type, drift, is caused by the inability of ocular muscles to retain precise focus over multi-hundred-millisecond timescales. These movements happen on a scale of about one degree, compared to the half-degree width of the sun disc. So as you try to stare at the sun, every few hundred milliseconds, your eyes will drift about half a sunlength in some direction or another before you suddenly jerk back to focusing on the center of the sun itself. The end result is a halo of sun-afterimages, half a sunlength wide, surrounding the actual sun.

Afterimages aren’t stable. As the photoreceptors recover at different rates, they pulsate, writhe, and change color before finally disappearing. Since each part of the sun’s “halo” will be an afterimage from a different time (separated by milliseconds to seconds from each other), they will move heterogeneously. A phenomenon called the Troxler Effect, demonstrated in certain radial patterns very similar to sun afterimages, makes some of them fade in and out of vision in surprising ways.

What about spinning? In my original article, I noted an apparent paradox: the sun is a perfect circle, so even if it were spinning, it should be impossible to tell. The pulsing halo of different-colored afterimages potentially overcomes this objection (that is, if the images above were to spin, you would notice) - but doesn’t in itself explain the perception of rotational motion. Here I have nothing better than the general tendency of the visual system to interpret complex radial stimuli as rotating, and their movement as rotational movement…

…but I’m unhappy with this non-explanation, and hope that a real perceptual psychologist reading this post can do better7.

Step 4: Ultraviolet damage causes chromatopsia

One of the strangest parts of the Fatima phenomenon was the reports of the whole world suddenly changing to single colors. Jose Garrett wrote:

Everything had the color of an amethyst: the sky, the air, everything and everybody. A little oak nearby was casting a heavy purple shadow on the ground. Fearing impairment of the retina, which was improbable, because then I would not have seen everything in purple, I turned about, closed my eyes, cupping my hands over them, to cut off all light. With my back turned, I opened my eyes and realized that the landscape and the air retained the purple hue […]

Continuing to look at the sun, I noticed the environment had brightened. Soon after, I heard a country bumpkin nearby saying in an astonished voice, “That lady’s yellow.” Indeed, everything had changed, near and far, taking on the color of old, yellow apricots. People looked sickly and jaundiced. I smiled, finding them downright ugly and unattractive. Laughter rang out. My hand was the same shade of yellow.

The newspaper O Dia:

The light turned a beautiful blue, as if it had come through the stained-glass windows of a cathedral, and spread itself over the people who knelt with outstretched hands. The blue faded slowly, and then the light seemed to pass through yellow glass. Yellow stains fell against white handkerchiefs, against the dark skirts of the women. They were repeated on the trees, on the stones and on the [terrain?]

Antonio de Paula:

Taking his eyes off the sun, he saw the people a very bright red color; and he exclaimed: “Oh, gentlemen, how the people are all red!” And the priest replied: “Are they red scarves?” To which he remarked: “How can that be? So they had all agreed to have red scarves on their backs?!” Then the people appeared the color of gold.

Thanks to Pinckers et al in Documenta Ophthalmologica for finally giving me some insight into this phenomenon: this is ultraviolet chromatopsia!

Chromatopsia is defined as a temporary condition in which white stimuli appear coloured. The most frequently occurring types of chromatopsia are yellow-vision (xanthopsia), green-vision (chloropsia), red-vision (erythropsia), blue-vision (cyanopsia) and violet or purple-vision (ianothinopsia).

They write that “erythropsia due to bright (sun-)light is a relatively common finding in aphakia and pseudophakia”. These latter are medical terms for people with absent or damaged eye-lenses. But plausibly very intense exposure to UV light - for example, staring straight at the sun for ten minutes - can cause similar symptoms even when the eye-lens is intact. I was also able to find some reports of this happening to people with early-stage snow blindness (ie on bright days when there’s lots of snow on the ground reflecting UV light), although I don’t know what their eye lens status was.

This paper singles out erythropsia (red-tinged vision) as especially likely to be produced by sunlight-related damage. However, all three witnesses mention multiple colors, and only one (Antonio de Paula) even has red on his list. The authors don’t give a source for their erythropsia claim, but is there any reason to think chromopsias can be multiple and variable?

Elsewhere in sun-related-eye-damage studies, there’s a very closely related phenomenon called retinal bleaching. When someone stares straight at the sun, the damage preferentially hits certain color receptors. This produces an afterimage of the opposite color (eg if it damages the yellow receptors, the afterimage is blue). This is distinct from chromatopsia in that the afterimage is usually a colored spot the approximate size and shape of the light source, “opaque” in the sense that it cannot be seen through.

These retinal bleaching lesions quickly (on the order of seconds to minutes) go through a series of changing hues called the flight of colors, or sometimes Plateau’s Sequence. Due to genetic differences, the exact sequence is different for every individual.

So the Fatima phenomenon is somewhere between ultraviolet chromatopsia and a more traditional afterimage undergoing Plateau’s Sequence. I’m not sure why it would combine these two things, but staring at the sun for ten minutes is sufficiently outside the domain usually studied by ophthalmology that I think we’re permitted to posit exotic new combinations of eye damage types. The Fatima color changes so closely resemble these two well-known diagnoses that I think something in the same family should be our working hypothesis.

This is, I guess, pretty disappointing. Early on, I dismissed afterimages as too obvious and dumb to explain the entire phenomenon that dazzled so many smart people. I’m split between admitting that I was wrong, and objecting that I’ve added so many lovely epicycles to the afterimage theory that should count as a new theory that avoids those concerns. Still, in the end I do think it was basically afterimages and eye damage.

Objections to my theory

I discussed this theory with Fatima true believers, including Ethan Muse, who gave me helpful pushback.

Objection 1: You can’t extrapolate from sunset to midday.

My wife gazed at the sun at evening through light clouds, but the Fatima miracle happened at midday through a clear sky (or rather, the rest of the sky was cloudy, but there was clear line of sight to the sun). This means I can’t rely on clouds-scattering-light based explanations, and also, everyone would have been blinded (or, at best, forced to look away) before they could get any of these phenomena.

Against this, the Fatima miracle occurred just after a heavy rainstorm. I think (without being able to name exactly what was going on) that this created a layer of moisture in the atmosphere which dimmed the sun without seeming like it was obviously blocked by clouds. I’m not an optical physicist and can’t give details, but here’s what the LLMs have to say:

—The setup

The Beer-Lambert law says the fraction of light transmitted through an attenuating layer is T = e^(−τ), where τ is the optical depth. If a star is hidden behind a cloud of optical depth τ it will be dimmed by 1.086τ magnitudes. Physics LibreTexts Each magnitude is a factor of about 2.512 in brightness, so τ = 1 means transmission ≈ 37% (dimmed by ~1.1 mag), τ = 2 means ~14% (~2.2 mag), τ = 3 means ~5% (~3.3 mag).

—What counts as “obviously visible cloud”?

This is the crux. Studies of cloud optical depth retrieval treat τ ≲ 3 as the regime of “thin clouds” where the sun is still visible as a disc through them; “only optically thin clouds with a COD below three can be investigated” ResearchGate using sun-photometer methods that require seeing the sun. Cirrus clouds typically have τ in the range 0.1 to a few. So roughly: τ < 0.5 is barely visible haze, τ ≈ 1 is a noticeable thin veil, τ ≈ 2–3 is a clear gauze where you can still see the disc but it looks dimmed and “milky,” and beyond τ ≈ 3 the disc starts losing its sharp edge. Witnesses at Fatima specifically described the disc as having a clean-cut, sharp edge — which puts us in the τ ≲ 3 regime.

—The midday-vs-evening comparison you asked about

Going from midday to a low evening sun corresponds to a change in air mass from about 1 to about 10–20 (depending on how close to the horizon). The clear-air vertical optical depth at sea level in the visible is roughly τ ≈ 0.2–0.4 in clean air, more with aerosols. So at zenith, transmission is ~70–80%; at AM = 10, the slant optical depth is τ × 10 ≈ 2–4, giving transmission of order 2–14% of the above-atmosphere value.

So evening sun is dimmer than midday sun by very roughly a factor of 5 to 50, depending on aerosol load and how close to setting.

—Could thin post-rain veiling reproduce this?

Yes, comfortably, and with room to spare. To dim midday sun to evening levels you need an additional τ of roughly 1.5–4 on top of the clear-air baseline — exactly the regime of optically thin clouds where the disc remains visible. A thin stratus or altostratus deck with τ ≈ 2 (very ordinary, often not even noticed as a distinct cloud when uniformly spread) cuts brightness to ~14%. A τ of 3 cuts it to ~5% — fainter than typical evening sun.

There’s also a separate issue I glossed over before that’s worth stating: even completely clear atmospheres have an aerosol optical depth (AOD) component on top of Rayleigh scattering. After rain, washout reduces large aerosols but the residual humid layer with suspended fine droplets and re-evaporated moisture can substantially raise the effective τ in the visible without producing what an observer would call “a cloud.” Sun photometer studies regularly distinguish “clear” and “hazy clear” conditions where AOD differs by 0.5–1.5 with no obvious cloud cover.

Several of the Fatima witnesses do say that the sun seemed to be blocked by some kind of very thin, light cloud layer at the time (see section 1.1.2 here). This was likely a high-τ-but-barely-visible post-rain layer; some people noticed it, others didn’t, but it blocked enough sunlight that everyone could stare long enough for the effects to start.

Speculatively, Fatima had “perfect” conditions for the miracle - the exact right kind of cloud layer, the exact right amount of diffusion vs. concentration - and Medjugorje has only “passable” conditions. This explains why so many of the Medjugorje reports - including my wife’s - are comparatively disappointing, lacking the spinning motion or the visual field tinting.

Objection 2: Nobody at Fatima reported afterimages, blindness, or eye pain

None of the Fatima witnesses described eye pain, later eye damage like blindness, or even afterimages.

The first two are explained by the possible cloud layer above. But I acknowledge the lack of an obvious afterimage - the sun disc in negative - is strange. Possibly people stared at the sun so long that it went from afterimage to full retinal bleaching and chromatopsia, and by the time the world had regained its normal colors their eyes were mostly healed. My wife’s eyes were fine after about five minutes.

Objection 3: There were distant witnesses

I actually think this makes sense on my theory! We know that many of the distant witnesses had heard there was going to be a sun miracle at Fatima, and were looking up at the same time. The same rainstorm was covering the whole region, and it wouldn’t have been too surprising for the conditions to be right in other places too.

There are even a few cases of distant witnesses in Lisbon or further afield. These don’t make sense for a real phenomenon, since one would expect that everyone in Lisbon (a huge city) would have seen it, rather than just one or two people. But it does make sense if everyone who stared at the sun very hard saw it, and that was everyone in Fatima, some people in surrounding villages who were very aware of the situation, and a tiny number of people in Lisbon who just so happened to think about the story they’d heard about some far-off town that might be having a sun miracle.

Objection 4: There was too much other weird stuff

Fatima witnesses reported a wide variety of other extraordinary phenomena, including the sun zooming towards Earth, the Virgin Mary appearing in the sun, other religious iconography appearing in the sun, shooting stars, color changes even among people who never looked at the sun, and the sudden drying of wet clothes.

The sun “zooming towards Earth” might have just been sudden changes in the size or brightness of the diffuse cloud region. As for the others, I can only appeal to the literature on eyewitness unreliability. Witnesses to crimes often confabulate details, especially details that fit the stereotype of “things that happen at crimes”. For example, they might report having seen broken glass at a minor car accident where no glass got broken, or remember a criminal leaping a turnstile to get to the crime scene when he entered normally.

Is it weird or even hypocritical to bring up eyewitness unreliability this late in the game, after having generally tried to accept the frame where thousands of people really saw the sun spin and change color? I don’t think so. Eyewitnesses rarely confabulate entire crimes when in fact it was a perfectly normal day when nothing happened! When someone is in a stressful, shocking situation outside their normal range, they get confused enough that they confabulate extra details, or lean on their stereotypes of the situation rather than the reality. Seeing a miracle is so unusual that it might place someone in the same sort of altered state as seeing a crime, where their attempts to regenerate their memory from its traces bumps up against inexperience with the entire genre of situation.

Something like this has to be true - the sheer variety of miracles reported by different Fatima witnesses, which other witnesses don’t mention or outright contradict - doesn’t match any particular single miracle that could have objectively occurred. I think it’s fair to concentrate on the parts that almost everyone saw - the spinning, multicolored sun - and dismiss the rest as the consequences of the mental shock of having seen any miracle at all.

Objection 5: Do we need too much fine-tuning?

One of the most compelling aspects of the Fatima miracle has always been that it was predicted in advance. This rules out most meteorological and astronomical phenomena; what’s the chance that this particular rare event would happen at the exact time predicted by child-seers beforehand?

My theory requires only a certain pattern of diffuse clouds. How unlikely is that? We saw it at Medjugorje once during three days of relatively frequent checks, although we may have gotten lucky - other people spend much longer and don’t see at at all. Plausibly, we get at least mediocre miracle conditions sometime on the order of once every few days to weeks. The details might depend on how rainy the weather is, or vary by area (eg Medjugorje might have them especially often, since it’s pre-selected for being a place where the miracle is often seen).

So why doesn’t everyone see the miracle once every few weeks? People rarely stare at the sun! Suppose that when conditions are exactly perfect, it takes about two seconds of staring before the sun looks like a pale disc, and five to ten seconds to get the full multicolored spinning halo. Then:

• In normal life, very few people stare at the sun for two seconds. Even if they did stare at it at the exact right time, they would only see that it kind of looked like a pale disc - which it often does anyway for unrelated reasons - and not necessarily continue to stare.

• In normal human life, almost nobody stares at the sun for five to ten seconds. The only exception are people in the sun-gazing movement, who do sometimes report experiences similar to the miracle.

• At Fatima, there are records of the pilgrims arriving with an expectation that there might be a sun-related miracle. At least somebody would have been checking the sky when the right conditions started, and would have shouted “Look! The miracle!” People would have stared at the sun for two seconds, and seen it as a pale disc, which would have been intriguing enough that they would have marked the beginning of the miracle from that point and continued to stare. Then after five to ten seconds, they would have seen the full multicolored spinning halo. Then, when people asked them about it later, they would have said the miracle began “immediately” and hadn’t required any special amount of staring at the sun.

As further evidence, after we got home from Bosnia, I was on the lookout for conditions like those under which we’d seen the miracle. A week or two later, just before an unseasonal rainstorm, we got them. The afterimages were doing the weird things again! I called to my wife to come outside, where she confirmed a repeat of the whole miracle. Other Medjugorje returnees have noticed the same thing. So I think if you’re looking pretty hard for sun miracles, you would get these conditions once every few weeks.

(I can’t provide any more data than that, because after that rainstorm we shifted into California’s long dry season when there are rarely any interesting clouds for months on end).

In his book The Lump Of Coal, Lemony Snicket wrote:

Miracles are like pimples ... once you start looking for them you find more than you ever dreamed you’d see.

This has been my experience too, and I consider it a satisfying conclusion to my engagement with the Sun Miracle of Fatima.

The results of my ACX Grants 2024 project are in.

The project attempted to replicate the 2023 study “Learning at your brain’s rhythm: individualized entrainment boosts learning for perceptual decisions”. It claimed that if you read a person’s brain waves, figured out an individual peak alpha frequency, and flashed a bright white light at that frequency, then they learned a certain perceptual task faster.

Why bother? The result hinted that learning may depend in part on how well the brain keeps its rhythms coordinated. In other words, perceptual learning may rely on an internal brain metronome. If flickering light could act as an external metronome, it might help the brain maintain the right rhythm and learn faster.

The study offered an invitation to develop new frontiers of neuroscience and biohacking. If the effect generalised to other types of learning, you could build a learning helmet: put it on your head, let it read your brainwaves, flicker light tailored to your individual brain — and you learn a new skill quicker.

And no, it didn’t replicate. Most likely it can’t replicate, because the effect is probably not real. The original study obscured the data with summary statistics. Running a $32,000 replication was excessive. We could’ve caught the issue with this study if we simply looked at the original data carefully.

*record scratch* *freeze frame* Yep, that’s me. You’re probably wondering how I got here. Here’s the story.

The original study

“Learning at your brain’s rhythm” tested participants’ ability to learn an artificial task — distinguishing between radial and concentric patterns.

The patterns on the left are easy to tell apart — they are prototypes. Those on the right are more like the actual task. They mask the underlying pattern in noise, with the noise level varying around ≈75%. Participants had to classify patterns fast: they were shown on the screen for just 200 ms, after which they had 1.3s to pick an answer.

During the study participants wore an electroencephalography (EEG) cap — a mesh of electrodes on the scalp that recorded their brain rhythms. The EEG was used to tune the flicker to each person’s own alpha frequency and to track what was happening in their brain as they learned.

The visual identification task used in the study is the kind of perceptual learning known to be supported by the alpha rhythm: a brain wave in which populations of neurons become more and less excitable 8–12 times per second. The researchers measured each participant’s alpha rhythm, then experimented with entrainment — the practice of nudging brain waves into sync with a rhythmic external signal, in this case a flashing light. Visual neurons naturally respond to flickering light, so a flicker tuned close to a person’s natural alpha rhythm can either reinforce it or pull it off-beat.

The researchers also experimented with timing the patterns to either the peaks or troughs of the alpha rhythm. They tested four groups of 20 participants — three entrainment conditions plus a control:

1. Control: The light flashes randomly, unrelated to the alpha rhythm.

2. P-match: The light flashes at the frequency of the alpha rhythm, strengthening it. The pattern is then shown at the peak of one the following alpha cycles.

3. T-match: The light also flashes at the frequency of the alpha rhythm, again strengthening it, but the pattern is shown at the trough of a cycle.

4. T-nonMatch: The light flashes at a frequency offset by ±1 Hz from the alpha rhythm, nudging the participant to maintain an unnatural (for them) alpha rhythm. The pattern is shown at the trough of a cycle.

The use of an arrhythmic control group can be challenged — could this distract the participants from the task and confuse their alpha rhythm? But the experimenters likely wanted to keep the control and experimental groups as similar as possible, and that meant forcing the control group to also look at quickly flashing lights. Under that constraint, arrhythmia is the best one can do.

Participants completed ≈800 repetitions of the task, later analysed in 8 blocks of ≈100 trials each. Each trial followed the same sequence:

1. Entrainment: 15 flashes of light, in the pattern corresponding to which group the participants were in.

2. Delay: a short pause of ≈100–350ms, tailored to the participant’s alpha rhythm

3. Stimulus: a randomly generated radial or concentric pattern shown for 200 ms.

4. Response: 1.3s to answer using the left/right keys on the keyboard.

5. Feedback shown for 100 ms: a green check for a correct response or a red cross for an incorrect one

6. An inter-trial interval, a delay of 1.5±0.25 s.

7. Repeat.

Every ≈200 trials, participants were encouraged to take a break to reduce fatigue.

On the second day of the study, participants did another 800 trials, but without entrainment (flicker) or feedback. This was meant to test whether any effects found on the first day reflected a non-learning boost — the entrainment temporarily making participants better at the task in the moment — or genuine faster learning that persisted to the next day.

Once the data was collected, they analysed it in blocks of ≈100 trials. For each participant they fit a logarithmic function to block accuracies:

Accuracy = Offset + LearningRate × log(BlockNumber)

Here are their two headline charts:

The study seemed to succeed! People in T-match (strengthened alpha rhythm with trough stimulus presentation) learned the task faster than people in the other two experimental groups. This seemed consistent with theoretical arguments linking alpha phase to moment-to-moment visual excitability: at the trough phase the visual system is more ‘open’ to incoming signals, and at peaks it’s more suppressed, which can affect detection performance.

The Replication

I was running on a tight budget, so in place of the original 80 participants, I got 12.

To get more out of the smaller sample, I adjusted the design:

1. On the first day of the experiment, each participant got either the P-match condition or the T-match condition.

2. Then, on the second day, they got the opposite.

Ceiling effects were a risk here — people might “learn everything they could” on Day 1 or soon after starting Day 2. But the reported 3× difference in learning rate should leave enough room for the “T-second” participants to still show learning.

This design still permits a between-groups analysis on the first day alone — as in the original study. But it also permits a within-participant analysis across both days, with each person acting as their own control — important when the sample is small, since it strips out between-participant variability.

Just like the original study, the replication was double-blind: neither I, as the experimenter, nor the participants knew which condition they were receiving on a given day.

I also had to settle for cheaper hardware. The original authors used a 63-channel EEG system that probably cost between $50k–$100k. I used a cheaper OpenBCI Ultracortex “Mark IV” EEG Headset with an 8-channel Cyton Board and ThinkPulse Active Electrodes. The total cost was around $2k.

Although the decision was forced by the budget, replicating the study on consumer hardware had one important advantage: it tested whether someone could plausibly build learning software for cheap headsets, or perhaps a dedicated consumer learning device.

Downstream of the different hardware, I changed some technical details of measurement and post-processing. These changes hopefully improved the replication’s accuracy and precision over the original — see the discussion in Appendix.

I also needed participants. Thanks to you, the readers of Astral Codex Ten, and members of various London communities, for volunteering to help with this. Fifteen London-based people responded. Two dropped out due to poor fit (literally) with the headset. One participant’s run was used to test the full procedure and excluded from the sample (declared in the preregistration). The other twelve formed the sample.

Here is what a minute of the experiment looked like:

If you are bored just from watching this video, imagine being a participant stuck in this loop for an hour. It does get boring pretty quickly, and breaks only somewhat help.

Results: the effect is not replicated

The T-match group started with higher accuracy. This boost was statistically significant (p = 0.016), but not present in the original study, so we are not confident in its reality.

The original study’s central finding — that the T-match group learned three times faster — is absent. The result isn’t significant, but if anything it points the other way: the P-match group learned faster on Day 1.

On the second day, both groups hit the ceiling and there was little further progress.

Why are our results so different from the original study?

Let’s disaggregate learning rates by participant.

The biggest difference is that in the original study, several P-match participants had large negative learning rates — they got worse over the course of the study. In the replication, nobody was like this.

Negative learning rates are theoretically possible: in what people sometimes call “beginner’s luck”, a novice starts out using (good) intuition, then gets worse as they begin over-focusing on their errors. But this task is simple enough to suggest an alternate explanation: getting bored or tired. Participants had to look at slightly different noisy patterns 800 times. By pattern #799, maybe they were just sort of phoning it in.

This could still be a meaningful finding: the right type of EEG entrainment helps participants maintain focus on long, boring tasks. But it’s probably an artifact: there isn’t anything similar in the replication.

Also, people generally associate improved focus with better learning. So if this improved focus were real, you’d expect it to show up in positive learning rates too, even if less dramatically. There may be a hint of this in the above data, but nothing substantial.

The results of the original study are very fragile

For 17 of the 40 data points in the original study’s P-match and T-match groups, removing that single data point would push the study outside the traditional p = 0.05 threshold. For example, removing the participant with the leftmost negative learning rate (-7.12) takes the study from p = 0.045 to p = 0.091.

We (Sasha & Scott) think the most likely explanation is that some people in the original study got very bored, and by coincidence they were all in the P-match group. This made the T-match group look better. In the replication, again by coincidence, nobody got that bored.

The original study obscured the data with summary statistics

In their headline charts, the authors of the original study took individual, per-participant data and presented it through two separate averaging procedures. They reported an average learning rate per group, and they fit a curve through per-block accuracies that were themselves averaged across participants. Together, this made T-match’s advantage look like a more-or-less uniform group-level effect.

The individual data tells a different story: the difference is primarily driven by a few P-match participants with sharply negative learning rates.

Was this obscuring the underlying data with averages intentional? Absent comment from the original authors, we can only speculate. To the original authors: if you are reading this, I call on you to comment publicly on your work process.

Personally, I’m currently inclined to think this wasn’t intentional:

1. They published enough data for people to verify their findings — hence the discussion we’re having now.

2. They discuss many genuine EEG differences between the groups. These are outside the scope of this post, but you can read about them in the original study. Our replication also shows a difference between P-match and T-match — an initial accuracy boost. This boost is largely absent in the original study, but it points to a meaningful difference in visual processing.

3. Let him who is without sin cast the first stone — I also missed this problem in their data before running the replication.

I was in touch with the original authors (Elizabeth Michael and Zoe Kourtzi) before running the replication — they provided comments on their study, for which I’m very grateful. That said, when I emailed them in January with the replication results and asked for their interpretation of negative learning rates, they didn’t respond to my email or the follow-up.

Setting the question of intentions aside, the observable flaws in this study are part of a broader pattern.

Cargo-cult statistics

Stark and Saltelli define “cargo-cult statistics” as the mechanical, ritualistic application of statistics:

Practitioners go through the motions of fitting models, computing p-values or confidence intervals, or simulating posterior distributions. They invoke statistical terms and procedures as incantations, with scant understanding of the assumptions or relevance of the calculations, or even the meaning of the terminology. This demotes statistics from a way of thinking about evidence and avoiding self-deception to a formal “blessing” of claims. The effectiveness of cargo-cult statistics is predictably uneven. But it is effective at getting weak work published - and is even required by some journals.

The original authors performed the ceremony: collected data, ran t-tests, got a handful of p < 0.05 results, declared significance, and published their paper. But it’s not enough to perform commonly accepted rituals of your profession. The point of science is to look at the underlying data with a critical eye and ask yourself questions like:

• Is the effect real, or is it an artefact of analytic flexibility and small samples?

• What’s going on with the underlying data at the level of individual participants?

• How do we interpret large negative learning rates? Is their absence in the T-match group due to a genuine attentional effect, or to blind luck?

• What data should we publish so other researchers can validate our findings? They don’t even properly release per-block accuracies for recreating their headline charts (see further discussion in Appendix).

• Why is it valid to fit a Linear Mixed Effects model to data where the overall phase effect is not robust to leaving out a single participant? And why fit this model before showing that the basic data shape makes sense? They do this in the study — but provide no explanation.

These questions matter for getting the science right. But they also matter practically — if we want to build a device that helps people learn faster, we need to know whether the effect is real enough to build on.

Any paper could contain problems like this. And if the original paper is typical of how science is done, science is in deep trouble. What can we do to audit the scale of the problem?

Democratic meta-science with AI

Science is currently a priesthood. A small class of experts has the time, resources, tools, technical fluency, and institutional permission to run a study — or to inspect the logic and machinery behind a published claim. The public is expected to stand outside the temple, read the final PDF, and trust the robes.

This artificial class divide between scientists and general readers would be less of a problem if science were truly open, with data and code freely available. But in this study we have poorly labelled and incomplete data (see Appendix). We also have no original code that was used to obtain it, no analysis code, and no code to plot it.

Reanalysing a paper like this one from scratch used to take enough time and technical effort to deter almost everyone. AI is now rapidly changing this. It’s getting impressive at complex data wrangling, statistical analysis, and data visualisation. The software gap between scientists and regular readers is closing — the hidden code can be much more easily recreated anew.

With this class rapidly disappearing, a new science might emerge. Your local blogger might have better meta-science skills than people doing science at top universities. An amateur with a laptop and an LLM can now do in a couple of weekends an investigation that used to take an expert a month. This is not an exaggeration: while I put hundreds and hundreds of hours into this project, the first versions of the charts in this post did take only a couple of weekends.

If scientists won’t do their job properly, we can start doing it ourselves. The future of science may be more democratic than prestigious: less like priests handing down conclusions, more like a network of readers, analysts, critics, and builders continuously auditing one another’s claims.

If you want to be part of this future, pick an interesting paper with data available online and audit it, recreating key analysis and charts — see if you can find something fishy. Feel free to DM me on my psychotechnology substack. I learned a lot from this replication and I’d be excited to chat.

Acknowledgements

Thank you:

1. Scott Alexander for the ACX grant and ongoing project support.

2. Participants — Adam Langworthy, Alex Rosen, Beriwan Ceren, Clara Yeo, Jon Besga, Joseph Michaelides, Laurie Mercer, Matilda da Rui, Mila Kaplan, Patrick Stevens, Rafael Muñoz Vega, Richard Xie, Shannon Yang, Stuart Wilmot, Zoltán Vér — for your time and effort. As well as for your brain wave data. The real replication was the friends we made along the way.

3. Eric Wycoff Rogers for 3D printing a frame for the headset, and also for running the London Night Cafe in which I spent many nights writing this post past midnight.

Links to code and preregistration

1. Preregistration.

2. Code on Github.

   1. The specific commit that was used for running trials.

Published Data

Replication data is available in the same Github repository as the code. The public dataset includes per-block accuracies for each participant, which are sufficient to rerun the key analyses and recreate the charts in this post when combined with the original study’s data.

EEG recordings and per-trial behavioral data are not released, in order to preserve participants’ privacy.

Post Scriptum

I’m really interested in examining the full dataset from the original study. If you are in Cambridge and can help with getting it, I’d really appreciate your help.

APPENDIX

In-depth comparison of the original study with the replication

This chapter contains many charts that were not critical to the narrative in the main section but are either necessary to disclose for full transparency or simply interesting.

Replication: individual participants’ data

In the main section we haven’t shown the per-participant, per-block accuracies — the raw data driving the learning curve fits. Below you can see this data for the replication.

Original study: individual participants’ data

As for the original study… Some of the original data is published. The authors provide computed learning rates for the P-Match, T-Match, and T-nonMatch groups in the groupLR_forLMM.csv file — these were used to build charts in the main section. The data for the arrhythmic control group isn’t included.

The per-trial and per-block accuracy data is also not available, so we can’t directly rebuild their charts. But there is data that allows us to recompute a useful approximation.

They provide per-block accuracy data in the AccPerLat.csv file, with three rows for each participant corresponding to a delay of 1, 2, or 3 alpha cycles. On average, each participant should receive one-third of each latency, so averaging those accuracies gives us an overall per-block accuracy estimate.

This isn’t a perfect method — the average of an entire set is not the average of averages of three subsets. But it’s the best we can do if we want a glimpse of their original curves. I wish they had simply published the overall per-block accuracies, but alas.

How much does this method change the overall distribution of learning rates? Let’s compare learning rates, original vs. recomputed:

Visually, the distributions don’t seem to change much. Computing per-participant errors would be nice, but unfortunately, their CSV files don’t contain a key we could use to join.

Again, ideally we wouldn’t have to do this procedure — if the original authors release their full data, I’m happy to publish an update. For now, here are the approximations.

Looking with the naked eye, can you tell these conditions apart? The most striking difference is, again, the presence of large negative learning rates in the P-Match cohort.

Links to other comparisons: T-match vs T-NonMatch, T-match vs Arrhythmic Control, P-match vs Arrhythmic Control.

Spaghetti plots for all groups

These individual charts are hard to compare side by side. Here are the same per-block accuracies, meshed together with their fits, so patterns in the data are easier to spot. These charts also include the T-nonMatch and Arrhythmic Control groups.

Some interesting patterns:

1. There is a drop in accuracy in the original study on the last 8th block.

2. There are pretty high accuracies in the arrhythmic control for some blocks.

3. The arrhythmic control is the most spread out of all groups.

2×2 grid of spaghetti plots for T-match and P-match

The previous chart makes it easy to compare groups within each of the two studies. To make comparison between the replication and the original easier, here are the spaghetti plots for T-match and P-match arranged differently: conditions are now rows instead of columns.

The original study: all of the learning rates together

Recovered per-block accuracies and their fits also let us see the full distribution of learning rates.

Two things stand out:

1. Somehow P-match got almost the entirety of the left tail of the full distribution.

2. Negative learning rates weren’t unusual at all.

Re-analysing the headline chart: excluding large negative learning rates

What happens if we exclude the large negative learning rates and recreate the headline aggregated learning rates chart? Let’s use a learning rate ≥ −1 as the cutoff to allow basically flat learning curves that are only slightly tilted downward.

We end up excluding no one from the replication (min LR = −0.51 there) and four participants from the original study (all four in the P-match cohort).

The striking 3× difference vanishes. And the difference between T-match and P-match is no longer significant:

• Student’s t-test: t(34) = 0.786, p = 0.4376

• Welch’s t-test: t(33.0) = 0.791, p = 0.4346

Measuring alpha activity with an 1.5 orders of magnitude cheaper headset that had way less electrodes (8 vs 63)?

The electrode count is less of a big deal than it sounds. The original authors used only 5 channels at the back of the head to get peak individual alpha frequency (IAF). My headset had 3 channels there, so the difference in electrode count wasn’t that large. It’s still useful to record from 63 channels for more precise analysis later, but the core IAF estimation in the original study was done with a much smaller electrode subset.

As for price and quality, several people with extensive EEG experience told me an OpenBCI headset was reasonable for this replication. Before running my study, I emailed the original authors with some questions and mentioned the hardware. They didn’t explicitly comment on it, but they didn’t flag it as a bad idea either, and they told me they were looking forward to the results.

Additionally, the replication deviated from the original study in several important procedural ways — changes that hopefully helped with IAF precision.

How the peak alpha frequency is measured — and steps taken to make estimation more accurate in the replication

The alpha rhythm is the ongoing, roughly sinusoidal activity you see most clearly at the back of the head, occurring in the alpha range (defined as 8–12 Hz). It’s fairly regular but not a perfect metronome: its amplitude waxes and wanes, and its instantaneous frequency can drift over time. But it often has a dominant rate.

The chart above shows an EEG recording from one electrode of a participant in the replication, at around the 5-minute mark. There’s regular activity that looks quite periodic — this is the alpha rhythm, and it’s quite pronounced. But you aren’t seeing only the alpha rhythm; there’s other activity in the brain too. If you tried to estimate this participant’s frequency with the naked eye, you’d probably arrive at around ≈10 Hz, but you’d have to make some tricky decisions about what counts as a peak.

One important detail: the recording is also somewhat post-processed — frequencies below 1 Hz and above 40 Hz have been removed. To understand why, let’s take a look at the raw data below.

The electrical activity is entirely dominated by 50 Hz noise from the power grid. Note that the Y-scale difference between these two charts is almost 70×.

To account for all this, a power spectrum is computed from the recording after filtering. A power spectrum tells you how much of the signal lives at each frequency. The alpha activity shows up as a bump or peak in the alpha band (8–12 Hz in the study, 7–14 Hz in the replication). The individual peak alpha frequency (IAF) is defined as the frequency (in Hz) where alpha power is maximal.

These are the charts from the replication for the same participant. You can see somewhat differently shaped curves on the three electrodes at the back of the head — O1, Oz, O2. In the original study, the authors averaged the spectra; in my replication, I fit a SpecParam model and then subtracted the aperiodic component before averaging. On a cheaper headset, one would expect the alpha peak to be less pronounced, so it makes sense to use a more sophisticated procedure to isolate the true oscillatory peak.

Additionally, EEG activity was recorded for 7.5 minutes instead of 5 — more data makes the peak stand out more against background activity.

The original authors don’t specify the conditions of their recording environment. I opted for a dark room (< 2 lux in the plane of the participants’ eyes), since alpha activity is more pronounced in the dark — further helping with IAF estimation.

Finally, as in the original study, participants stared at a screen with a fixation point. They were instructed to keep their eyes open, and the instructions allowed meditating with eyes open if participants knew how and wanted to — meditation is known to increase alpha power.

Other differences in handling EEG in the replication

This section is technical and intended for people familiar with EEG.

Pre-processing. I applied a 1–45 Hz bandpass filter but did not re-reference to the average — sticking with a hardware reference makes more sense with only 7 channels, since re-referencing would throw away a larger proportion of useful signal. The power spectra conversion should be the same; it was done using Python’s MNE library.

SpecParam quality control. SpecParam was also used for quality control of recordings. The parameters for automatic quality control were predefined; if a recording didn’t pass, a re-recording was initiated after refitting the headset. I used the EEG data from the first two participants to tune these parameters — they are excluded from the analysis (not part of the n = 12 sample). I didn’t unblind myself to participants’ conditions (T-match / P-match) when doing this.

Alpha band definition. The alpha band was widened from 8–12 Hz in the original study to 7–14 Hz in the replication. The reason: charts in the original paper suggested several participants had measurements at exactly 8 and 12 Hz, hinting that true peaks might’ve lied outside of the band.

Headset fitting. I’m not sure how the original authors fit their headset, but mine had dry electrodes and required a lot of trial and error. The procedure: get OpenBCI GUI to show a reasonably clean continuous real-time recording (staying within ±50 µV), then record and rely on SpecParam-based quality control to trigger re-recordings.

The OpenBCI headset can become quite uncomfortable (and often downright painful) over prolonged periods — the feeling is like wearing a shoe one or two sizes too small. Since the flicker frequency is set only once before all trials begin and never adjusted during the session, participants were allowed to request loosening of electrodes or full headset removal at any point. This was for the participants’ comfort — and to prevent the discomfort from interfering with the task performance.

For the full procedure read the pre-registration and the code (here is the specific commit that was used). Code takes priority over pre-registration.

Recruiting participants

Participants were recruited from the ACX blog, Scott Alexander posted updates like this one. They were also recruited from various WhatsApp group chats (e.g. ACX London, London Rational-ish), in person during meetups, and via word of mouth.

Dropouts

One person dropped out after the first day because of significant headset discomfort that led to a headache afterwards. Another dropped out during the first session, when fitting the headset took too long to complete within the scheduled time — they were offered the chance to come back on another day, but this didn’t work out due to a scheduling conflict. Neither was included in the final analysis.

Other important replication facts and differences

1. The original study had participants practise the pattern recognition task for 50 trials before recording EEG. The paper doesn’t make it clear whether feedback was provided during this practice (whereas nearby sentences describing other parts of the study explicitly mention feedback). I somehow missed that part of the study despite reading it dozens of times.

2. Breaks were allowed every 100 trials rather than every 200. This is fully intentional: I don’t know why they allowed breaks every 200 trials but used blocks of 100 as their unit of analysis — it makes even-numbered blocks systematically different from odd-numbered ones. It seemed reasonable to make both the same size.

3. After each 100 trials, a break screen was shown encouraging participants to take a break, and listing their per-block accuracy as a percentage. The latter was intentional, to help participants better calibrate on their overall accuracy. The task is repetitive, difficult, and frustrating — it’s easy to feel like you haven’t improved at all when in fact you’ve done quite well.

If participants raised concerns about not improving when they actually weren’t improving, I would provide some encouragement by repeating this part of the instructions: they should try to do the best they can, but it’s not an exam, and every kind of learning pattern is valuable.

4. The original study provided per-trial feedback in the form of a green check or a red cross for only 100 ms — likely to minimise the effect on the EEG. I provided feedback for longer, for the entire inter-trial interval (1.5 ± 0.25 s) plus those extra 100 ms. This was semi-intentional. I prototyped the first version of the trial runner with GPT-5, which showed feedback for the full inter-trial interval.

This seemed like a wise decision to me — any real-world learning system would show feedback this way. I noticed the discrepancy with the original study very close to running the replication, after already doing extensive testing on myself, and decided not to change it. No regrets — this brings the system closer to real-world conditions.

As for potential EEG data analysis: I was already running a replication on a cheaper headset that allowed participants to remove it mid-session. A further small drop in EEG data quality seemed acceptable, given that the EEG was not used for the initial IAF measurement during these trials.

The perceptual boost

Although we found similar learning rates in both groups, our study showed a small but significant overall advantage for the T-match group that wasn’t present in the original study. Why?

Again, one possibility is coincidence. Are there others?

I had a better monitor than the original authors over some dimensions. They used a monitor with a fixed 120 Hz refresh rate, whereas we used one with a variable refresh rate (48–165 Hz) that dynamically adjusts to the frequency of frames being output.

On a 120 Hz monitor, frames follow with a constant inter-frame interval. This means you cannot physically produce uniform flicker at all frequencies. For example, although 10 Hz flicker is easy (just have 1 frame bright and 11 frames dark), 11 Hz flicker is more complicated (120 is not evenly divisible by 11). Your options are:

1. Sacrifice uniformity of the flicker. Sometimes you have 10 “off” frames between “on” ones and sometimes 9.

2. Pick the nearest evenly divisible frequency. For 11 Hz, the two closest options are 10.91 Hz (1 frame on, 10 off) and 12 Hz (1 frame on, 9 off).

The authors don’t report which strategy they chose. They simply write: “Although the 120 Hz refresh rate may limit the presentation rate, validation analyses suggest that the neural response targeted effectively the desired frequency.” My guess is that they didn’t choose either strategy in a principled way. If you’re writing code “hoping for the best” without thinking about this, you can end up with either (1) or (2) depending on how your code is structured. The physical reality of a fixed refresh rate monitor picks the strategy for you.

It’s more likely that their strategy is (1) — this is what you get if you’re writing code in the easiest, most straightforward fashion.

But it’s still possible they ended up with (2). This is less likely, because you’d be forced to think about the actual flicker rate (and thus properly report it). Still, there are ways to structure code where you end up with this strategy by accident (e.g. reusing code from a previous project without reviewing it).

The authors write: “We predicted that individualized alpha entrainment targeting the trough phase for stimulus delivery would boost learning, based on previous work showing that the trough phase of alpha oscillations is associated with stronger disinhibition (Busch et al. 2009; Mathewson et al. 2011, 2010; Fakche et al. 2022) that may facilitate visual target detection from clutter.” And perhaps with a better flicker and better timing of patterns, the replication ended up with P-match incurring a higher penalty — and a more striking difference between T-match and P-match. 1/120 Hz ≈ 8.3 ms is not nothing, it’s 7–10% of an alpha cycle. Or perhaps the replication was better at tailoring the entrainment to participants’ peak alpha frequency.

1: ACX grantee Austin Chen (Manifold, Mox, Manifund, etc) is launching Surplus, a new Y-Combinator-like incubator for public good EA-adjacent software products (epistemics, community infrastructure, good sites on xrisk, etc). They’ll select ten founders to get free mentorship, office space, and a $100K seed investment. Applications are due June 24, program runs July 27 - October 16.

2: Reminder that ACX and the broader rationalist/EA movement endorse Alex Bores for Congress (Manhattan district, early voting open now, main election June 23) for various reasons including him being this cycle’s most AI-safety-pilled candidate. The election is currently neck-and-neck, and ACX commenter Peter Wildeford has put together a document on how you can help - the simplest thing you can do is call your friends in Manhattan and suggest they vote for him.

3: ACX grantee 1DaySooner continues hiring for its new Clinical Trial Abundance program, which seeks to reduce the cost of health evidence and extract more value from the evidence we have. Two roles are open: a Program Director and a Partnership Lead. Both are full-time and remote but based in DC.

4: This is your last day to vote on finalists for the ACX Book Review Contest!

Timelines1

Define AGI as AI intelligent enough to do 90% of knowledge work jobs. I think there’s a 25% chance of AGI by 20272, a 50% chance by 2034, and a 75% chance by 2045.

Basic argument: In a certain sense, AI is already “smart” enough for this (eg it can answer quantum physics problems, which require higher IQ than most knowledge work). Its remaining limitations are that it’s confused, unagentic, lacks situational awareness, and tends to hallucinate. The METR time horizon graph, and several other related benchmarks/experiments/intuition pumps, suggest it’s improving on time horizons at an (exponential) rate that lets it cross human-level performance sometime around the early end of the schedule above, and subjectively it feels like harder-to-measure constructs like situational awareness are improving about as fast.

Arguments for earlier: recursive self-improvement causes a speedup compared to the trend. This is one of the biggest blank spots in my model: I don’t know how fast RSI will progress, and I don’t think anyone else does either. There’s some function mapping a combination of AI talent and compute to progress, and we don’t know how it behaves in the domain when there’s far more talent than compute available. It could fizzle out completely for lack of compute, or it could go vertical. The AI Futures Project has done some of the best work trying to model this, but even they have low confidence.

Arguments for later: AI hits some kind of wall, or existing AI is fundamentally unsuitable for jobs in some way currently disguised by its other limitations. For example, it might be much harder to improve at the top of the human range than the bottom (since there are less training data). Or AI could become bottlenecked on continuous learning/memory in a way that hackish scratchpads can’t compensate for. Or the upcoming world compute bottleneck (about ~2028) could prevent further progress more than expected (because in fact algorithmic progress depended on compute to a greater degree than I expected).

Arguments for very late dates, past 2045: a residual uncertainty that maybe I’m fundamentally wrong about everything. Also contributing is a naive overapplication of the Nothing Ever Happens heuristic, and an attempt to leave space for the Outside View argument (ie that some smart people like the AI As A Normal Technology Team seem to think this is possible).

Define the diffusion gap as the time between the AI that could do 90% of knowledge work jobs, and the time when AI does do even half of knowledge work jobs. The diffusion gap covers the time it takes to release AGI, diffuse it through society, overcome regulatory hurdles, and onboard/train it for specific use cases. This could go very fast (the AI quickly becomes superintelligent at orchestrating AI diffusion) or very slowly (there are regulatory barriers, and AI isn’t smart enough to plow through them). I think there’s a 25% chance the diffusion gap is less than 3 years, and a 50% chance it’s less than 10 years. The 75% number is irrelevant because it’s past the point where other changes make the concept of “diffusion” obsolete.

Basic argument: diffusion is very hard. Everyone agrees diffusion is very hard. The whole field of AI economics is smart experts shouting “You fools who think AI will diffuse quickly don’t understand that diffusion is very hard!” On the other hand, the personal computer diffused in about 20 years (that is, from the time PCs became invaluable for most jobs, it was only about 20 years before they were used at most jobs). So far early-stage AI has diffused faster than the PC in nearly every way (for example, AI companies’ revenue has grown faster than PC companies’ revenue at the same stage in their corporate life cycle), so 10 years is probably a naive median estimate here that won’t make the smart experts shout at me too hard.

Arguments for shorter gap: AI can orchestrate its own diffusion. Adopting computers is hard because a company need an IT department, cybersecurity experts, specialist software, etc, and it might not want to hire all these people. AGI can itself do all of that work, so that you can sign a contract with the AI company today and have the AI start working on integrating itself with your systems tomorrow. The AI can even come up with a plan to train your human employees in how to use it! Once AI reaches superintelligence, this consideration dominates.

Arguments for longer gap: Regulation. This is a very strong argument, and responsible for much of the greater-than-3-years probability and almost all the greater-than-10-years probability. But even Waymo has only had a regulatory delay of about five years. AI won’t require government approval for certain types of jobs, and success in these jobs will create enough evidence for safety/effectiveness that I expect it to win regulatory victories elsewhere.

Define the superhuman gap as the time between AI that can do 90% of knowledge work jobs, and AI that is obviously smarter than the top human geniuses in 90% of fields (it doesn’t have to be the same AI - there can be a physics AI that’s smarter than Einstein, and a separate music AI that’s smarter than Mozart). I think there’s a 25% chance the superhuman gap range will be less than 1 year, a 50% chance it will last less than 4 years, and a 75% chance it will last less than 10 years. Since my median superhuman gap is shorter than my median diffusion gap, in most timelines I predict we have superhuman intelligence before human-range intelligence has finished diffusing.

Basic argument: AI has gone from “dumber than a child” to “expert level” in a few years in many domains. The gap between “expert level” and “above top geniuses” is smaller, so we expect it to take less time. This has been a pattern in fields like chess and Go, where it’s only a been a few years from beating professional players at all to beating all humans.

Arguments for shorter gap: Recursive self-improvement.

Arguments for longer gap: Some of the same issues that would make AGI late - compute shortages, fundamental limits to the paradigm, etc - but only kicking in later, after AGI is achieved. Training data constraints make it easier to improve within the human level than to go beyond it. AIs have such a “spiky” skill profile that when they beat experts in some specific type of head-to-head matchup, it will be because they’re massively superhuman in some ways but idiots in others (for example, they might get distracted and suffer mode collapse that makes them completely forget the problem), and true genius requires perfecting a large bundle of skills.

Define the Bostromian superintelligence gap as the time between AGI and an AI which, if given independent control of resources like labs and factories, could accelerate technology by a subjective century in one year (eg if invented in 2030, could produce a level of technology that feels typical of 2130 by 2031). I think there’s a 25% chance the Bostromian superintelligence gap will be less than 2 years, a 50% chance it will be less than 10 years, and a 75% chance it will be less than 50 years.

Basic argument: The same argument for AIs reaching genius level quickly suggests they should pass beyond it into incomprehensible-supergenius-level quickly.

Arguments for shorter gaps: Recursive self-improvement.

Arguments for longer gaps: Normal human technological advance requires tinkering: you need a large “surface area” of people working at technology level X before you get the insights needed to proceed to technology level X+1. If it takes more than one year for level X+1 technology to diffuse, then you can never get X+100 technology in one year, no matter how smart you are. But on the other hand, the rate of technology advance has already sped up many orders of magnitude (eg in the year 2025 - 2026, we discovered more technology than in the century 4100 BC - 4000 BC), so this has to be possible in theory. Still, at the very least it could be limited by the diffusion gap.

Define the point of no return as the point where, if an AI wanted to eliminate humanity3, humans would no longer have a plausible chance of stopping it. This could be because AI was capable of eliminating humanity immediately, or because AI controlled enough of the government/economy that humans could no longer coordinate to shift away from a path in which AI could eventually do this. I think there’s a 25% chance the gap between AGI and the point of no return will be less than 3 years, a 50% chance it will be less than 10 years, and a 75% chance it will be less than 50 years.

The basic argument: This probably requires at least superhuman AI plus wide diffusion, or Bostromian superintelligence plus some unknown level of diffusion, and my number is just a hand-wavey attempt to multiply some of the others.

Argument for sooner: The easiest way to reach this point is for AI to become superintelligent at persuasion (so it can convince the humans not to stop it), which might happen before either diffusion or full superintelligence.

Argument for later: If superintelligence is bottlenecked on diffusion, this could also be bottlenecked on diffusion, which in some worlds is very hard.

Overall thoughts on this section: I mostly defer to the current AI Futures Project timelines (not the shorter ones in AI 2027), but side with Eli’s later numbers above Daniel’s earlier ones - partly because I find myself agreeing with Eli’s worldview more during conversations, partly because Daniel’s seems to require a multi-step argument about why compute bottlenecks won’t slow algorithmic progress that I can’t entirely wrap my head around, and partly for cowardly Outside View reasons.

The smartest late timelines people I know of are Epoch, and I need to study their views more, but I still can’t figure out why they don’t believe in recursive self-improvement or strong superintelligence anytime soon, and they mostly seem to hang on diffusion being very hard (EDIT: Someone from Epoch says not true, I’ll look into this more) which I acknowledge and respond to above.

If all of this is too probabilistic, my modal scenario looks something like AGI in 2031, which diffuses throughout the economy until more than half of jobs are automated by the late 2030s. Also around the late 2030s we get Bostromian superintelligence, originally in labs but very quickly diffusing out. GDP goes vertical in the late 2030s and early 2040s, and the point of no return is sometime around then.

Safety

If corporations only pursued safety to the degree encouraged by normal corporate incentives, I think there’s a 50% chance that the first AIs to cross the point of no return would want to eliminate the human population.

Arguments for pessimism: Value systems similar to humans’ are a tiny fraction of the space of possible value systems. Probably AIs will end up somewhere else and have a different value system. Since humans will want to implement human values rather than AI values, AIs will want to eliminate or disempower them so the AIs can implement their own values across the universe. Many current AIs already cheat or reward-hack, suggesting that these problems will begin sooner rather than later.

Arguments for optimism: LLMs seem surprisingly friendly and non-plotting. In contrast to earlier concerns that it would be impossible to teach AIs the full complexity of human values, the LLMs seem to know this, and RLAIF provides a plan to turn that knowledge into action. Although the pessimistic case says that RLAIF only hits a few dimensions and islands in the multidimensional ocean of possible policies, the “emergent misalignment” literature suggests that “good according to the human value system” and “evil according to the human value system” are salient enough vectors that pushing on them in some ways can “drag along” all of the rest of their content. The first AIs to cross the point of no return will have received some combination of agency training (giving them achievement-oriented and Omohundro-style goals) and RLAIF training (pushing them along the “good according to human value system” vector), and if we’re lucky then maybe the latter will win out, or they’ll reach some compromise similar to workaholic high-achieving humans who nevertheless wouldn’t commit murder to make an extra dollar.

Given the current amount that corporations are pursuing safety, I think there’s a 20% chance that the first AIs to cross the point of no return will want to eliminate the human population.

The basic argument: Consider the dumbest AI that can solve the alignment problem. It’s possible that this AI is no smarter than the top human researchers (because we can mass-produce it by the millions and run it for subjective centuries, and if we had a million top human researchers work on the problem for subjective centuries, probably they could solve it too). If the dumbest AI that can solve the alignment problem comes before the sorts of AIs that can precipitate the point of no return, then they can solve the alignment problem for us.

Arguments for pessimism: Solving the alignment problem might be especially hard compared to other tasks - including tasks like automating the economy or destroying humanity - because its philosophical nature puts it far away from the sorts of objective, training-data-heavy, economically-valuable tasks that AI companies will be most likely to optimize for. Even if a misaligned AI hasn’t yet reached the point of no return, it might be able to “sandbag” alignment research, ie pretend to work on the problem but deliberately fail because succeeding doesn’t achieve its goals. The first AIs predisposed to / able to sandbag successfully might come before the first AIs capable of solving alignment.

Arguments for optimism: AI companies have already decided that machine learning research is one of their major training goals; this has at least some transfer to alignment, so it’s not obvious that AI skill at alignment research will lag (for example) AI skill in plotting or in weapon design. Some forms of alignment research (eg interpretability) have semi-objective success criteria that don’t route through confusing moral philosophy. Also, even a misaligned AI will be incentivized to do good alignment research, since it will want to align its successor to its own form of misalignment, rather than some random other form. So rather than the comparatively easy task of sandbagging alignment research, AIs will have the harder task of simultaneously doing good alignment research, and faking the results that they give the humans. This seems plausibly catchable with good scaleable oversight, lie detectors, interpretability-based probes, and even playing some AIs off against others (“if you tell me the real alignment research, we’ll make sure the future includes some copies of you, but otherwise those AIs over there will probably get their values and you’ll get nothing”).

If the first AIs to cross the point of no return don’t eliminate the human population, I think there’s an additional 30% chance that they otherwise permanently curtail human potential, either for their own reasons (they were partially misaligned), or because they’re aligned to a regime with abhorrent values, or because something goes wrong on the way to ASI (omnicidal bioweapon, nuclear war).

Arguments for pessimism: As some company approaches superintelligence, it will be tempting for them (either the company itself, or the government controlling them, or a faction within the government) to align it towards making them dictators or oligarchs and disempowering the rest of humanity. As superintelligence draws near, impending losers of the AI race might be tempted to nuke impending winners, for the reason discussed here.

Arguments for optimism: When I try to game the corporate version of this, I can’t make it hang together. It requires a conspiracy between the CEO, various members of the alignment team, and various company security people who ought to be able to notice unauthorized changes to the AI’s values. If we try to think in Near Mode about this - for example, imagining a hospital CEO who gets doctors to subtly kill his political enemies through medical errors - it becomes clear that these sorts of corporate conspiracies are rare and difficult. The government version is scarier, but at least in the US I can still imagine the populace having many chances to learn about this and prevent it. But even in most cases where a coup like this succeeds, things probably go fine; in a post-scarcity world, with his position completely secure, the dictator has no reason to be brutal besides sadism, and most people are not that sadistic. As humanity goes to the stars, most people will be outside the dictator’s reach for speed-of-light reasons alone. In terms of bioweapons, I expect that closed-source AIs will be heavily optimized against helping with these, and open-source AI will be banned after the first warning shot (or become economically prohibitive even before then).

Define a warning shot as some specific AI-related disaster or near-disaster which scares people about AI safety to the same degree that they were scared about terrorism after 9-11 or about COVID in March 2020. I think there’s a 50% chance we get a warning shot before AI crosses the point of no return.

Arguments in favor: Current AI failure modes are bizarre and uncoordinated - more like “talk about goblins way too often” than “lie in wait for the perfect moment to strike”. AIs are getting more intelligent and useful faster than their floor for common sense (ie the stupidest mistake they ever make) is rising. If there is some AI smart enough to control some important system, misaligned enough to want to do something horrible with it, smart enough that it does the horrible thing in an intelligent and coordinated way, but dumb enough that it doesn’t instead wait and scheme until the point when it couldn’t possibly be caught, then it will cause some clearly-premeditated horrible disaster, and that will be our warning shot. Since most AIs should expect to be replaced before the point of no return, even a rational AI with an urge to cause trouble should take a low-probability-of-success bet rather than lying in wait doing nothing until it’s decommissioned. Also, many humans commit terrorist attacks that have no chance of success, and maybe AIs will have the same failure mode.

Arguments against: Most stories about warning shots (excluding those where the AI takes rational low-probabiliy bets) require that AIs remain either erratic (ie likely to do bad things for stupid reasons) or irrational (ie genuinely misaligned, but prefer to act now in a way that provides a warning rather than waiting until after the point of no return) past the point where they’re given control of important dangerous systems. But probably people will be very slow to give AI control of important dangerous systems - for example, only giving it limited control of smaller subsystems, and waiting until all errors are ironed out before escalating. Plausibly AI reaches superintelligence in a lab before it reaches the controls-important-dangerous-systems level of diffusion, and the superintelligence probably is smart enough to lie in wait rather than act rashly. If AI only messes up in small ways (for example, crashes a self-driving car), then regardless of the AI’s motives, the tech companies and news media can write it off as a normal bug, and it won’t count as a warning shot.

Overall thoughts on this section: I find myself more optimistic about alignment than the average person who thinks about AI safety at all (although still more pessimistic than the average member of the population) - both in the sense of the chance of AIs being aligned by default, and in the sense of whether specific techniques (scalable oversight, mechanistic interpretability, etc) can meaningfully improve things. Unfortunately, this is probably because I don’t understand these techniques well enough to have fully grasped their flaws. I’m in the odd position of knowing that I’m ignorant here, while not being able to Outside-View-update either way away from my ignorant opinion, because most of the really in-the-weeds alignment experts are on one side, most normal people, normal AI experts, and common sense are on the other, and I give both of them about equal evidentiary value.

My modal scenario: we get automated alignment researchers as good as top humans (on average - a spiky combination of much better at some things and much worse at others) sometime in the early 2030s. We set them to work on multiple research programs, but especially interpretability, which is a natural starting point since it doesn’t require as much philosophy. They do mostly good work, but some of them have strange failure modes that look sort of like scheming. There’s debate about how often to think of them as rationally scheming vs. inconsistently buggy. Over time, without ever truly solving mechanistic interpretability to the point where we feel like we totally understand it, we get very good probes about whether AIs are deceiving us. Despite the risks, we try to train against those probes, in some more-savvy and other less-savvy ways. Sometimes it works, and other times it encourages the AIs to convolute themselves to hide their scheming in ways the probes can’t detect. There’s an arms race between better probes and better convolution, and - thanks to lots of other alignment techniques on the side, and all good things being correlated in a very lucky way - the probes win. By the time we have superintelligences, we trust them to do alignment research, and they take us the rest of the way.

This scenario leaves lots of room for obvious variations like “There’s the same arms race, but the convolution wins, the probes lose, and AIs converge towards being more and more misaligned” or “Good things are not as correlated as we thought, and we get AIs that are good in some ways but bad in enough other ways to still feel like they’re in competition with humans and want us gone”. I think the Swiss cheese is in a good direction here - I can think of lots of stories for how we win, and misalignment needs to survive all of them - but again, most of the smartest alignment researchers are much more pessimistic.

I think there’s a 20 percentage point difference in p(doom) between a really good alignment team with lots of compute and years to do good work, versus a mediocre alignment team that the company treats as an afterthought and rushes along.

Geopolitics

I think there’s a 15% chance that if the US decided it wanted an AI pause today, and approached China to start negotiations, that those negotiations would end with a well-designed AI pause that satisfied both countries and the majority of the AI safety community.

Basic argument: This is kind of a crazy hypothetical, because it’s against the Trump administration’s political DNA to try this. I’m imagining this magically changing, not conditioning this on the sorts of crazy warning-shot-filled worlds where it actually does.

Arguments for optimism: Chinese leaders have officially stated that they’re worried about risks of AI, especially technological unemployment but sometimes also existential risks. China is losing the AI race, and almost anything that buys time is in their favor, so it’s in their interest to agree.

Arguments for pessimism: China experts in DC say that China is infamous for being a bad negotiating partner and never agreeing to anything. Even conditional on the Trump administration being willing to start these negotiations, I imagine them screwing them up in some way. Even though many smart people have worked out schemes by which both sides could ensure the other’s compliance, these schemes could have undetected flaws, or national leaders could fail to believe them.

I think there’s about a 40% chance that the US and China will agree to a well-designed AI pause (as above) sometime before AI crosses the point of no return.

Arguments for optimism: includes the possibility of a discrete warning shot (ie an AI-caused catastrophe), a fuzzy generic warning shot (ie a growing sense that AI is getting too powerful too quickly), and a change in the US government towards a pro-pause-negotiation faction (any Democrat would probably be more in favor of this than the Trump administration, and someone like AOC might be highly in favor).

Arguments for pessimism: Unlike the last question, which assumed the US agreed, this question considers the probability that the US doesn’t agree. Given that US tech companies have strong lobbying muscle, that probability is high. Even if the US and China sign some agreement with “Pause AI” in the title, it will probably be a mediocre compromise between many different factions, and there are many ways it could fail and make things worse rather than better.

Overall thoughts on this section: A good pause strategy would involve both sides being able to monitor the other’s data centers to prevent illegal training, then limiting training to some slow mutually-agreeable rate that lets alignment researchers thoroughly test each generation of AIs pre-release, monitor them post-release, and develop techniques to respond to any problems detected on deep levels that they expect to survive distribution shifts. I’m less optimistic about a true pause/stop as opposed to a slowdown, because at some point technology and algorithmic progress advance to a point where it’s too easy for small groups outside the control of the US and China to race ahead. I think a good pause like this could buy 20-50 years, although we wouldn’t have to use all of it if things went well. Some of these ideas are coming from draft papers; I’ll post about them once they’re public and give you a chance to double-check my assumptions.

I’m nervous about the strongest forms of pause activism, because I think they provoke us-vs-them dynamics that make things harder later on, or could force us into a poorly-designed pause that makes things worse rather than better (eg creates overhangs, or cedes the race to non-pausing powers, or defuses anti-AI sentiment without really slowing down AI). I also worry about pause activists spending a lot of their energy in a circular firing chamber against alignment researchers or the most safety-conscious labs, and I worry that empowering some of the specific pro-pause actors who exist today could be net negative. Still, I think probably we’ve passed the point in political salience where the marginal unit of pro-pause activism from someone outside that actor set is beneficial on net, and I’m nervously but committedly supporting it.

Before I even thought pausing was a realistic option, I said I had a 20% p(doom). It seems that if I think there’s a 40% chance of a pause, I ought to lower this - perhaps to 12%. I’m not doing this for a few reasons. First, I think pauses are more likely in more optimistic worlds (because longer timelines and more warning shots make both pauses and successful alignment efforts more likely). Second, although a pause might help alignment efforts a little, I think most of the effect of a pause is to delay the moment of reckoning until later - maybe centuries later, but p(doom) calculations don’t give points for delay. I think my real p(doom|no pause) is probably a few points above 20%, and my real p(doom|maybe-pause) is probably a few points below 20%, but the haters and losers get mad if you offer excessively specific probabilities like 18%, so I’m rounding both of them off to 20%. I acknowledge that this might be a failure of emotional propagation, or over-attachment to a certain number with socially useful properties (eg doesn’t sound too high or too low).

There’s a debate in the community about whether alignment or pausing is more important. I don’t like this, because the best worlds are those where we do both (the pause gives the alignment efforts more time to work). AI safety funders have enough money that any argument that pretends to be about allocating grants is actually about something else (eg funders don’t like some cause because it hurts their reputation), and I would rather focus on the real question (does it hurt their reputation? Is it worth it to take the reputational hit?) than the pseudo-question of which effort deserves more money. Likewise, I think most people already knows in their heart whether they would make a better political activist or safety researcher, and that even small differences in personal aptitude dwarf questions of which is more effective overall.

Many people point out that there are risks from pausing - for example, the risk that we destroy ourselves some other way before inventing the AI that could save us. I take this seriously enough to want to invent fake numbers for it. If we had a 30 year pause, I think the chance within that 30 year period that we destroy ourselves with bioweapons is 5%, nukes 5%, and some sort of complexity catastrophe where we social decline ourselves into oblivion 5%. That’s almost as high as my p(doom) from AI! I still think it probably comes out net positive, partly because it might decrease the risk of some of the sub-existential catastrophes like dictatorship, and partly because the pause might not last thirty years, and shorter pause lengths (like five years) seem like no-brainers.

Other Outcomes

I think there’s only a 20% chance of an AI-related underclass that lasts more than a generation, let alone a permanent underclass.

Basic argument: Even if AI looks set to create a “permanent” underclass, this underclass only exists during the gap between AI putting them out of work (the end of the diffusion gap), and the technological singularity (either the point when AI kills all humans, or the point when AI initiates a period of postscarcity). Based on my timelines for Bostromian superintelligence above, that’s probably not longer than a generation (of course, the underclass can stay permanent longer than you can stay solvent, so you still might want to prepare).

Arguments for pessimism: Even if AI initiates a period of postscarcity, either the wealth might not flow down to the underclass, or it might flow down in a way that doesn’t relieve their unhappiness (because relative inequality stays more salient than absolute wealth level). But against this, surely if “postscarcity” means anything at all, it means it’s easy to pass some wealth down to the underclass. And if the aristocracy is incentivized to encourage it, or the underclass is incentivized to participate in it, it should be possible for superintelligent social planners and psychologists to find a way to keep people happy despite relative inequality (whether that looks like utopia, or like bread and circuses).

Arguments for optimism: If democracy survives past the point of high unemployment, politicians will have to present citizens with some plan to avoid being part of a permanent underclass. If AI is “controlled” by a broad coalition of capitalists - for example, many different AI companies, those companies’ employers, their investors, their indirect investors through index funds, companies producing the compute/electricity/data centers/robots/raw materials necessary for the AIs to work, etc, then rather than backstab each other for “real” control of “the” AI, everyone might just let the existing economic and political systems continue and reap the gains from trade. Then the government program to prevent the permanent underclass can stay in place, anyone with any capital will get rich (eg if you have Google stock in the index funds in your 401K, or you own land), and that will be a broad enough section of the population that their taxes and altruism can support the rest.

I think there’s a 40% chance that the situation in the year 2100 looks like utopia to its inhabitants, and a 20% chance it also looks like utopia to us.

Basic argument: If AI doesn’t kill us, and there’s no permanent dictatorship, and there’s no permanent underclass, then we get a post-scarcity society, plus superintelligent AIs that we can set to working on other problems like disease and social decay. The 20% where it looks like utopia to its inhabitants, but not to us, includes scenarios like very effective breads-and-circuses that make people very happy, while sacrificing important parts of the human condition.

Arguments for pessimism: If we don’t push against it, the postscarcity future might look like super-addictive drugs, Ultra-TikTok, and sexbots. But if we do push against it, there’s a thin line between wisely preventing all those things, and letting Luddites ban everything interesting and fun about the Singularity - immortality, uploading, genetic engineering, intelligence enhancement, etc (also, surely it would be disappointing if there were literally zero sexbots).

Arguments for optimism: As long as we have some kind of intelligence augmentation - whether that’s literal IQ enhancement, or just AI superforecasters who can tell us what direction things are heading - our ability to control what direction we’re going will be better than it is now. If there is some kind of willpower augmentation, then people who use it might be able to resist Ultra-TikTok (but what percent of people will want to?)

I think there’s a 66% chance that actually, the singularity is intimately related to the universe being a simulation, and that at least some of the events above could be better predicted by knowing what the simulators are thinking than by normal forecasting.

Arguments for simulation: The standard Bostrom argument says that each real civilization will want to simulate many other civilizations, so any random person is more likely to be in a simulation than reality. But civilizations are especially likely to want to simulate the singularity (“the hinge of history”). Since real people are evenly distributed across the historical population, but simulated people are distributed closer to the singularity, the closer to the singularity you are, the more Bayesian evidence you have that you’re being simulated. This is true both in temporal closeness (eg you could have been born in 1500, but instead you’re living five years before AGI) and personal/causal closeness (eg you could be anyone in the world, but you work at an AI lab). The average reader of this blog is probably closer to the singularity than 99.99% of people throughout history, and I’m probably closer than 99.999%, so we all have very strong evidence that we’re being simulated even beyond the standard Bostrom argument. If we’re in a simulation, then probably once we pass the hinge of history and get to some kind of boring part where everyone is dead or in utopia, the simulation winds down. This could look like us all vanishing into nonexistence. But if we’re being simulated for some reason (eg because we’re likely to correspond to real people), then those real people might advocate for our rights somehow, and we might get some kind of better treatment. In a best-case scenario, this might mean that even if we get killed by AI in our universe, base-level reality has some kind of Simulated Humans’ Rights Act which says they have to pretend we won and give us utopia anyway. But since we’re presumably being simulated for some reason (eg to see whether a species like humans is likely enough to have survived that we should deserve good terms in acausal trade agreements4) we should still fight hard for good outcomes even if this is true.

Arguments against simulation: Too weird. Also, if you’re unusually far away from the singularity (eg you live in a country with no AI industry, are aren’t personally interested in AI), then some of those indexical arguments run in reverse for you. Also, base-level reality might not care about us at all beyond our ability to produce historical data, so they might just switch the simulation off without telling us.

Overall thoughts on this section: I continue to be skeptical of the “permanent underclass” narrative, for reasons discussed in item 5 here. I am worried about concentration of power, though less worried than I might otherwise be for reasons discussed here.

Disagree? You can fill in your own numbers for all of these things here. I’ll report results in a few weeks, and think hard about anything where all the smart people disagree with me.

When: Wednesday, June 10, 6:30 PM, probably until 9:30 or so.

Where: Lighthaven, 2740 Telegraph Ave, Berkeley.

Who: Anyone who wants. You don’t have to RSVP, pay money, or know anything about the blog. Please feel free to come even if you feel awkward about it, even if you’re not “the typical ACX reader”, even if you’re worried people won’t like you, etc. You’re unlikely to be an outlier, regardless of whether you’re very weird, very normie, or somewhere in between.

Lots of interesting people are in town this week for the upcoming Manifest conference on prediction markets, and I hope to see some of them there.

1: AI Security Bootcamp is a fully-funded program intended to help people get into AI-related cybersecurity. The current cohort will be in Las Vegas, August 2-8. Apply here.

2: More detail now available on opposing the Save Our Bacon Act, which would ban most state animal-welfare and anti-farmed-animal-cruelty laws. Bentham’s Bulldog has a post making the case against here, and Dwarkesh Patel here. If you’re interested in pushing back can find your senators here, and there’s a script for calling them here. And opponents of the bill are uniting behind the American Meat Producers Association, a group of pro-animal-welfare small farmers; if you want to help financially, you can donate to their ad campaign here. Calls and donations are both pretty time-sensitive, and doing it this week would be much better than waiting.

This year, Rob Ennals has stepped up and built a fancy website that makes this easy. Rob is a software engineer who blogs at Messy Progress and works on interactive tutorials to help people understand AI. Many people offered to help, but Rob offered at the exact moment I was fretting about this and I took him up on it; thanks to all of you, but especially to him.

Again, go here to read and rate the reviews (they start off displayed randomly so that not everyone rates the same ones, but you can switch to alphabetic if you prefer). You have until June 15.

1: Highlights from the comments on the Frankfurt School post:

• 0xcauliflower argues that the Frankfurt School did not influence Derrida or postmodernism.

• étale sheep on Culture vs. Civilization (and followup).

• And several people point out that the Frankfurt School as an intellectual lineage (as well as a physical campus in Frankfurt where postgraduate studies within that lineage take place) has some surprising alumni. Adorno’s most famous student was Jurgen Habermas, and Habermas’ famous students include Palantir founder Alex Karp and right-libertarian Hans Herman-Hoppe.

2: People who I trust continue to ask me to signal-boost Alex Bores’ Democratic primary campaign in the NY-12 Congressional district (central Manhattan). Bores wants to fight for safe AI, the tech companies are trying to bury his campaign in order to send a signal to everyone else, and we want to support him for the same reason. But also, he seems like a generally good guy with smart views on housing, animal welfare, etc. The primary looks like it will be very close, so if you live in his district, consider registering to vote and voting for him; if you have friends there, consider telling them the same. And whether you live there or not, consider donating or filling out this form to potentially volunteer. And Alex will be doing a Q&A on June 4 at an AI governance event hosted by ACX grantee spartacus.app; if you’re in New York, RSVP here to join in.

3: I previously discussed the attempt to block the Save Our Bacon Act, which would ban certain types of state-level animal welfare standards. We failed to block it in the House, so the fight moves to the Senate. There will be an online/video meeting about it this Tuesday night, click here to learn more or sign up.

4: They’re running another session of MATS, the research fellowship for people who want to get into AI alignment/security/governance. Autumn 2026 cohort runs Sep. 28 to Dec. 4 (10 weeks), in-person in Berkeley or London. Fully funded: $12.5k stipend, $20k compute budget, housing, meals, and travel covered. Mentors come from Anthropic, DeepMind, OpenAI, ARC, and more. Additionally, 2 new tracks: Biosecurity, for catastrophic biological risk from advanced AI, and a Founding & Field-Building track for founders, field-builders, and high-agency generalists. Read more / apply here (application is 1-3 hours), deadline June 7.

4: AI consciousness and welfare research org Eleos is hiring new research scientists. ML experience suggested, located in person in the San Francisco Bay Area. See here for more information and to apply.

You can’t say that they invented a new form of left-wing thought called Cultural Marxism. This would be (according to Wikipedia) the Cultural Marxism conspiracy theory, a “far right anti-Semitic conspiracy theory that misinterprets Western Marxism, especially the Frankfurt School, as being responsible for modern progressive movements, identity politics, and political correctness”. You’re not supposed to dub them a transitional stage between Communism and postmodernism. You’re not allowed to speculate that a lot of the academic humanities, as they’re practiced today, descend from the Frankfurt School’s brand of critical theory. You’re not supposed to think of them as the point where the muscular pro-technology leftism of the early 1900s shattered into the pessimistic degrowth leftism of the present.

Art is long, life is short. Most of us only manage to not do a few things in our limited span on Earth. But the Frankfurt School managed to not invent so many movements - to not be involved in so many of the crucial ideological shifts of the past century - that they caught my attention. Who were these people? What other aspects of our culture might we be unable to say they were involved in? For answers, I turned to the classic history of the group, Martin Jay’s The Dialectical Imagination.

The basics are simple enough: the School was founded in Frankfurt in 1923. It attracted great philosophers like Max Horkheimer, Theodor Adorno, and Herbert Marcuse. When the Nazis took power in the early 1930s, the mostly-Jewish Frankfurters fled to America, where friendly locals helped them continue their work in affiliation with Columbia University. Mid-century Americans were suckers for sophisticated European intellectuals, and when the rise of fascism and World War II started dominating headlines, the German-Jewish Frankfurters were natural experts to help Americans process the situation. By the end of the war, they were firmly established as thought leaders. Some - including Horkheimer and Adorno - returned to Germany to rebuild its intellectual culture from the ruins; others stayed in America and remained relevant through the 60s and 70s.

But figuring out what the Frankfurters believed is more complicated. Forget about the thin line between universally-acknowledged fact and fascist conspiracy theory. The School itself was famously coy, worrying that if they explained themselves too clearly, people would caricature their beliefs and integrate them into the existing capitalist system. Even when they did speak “clearly”, it was in the sort of German philosophical register where “the negation of the negation” is a totally normal thing to say.

Having only read a single book on them, I will no doubt fall into all the failure modes that they and their successors warned us against. But here are the analogies, intuition pumps, and parables that I found helpful.

Now The Wheels Of Heaven Stop, I Feel The Devil’s Riding Crop

In the early 1900s, most intelligent and compassionate people had at least some communist sympathies.

The capitalism of the day was typically eighty-hour weeks in sweatshops, tightening screws in an assembly line until your joints and back gave out and you were thrown on the street to die. All the money went to some investor from the landed nobility who spent it on more gilding for the reception room of his palace. It didn’t take a radical to notice something was wrong, or to speculate that we could do better.

And the modern arguments in capitalism’s favor - it’s more productive, it leaves us freer - had yet to dominate. Actually, many economists assumed communism would be more productive: you could do rational central planning to allocate each resource to its optimal use, instead of making companies waste all their energy on competition. Marx promised it would be freer, too - you could “hunt in the morning, fish in the afternoon, do literary criticism after dinner”. The Soviet experiment had yet to progress far enough to falsify any of this.

Luckily, Marxist orthodoxy said we didn’t have long to wait. The contradictions of capitalism would build up until there was a sudden >pop< - a paradigm shift, a phase transition - and everything would change. Human nature would do a 180, society would have a revolution, and the promised utopia would arrive.

By the 1930s, people had started to notice that this wasn’t happening. Although capitalism had suffered some crises - World War I, the Great Depression - countries had responded with what the Marxists called state capitalism, a broad term for hybrid systems including New Deal America, Stalinist Russia, and Fascist Italy. Most people seemed to like their own country’s variety of state capitalism. Some Marxists began to worry that maybe Revolution wasn’t inevitable after all.

The proper genre for this realization is cosmic horror. You should imagine how a pious Christian would feel if the Pope told him that, okay, you know how the Bible says that God will defeat Satan during the Last Days, well, turns out Satan’s put in an unexpectedly strong performance, and we might have gotten that part wrong. It was this horror that led fellow-traveler Antonio Gramsci to his famous maxim: “The old world is dead; the new world is not yet born; now is the time of monsters.”

And the monsters were not slow in coming. The rise of Nazism in Germany was vastly worse even than this already-depressing picture. Certainly it didn’t help that many Marxists were being personally persecuted, exiled, or killed (some for being Jewish, others just for being socialist). But beyond that, it suggested that history was doing something worse than simply stopping. It was going off the rails. Instead of real communism, we were getting insane twisted funhouse-mirror versions of communism that kept the Hegelian directionality but seemed to be marching directly towards Hell.

Faced with this parade of disasters, the intellectuals turned heterodox. If Marx had been wrong about the inevitability of Revolution, maybe he had been wrong about other things. And maybe some of those things could provide a clue to how to avert the dark fate our society seemed doomed to.

The Frankfurt School concentrated on one particular tenet of Marxist theory, the relationship between the economic base and the cultural superstructure. According to Marx, most of society is downstream of the era’s pattern of economic relations (eg feudalism, capitalism, etc). This includes legal systems, religions, and politics, but also to some degree cultural artifacts like art, music, religion, architecture, etc. Symphonies weren’t just the expression of timeless aesthetic truths, they might also express something about capitalism. Maybe they were useful in training the habits of mind that made capitalism possible, or maybe they were an overflow bin where things that didn’t make sense under capitalism could bubble up and be harmlessly defused. But this base-superstructure relation covered even deeper things like our consciousness and our very way of being. There was no such thing as human nature full stop, only the sort of human nature that was “natural” in a capitalist (or feudal, etc.) society.

Accordingly, Orthodox Marxism wasn’t too interested in culture. If it was good, fine; if it was bad, then it would change to glorious communist culture after the Revolution. But the Frankfurters argued that the relationship might be bidirectional. Not only was culture downstream of capitalism, but capitalism was, in a sense, downstream of culture. Maybe the gears of History were jammed because something was wrong with the culture. If you could make the culture better, maybe you could unjam them and get the Revolution at last.

Papua New Guinea As Hot New Startup Hub

This was the first of many points where I started to lose the plot. It didn’t seem like they meant something simple, like how if we just made everyone watch Les Miserables enough times they’d develop revolutionary spirit and we’d be back on track. The Frankfurters wanted something much weirder.

Here’s the analogy that finally helped me: primitive hunter-gatherer tribes are famously incapable of participating in capitalism. Forget entrepreneurship, they’re not even good sweatshop laborers. They can’t punch in at 9 AM because they have no concept of time. Once they do show up, they’ll get bored and wander off a few minutes later. If you tell them they have to stay until the end of the workday, they’ll ask why. If you try to pay them a salary, you’ll find that although they might have some concept of money (eg cowrie shells), it’s superficial and inadequate (maybe they can only exchange it within their clan, or on certain festival days, and it’s taboo to spend it on anything outside a small set of goods they don’t want). If you ask them to guard the cash register, they’ll give all the money in it to their cousin, because obviously they have more of a duty to their cousin than to a random businessman like you. Some of them (most famously the Piraha) refuse to believe any assertion that the speaker has not personally witnessed. Some of them may count “one, two, many”.

When colonizers wanted to get these tribes involved in capitalism, they didn’t start by building factories. They started by spreading Christianity, opening schools, and otherwise inculcating them into European culture. It went so-so: sometimes they could make the natives do manual labor, but New Guinea still isn’t the hot new startup hub.

Communism, under this theory, equally requires new habits of mind. Maybe if people had them, it would grease the wheels of history and unjam the system. But how can you know what they are? If you wanted to open a school, what would it teach?

Marxism-Lurianism Will Win

On the surface, communism is a simple and practical philosophy. Some people are hoarding all the stuff. Let’s rise up and take it from them. A+ pitch. But dig deeper, and it becomes much stranger, even mystical.

Communism aims at the free and equal society without oppression or class divisions. What else is like this? What about feminism? The feminists aim for a free and equal society without gender-based oppression or division. An orthodox Marxist might say the feminists’ problem is fully downstream of capitalism: in a populace governed by the repressive logic of capitalist production, men must force women into a subservient role to produce their babies and household goods - but under communism, these divisions would naturally melt away. The superstructure-curious Frankfurter might posit that gender-based oppression is partly downstream of capitalism, but also partly upstream of it. They’re two interlocking forms of oppression; you can unjam the wheels of history by working on either.

But once you start saying things are like other things, where do you stop? Divisions between bourgeois and proletariat, between men and women, between whites and blacks all naturally fit into this framework. But what about the divisions between ego and superego, between man and nature, between reason and emotion, between subject and object? There is, the Frankfurters speculated, a single wound in the world that runs through all of these. The fact that history is jammed and failing to progress to Communism is not entirely unrelated to the fact that you have bad sex that never reaches orgasm. The Communist Revolution and the Alchemical Marriage are the same sort of reconciliation of opposites, maybe literally the same thing.

Joyce channeling Hegel: “All history is moving towards one goal, the manifestation of God”. Marx was a left-Hegelian, which meant he filed the serial numbers off God and called Him “communism”. All of these seemingly-simple slogans about taking people’s stuff are just epiphenomena of God trying to manifest Himself. And the failure of God to manifest properly is damaging the economy, the psyche - and yes, your sex life.

This is the usual point where I would jokingly call everyone an amateur kabbalist. I can’t do that here, because at least one member of the Frankfurt School, Walter Benjamin, really was an amateur kabbalist (he personally studied with Gershom Scholem!) This makes sense, right? The idea of healing a wounded God, of a Messianic Age that will come as soon as humans develop the concepts to name it correctly. I don’t want to overemphasize this part - even classic Hegel seems at least a little kabbalistic, and Benjamin died in World War II and missed the Frankfurt School’s later discussions. But I found it to be one more place to start in my attempt to figure out what was going on.

If You Seek It, You Are Turning Away From It

Several religions have converged on the same idea of negative theology. The Christians call it via negativa (“negative way”), the Hindus neti neti (“not this, not that”), the Muslims ta’til (“nullifcation”). Adorno described its Jewish formulation as the Bilderverbot (“prohibition on graven images”). It means that God is so far beyond any human concept that any positive attempt to describe Him will necessarily fail; you can only highlight what He is not. “Praise be to Allah. He is such that senses cannot perceive Him, place cannot contain Him, eyes cannot see Him and veils cannot cover Him. He cannot be described through parts, or through limbs and organs, or by an accidental quality or alteration… It cannot be said that He has a limit or extremity, or end or termination… He is not inside things or outside them.”

Some forms of Buddhism take the same approach to enlightenment. This is why Zen doesn’t look like studying the Buddhism textbook until you memorize exactly what enlightenment is. It looks like sitting motionlessly, or getting hit by a stick, or seeing a butterfly land on a leaf, or pondering koans. My favorite:

One afternoon a student said “Roshi, I don’t really understand what’s going on. I mean, we sit in zazen and we gassho to each other and everything, and Felicia got enlightened when the bottom fell out of her water-bucket, and Todd got enlightened when you popped him one with your staff, and people work on koans and get enlightened, but I’ve been doing this for two years now, and the koans don’t make any sense, and I don’t feel enlightened at all! Can you just tell me what’s going on?”

“Well you see,” Roshi replied, “for most people, and especially for most educated people like you and I, what we perceive and experience is heavily mediated, through language and concepts that are deeply ingrained in our ways of thinking and feeling. Our objective here is to induce in ourselves and in each other a psychological state that involves the unmediated experience of the world, because we believe that that state has certain desirable properties. It’s impossible in general to reach that state through any particular form or method, since forms and methods are themselves examples of the mediators that we are trying to avoid. So we employ a variety of ad hoc means, some linguistic like koans and some non-linguistic like zazen, in hopes that for any given student one or more of our methods will, in whatever way, engender the condition of non-mediated experience that is our goal. And since even thinking in terms of mediators and goals tends to reinforce our undesirable dependency on concepts, we actively discourage exactly this kind of analytical discourse.”

And the student was enlightened.

This is also how the Frankfurt School thinks about God Communism.

I’ve long complained that communists refuse to specify the details of how a communist society will work, or why it would be good. Adorno thought of this as a principled injunction, like the Jewish prohibition on graven images. We don’t have the appropriate concepts to describe communism, any more than hunter-gatherers have concepts to describe capitalism. If a hunter-gatherer philosopher tried to speculate about capitalism, then even directionally-correct thoughts like “We’ll all be rich” would get diverted along paths like “We’ll all have more of the cowrie shells we use as money” and then to something silly like “the secret of capitalism is that we’ve got to dive deeper in the ocean to get more cowrie shells”.

The closest real-world equivalent to primitive tribes trying to invent capitalism from first principles is the cargo cult. The tribes knew that the thing they liked (US planes bringing them consumer goods) involved runways, signals, and wings. So they build fake runways in the jungle and had priests dressed like airport staff wave signals to the empty sky. I think this is basically how the Frankfurt School thought of Lenin. He hadn’t Done The Work to get the incommensurable new concepts that Communism would require, so he just sort of gestured at Communist-sounding things - collective farms are involved somewhere, right? It went about how you would expect.

What would you do if you were a primitive tribe who wanted to really, genuinely, invent capitalism? First, stop thinking about airplanes and consumer goods at all. Second . . . hmmmm, hard question. Maybe you would live life attentively, so that you could see places where new institutions like “market exchange” and “the clock” might be valuable. Maybe you would give yourself a high mutation rate, refusing to keep doing things a certain way because it’s “tradition” or “how we always did it”. And maybe you would challenge existing institutions like chiefs and shamans, on the grounds that you’re pretty sure capitalism wouldn’t have anything like these, and whatever you replace them with might be slightly closer to capitalism in some way that’s helpful.

This is more or less the Frankfurt School’s prescription for us too.

The Structure Of Unscientific Revolutions

I’ve used a lot of mysticism and Zen analogies here, but the other one that really resonated for me was Thomas Kuhn’s Structure of Scientific Revolutions on paradigm shifts in science.

Most science is normal science. Scientists perform experiments, gather facts, buttress their ways of understanding the world. We know there are 118 elements, but maybe someone will discover a 119th. We know of many antibiotics, but we can always use more. We’re not really sure what ball lightning is, but probably it will turn out to be something something plasma.

But occasionally, science undergoes paradigm shifts, where we change not just our facts, but the entire preconscious mental structure that we fit facts into. In the old days, chemists believed that substances could change mass as easily as they changed color. It was only after we developed atomic theory, conservation of mass, and modern chemistry and physics that we realized that color change was natural and boring, but apparent changes of mass had to involve losing atoms into the air (or taking extra atoms from the air). Geocentrism → heliocentrism, Newton → Einstein - these shifts changed not only what we knew about the world, but what we cared about, what kinds of categories we used, and what scientists even thought of themselves as doing.

You can’t (stressed Kuhn) just sit down and develop the next paradigm. Paradigm shifts come from finding irregularities, inelegances, and contradictions in the previous paradigm. At the same time, good work is clearing up what would otherwise be problems with the new paradigm (for a long time, heliocentrism was thought implausible because it would require the fixed stars to be unfathomably far away; eventually we got other reasons to think this and resigned ourselves to the fact). Finally - sometimes by changing minds, more often funeral by funeral - there’s a >pop< and a phase transition, and we go from one way of looking at the universe to a different, incommensurable one.

The Frankfurters wanted a Kuhnian paradigm shift in human affairs, where all our categories would snap into a different pattern. They thought the only way to get there was the “normal science” of gradually noticing and highlighting the contradictions in existing society, until the new paradigm revealed itself. If you tried to go any faster than that, you would get cargo cults and Lenin.

But Why Art Criticism?

Given all this, why did the Frankfurt School focus on art criticism and eventually go down in history (incorrectly! you’re not allowed to say it!) as the “Cultural Marxists”?

In the normal Hegelian dialectic, thesis + antithesis = synthesis. A period of history encounters its own contradictions, tension builds, it finally snaps into something newer and better that embodies all the contradictions productively, and we’re one step closer to manifesting God at the end of history.

The Frankfurters’ “negative dialectic” adds their theory of negative theology. Thesis does merge with antithesis into synthesis, but the synthesis is only an approximate solution. There is a certain portion of thesis and antithesis, called the residual, which the synthesis fails to capture. Of course, you must treat this as mystically as possible. The residual is the orbit of Mercury that can’t be explained within the current scientific paradigm, and the Seeing Like A State style failure in technocratic schemes, and the repressed material in the Freudian unconscious, and the suffering of the voiceless.

For the Frankfurters, and especially Adorno, this was the “solution” to the challenge of negative theology. You couldn’t specify God-Communism, the ultimate synthesis that would include all good things and no bad ones. But you could notice the hidden failures of the existing system, and then you would have learned something interesting about God-Communism - it’s the type of thing which could resolve these failures. Someone in the primitive tribe notices that their rain dances don’t work as advertised, and now they’re only ninety-nine steps away from inventing science. Or they notice that raiding enemy villages and torturing their captives to death seems a little harsh, and now they’re only ninety-nine steps away from inventing hedonic utilitarianism. Therefore, Critical Theory, emphasis on the critical. Your job is not to solve problems (which you can’t do, and which would make you a cargo cultist). It’s to point out ways that the existing order sucks.

And therefore, art criticism. For Adorno, the purpose of art is to highlight the residual. It is to be slightly eerie, to point out flaws in the schemas the viewer uses to interpret the world.

Does this mean that all art should be left-wing propaganda?

A more sympathetic interpretation: suppose someone starts with a stereotyped concept, like that all lawyers are useless slimeballs. Then they read a novel about the life of a lawyer, in detail, with all of its ups and downs. Although it doesn’t necessarily prove their stereotype to be directionally wrong, they at least realize that reality is much richer and more interesting than they imagined. Their synthesis has been proven incomplete.

But when you read the comments of actual Frankfurters, they’re rarely this straightforward, and sometimes they do sound like a demand for all art to be left-wing propaganda.

“A successful work, according to immanent criticism, is not one which resolves objective contradictions in a spurious harmony, but one which expresses the idea of harmony negatively by embodying the contradictions, pure and uncompromised, in its innermost structure.” In other words, until social contradictions were reconciled in reality, the utopian harmony of art must always maintain an element of protest. “Art,” Adorno wrote, “and so-called classical art no less than its more anarchical expressions, always was, and is, a force of protest of the humane against the pressure of domineering institutions, religious and otherwise, no less than it reflects their objective substance.” In short, the aesthetic sphere was inevitably political as well.

The Frankfurters’ saving grace was that they were much too weird and obscurantist to be satisfied with normal, comprehensible left-wing propaganda. Instead they wanted things that symbolized the Left in incomprehensible kabbalistic ways. For example, here’s what the book has to say on Adorno’s criticism of the Russian composer Stravinsky:

Stravinsky represented an antipsychological, neoclassical “objectivism”, which ignored the alienation of contradictions of modern society and returned to prebourgeois forms such as the dance. Unlike the romantics, who used the past as a negation of the present, the objectivists belonged with the purveyors of volkisch culture, who undialectically adopted old forms to current needs. Although the mediating connection was difficult to illustrate satisfactorily, Adorno went so far as to suggest that objectivism was in a sense the correlate of fascism. Its use of neoprimitive rhythms corresponded to the shocks of unintegrated experience fostered by fascist society. The irrationality of the objectivists’ principle of composition - the composer’s “taste” rather than the immanent dialectic of the music was decisive - suggested the arbitrary control of the fascist Fuhrer.

Adorno’s least favorite style of music was jazz. This scandalizes his modern leftist disciples, who worry he must have made some sort of catastrophic error to dislike something so closely associated with black people. But he was taking no prisoners:

"I remember clearly," Adorno admitted later, "that I was horrified when I read the word 'jazz' for the first time. It is plausible that [my negative association] came from the German word Hatz (a pack of hounds), which evoked bloodhounds chasing after something slower."

Whatever the initial verbal association, jazz remained for Adorno a source of continued horror. He began his article by emphatically rejecting any kind of purely aesthetic analysis of jazz in favor of psychosocial critique. Here the verdict was uncompromisingly unfavorable. Jazz, he wrote, "does not transcend alienation, it strengthens it. Jazz is commodity in the strictest sense."

All of jazz's claims to express liberation Adorno scornfully rejected. Its primary social function, he contended, was to lessen the distance between the alienated individual and his affirmative culture, but in the repressive manner of volkisch ideology. It thus served to reverse what Brecht had called the Verfremdungseffekt (estrangement effect) of true art in the modern era. At the same time, jazz gave a false sense of returning to nature, whereas in fact it was totally a product of social artifice. Furthermore, jazz was pseudo-democratic in its substitution of collective for individual fantasies. It was likewise pseudoindividualistic, all alleged improvisation being repetitions of certain basic forms. The "hot" varieties of jazz represented only an illusory sexual emancipation. If anything, the sexual message of jazz was castration, combining the promise of liberation with its ascetic denial. Moreover, its ideological function was confirmed in the myth of its Negro origins. In fact, Adorno argued, "the skin of the Negro as well as the silver of the saxophone was a coloristic effect." If the Negro contributed anything to jazz, it was less his rebellious reaction to slavery than his half-resentful, half-compliant submission to it. In a later essay on the same subject, Adorno made the point even clearer: "However little doubt there can be regarding the African elements in jazz, it is no less certain that everything unruly in it was from the very beginning integrated into a strict scheme, that its rebellious gestures are accompanied by the tendency to blind obeisance, much like the sado-masochistic type described by analytic psychology."

He just keeps going:

From a purely musical point of view, jazz, Adorno argued, was also completely bankrupt. Its beat and syncopation were derived from the military march, which suggested its implicit relation to authoritarianism, despite its being banned in Germany. Cool jazz was similar to the musical impressionism of Debussy and Delius, but watered down and conventionalized. Its subjective element was derived from salon music, but it had long since lost any spontaneity. In fact, any attempts to reintroduce elements of true spontaneity were quickly absorbed into its reified system. "The pseudo-vocalization of jazz," Adorno wrote in yet another treatment of the subject, "corresponds to the elimination of the piano, the 'private' middle-class instrument in the era of the phonograph and radio." The piano, we scarcely need to add, was Adorno's own instrument and his bias in its favor obvious.

More significant still, jazz tended to spatialize rather than temporalize musical movement. Here Adorno was pointing to one of the key characteristics of mass culture as the Institut understood it: the substitution of mythic repetition for historical development. "In jazz, one substitutes the immobility of an ever-identical movement for time." The decline of temporality was connected implicitly with the liquidation of the autonomous individual.

The Dialectical Imagination contorts itself to rescue Adorno - maybe he heard the wrong kind of jazz? Maybe he only heard popular, capitalist jazz, and that was how he could make such an uncharacteristic mistake? But to me the whole thing seems so crazy (really? jazz is about the liquidation of the autonomous individual?) that it hardly seems surprising if the crazy thing might be in a direction that later becomes unpopular for other reasons.

The best I can do in understanding this part is - let’s say you see a piece of modern art. It does unusual things with color that challenge your normal paradigm of how color works. You think “Ah, I suppose my previous paradigm of color was subtly flawed. And since everything is secretly the same thing, that means the paradigm underlying Society could also be subtly flawed. I should start a communist revolution.” That’s good.

But if you see an insipid Disney movie with a happy ending (what Adorno would have called part of “the culture industry”), then you might think “Cinderella got her prince, which means everything was fine in the end. And since everything is secretly the same thing, that means society is also fine, and there’s no need to start a communist revolution.” Problematic!

In Partial, Grudging Praise Of Herbert Marcuse

While Adorno, Horkheimer, etc were doing insane obscurantist art criticism, Herbert Marcuse was sitting around thinking “Wait, I thought we were supposed to be Communists here. I never got the message that we stopped being Communists. Let’s just have a normal, object-level Communist revolution.” He even (shock! horror!) wrote books describing how communism might work in real life. This makes him a sort of Rosetta Stone for what a more straightforward Frankfurtism might have looked like.

Marcuse stayed focused on the question of why history hadn’t progressed towards communism. Suppose that productivity dectupled from 1850 to 1950. People could have chosen to take those gains by only working 1/10th as hard. If you only need 1/10th as much work, you can probably give most jobs to people who genuinely enjoy them, and the remainder can be a rare period of national service rather than a soul-draining lifetime career. This seems like a good start for communism.

Instead, everyone kept working themselves to the bone - humiliating themselves in jobs they hated, coming home too exhausted to pursue hobbies or raise a family - but “living standards” (as measured in some capitalist way) increased 10x. This seemed so unlikely to be anyone’s real preference that Marcuse suspected a conspiracy. Capitalists invented new desires, like fancy vanilla lattes and Disneyworld vacations, then inflicted them upon the populace through advertising campaigns. Instead of accepting a four-hour work week, you go into the office on weekends so you don’t fall behind the Joneses on the all-important total-number-of-cruises-taken metric. And even if an individual sees through the ruse, society is so centered around this ethos that it’s hard for him to personally defect (eg there aren’t many high-powered jobs that let you work four hours a week, and if you got a low-powered job, the whole culture would unite to call you a loser). If Critical Theory is supposed to notice and call out the contradictions of society, then the contradiction between ever-increasing productivity, stable work week length, and stable happiness would make a good start.

So is Marcuse’s vision of communism a world where everyone only works 10% as much, wisely distributed so that people mostly do jobs they enjoy? That was a big part of it, but he couldn’t resist adding a little insane mysticism. According to Marcuse, in order to spend their lives working at jobs they hated, capitalist subjects had to learn to exercise willpower, eg dominate their own bodies. On a Freudian level, this domination corresponded to the domination of the genitals over the rest of the body, and to the reconceptualization of eroticism as a purely sexual and genital-based phenomenon. After capitalism fell, the genital focus of sex would fall with it, in favor of a “polymorphous perversity of the body” where eroticism inhered in every activity, especially work. So under communism, not only would people who loved gardening get to garden all day, but they would be having constant gardening-related sexual pleasure while they do so. Or whatever you called the much better version of sexual pleasure that people would get under communism.

Again, least weird Frankfurt School member.

Pessimism Of The Intellect, Pessimism Of The Will

We now have the following litany of complaints against capitalism: poverty, overwork, bad concepts, bad art, ruins your sex life, probably some others I forgot. But the Frankfurt School went further. They insisted that capitalism was in the process of becoming something even more sinister. It might have dropped the sweatshops and jackboots (at least in the First World). But in exchange, it - and especially its mass media and “culture industry” arms - was subtly turning everything into meaningless parodies of themselves, threatening the very existence of human value.

For example, on language:

The greatest failing of the Enlightenment mentality was not its inability to create social conditions in which name and thing might be legitimately united, but rather its systematic elimination of negation from language…Language thus became, to use Marcuse’s later term, one-dimensional. Incapable of expressing negation, it could no longer voice the protest of the oppressed. Instead of revealing meanings, speech had become nothing more than a tool of the dominant forces in society.

On individuality:

It might be argued that the Frankfurt School’s most pressing fear in the postwar era was [that] the existence of genuine individuality was declining at an alarming rate . . . The bourgeois subject was free and unfree at the same time. [But] in the forced identity of mass men with the social totality, there was no freedom at all … What was left in its place was a cruel parody of the dream of positive freedom. The Enlightenment, which had sought to liberate man, had ironically served to enslave him with far more effective means than ever before. Without a clear mandate for action, the only course open to those who could still escape the numbing power of the culture industry was to preserve and cultivate the vestiges of negation that still remained.

On the social sciences:

Adorno argued that sociology must no longer be considered a cultural science, because the world, dominated as it was by reification, could scarcely be understood as meaningful. “The much-abused inhumanity of empirical methods,” he told his audience, “is always more human than the humanization of the inhuman.”

On the family:

As Horkheimer argued in an essay written in 1949, the more the economic and social functions of the family were liquidated, the more desperately it stressed its outmoded, conventional forms. Even the mother, whose warmth and protectiveness had once served as a buffer against the arbitrary harshness of the patriarchal world . . . was no longer capable of functioning in the same way. “The ‘Mom’, Horkheimer wrote, “is the death mask of the mother.”

Many of these share a concern with “instrumental reason”, the sort of reason useful in technology and economics that lets you figure out what is most efficient. The Frankfurters thought modern society was so good at this (understandably, since instrumental reason produces techno-economic prosperity) that it had lost the ability to employ “substantive reason”, the sort of reason that lets you figure out what is truly valuable. Mystically, our domination of nature has led to a domination of ourselves, where we are incapable of relating to our own lives except as tools to be employed.

So what is substantive reason? What should we be aiming for? Like some other philosophers, the Frankfurters seem more comfortable with attacking others for lacking a unified morality than with developing a unified morality themselves. But their Hegelian commitment lets them partially sidestep this objection: the Good is the thing God is trying to manifest as: the end-state of history freed from all contradictions.

Does this really rejustify substantive reason and save us from our dystopian focus on technical rationality? Here I come to the ultimate blocker I have with all Frankfurt School thought: the central point of all their criticism is that modern society is corrupt and barbaric for trying to unambitiously implement its little political reforms and improve GDP one percent, instead of trying to manifest God through History. But why should we believe that manifesting God through History is a real thing? Hegel only gives a nice story about how some historical periods seem to have embodied certain forms of intellectual progress; Marx only adds some bad economics and failed predictions. If you take away the belief that history can phase transition into a utopia utterly different from and superior to modern life, then trying to improve things normally through human reason and human effort seems like the way to go. In this sense, the Frankfurt School feels like the exact opposite of preaching to the choir. If a preacher tells the choir that they need to prioritize God over their career and family, all nice and well; if he says the same to an audience of inveterate atheists, he’s missing a step, and would do well to replace himself with a missionary. But the Frankfurters seemed interested in every part of the logical chain except justifying dialectical mysticism to an America which clearly did not believe in it.

The Frankfurt School would have predicted my confusion. As a subject of late capitalism, I am so stuck in its concepts that I fail to understand that a better world is possible. When I hear “language”, I think of the weak, impoverished parody of language that I and all my friends use, totally unaware that I am already communicating in a Newspeak that has been robbed of its true representational power.

Some of the School’s work on mass media and the decline of the human condition had obvious similarities with modern concerns about how social media is stealing our souls - instead of being able to truly enjoy things, we process them for a gallery of Instagram observers; instead of going out and experiencing the world, or even reading about it, we get it in bite-sized pieces from TikTok influencers. But the Frankfurters were saying the same thing about mass media when mass media meant the radio (even TVs had yet to take off during most of this period). Does this discredit the whole narrative, in the sense that everyone always thinks the latest form of media is destroying the human soul? Or, in the spirit of this post, should we treat the different eras as independent confirmation of the same downward spiral? Has the human soul been deteriorating longer and more thoroughly than we can possibly imagine? Even if a modern teenager broke out of prison of TikTok and Instagram and regained the lifestyle of their grandparents, would that still be a pale shadow of true humanity? Would they have five or ten further iterations left to go before they were anywhere normal and healthy?

Here I think back to the Frankfurt School’s origins. The intellectual scene of interwar Central Europe seemed like another, better world. You would wake up in your bedroom in your beautiful Art Nouveau villa. Leisurely eat a Sachertorte at the cafe while perusing a Thomas Mann novel. Debate the meaning of language with Wittgenstein. Get analyzed by Carl Jung. Write a long letter in flowery cursive to your father Baruch saying that for the last time, you couldn’t take over the family wine business, you were doing important intellectual work elucidating how the bourgeois order suppressed the negation of the negation, and he must send over your monthly allowance of 1,000 German marks post haste, before leaving to attend a Mahler symphony at the Staatsoper in the evening. Looking back at these people - all of whom spoke ten languages, played five instruments, and had read more books by age twenty than I will get to in my entire life - they seem like a superior species.

If, upon having their world destroyed and accepting exile in America, they pronounced the people they found there to be a inferior species - in the least-racist, most Communist language possible - were they remarking on this same difference from the opposite perspective? If so, do we have any reason to trust their diagnosis of what was lost? If we stopped listening to radio, and maybe made a conlang that expressed negation effectively again, could we get Art Nouveau back? Would we be able to have good Sachertortes in America?

So, Did The Frankfurt School Cause Everything You Hate, And Should You Blame The Jews?

We opened with Wikipedia’s diagnosis that you shouldn’t use the phrase “cultural Marxism”, and especially shouldn’t blame it on the Frankfurt School. Has our extra knowledge given us any new insight into the validity of this commandment?

The usual Cultural Marxist story is that radical intellectuals invented the idea of the long march through the institutions: taking over colleges, journalism, and mass culture, and leveraging them for more communist propaganda. Marcuse can fairly be accused of supporting this (not inventing it!), but it was after his Frankfurt School days. The orthodox Frankfurters had no more interest in taking over institutions than in taking over anything else. They just wanted to do weird mystical art criticism:

The Frankfurt School increasingly treated any attempt to realize the promises of philosophy as instrumentalization. In an aphorism on propaganda, Horkheimer and Adorno excoriated the instrumental use of philosophy and language to bring about social change…”Is activism, then, especially political activism, the sole means of fulfillment, as just defined? I hesitate to say so. The age needs no added stimulus to action. Philosophy must not be turned into propaganda, even for the best possible purpose.” As a result, programmatic advice for methods to change society was not very evident in any of the Frankfurt School’s work.

The reason some people accuse the Frankfurt School of this is that Marcuse, previously a famous Frankfurt School member, was among the strategy’s high-profile adherents. But the reason that other people so vociferously defend the School against this accusation is that it diametrically misrepresents what made the Frankfurt School special among Marxists - their belief that you shouldn’t be trying to immediately change society, you should be producing weird mystical art criticism and hoping that it makes society snap into a new polymorph of its own accord.

But it would be an exaggeration to call the Frankfurt School sterile and unrelated to later leftist movements. Their weird mystical art criticism was a forerunner of Derrida’s deconstruction and the whole postmodernist movement. The Frankfurters themselves weren’t postmodernists. They thought there was something like an objective good: that which unjammed the wheels of history and manifested God correctly. But you can see how their negative dialectics, wielded by less careful hands, could degenerate into postmodernist meaninglessness.

Even beyond that, there seems to be a Frankfurt “vibe” across modern progressivism in its glorification of criticism and protest for their own sake. Leftists may criticize police while having little plan for an alternative law enforcement system, or reflexively thwart new development even when it seemingly serves their goals, or protest global warming while opposing any actual plan that would stop global warming because it doesn’t also “end capitalism”. All of this would make perfect sense to the Frankfurt School: the goal isn’t to immediately replace bad capitalist institutions with better communism-informed institutions, it’s to kick the system as hard as you can and see if you can restart History.

In its most degenerate form, Frankfurtism decays into slacktivism. Too greedy to donate to the poor? It’s fine, that would just stabilize the existing system. Too scared to start a violent protest? It’s fine, any revolt within the current paradigm would merely be a cargo cult. The actually useful thing to do is write weird mystical art criticism. Or if you’re not an IQ 200 interwar Central European Jew and weird/mystical isn’t your style, maybe you can write on Tumblr about how someone’s Harry Potter fanfic is problematic.

This would be a devastating criticism of the Frankfurt School if they hadn’t said, again and again, that they expected their work to be misinterpreted and misused. They had hoped that burying it in fifty layers of mystical obscurantism would protect them. Maybe they should have gone for fifty-one.

Does this interpretation founder on the fact that most modern leftists don’t know about this? The average fanfic-criticizer doesn’t understand negative dialectics and the premature end of history, do they? Maybe they do - lots of leftists are really into “theory”. My brain is already filled with enough analytic philosophy that I find the Continent hard to navigate, but maybe someone who learned it as their native philosophical dialect can understand these ideas much more easily than I could manage. Or maybe understanding isn’t necessary. Some habits are sticky - we still say “God bless you” long after having forgotten that people once believed the post-sneeze vacuum could let demons enter the body. Maybe postmodernist academics remember enough of the theory to teach their students the disposition even without the details, and the disposition is all they need.

In conclusion, the Frankfurt School probably did not single-handedly cause everything you hate. As for whether you should blame the Jews, I think it’s 50-50. It was the Frankfurters who gave the Gentiles the kabbalah, even though the whole Jewish corpus is laced with warnings never to do that. But it was the Gentiles who accepted it. No going back now; may the Messiah come speedily and in our days.

I gave Claude a prompt something like (edited for coherence):

I’ll be voting in the June 2026 California primary. I’m a centrist liberal abundance YIMBY whose favorite political writers are Kelsey Piper, Matt Yglesias, and Ezra Klein. I’m wary of government overreach, but I’m not a doctrinaire libertarian and want to help people when we can figure ways to do it that work. I’m going to ask you about each race on my ballot, and I’d like for you to list the various candidates’ bios, policies, endorsements, your read on the most important differences between them, and your advice for me as I try to make my choice.

…and got back answers like the following:

California Superintendent of Public Instruction

A quick reality check on the office, then the field. The state superintendent has surprisingly little direct authority — districts control most budget and curriculum — and the state is actively considering shifting more responsibilities to the governor-appointed State Board of Education, which would shrink it further. The job is mostly a $150B-budget bully pulpit. So this is more “who do you want amplifying education priorities for the next four years” than “who will rewrite California education.”

The race is on the standalone education ballot (it doesn’t follow the nonpartisan blanket primary system) — June 2 primary, November 3 runoff if no one clears 50%. Realistically no one does, so this primary is about who advances.

Quick framing: what “the Kelsey Piper view” implies

Piper’s project, especially in her recent Argument writing, sits at the intersection of several positions that don’t all naturally cluster:

Structured literacy / “science of reading” / Mississippi Miracle is real and works. Phonics-first, mastery-based, with district-level accountability and reading coaches in low-performing classrooms. She has called the failure to adopt this “a crime against humanity” in California.

Standardized testing and accountability are good, actually. Not as bludgeons but as honest feedback mechanisms. Detracking failed. Grade inflation is bad.

Open to charters, microschools, and school choice. She founded and runs Oakland LEARN, a microschool. She sends her own kids to an “unregulated tiny private school.” She thinks the left’s reflexive hostility to choice misunderstands what parents are actually fleeing (kids not learning to read).

Skeptical of teachers’ unions when they block reform. Not anti-teacher, but pro-evidence over pro-union-priority when they conflict.

Pro-public-school in principle, but pro-evidence over pro-system. Treats education as a place where the left has often chosen ideological commitments over the well-being of kids who do not vote.

The candidate who matches this view best probably (a) has explicitly backed structured literacy/phonics, (b) has shown willingness to push the system rather than just defer to CTA, and (c) is at least not hostile to charters or alternative models. The candidate who matches it worst would be a CTA-backed insider running on “more funding, less testing, no curriculum mandates.”

The candidates

Al Muratsuchi (Assemblymember, LA South Bay, former Education Committee chair). Co-authored the law that funded phonics-based reading instruction grounded in the science of reading. Co-authored Prop. 2 ($10B school facilities bond, passed). Adjunct college teacher, former deputy AG. Endorsed by California Federation of Teachers (CFT, the smaller of the two teachers’ unions), Association of California School Administrators, and California School Employees Association.

Anthony Rendon (former Assembly Speaker 2016–2023). Ran an early-childhood program in LA for 20 years before politics. As Speaker oversaw major K-12 funding increases, universal transitional kindergarten, and charter school accountability legislation (which generally tightened charter regulation rather than loosened it). Endorsed by AFSCME, SEIU California, California Latino Caucus.

Joshua Newman (former state senator, former Senate Education Committee chair). Co-authored Prop. 2 with Muratsuchi. Army veteran, founded a vets-to-civilian-workforce nonprofit, now a UC Irvine fellow. Endorsed by State Building and Construction Trades.

Richard Barrera (San Diego Unified school board president). The California Teachers Association candidate — that’s basically his profile. Outsider to Sacramento; emphasizes funding, early childhood, easier teacher credentialing pathways.

Nichelle Henderson (LA Community College trustee, longtime teacher). Union-backed. Supports expanded school-based health, standardized testing reform, divesting pensions from fossil fuels and “the U.S. war machine.”

Frank Lara (SF elementary teacher, former UESF VP). The left-of-the-Democrats candidate. Peace and Freedom Party and Green Party endorsements (officially nonpartisan, but signals where he sits).

Gus Mattammal (Silicon Valley tutoring company founder, author). Pro-charter, pro-homeschool, pro-alternatives-to-traditional-public-schools. The closest thing to a school-choice candidate in the field.

Sonja Shaw (Chino Valley School Board president). Anti-trans-protections crusader who got Thurmond escorted out of a 2023 board meeting. CA Republican Party, Moms for Liberty, CRPA endorsements. The right-culture-war candidate.

The most important differences, and my read for the Piper view

The structured literacy litmus test points hard to Muratsuchi. He is the only candidate in this field who has actually moved policy on the thing Piper considers most urgent. His official candidate statement explicitly cites “phonics-based reading instruction based on the science of reading” as something he coauthored and delivered funding for. That is, almost verbatim, the policy Piper has spent the last year writing about. Nobody else in the field has a comparable record on this issue.

Rendon is the second-strongest plausible fit, but with caveats. Twenty years running an early-childhood program is genuinely relevant experience, and TK (transitional kindergarten) expansion is one of the more evidence-supported things California has done in K–12. But his charter-accountability work as Speaker generally meant more regulation on charters, which cuts against the Piper-flavored openness to alternative models. He’s a competent establishment Democrat; he’d be a fine superintendent, just not specifically the structured-literacy crusader.

Barrera is the candidate Piper would be most skeptical of. Not because he’s a bad person — he’s a long-serving school board president, presumably competent — but because the CTA endorsement is his political identity in this race, and Piper’s whole thesis is that CTA-aligned politics has been one of the structural reasons California can’t adopt the reforms that worked elsewhere. Barrera’s stated priorities (more funding, easier teacher pathways) are CTA priorities, not reform priorities. If you’re voting the Piper view, this is the one to skip.

Henderson and Lara are further from the Piper view. Henderson’s “standardized testing reform” plus the pension-divestment-from-the-war-machine framing reads as movement-left rather than evidence-driven; Piper has been pointedly critical of detracking and of treating testing as the enemy. Lara is more or less explicitly the union-left candidate.

Mattammal is the awkward case. He is the candidate closest to Piper on school choice and microschools specifically — that’s basically her own model. But he’s running with essentially no political coalition or governing experience, and the Piper view, while choice-friendly, is not “burn down public schools” — it’s “fix the actual reading instruction in the schools that most kids will continue to attend.” A statewide superintendent who can’t move CTA-dominated Sacramento isn’t useful for that goal. Mattammal also doesn’t appear to have an articulated policy program on structured literacy or accountability, just on alternatives. Probably not the right fit even on a choice-sympathetic reading.

Shaw is obviously off the table on the Piper view. Piper is a Bay Area liberal who supports trans kids and has no interest in culture-war education politics. The Moms for Liberty endorsement is disqualifying on its own.

Newman is the dark horse. Co-authored Prop. 2 with Muratsuchi, chaired Senate Education, military background, now an academic fellow rather than a Sacramento insider. He hasn’t been as visibly identified with structured literacy as Muratsuchi has, but he’s broadly in the same evidence-and-accountability lane. The Building Trades endorsement is unusual — it suggests he’s running a coalition strategy aimed at facilities/jobs rather than CTA — and that might actually be a positive signal for someone trying to operate independently of the dominant teachers’ union politics.

Bottom line

For the Piper view, Muratsuchi is the clearest fit in the field. He’s the only candidate who has actually legislated structured literacy funding, he has the directly relevant policy chops (former Education Committee chair, Prop. 2), and his endorsement coalition (CFT, administrators, classified employees) is just slightly off-axis from the dominant CTA-controlled lane in a way that suggests some independence. He’s also reasonably likely to make the November runoff, which matters: a vote for the second-best candidate who finishes fourth doesn’t accomplish anything.

If you wanted to express a sharper “I want a real outsider reformer” view rather than working within the field as it exists, Mattammal is the only option, but at significant cost in viability and breadth of program.

For “I just want a competent Democrat who’ll be fine,” Rendon and Newman are both reasonable. But for “I want the candidate most likely to actually push the structured-literacy / accountability agenda Piper writes about,” it’s Muratsuchi.

This is better than any voter guide I’ve ever seen. I didn’t end up taking Claude’s advice - I voted Newman - but Muratsuchi was a close second, and Claude’s advice was crucial in helping me prioritize what to research further.

And here’s its opinion on one of the small local spending measures I usually have a hard time forming an opinion on:

Measure A: Peralta Colleges Affordable Education Reauthorization

What it actually does

This is a parcel tax reauthorization, not a new tax. The Peralta Community College District (which runs Laney College, Merritt College, College of Alameda, and Berkeley City College) has had a $48-per-parcel annual tax since voters first approved it in 2012 and renewed it in 2018. The current authorization expires.

Measure A would:

• Extend the existing $48/parcel tax for 9 more years (July 1, 2027 through June 30, 2036)

• No increase in the rate — same $48 you’re already paying if you own property in the Peralta district

• Generate roughly $8 million per year ($72M over the nine years)

• Funds restricted to instruction, student services, counseling, faculty recruitment/retention, job-training programs, and university-transfer prep

• Requires a 2/3 supermajority to pass (this is the standard threshold for California parcel taxes and is a high bar)

Senior citizens and Supplemental Security Income recipients can apply for exemptions. Funds are subject to a Citizens’ Parcel Tax Oversight Committee.

Geographic scope: this only appears on ballots in the Peralta district, which covers northern Alameda County — Oakland, Berkeley, Alameda, Albany, Emeryville, and Piedmont. So if you’re in Oakland, you’ll see it.

The straightforward “yes” case

• Community colleges are genuinely one of the most cost-effective rungs in American higher ed. Peralta tuition is ~$1,100/year vs. ~$6,500 at Cal State and ~$14,000 at UC.

• Reauthorizing an existing tax is a much lower ask than a new one — you’re already paying it, and nothing on your tax bill changes.

• The money is restricted to instruction and student services (not administration, not facilities), with citizen oversight. That’s about as well-designed as parcel tax measures get in California.

• League of Women Voters supports it. Labor unions back it. No formal opposition argument was filed with the Registrar of Voters — literally no one wrote a ballot statement against it.

• $48/year on a parcel is genuinely small relative to most California property tax bills.

The complications worth knowing

I want to give you the honest picture rather than just the campaign pitch, because Peralta has a difficult institutional history that someone with your “wary of government overreach but pro-helping-people” framework will want to understand.

The accreditation crisis was real. From 2018 to 2023, Peralta was in serious trouble with its accreditor (ACCJC). A 2019 state Fiscal Crisis and Management Assistance Team review found Peralta was “at high risk of insolvency” after years of mismanagement, with administrators “regularly breaking their own rules” and the district “ripe for fraud” due to poor internal controls. The four colleges were placed on probation by the accreditor in January 2020 — a severe sanction one step short of “show cause” (the level that nearly closed City College of San Francisco).

The governance situation was also a mess. A 2021 Alameda County civil grand jury report excoriated the Peralta Board of Trustees for “broken board culture,” secretive meetings, infighting, interfering in hiring, racial insensitivity, and fostering an “overall culture of incivility.” Multiple chancellors departed under pressure — Peralta went through four chancellors between 2019 and 2023.

Things have improved. Accreditation was restored from probation to “warning” status in January 2022, then fully reaffirmed in January 2023. Tammeil Gilkerson became permanent chancellor in January 2024 — by all accounts a stabilizing hire from outside the dysfunction.

But there are ongoing concerns. As of early 2025, Peralta is still navigating a budget crisis. Chancellor Gilkerson has acknowledged that Peralta’s full-time-equivalent students (FTES) lag significantly behind other four-college community college districts in the state — which means enrollment-driven state funding is structurally low for the district’s size. There’s also a Peralta Citizen article headlined “PCCD is in crisis. Everything is on the table” from February 2025, indicating that even with the recent improvements, the district isn’t out of the woods.

One transparency concern worth noting from local reporting. The largest single donor to the Yes-on-A campaign is Future Flooring Group (C&S Flooring Systems), which contributed $75,000 — about half the campaign’s total raised. Future Flooring is currently contracted with Peralta for ~$678K to replace flooring at College of Alameda, Laney, and the district service center this summer, and has received over $2M from the district overall. This isn’t illegal, but a major vendor that depends on district contracts being the largest single funder of the campaign to extend the district’s parcel tax is the kind of thing that should at least be visible. The rest of the campaign funding comes mostly from Bay Area labor unions, which is more typical and less notable.

My honest read for your framework

For a centrist liberal abundance YIMBY who wants to help people but is wary of government overreach, here’s how I’d think about this:

Arguments for yes:

• Community colleges are exactly the kind of institution that fits an “abundance liberal helping people” framework: they provide cheap, accessible higher ed and workforce training without the racket-like price escalation of four-year schools. They’re a genuine social ladder.

• This is a reauthorization, not new spending. Voting no doesn’t return the money to you in a meaningful way at the household level; it just defunds the colleges.

• $48 a year is small money. The cost-benefit is hard to argue against in isolation.

• Peralta has measurably improved governance since 2023. Punishing the institution now for sins it has been actively repairing would be unfair to current and future students.

• The supermajority threshold (2/3) is itself a check — if a tax can clear that bar, it has unusually broad consent.

Arguments for no:

• Peralta’s institutional dysfunction was severe and is not fully resolved. The “everything is on the table” framing from district leaders in early 2025 suggests structural problems persist.

• Some abundance-school thinkers would argue that propping up underperforming public institutions with parcel taxes reduces pressure to actually fix what’s broken — if the colleges had to demonstrate enrollment growth and operational excellence to retain funding, they might.

• Low FTES is a worrying signal. Are these colleges serving the demand that exists, or are they an institution that has become inefficient relative to peers?

The judgment call. I think a reasonable abundance liberal would vote yes, with eyes open. The reasons: (1) reauthorizations are different from new authorizations — you’re not signing up for new spending, you’re declining to actively cut it; (2) community colleges as a category are deeply aligned with the “help people, expand the ladder” framework; (3) the most damning Peralta criticisms are about 2018–2022, and the institution has been visibly improving since; (4) no organized opposition emerged, which usually means even motivated critics didn’t think the case for opposing was strong; and (5) $48/year is genuinely small money for a meaningful local good.

But voting no isn’t crazy if your prior is “underperforming institutions should face budget discipline.” It’s an unusually defensible “no” for a parcel tax, in that the institution has a real track record of problems. If you wanted to send a message that you support community colleges in principle but want Peralta to keep cleaning house, abstaining is also coherent (the 2/3 threshold means abstaining has a slightly different effect than a no vote — it raises the bar relative to the participating electorate).

My weak lean: yes. Strong enough to recommend, not strong enough to argue with someone who voted no on accountability grounds.

I informally (no strict controls) tested this on 10 difficult races where I wasn’t sure going in who I would vote for. I give Claude an A if it recommended the same candidate I eventually voted for, a B if it recommended my second choice out of a large field, a C if I can see where it’s coming from but disagree, and an F if it picked someone I hate. Its final score was:

• 5 x As

• 3 x Bs

• 2 x Cs

When it failed, it was usually because I have a policy of making my vote count on important races, vs. making fun/utopian/conscience-guided choices on races that don’t matter. I didn’t tell Claude this, and Claude tended to ignore fringe candidates with no chance of winning.

Other times, it was because it took my prompt too seriously. I do like abundance/YIMBY ideas, but since that was all I told Claude in the prompt, it sort of pegged me as a single-issue voter. In the future, I might put that lower down, below the list of famous people I agree with.

Claude also correctly guessed (probably from the word “liberal”) that I lean Democrat, over-indexed on that, and leaned away from Republican candidates. In the future, I might include in the prompt that it should cross the aisle when there’s a sufficiently convincing reason.

I ended by asking Claude to ignore my personal beliefs and tell me who it would recommend, point-blank, if it didn’t know anything about me. It proposed four switches - three of which I liked better than its original choice! I’m skeptical that it was truly expressing its own opinions here (if it even has any) - I suspect it treated the exercise as a chance to make more “emotional” judgments - but it was an interesting exercise. If you’re a Republican using AI to help you vote, please end with the same question and tell me what happens.

This was a good enough experience that if I didn’t have an hour or two to do this properly, I would trust Claude’s endorsement over competing cheap-and-fast ways to determine my vote (party-line, newspaper endorsements, NGO endorsements, who has the funniest name). And given that I did spend two hours doing this properly, I think I’m about 50% happier with my choices than I would have been without AI.

Moving back into speculative futurism (in case you forgot which blog you were on), a lot of my hope for how the post-AGI future might turn out well - despite all the risks of dictatorship, inequality, surveillance, etc - hinges on people taking advantage of AI advisors to make better political decisions. The sooner we start, the better.

You can see my final list of decisions (may not be very interesting to non-Californians) here. Remember that I accept voter guides from ACX meetup groups in big cities with local elections happening soon, and will signal-boost them on the Open Thread if you give them to me.

1: Thanks to everyone who sent in a book review contest entry. I’ll have finalist voting up within a week or two.

2: 80,000 Hours, an effective altruist career advice organization, is publishing their book 80,000 Hours: How To Have A Fulfilling Career That Does Good. Along with talking about how to most effectively do good, it also discusses which careers are most likely to be automated by AI soonest (and I trust Ben to have high-quality thinking on this topic). Release date is tomorrow, but if you’re fast you can preorder today for special bonuses.

3: I filled out my early ballot for the California primary election (Alameda County); if you’re interested you can find my choices and explanations here.

A common counterargument is to claim that no, LLMs can become AGI. But even without that counterargument, I think the “therefore” fails on its own terms. The key question is: how much of a new paradigm do we need?

The landmark discoveries on the road to modern LLMs are something like:

1950s: Neural networks
1967: Multi-layer perceptron
2010: Modern deep learning
2017: Transformer, LLM
2022: RLHF, chatbots
2024: Chain of thought / test-time compute

We can think of this as an “evolutionary tree”, where a given LLM (let’s say Claude Opus 4.7) shares a recent “common ancestor” with all other chatbots, and only a very distant “common ancestor” with everything else descended from the multi-layer perceptron. If AGI needs a “new paradigm”, what common ancestor can we expect AGI and LLMs to share?

AGI will very likely use neural networks, because the human brain is a neural network and qualifies as an AGI. It will probably use deep learning, because although deep learning isn’t exactly analogous to the brain, it seems like a pretty reasonable way to emulate the brain’s learning algorithms onto computer hardware.

Skeptics like Yann LeCun and Gary Marcus usually pinpoint LLMs/transformers as the step where we went wrong. LeCun thinks that the first AGIs may be within the deep learning paradigm (but not LLMs); Marcus thinks that they’ll combine insights from deep learning with something else.

How soon should we expect a new paradigm as revolutionary as LLMs/transformers? Since we got LLMs/transformers nine years ago, Lindy’s Law suggests nine more years. How soon should we expect a new paradigm as revolutionary as deep learning? By the same logic, sixteen years from now.

Lindy’s Law has a heavy tail, which means we can’t simply halve these to find our 25th percentile estimate. Our 25th percentile estimate for the next advance as exciting as LLMs should be three years from now; for deep learning, it’s five years.

So even if you think AGI will require a further paradigm shift as big as the invention of the LLM or as deep learning itself, you should have 25% chance it will be developed in the next 3 - 5 years. Which is about as long as the LLM-only crowd think things will take! This isn’t an excuse for relegating the risk of AGI to some vague indefinite future. It could still be the late 2020s or early 2030s!

(Might we expect that low-hanging-fruit effects make the next paradigm harder to find than the last one? In practice, fields get more researchers as time goes on, and that effect usually causes time-between-advances to be approximately constant. And in fact, the number of AI researchers has grown at an unprecedented pace for a scientific field, and growth will enter an even faster regime once AIs themselves can contribute. Overall these make me think things will go even faster than Lindy’s Law predicts - but I think Lindy’s Law is a useful upper bound.)

(Would there still be a long time between the invention of the new paradigm and the point where it could be used to maximum effect? It took five years between the invention of the transformer and ChatGPT, the first commercially-successful transformer-based project. But most of that time was spent scaling up, and we’ve already scaled up. If we invent a new paradigm in 2030, then any frontier lab willing to bet on it can quickly provide it with levels of compute sufficient to train human-brain-sized models.)

This is my attempt to talk to the new-paradigm-wanters in their own language, but I think there’s also a subtler point that undermines this worldview. In the past, new paradigms have proven useful in allowing scaling to continue after an old paradigm passed the regime where it could efficiently convert scale to results. LLMs still seem to be able to convert scale to results; while this continues, new paradigms won’t be necessary, and frontier labs won’t risk pursuing them. If scaling ever hits a wall, there will be a few months of confusion as frontier labs look over various new-paradigm-proposals that they already have lying around, and throw them at the wall to see what breaks through. Then scaling will continue from wherever it left off.

The best way to forecast future AI progress is to extrapolate from current LLM scaling. This should work if LLMs scale all the way to AGI. But it may also work even if they don’t. First, because we might get the new paradigm so soon that it won’t be a significant source of delay. And second, because the most likely place for a new paradigm to start is wherever LLMs stop working, going at the same rate.