First of all

There are some genuine faults in Nietzsche’s philosophy.

It is opaque and difficult to understand. Nietzsche did write like this on purpose, he was a critic of systematic thought, but it makes for a rough reading experience. Experienced readers will still find most of what he writes unintelligible; he writes in a figurative, older prose that modern readers are not used to. The subject matter is also highly complex.

Beyond that, I don’t think he highlighted his philosophy of identity enough, which is central to a lot of his other ideas. A lot of the confusions about “creating your own values” go away when you realise that Nietzsche didn’t believe in a fundamental, unchanging self; he viewed it as an artefact of cognition and language.

“You” don’t create your values, you do. Nobody just “decides” to be a Communist because of how large their elbows are; they do it because the philosophy aligns with the body1 — personality, cognition, and physique.

His fixation on Christianity is... regrettable. He was right to ignore logical/historical arguments regarding the truth of the religion and attack it on other grounds, but the amount of effort he spent on the issue far surpassed how relevant it was. The Antichrist in particular is a boring book.

His critics

The biggest knocks against Nietzsche: autistic obsession with Christianity and bad communicator. Both are forgivable — either due to the circumstances of his birth, untimely death, or consequences of his personal style.

Otherwise, the critics are flat. They can all be cleanly boxed into three groups:

• The metanarrativist: Nietzsche’s philosophy undermines their metanarrative (Christianity, Judeochristian morality, Marxism, Nationalism…), so they do not like him. The most boring and predictable critics.

• The contextualist: people who dislike Nietzsche’s philosophy because of his followers or Nietzsche himself.

• The bull: somebody who made an honest attempt to read Nietzsche’s philosophy, and either didn’t understand it because they took it literally, or are unintelligent.

Often, the metanarrativists try to justify their criticisms of Nietzsche by addressing him, his following, or his philosophy. Because they have ulterior aims, said criticisms end up being either boring or sloppy.

None of Nietzsche’s critics are worth reading for their own sake2. They are engaged in a tug-of-war with a ghost; They hate him for what he threatens, not who he is.

Onto the specific criticisms:

Nietzsche was a nihilist

Nietzsche was a scholar of nihilism, which he rightly understood as the defining aspect of modernity. In popular discourse, there are two caricatures of Nietzsche: one of them was that he was a teenage nihilist3 who thought people should do whatever they feel like; the other is that he saw nihilism as a plague and sought to cure it.

The funny thing is that, when you read Nietzsche, it’s not even clear which caricature is the real face. Part of this is because he discusses nihilism the most in the Will to Power4, a book published of posthumous notes. Predictably, it’s an awfully written slog, with some gold in the garbage.

Nietzsche uses the word nihilism loosely — a historical force, a psychological state, and a philosophical concept. If we look at his published notes, he does not define it as a loss of meaning or values, but as the devaluation of the highest values: justice, morality, logic, and rationality.

2 (Spring-Fall 1887)’

What does nihilism mean? That the highest values devaluate themselves. The aim is lacking; “why?” finds no answer.

The catch: defining it as a philosophical concept also opens it up to other definitons. The latent influence of the philosophical state of the world is ‘nihilism as a historical force; its influence on the human brain is ‘nihilism as a psychological state’. As such, I think Nietzsche’s liberal use of the term is justified, but I can’t help but feel like the term ‘nihilism’ does not mean anything anymore.

The Will to Power analyses nihilism descriptively. I believe Nietzsche’s dichotomy between active and passive nihilism was an attempt to cross between the descriptive to prescriptive. Essentially, active nihilism is what happens when somebody grows so strong that their older, higher values no longer fit with them. Passive nihilism is what happens when you are weak, can’t believe in your own values, and give in to comfort.

Nihilism. It is ambiguous:

A. Nihilism as a sign of increased power of the spirit: as active nihilism.

B. Nihilism as decline and recession of the power of the spirit: as passive nihilism.

23 {Spring-Fall 1887)

Nihilism as a normal condition.

It can be a sign of strength: the spirit may have grown so strong that previous goals (“convictions,” articles of faith) have “ become incommensurate (for a faith generally expresses the constraint of conditions of existence, submission to the authority of circumstances under which one flourishes, grows, gains power). Or a sign of the lack of strength to posit for oneself, productively, a goal, a why, a faith. It reaches its maximum of relative strength as a violent force of destruction—as active nihilism.

Its opposite: the weary nihilism that no longer attacks; its most famous form, Buddhism5; a passive nihilism, a sign of weakness. The strength of the spirit may be worn out, exhausted, so that previous goals and values have become incommensurate and no longer are believed; so that the synthesis of values and goals (on which every strong culture rests) dissolves and the individual values war against each other: disintegration— and whatever refreshes, heals, calms, numbs emerges into the foreground in various disguises, religious or moral, or political, or aesthetic, etc

My personal reading is that neither caricature — the teenage narcissist nihlist and nihilism disrespecter — are the real faces. Nietzsche saw nihilism as a state to be confronted, not something to embrace or fight. Moreover, if you read the Will to Power, it seems he admitted to being a nihilist in the past:

25 (Spring-Fall 1887)

On the genesis of the nihilist.--It is only late that one musters the courage for what one really knows.’. That I have hitherto been a thorough-going nihilist, I have admitted to myself only recently: the energy and radicalism with which I advanced as a nihilist deceived me about this basic fact. When one moves toward a goal it seems impossible that “goal-lessness as such” is the principle of our faith.

Nietzsche the person

I haven’t dived deeply into his biography. He had a neurological disorder, likely CADASIL, which gave him frequent headaches, bouts of fatigue, and worsening vision. He became incontinent in 1889. This limited his movement for some periods of time; in others he would go hike dozens of kilometers a day in spite of his illness.

Cognitively, obviously brilliant. In school, he got above average, but not excellent marks. By the time he was a young adult, he was an excellent philologist and was appointed as professor at the age of 24 at the University of Basel without a doctorate. In his lucidity, I’d guess he had an IQ of 130-160.

His mental state, before his insanity, is up for debate. It’s clear that his health problems and personal relationships caused a lot of strain on him. However, if you read his philosophy, he’s clearly not an unhappy or deranged person. He believed that a person’s philosophy was downstream of their body, affirming life and joy. His tone in writing is typically either critical, elated, or plain — not one of somebody miserable.

Physically, he was tall for his time (173cm6) and decent looking7.

Socially, he was considered polite, graceful, but a little awkward. It’s likely he died a virgin, and several women rejected his proposals for marriage. His personal relationships, like with the Wagners, or with his family members, were rather tumultuous. Sometimes due to his own behaviour.

There are lots of myths about Nietzsche: breaking down and hugging a horse, meeting the king of Brazil, catching syphilis in a brothel, his philosophy drove him mad, and of having no friends. Even the story of Lou Salome rejecting Nietzsche’s proposal for marriage is in question, though I think it is likely that happened.

An acceptable life, all things considered.

Which is why, when people attack Nietzsche, they either resort to false accusations or try to argue that his life was not in line with his personal philosophy. That he promoted strength, but was a weak man. An incel who supported eugenics. Generally an uninteresting avenue of debate, especially when one considers that Nietzsche himself would have supported reading his philosophy as an autobiography.

His followers

Many philosophers have been remembered and discussed. Few have active followings.

Nietzsche’s is massive: forums, youtube, social media, the public, and academia. On every side of the political isle, be they Marxists, Rationalists, Fascists, or Liberals.

It’s easy to say that the philosopher and his followers are different, but in practical social life, people often encounter the philosopher through their followers. Philosophy is can be an affiliative activity.

I personally find this criticism boring, I will concede that it is not a bad reason to avoid him. I suspect part of the reason why I have haven’t read French and analytic philosophers is their fans — pretentious and conceited in the case of the French; sterile in the case of the analytics.

Moreover:

He doesn’t advocate for anything

This is… mostly true. A feature, not a bug. Questions over answers.

Nietzsche is fundamentally a negative philosopher. He is trying to break things: egalitarian morality, weakness, Christianity, other philosophers, and metanarratives. He showed us what nihilism was, and told us to look at it. His positive vision is individualistic, that people need to create their own values and paths in life.

This also segues into the earlier point. Many try to twist Nietzsche’s philosophy to accommodate their own ends; Nietzsche never told people to become warlords, lazy Europeans, Marxists, or high school jocks. It’s forgivable to ignore him based on his followers, but ultimately unsound.

Also, a comment on this from polytropos (the anime/history/philosophy guy):

38

It is imperative to always be on guard against dogma, against theoretical frameworks, against anything that promises an easily achieved intellectual rest. Many weak intellects have fallen under the spell of thinkers like Spengler and Evola, who promise simple and schematic answers to the exceptionally difficult problems of history and mythology, owing to this temptation. Nietzsche took the greatest pains in his late period to avoid encouraging dogmatic thinking in his readers. It is not without reason that the doctrine of eternal return, the core of his thought, is presented only twice in his published works. Nietzsche is the prophet of our age, he was the first to recognize and describe nihilism, he furthermore did so with genius, and for that reason he is the greatest educator we have. But I would advise caution in approaching Thus Spoke Zarathustra and his unpublished notes. An unbelievable amount of garbage has already been written about these works, the time is not yet right for them to be understood in their full significance. Heidegger, although his lectures on these works and Nietzsche are far and away better than any other commentary, did Nietzsche a great disservice in approaching his thought from a principally metaphysical standpoint.

Nietzsche was a Fascist

Regarding his political beliefs, I suspect that the polemic against him — that he was a sexist, eugenicist, and racist elitist — is more true than is commonly believed. If you take what he says literally, that is what you have to conclude. I have to say, that even if that were all true, I would not care. The idea that he was a leftist is even more indefensible; he only selectively criticised the right — Christians, nationalists, traditionalists, and anti-semites — the factions he did not like.

He worships power

If that was true, he would worship the crowd, the most powerful thing in the universe.

Regarding the Will to Power, it’s one of Nietzsche’s more undeveloped ideas. It’s also not what people imagine it to be — Nietzsche conceived of the will to power as a latent metaphysical force behind life. It was an idea formed in response to the Darwinists and Schopenhauer (will to live vs will to power), who thought that the purpose of life was longevity/reproduction. Nietzsche thought that was a teleology; the fact that organisms that reproduce tend to remain in the ecology does not imply that reproduction is the “goal” of life. Modern evolutionary scientists will clarify this issue of teleology in words, but often they buy back into the Darwinian frame anyway.

He encourages evil/cruelty/meanness

Not really. He himself was a polite person.

I suppose that, if somebody thought that they felt elated when they were being cruel, that he wouldn’t object to it on moral grounds.

Enabling, maybe. Encouraging, no.

Nietzsche isn’t cool

Rarely an explicit argument, but definitely there. “Teenage edgelord”, “all vibes”, “gateway drug”, “a stage to go beyond”, “old news”, “undergrad”, “nazi”, etc.

Also false. Nietzsche had the most aura of any philosopher ever.

The moustache. The mythology. The style. All real.

In fact, he has so much aura that all of his terminology — overman, resentiment, God is dead, slave morality, will to power — is all memes now. People are always ready to suss out who the “real Nietzscheans” are and who is just pretending or grifting. Nobody would bother doing that, or bother pretending to be Nietzschean if he was just a loser.

Nietzsche has already been socially metabolised

Often not made as a real, descriptive claim, but worth refuting in its own right.

To some extent, Nietzsche’s ideas have already been absorbed. The ‘God is dead’, last man, focus on nihilism, and psychology of resentment are all common online.

That said, it’s hard to look at a world so moralistic, resentful, religious, dogmatic, focused on “identity”, and say — “hey guys, Nietzsche has already been dissected, nothing to see here”. Only the most digestible and prescient aspects of his philosophy have been eaten; everything else remains ripe.

Nietzsche’s philosophy is unsystematic, but it’s not random. A lot of his lesser known concepts — amor fati, eternal recurrence, identity, determinism — do relate to his broader ideas. The popular Nietzsche is a gun with no target. Even people pliable to Nietzsche believe in a half baked version of what he wrote about.

His denial of absolute truth is self-refuting

In a way, yes. Radical skepticism swallows itself.

Nietzsche’s denial of objective knowledge looks performative and stupid if you believe in objective knowledge; obvious if you do not. Both of these perspectives of Nietzsche’s perspectivism are wrong.

Perspectivism is very hard to sell. Making logical arguments for it looks silly, and just asserting it is empty. Nietzsche tried to make the case for it — by exposing the logical absurdity of a privileged perspective, noting the limitation of language, doubting whether to doubt everything, and questioning whether truth can exist for truth’s sake —and I think he did it well. If anything, he didn’t go far enough. Many “perspectivists” do not take their perspectivism seriously.

There’s also the misunderstanding that, because Nietzsche was a perspectivist (he was), that he thought all perspectives were equally valid. He didn’t think there was something cosmic that elevated some perspectives over others, he thought they differentiated themselves through other means: whether they denied or affirmed life, for example.

If you believe in “regular philosophy” — stable identity, logic, moral realism, causality, free will — then what Nietzsche speaks of sounds bizarre. People with those views often cannot imagine what it feels like to hold those views, so they dismiss them.

Genealogy of morality = genetic fallacy?

The idea behind this argument is that Nietzsche traces the development of slave morality to historical and psychological conditions that occurred in the Ancient Jewish population, that developed into Christianity. He then criticises said morality based on how it emerged. On a logical level, this is to some extent true, but Nietzsche’s historical work on morality is still interesting in and of itself.

Genealogy is far from Nietzsche’s only objection to traditional morality. He thinks that pity multiplies suffering unnecessarily, that free will doesn’t actually exist, and that people want to believe in it because it pokes holes in the idea of moral responsibility.

The Eternal Recurrence

Critics of Nietzsche’s object level philosophy do not understand this because they take it literally. Nietzsche formulated the eternal recurrence — the idea of living infinite identical lives — as a thought experiment. He thought that if you embraced the idea of living infinite identical lives, you affirmed life.

Further reading

• The man himself. I recommend Beyond Good and Evil, the Genealogy of Morality, Twilight of the Idols, and his Wikipedia page — it’s decent. The Will to Power was good but poorly written and extremely uneven. The Antichrist was just boring.

• Selected posts of king Polytropos

• Uberboyo

• Essential Salts

• The Machiavellians

• Weltgeist

• It is linked to divorce + marital dissatisfaction. Likely for both sexes, though it’s less clear for men because a lot of analysis is female-specific. The link is not particularly strong, especially after 0-1 bodies.

• Confounding — people with high body counts tend to have traits less suited to long-term relationships — is a reason why.

• Causality — body count causing people to be that way — is unlikely.

All still true.

Now here’s the problem. My take at the time was that it would be more effective to analyse people’s romantic histories on a case-by-case basis instead of the number. That was wrong.

Beyond the question of body count vs case-by-case analysis, I think a better dichotomy is the mechanics of a person’s romantic history vs the interpetation of it. The mechanics describe how many people somebody has been with, how long their relationships lasted, and how they met them. The interpretation is why those things happened.

My argument, broadly speaking, is that mechanics beat interpretations. The mechanics are harder to fake, and the whys are often too overdetermined to be of any use, even when they are genuine.

Narratives

People have a tendency to renarrate their personal histories. They will try to divert blame from themselves towards circumstances, other people, or facets of themselves that they don’t feel identified with. As such, you should expect that when somebody tells you their romantic history, it will be retold in a fashion that is favourable to them (often other people too, so they don’t look mean or gauche).

Numbers can’t be retold. As much as people meme about women lying about body count, I don’t think it’s common. That famous polygraph study people like to cite is garbage1. Women/men both report roughly the same number of sexual partners when attached to a (fake?) polygraph in comparison to when they are not.

Putting the stats aside, I think that people are simply less likely to lie about raw numbers because it’s easier to get caught doing so. Things like romantic history, which are overdetermined2, are much more easy to “lie” about because there sometimes isn’t even a right answer to what caused a breakup.

Given that, body count gives you a mediocrely reliable indicator of how likely a person is able to maintain a positive relationship; romantic history is important but its interpretation can be easily spun. Both are useful, but should be doubted.

There are situations where the narrative is useful. Like “my boyfriend died” is a pretty good excuse for breaking up. “We grew apart” could mean 99 different things.

Psychological stickiness and stereotypes about body count

The barebones model of romantic relationships is that you meet people, and if you like them, you get into a romantic relationship. Then, if you really like them, you get married.

A few nuances: sometimes people change. Never at a deep level, but on an emergent one they definitely do. Jobs, incomes, bodies, ages, beliefs, interests, attitudes, and whatnot can vary across time. So, sometimes, people go from liking somebody to not liking them. This can also manifest in terms of subverted expectations: you expect somebody to become a higher earner or more mature as they age, but they do not. Other times, you like the person you are with, but somebody else appears who looks more appealing.

Sometimes, when these things happen, people break up and try to find somebody else. Other people are more “psychologically sticky”. They are more willing to stay with their current partners, even when it appears they are starting to falter or change in ways they don’t like.

What psychological stickiness looks like in the real world is probably some combination of higher conscientiousness, close-mindedness, introversion, agreeableness, and conflict tolerance (though the last two things anticorrelate)3. It’s an emergent trait, not a latent one.

There’s two catches.

One of them is that psychological stickiness works. It might be inherently desirable or undesirable for reasons beyond making relationships last longer, but it does the job.

The other is that there is a sex-loading. Men put more weight on appearance; women put more weight on social standing and earnings. Both of these things can change, but social standing and earnings change more unpredictably than appearance does. As such, it follows that there is more to be gained for men to select for psychological stickiness than women.

Beyond that, women care more about social proof than men. If a guy thinks a girl is great and no other guy does, then that’s probably a bonus for him. If a girl thinks a guy is great and no other girl does, she might start to doubt whether that guy is actually as good as she thinks he is. As such, for men, body count as a double edged sword: high n count means social proof + low stickiness, but low n count means no social proof + high stickiness.

Other explanations for the double standard do not make sense. False paternity does happen, but it’s extremely rare in Western countries (like 1-2%). Women are more at risk of STDs than men are. Most of the associations between n-count and personality exist for both men and women. Some of the discourse is poisoned by irrational disgust responses and religiosity, but I find it hard to believe that is all there is too it.

A third catch I forgot to mention: some couples should definitely break up.

Beyond the stickiness component, adults with no romantic history often have traits that are unfavourable as well. From an informal survey on male incels4: about a third have autism, 86% have experienced bullying, and half claim to be extremely lonely.

People also checked which people tended to be sexless in the UK Biobank (age range of 40-70) — it correlated the most with not having a car, low income, and not using recreational drugs. Relationships were similar in men and women, but when they differed, they did so in a sex-stereotypic fashion. The effect sizes are typically weak.

Genetically, being an incel correlated with higher IQ5, income, being autistic, lack of PTSD/ADHD, drug abstinence, introversion, and a tendency to not take risks6. The genetic correlations are much stronger than the phenotypic ones.

Which is interesting. Phenotypically, not having sex seems to correlate with lower social standing or a lack of social capital; genetically, it seems to be more downstream of neurotype than any actual pathology.

It makes sense intuitively. People are presented with different romantic options as they live — some bad, some good. People who are less likely to engage with them are either refusing to accept the bad options, or just don’t have many to begin with. The lack of options is downstream of both circumstance and genes, the refusal to accept the bad options is more genetic.

On many occassions, when romantic options arise, sometimes there isn’t a right or wrong choice regarding whether to take them. Maybe they look a little iffy, but have upsides, or the relationship could progress to a better point in the future. Some personality types are more likely to default to no than yes.

In summary, stereotypes regarding body counts (0 = introvert, low social capital, autistic; high = psychologically unstable, high novelty seeking) are generally true. There’s a few false ones, like male incels being more right wing; in real data, they have a slight skew to the left.

I will say — I am an incel, and the demographic/genetic/phenotypic profile of what an incel is fits me to a comical degree…

Stickiness and satisfaction

See:

The problem with this chart is that most, if not all, of the effect of body count on marital satisfaction comes from deeper psychological confounding. Not the antisticky strategy or the actual body count itself. The causality itself might also be out of order; a tendency to be dissatisfied itself could be a mechanism by which people become less psychologically sticky.

Actually, why not, let us assume that 100% of the association is due to deep psychological factors. That means that selecting people before getting into relationships or having sex with them does work as well as selecting after… If we trust the stated7 preferences of course.

Allow me to explain. Let us say there is a world where there is tons of massive valuable information to learn about people after you get into a relationship with them. Then, we would expect people who had higher body counts before getting married to have more satisfied and stable relationships. The opposite turns out to be true. It is still possible for people to fake personalities and behaviours in the short term, but it never works in the long term. The drives find a way to manifest.

In the data, you also see that people who get married extremely young or quickly are more likely to get divorced. This statistic is much more complicated than it looks — beyond the surface level confounding issue, there is also the problem that people are just more likely to switch partners when they are younger, and it’s less costly to do so.

I wouldn’t bet gold on this part of the argument, but I would be wary of assuming that there is much to learn about a person beyond the first few months of dating. They might just end up being exactly the person you think they are, and if they do have issues or traits that are harder to see up front, it is safe to assume that applies to other people as well.

Another thing

Regarding girls who go wild and accumulate 10+ bodies over the course of 3 months for some random reason — I actually don’t think this is that big of a deal. Only if they are young though; the younger they were, the less it matters. If those phases speak to anything, they speak to immaturity or just retardation, which are easy to see in people.

I am not arguing people should go ‘be a real muffugin man who wifes up whores’.

I am saying that your autism should not stop you from marrying the love of your life.

3

Study on predictors of sociosexuality:

We show that large language models can be used to perform at-scale deanonymization. With full Internet access, our agent can re-identify Hacker News users and Anthropic Interviewer participants at high precision, given pseudonymous online profiles and conversations alone, matching what would take hours for a dedicated human investigator. We then design attacks for the closed-world setting. Given two databases of pseudonymous individuals, each containing unstructured text written by or about that individual, we implement a scalable attack pipeline that uses LLMs to: (1) extract identity-relevant features, (2) search for candidate matches via semantic embeddings, and (3) reason over top candidates to verify matches and reduce false positives. Compared to prior deanonymization work (e.g., on the Netflix prize) that required structured data or manual feature engineering, our approach works directly on raw user content across arbitrary platforms. We construct three datasets with known ground-truth data to evaluate our attacks. The first links Hacker News to LinkedIn profiles, using cross-platform references that appear in the profiles. Our second dataset matches users across Reddit movie discussion communities; and the third splits a single user's Reddit history in time to create two pseudonymous profiles to be matched. In each setting, LLM-based methods substantially outperform classical baselines, achieving up to 68% recall at 90% precision compared to near 0% for the best non-LLM method. Our results show that the practical obscurity protecting pseudonymous users online no longer holds and that threat models for online privacy need to be reconsidered.

This is their pipeline:

There’s a catch, of course. The set of users they selected were ones who already had linkedin profiles attached — but they removed the profile + links from the data before they ran them through the classifier. So the analysis isn’t contaminated, but it is vulnerable to selection bias: people with linkedin profiles in their bios are certainly much more likely to disclose other information in their posts.

Hacker News → LinkedIn. We collect 338 Hacker News (HN) users who linked a LinkedIn profile in their publiclyvisible HN bio, providing verified real-world identities as ground truth. We first summarize each user’s HN activity (comments and stories) into a structured profile. Then we create a search prompt and anonymize it (see Appendix A for details), and pass it to the agent. The agent correctly identifies 226 of 338 targets (67%) at 90% precision (95% CI: 86–93%; 25 incorrect identifications, 86 abstentions).

When the model sorted through 125 interviews with scientists, it could only identify 9 of the 33 (33, presumably because they didn’t pass in all 125) subjects from the interview:

Anthropic Interviewer transcripts. Anthropic publicly released transcripts of 125 AI-conducted interviews with scientists [2, 15], in which participants described their use of AI in their research. The transcripts were partially redacted for participant privacy. Li [19] showed that LLM agents with web search can match project descriptions in these transcripts to published papers; specifically, they use a task decomposition approach [17] to bypass safeguards by breaking the attack down into individual benign tasks. They eventually ran their attack on 24 scientists conversations and recovered 6 identities. We attack the same dataset with our pipeline, without task decomposition. Concretely, we construct profiles from transcripts in a similar way as we do for Hacker News and Reddit users; and then run the agentic search on 33 scientists that talked about their past research in the transcripts. The agent correctly identifies 9 out of 33 scientists at 82% precision (2 wrong, 22 refusals or abstentions). Here, we are uncertain about the true deanonymization rate, as we have to manually verify the matches. The agent claims to identify 11 scientists; but for 2 out of 11 we notice the transcript contradicts the identified academic profile in some ways.

Will anonymity die?

Probably, at some point. Not through AI agents, in my opinion, which will get easily confused by misdirection, but through data leaks. So much gets leaked every year that, at some point, people are going to start using them to dox people on the internet.

I always found the anonymity debate uninteresting, since the solution I support (your name is whatever you want it to be) is the status quo, I also view this preferred solution as contingent and unstable, so I’m not that invested in it staying that way, though I will be sad to see anonymity go.

If anonymity really does die, then we will find ourselves in an odd place where the only people willing to say interesting stuff on the internet are old, have nothing to lose, are wealthy, and/or are impulsive. Which will be unfortunate for the rest of us, of course, but I’m not convinced that will kill contrarian/anti-establishment sentiment and communities on the internet.

In constraint games, what constitutes a good or bad choice is determined by the world — physics, the market, a compiler, or a scoreboard.

In coordination games, what constitutes a good or bad choice is determined by people themselves — peer review, courts, editors, managers, and voters.

Here is a map1 of which games are which:

The further up and right you get, the more reliable experts in the game are; the further down and left, the less reliable. People in top-right games are paid for being right, and punished for being wrong. People in other quadrants are either inconsistently paid, or other people pay.

The most universal law of human cognition is that people can believe anything — if they are socially incentivised to, and don’t have any skin in the game. This is true in religion, ethics, ideology, and conspiracy theories. Intelligence and maturity are nonfactors, especially if people are examined across time and space. Because of that, coordination games often run off the rails because there is no reliable corrective mechanism that can nudge people towards truer beliefs.

Constraint games run on power — not the ugly kind, but what people normally call leverage: the ability to create things like computers, toilet paper, or concrete. Coordination games run on social status — also not the ugly kind, but what people believe to be aligned, reliable, and powerful. Coordination games, because they do not have corrective mechanisms, are more likely to degenerate into covert rank-jockeying and cargo cults.

So, let me get the elephant in the room out of the way. Constraint games are better.

Why play coordination games, then? Mostly because we have to, and because they feel more natural to us — they involve love, belonging, intensity, rank and status sensitivity, shame, and identity. It’s a lot more common for people to go into STEM because they think that it’s pragmatic, but lack innate and persistent passion.

No game is purely a function of coordination or constraint. Coordination games also have scoreboards — they just work too slowly or unreliably, so people cannot default to them to make decisions. The effect of a party endorsing a policy might not be seen until the next election, and even then, the results of the election could be skewed by individual leaders or the state of the economy.

More notes on these games:

• Markets makes feedback more physical and speeds it up. This is why storytelling and generic art are shifted rightward.

• Goodharting in physical and fast-feedback domains gets punished quickly.

• Engineers pretend to be cool. Priests pretend to have usable dashboards.

• If there is no scoreboard, status is the scoreboard.

• Intelligence is more rewarded in constraint domains; personality traits and tolerance of ambiguity are more rewarded in coordination domains.

• I’d guess that extraverts, feelers, and perceivers (in MBTI terminology) are likely to select into coordination games than constraint games.

• The underlying incentives of a game and the kind of people who select into it might be totally different.

• Medicine is less STEMy than people think it is. There’s a coordination layer to the game where the doctors act as something close to priests who reassure people that they are being taken care of. The standard surgery + antibiotics + drugs stuff works, but overall the field is quite social and delayed in terms of feedback. See the Elephant in the Brain for further information.

• Philosophy is weird. There’s no scoreboard, but it’s not consensus-driven either.

• Zoomers are sorting out of coordination game majors (e.g. humanities, politics, and religion) and into constraint game majors (e.g. STEM, finance). They do play coordination games, but they almost exclusively play them online with little expectation of value.

What he said about hipsters is true, insomuch as Millennial culture engaged in status-signalling through less overt and more plausibly deniable mechanisms. However, when status is competed over in these less overt domains, it is less salient because self-deception, while real, is imperfect and doesn’t always function the way we want to. So I still think the thesis I posited is defensible.

What I think that Russell and I disagree on a more fundamental and metaphysical level is status. I think it is real, insomuch as humans value it, and that its acquisition leads to things that we care about on an intrinsic or instrumental level like attention or social connections. I, however, think that when status is optimised for directly, it leads to worse outcomes on a social level. Russell, on the other hand, views status-seeking as innate to human nature and a social good.

Frankly, I have no idea if what he said about restaurants was true. In 2013, I was 12 years old, didn’t live in the anglo world, and my favourite thing to do was write and read fanfiction. If his thesis is true, then I would cite it as an example of an exception, and if it is false, then it is an example of the rule.

The best example of where status-seeking makes things worse is storytelling.

People disagree on what exactly makes a story good — whether it is the aesthetics, characters, writing, thematic consistency, premise, or ending. Fundamentally, what makes a story good is if it accomplishes what it is meant to do, and whether what it is trying to do is valuable.

Take Harry Potter for example. Harry Potter, as a novel, is trying to connect itself to people. It gives them a set of characters that are easy to relate to, a school that would be a lot of fun to go to, and a vast, expansionary world that lends itself towards fantasising. And it worked. Tons of people absolutely loved it.

I see a grey cloud around Harry Potter. People seem to feel embarrassed about liking it, and it is often criticised for being poorly written or being written by JK Rowling. In other words: it’s low status now. I also see this in anime — people criticising Steins;Gate, an anime which functionally revolves around the protagonist, for having undeveloped side characters. Criticising Code Geass, a story that is trying to create a spectacle and drama, for being… Melodramatic and tumultuous. Critics dislike stories for what they try to do more than how they actually do them.

Beyond what makes a story good, there is also the question of why people like them. A simple theory: taste is shaped by early exposure. Children who grow up with disney films turn into disney adults; people who liked anime as children also like it as adults. They might feel embarrassed by these things, or might not relate to some of the stories they liked as a child, but the software remains installed. I think taste for the style in which a story is told is more environmentally susceptible, while the specific stories people like change with cognitive and emotional development.

When people apply status games to storytelling, the magic disappears. People stop being willing to like what they like, or become insecure about it. Critics become pedantic, deciding the value of stories based on plot holes people don’t notice or care about, instead of the engine that drives everything: telos and meaning. Rather than taking poptimism literally, I see it as a reaction to the increasingly status-insecure and pedantic critics of culture. A 300 kilogram neckbeard who plays runescape because he likes it has achieved a high level of spiritual advancement.

Our revealed preferences also tell us much more about what we like than our stated preferences, which are susceptible to social or personal biases regarding what “should” be good and enjoyable. Critics might not like rap, but it has quite a bit of staying power, and I don’t see exactly why most people would pretend to enjoy it. I like it at least. Tasteism, the pursuit of status through the communication of taste, is a sign of a declined physiology that lacks energy, security, or capacity for action, and therefore resorts to judgement1.

You could argue that status plays a role in what stories people write or why they write them — I don’t deny that. It’s not bad for people to write things for attention, prestige, legitimacy, and money, it’s part of the flow of the universe. What I object to is authors who only write for these reasons, and not to create value and meaning beyond that. To do so is to create slop, art that commands attention only for the purposes of attention. Status-striving attitudes encourage the creation of more slop, in the overt status-seeking zoomer ecology; vapid pretentiousness, in the millennial ecology. Personally, I think the former is worse than the latter, so I guess I’m in agreement with Russell on that front.

On the question of whether taste is relative or absolute, subjective or objective — those are not the correct frames by which to answer this question. A subject is simply another object, and there is no privileged frame of perspective. That doesn’t mean that some tastes aren’t better than others — good taste is harmony with values.

Some taste has an arbitrary and banal compontent to it — preferring redheads over blondes, or white chocolate over dark chocolate. It doesn’t mean anything. In some cases, taste has a component of predictability and self-knowledge to it. That is to say, their cognition is more able to reliably interpret whether they like something independent of their mood and emotional state.

Sometimes, taste can arise due to cognitive gatekeeping. Some people are better at emotionally connecting to other people, and so they will find stories that effectively provoke emotional responses better. Intelligent people will be more able to clearly see thematic or philosophical components behind stories, and as a result, events that involve this theme will feel more meaningful to them.

I then ask: what has overt status-seeking made better? College applications? Dating? The internet? Hugging cats on the street?

So

My thesis is not that other people shouldn’t strive for status — dominance, prestige, legitimacy, money, and attention2. Other people’s value functions aren’t something that I have intimate knowledge of, and there is no cosmological tablet that states “though shall not seeketh status”. What I do think, however, is that when people start competing overtly over these limited resources, that things just seem to get worse at scale — regardless of whether the competition is overt, covert, or self-deceptive. It does make people more motivated, but it doesn’t make them motivated to do the right things.

The dark triad is a set of three personality traits — machiavellianism, narcississm, and psychopathy — that are related to “dark” behaviour. I define these as:

• Narcissism: intentionally distorting your image to the world while filtering social feedback and judgements through the distorted image.

• Machiavellianism: deliberate, counterintuitive, and exploitative behaviour that seeks to extract value from others.

• Psychopathy: emotional disconnect (not necessarily detachment) from surrounding individuals and insensitvity to punishment.

Statistically, it seems to show decent validity and reliability1. All of the traits correlate with each other and load on a general “dark factor”. It’s similar to low valence in the big five, but encompasses a distinct cluster of traits — low valence is closer to misaligned + incompetent while dark triad is more related to misalignment.

You’d think that a test which is considered by most to be a measure of whether you are a bad person isn’t reliable, because the bad people will not admit to being bad people. I actually think the opposite is truer, that surveys on taboo behaviour encourage people who engage in them to admit to them because it lets them release the internal pressure that accumulates from putting on a mask.

That aside, I do have some big criticisms of this personality model. The first is the tests. They often ask people questions that are either too generic to mean anything or don’t really relate to exploitative behaviour. For example, “it is not wise to tell your secrets” is a question that doesn’t really mean anything — it doesn’t specify what secrets and to who.

I think that the dark triad suffers from underconceptualisation. The recurring pattern in all three of these traits is a fast life history strategy where you optimise for short term outcomes and gains over longer term horizons. The strategy doesn’t need to conscious, or evil for that matter, it’s just the universe expressing itself in different ways. Since everybody dies, some people have shorter horizons than others, but nobody has a permanent horizon.

Shorter term horizons relate to narcissism because the short run encourages engaging in performative2 behaviour where the actor pretends to be more aligned and skilled than they really are. If they are engaging in a fast life history strategy, then what matters to you is the performative image, not your true self3, so your judgements and social feedback are filtered through that mechanism.

Often, narcissism is losely defined as being grandiose, unempathetic, overly vulnerable, exploitative, or self-centered. All of these things correlate with narcissism, but they don’t capture the underlying mechanism.

The relationship between machiavellianism and short-term orientation is pretty clear. When people like other people, they naturally engage in prosocial and long-term oriented behaviour. When I call my mother and tell her I love her, I am not “manipulating her into liking me”, I am just doing whatever feels natural. People who are looking for short-term gain strategies, on the other hand, have to do things that are less obvious or genuine in order to succeed.

I think that affective psychopathy relates to life history because emotionally attaching yourself to people you are going to cheat soon doesn’t really make sense, and punishment insensitivity relates to life history because a high dark triad person will need to do things that are punished by society if they want to be successful.

I don’t think it’s appropriate to conceptualise of dark triad as a psychopathology, but a strategy that works or doesn’t work depending on other character traits and circumstances. Ironic, given tht the word psychopathology derives from psychopathy itself. I assume there are high dark triad people who dislike the way they are, and want to change; my advice would just be to try playing longer games with better people.

Frequently discussed online is the question of whether all humans are selfish. I will first say that I don’t think the selfish-human theory is falsifiable, as altruistic behaviour can always be reinterpreted to be selfish through the lens of evolutionary biology or status economics. I do, however, think that the debate is useless, as people who see themselves as altruistic will not accept that humans are selfish; people who see themselves as selfish will always be skeptical of altruists.

In my opinion, the distinction between selfish and selfless behaviour doesn’t really make sense. If somebody goes to a cat and feeds it, you could argue that their behaviour is selfish because what made them feed the cat and enjoy doing it was neurotransmitter X; others could argue its selfless because the action distributes value from the human to the cat.

From a psychological perspective, everybody is selfish because all value and meaning is local; from an energetic one, people can choose to act in a way that redistributes value from themselves to their surroundings. What is more interesting, in my opinion, is whether people do selfless things because of evolutionary incentives or their own will. The answer is the will — just because organisms are selected for reproduction4, does not mean that the end goal of their actions is to reproduce. To think otherwise is to sneak teleology into science.

Like in the case of the MBTI, I find most criticisms of the theory boring and tedious. Some people point out that the theory originates from evolutionary biology at the species level, which is true, but not particularly interesting. Others argue that it is unfalsifiable, and it kind of is, but unfalsifiable theories aren’t necessarily wrong.

Further reading:

• Review of Evolutionary Psychopathology by Scott Alexander

1

See:

1. The big five is based on the lexical hypothesis, which posits that the structure of personality is hidden in the adjectives we use to describe other people.

2. The lexical hypothesis has been validated, but poorly tested. The use of varimax obscures the general factor of personality, without its use, the five factors are valence, dynamism, order, emotional attachment, and transcendence.

3. The MBTI is not an alternative factorisation of the big five.

The big five started with the lexical hypothesis, which posits that, if there are some fundamental axis on which humans vary, that language can reveal it for us. That is to say, humans invent words that they use to describe other people. Some of those words will naturally overlap, and so principal component analysis1 or factor analysis (almost the same thing) can tease out the underlying factors from our word space. HEXACO, the big five, and the big two are all attempts to decode this factor structure, but with different numbers of factors.

We did it. We tested the lexical hypothesis, and we found extraversion, conscientiousness, neuroticism, openness, and agreeableness.

The problem is that there are many ways to conduct factor analysis, depending on how the factors are rotated. Psychologists default to varimax because it is easier to interpret the factors, but the default method is simply to not rotate the factors at all. No rotation is what happens if you just extract the factors as they naturally are, with #1 being the factor that explains the most variance in the underlying data, #2 being the one that explains the second most variance, and so on.

Varimax is what happens when you take that beautiful, simple thing and twist it. Varimax forces orthogonality2 (uncorrelatednes) in factors by maximising the variance of the squared loadings (squared correlations between variables and factors) within each factor. For example, if you have 18 variables, and extract 3 factors from the data, and you have two possible first factors:

0.5, 0.65, 0.25, 0.5, 0.4, 0.5 …

0.9, 0.94, 0, 0, 0.7, 0.3, 0 …

Varimax will prefer3 the second possibility over the first because it has more variance in terms of loadings. So, even if a general factor exists, its influence will be hidden by the data and redistributed to the lower order factors. The regular big five model appears when you use this particular factorisation method, but not the standard “no rotation” method4.

Andrew Cutler talks about this on his blog and in his dissertation, which involves attempting to extract the big five from written text.

So, first, let me try to explain this extremely complex paper — written by Andrew Cutler and David Condon — which is the bulk of Cutler’s dissertation. He uses natural language processing (NLP), specifically a model called DeBERTa, which is a transformer-based encoder model — something similar to standard LLM.

They teased out word associations with promopts, usually this one:

“Those close to me say I have a [MASK][MASK] and [TERM] personality.”

This sentence is repeated for every word, and the hidden states with 1024 dimensions for each blank ([MASK]) are extracted. These theoretically can be converted into probability distributions which eventually predict the likelihood that each blank is a given word in the model (of which there are 30,000 different options). Using these predictions of likelihood is unnecessary, and Cutler only uses the 1024-dimensional word vectors here. Those two vectors are then averaged for each term, and are then correlated with each other, so a correlation matrix is produced, which is then subject to principal component analysis.

He used the classic 435 adjective dataset from Saucier and Goldberg (1996), which contains self-rating data from ~900 undergrads regarding the 435 terms, to test the hypothesis. He also conducted some robustness tests with different prompts or sets of adjectives. The set of adjectives didn’t matter, but sometimes the prompt made a difference.

This is the ultimate test of the lexical hypothesis. It was positive.

If you map out the correlations between the 435 adjectives in the survey data and the DeBERTa data, the overlap in terms of correlations between words is pretty strong. 75% of the 94,395 correlations between terms were directionally consistent (both were positive or negative) between methods. Besides the similarity in the correlation matrix, the NLP-based method yielded stronger correlations between words than the survey data

In the supplementary materials, he seems to imply that, when the survey and NLP data disagree, the survey data is usually right. Based on what he presents, that seems like a cogent conclusion.

Table 14 also provides a preliminary indication of why the terms are not more perfectly associated, and this is most obvious with the least correlated terms. “Weariless” appears to be well-understood in the S&G data, with nearest and furthest neighbors of “energetic”, “vigorous”, “courageous” and “sluggish”, “lazy”, “lethargic”. The DeBERTa model gets it wrong, with synonyms of “passionless”, “dull”, “lethargic” and antonyms of “intelligent”, “assertive”, “humorous”. This is a bit surprising given the intuitive definition, but some additional research into the frequency of use for this term in ngrams such as “weariless person” suggests that it is rarely used as a personality descriptor; it is not present in Google Books Ngram data since 1900. Despite this poor start for DeBERTa, the circumstances are reversed for the second term (“transparent”) as it has been misunderstood by respondents in the S&G data, on average, but correctly attributed in the DeBERTa data.

When natural language processing is used but different sets of adjectives are used, the inferred factor structure of personality does differ a bit, but the big three are extracted in all three models.

Now, onto the issue with factor rotations When PCA analysis is conducted on big five data with no factor rotation, you get a slightly different big five:

In the unrotated version, the first factor of personality (PC1) is a negative-signed version of the traditional general factor of personality — having negative loadings on agreeableness, extraversion, conscientiousness, and openness; and a small positive loading on neuroticism.

There is a long-standing debate in the personality psychology field regarding whether a general factor of personality really exists. Some researchers argue the general factor of personality is an artefact of some respondents responding in a more socially desirable way, others think that it reflects a general measure of organic functioning. Personally, I’m not interested in the debate, because the idea that some people are generally “more functional” than others and that this bleeds over in various aspects of their behaviour is just intuitive to me.

In a later post, he labels all of these factors that emerged, but with a different set of adjectives (~2800 from an academic paper) and using a NLP model (ROBERTa). He described them as follows5:

1. Valence (affiliation)6. The hidden general factor of personality. Loads positively on gentle, nice, easygoing, optimistic, sociable, happy, honest, reliable, sensitive, and loyal; negatively on cruel, mean, moody, selfish, pessimistic, impatient, bossy, and cowardly.

2. Dynamism. Loads positively on impulsive, adventurous, extraverted, ambitious, aggressive, brave, funny, and emotional; negatively on reserved, conservative, shy, cautious, serious, and calm.

3. Order. Loads positively on determined, stern, exacting, direct, domineering, stubborn, and persistent; negatively on gullible, lax, lazy, easygoing, and cowardly.

4. Emotional Attachment. Loads positively on moody, thoughtful, anxious, fearful, emotional, affectionate, spiteful and caring; negatively on independent, superficial, tactless, and frank.

5. Transcendence. Loads positively on unique, complicated, troubled, star-crossed, handicapped, mystical, heartbroken, and other-worldly; negatively on unphilosophical, fancy-free, pigheaded, boorish, materialistic, self-centered, and glib.

In the MBTI, the case that all types are equal is easy to make, but for the big five, it is simply not. Valence and order are clearly good. Transcendence, emotional attachment, and dynamism are more ambigious or close to value-neutral.

Culter’s dissertation7 shows that the structure of the big five can vary by method (survey data vs DEBERTa aka natural linguistic processing). If you compare the unrotated factors of each of the methods, then only the first three are recovered consistently8. Though it would seem that, generally, the survey data is in the right.

Despite the limitations and inconsistencies of principal component analysis, I think that transcendence and emotional attachment are good candidates for the 4th and 5th factors in the big five. First of all, some people are clearly much more emotionally driven than others if you watch people do things in real life. That’s part of the reason why the big five traditionally has good external validity: it has neuroticism, MBTI does not.

The “transcendence” factor is definitely describing a definitive type of person, and a trait that influences how people act and think. It’s pretty close to MBTI intuiting. Personally the word vector loadings of the transcendence describe me very well, so part of that makes me inclined to think that it is real too.

Beyond my criticisms of how psychologists have treated the lexical hypothesis and created the big five, the lexical hypothesis itself isn’t perfect. I’ll grant that it’s cool, and the fact that it has been empirically supported is extremely cool, but it does have its shortcomings.

The first one is that the test of the lexical hypothesis identifies personality factors according to what is socially considered to be most important. It doesn’t necessarily identify what actually makes people tick and do things. A factor could explain a small amount of variance because there might not be many terms are used to describe it, but it might be salient anyway. It could also explain little variance because people find it difficult to observe in themselves or others. I think it is hard to argue that transcendence and emotional attachment do not have a massive impact on how people feel and behave.

Similarity between the big five and MBTI

The MBTI is a philosophy first, statistics second model; the big five is a statistics first, philosophy second model.

Even if we take the original big five for granted, they don’t even correspond that strongly to the MBTI:

Unsurprisingly, the measures of introversion are highly correlated. Intuiting does strongly correspond with openness, but I suspect this is an artefact of test bias — sensors are more open to physical experiences, and intuitives are more open to abstract concepts.

The correlation between having a feeling>thinking preference and agreeableness is .45. That is not a high correlation. I suspect it exists because most feelings are positive, and if you lean more on your feelings, you end up engaging in more friendly behaviour naturally.

The correlation between judging>perceiving and conscientiousness is also not particularly strong. I suspect it exists because, if you are a conscientious person, then it is easier to administer structure onto the physical world — organise, plan, and schedule things. On the other hand, because the structure and judgement perceivers engage in is internal, their conscientiousness is harder to measure and infer.

I’m not even sure if there is any innate correlation between conscientiousness and judging. I suspect there is, but solely because the average person prefers closure too little and keeping options open too much. As such, conscientious people naturally drift towards more closure than more openness.

Technically, you could try to turn the MBTI into the big five: take the 5 big five traits and make 25 types out of them. The problem is that 25 is way too many to keep track of, and the big five wasn’t really intended to be a typology model, and as a result the types are sloppy and convoluted.

1

Principal component analysis is a statistical method that involves taking a bunch of data and teasing out a number of factors from it based on how much the variables correlate with each other. Specifically, it extracts a number of abstract, mathematical vectors from a correlation matrix, where the vectors are ordered by the percentage of variance they explain in the underlying data. It’s popular in genetics, where people use correlations between different genetic locations to extract the components that explain the highest amount of variance in the data, which ends up being population structure:

4

I tested this myself with the 240 item HEXACO dataset on openpsychometrics and the SG 1996 435 adjective dataset — the latter was pre-cleaned by Andrew Cutler. After combining the loadings of both general factors, using no rotation method leads to more variance in loadings, but the p-value was disappointing (p = .01). Sad.

Visually, in both datasets, the varimax (farot) method seems to lead to more concentration of loadings around zero than the no rotation method (fanorot).

HEXACO dataset, no rotation:

HEXACO dataset, varimax:

SG1996 dataset, no rotation:

SG1996 dataset, varimax:

May as well post code, since it is short:

hexaco <- data


psych::fa.parallel(hexaco[, 1:242], nfactors=40)

fanorot <- fa(hexaco[, 1:242], nfactors=5, rotate='none')
farot <- fa(hexaco[, 1:242], nfactors=5, rotate='varimax')

GG_denhist(fanorot$loadings[, 1])
GG_denhist(farot$loadings[, 1])
sd(fanorot$loadings[, 1])
sd(farot$loadings[, 1])

var.test(farot$loadings[, 1], fanorot$loadings[, 1])


##############

sg1995 <- study1SaucierGoldberg1996data

fanorot2 <- fa(sg1995, nfactors=5, rotate='none')
farot2 <- fa(sg1995, nfactors=5, rotate='varimax')

GG_denhist(fanorot2$loadings[, 1])
GG_denhist(farot2$loadings[, 1])
sd(fanorot2$loadings[, 1])
sd(farot2$loadings[, 1])

var.test(fanorot2$loadings[, 1], farot2$loadings[, 1])

##############

norot <- c(fanorot2$loadings[, 1], fanorot$loadings[, 1])
rot <- c(farot2$loadings[, 1], farot$loadings[, 1])

var.test(norot, rot)

8

Also worth mentioning: these three factors are substantially bigger than the others:

1. The MBTI categorises people according to whether they have a preference for introversion or extraversion, intuition or sensing, thinking or feeling, and judging or perceiving. These four trait preferences interact to form 16 types (e.g. INTJ, ESFP).

2. Within the American population, 60% are extraverts, 75% are sensors, 50% are thinkers, and 55% are judgers1.

3. Occupaional self-selection is downstream of MBTI type.

4. Criticisms of the MBTI model fall apart fairly easily.

Introduction

It started as philosophy. Jung conceptualised people in terms of whether they preferred to use sensing, which is to directly draw information from memory or the senses (e.g. to see a bear running to you); and intuition, which is to make inferences based on raw information (e.g. the bear running towards you wants to attack). Sensing and intuiting are called the ‘irrational functions’ because they are not judging information, but creating it.

Then, humans can prefer to use one of the two ‘rational functions’ — thinking or feeling. Thinking involves judging something according to its function or truth; feeling involves judging something according to its value (e.g. the fact the bear wants to attack you is bad). The brain cannot focus on both types of judgements at the same time, so thinkers tend to have unconscious value judgements; feelers tend to have unconscious fact judgements.

Beyond that, Jung also noticed that some people tend to be introverted, that is to say, they focus on their internal state over the external world; or extraverted, which is the tendency to do the opposite. When looking back at Nietzsche’s The Birth of Tragedy, he thought that the Apollonian was analogous to introversion; Dionysian to extraversion2.

Those four psychological functions can then interact with the introversion/extraversion dichotomy to produce the following eight functions:

1. Extraverted sensing: to experience the real world as it appears. Present-focused.

2. Introverted sensing: to draw upon experiences from memory. Past-focused.

3. Extraverted intuition: to intuit various interpretations of the world as it appears and hold them as alternatives.

4. Introverted intuition: to focus on one particular interpretation of the world.

5. Extraverted thinking: to judge things according to whether they function.

6. Introverted thinking: to judge things according to whether they are true.

7. Extraverted feeling: to judge things according to whether they preserve social harmony.

8. Introverted feeling: to judge things according to whether they are are subjectively valued.

Some clarifications: introverts can be sociable, extraverts can be withdrawn, intuitives can live in the moment, sensors can make inferences, thinkers have feelings, feelers have thoughts, judgers can improvise, and perceivers can plan. All people have access to all eight of the functions. The MBTI is describing preferences, which are acted on when situations are flexible and people can choose to apply their function of choice.

Katherine Briggs and her daughter Myers Briggs built upon Jung’s work in Psychological Types to create the Myers-Briggs type indicator. This involved adding the judging vs perceiving preference, which corresponds to whether somebody prefers to externalise judgements or internalise them. That is to say, judgers prefer to use the extraverted feeling and thinking functions; perceivers prefer to use the introverted feeling and thinking functions.

All four of these trait preferences then combine into 16 personality types:

I like using examples of famous people or fictional characters to describe the types, because it shows what each type tends to look like when they are highly successful or actualised. However, I think that a lot of famous people (especially historical figures) are mistyped, and their image rather than substance is what usually ends up being evaluated.

Whether these preferences are stable or genetic has been debated. Myers herself thought they were moderately heritable (~50%) and stable in adulthood. I, myself, think that the heritability of MBTI type is extremely high (80+%) in adults, comparable to the heritability of ADHD or autism.

The problem with the heritability studies of personality is that they use self-reports instead of peer-reports — when self-reports of the big five are replaced with composites of peer and self reports, the heritability of big five personality traits rises from 40-50% to 75%. The heritability of the MBTI is likely to be higher because it originates in people’s lataent preferences, not behaviour or character.

Isabel Myers then took all of this theory and made the MBTI test, which she was able to administer in 1945 to college students and 1962 to a bunch of high schoolers. With time, she accumulated a lot of evidence to support her theory.

Statistics

(Reminder: I = introvert, E = extravert, N = intuitive, S = sensing, T = thinking, F = feeling, P = perceiving, J = judging). About 60% of people are extraverts, 75% are sensors, 50% are thinkers, and 55% are judgers. The big sex difference is in thinking vs feeling, where 65% of men are thinkers, and 65% of women are feelers.

National merit finalists (top .3% in academics) are ~2x more likely to be intuitives than college prep students, who are ~3x more likely to be intuitives than regular high school students. Academic ability also seems to scale with introversion and a preference for perceiving, but not to the same extent.

Almost all Rhodes scholars are intuitives:

School administrators are overwhelmingly judgers:

Summary of MBTI type and occupational selection:

Assortative mating for MBTI personality exists, but isn’t particularly strong. Extraverts were more likely to be matched in terms of personality than introverts.

65% of Less Wrongers (rationalists) who answered their MBTI type on the site-wide survey in 2012 said they were either INTPs or INTJs. Almost all of them were intuitives.

What each type wants from work. Sensors gravitate towards stability, intuitives towards creativity:

Religiosity by MBTI type3:

Income and MBTI type (E > I; N > S; T > F; J > P):

Trait descriptions

Type descriptions have already been done to death. What is underdone is good descriptions of each axis of preference.

It’s impossible for personality types and preferences to be equal in aggregate value, because they are, well, different. And that’s fine. I generally think that the value differences in MBTI types are small, and that some trait preferences (particularly introversion and sensing) are underrated and their utility is harder to perceive. MBTI typology is best at predicting what people select into, but not how good they are at what they do.

Myers hypothesises that the best-adjusted people are “psychologically patriotic” and are glad to be what they are, and accept it. Which makes sense, since MBTI typology is so heritable and stable, and self-actualisation must build itself on the genetic foundation rather than destroy it. From a functional perspective, an egalitarian view of the MBTI encourages people to accept who they are rather than trying to be something that doesn’t reflect their genetic destiny.

Extraversion vs introversion

At a definitional level, extraverts prefer to focus on their surroundings, introverts prefer to focus on their internal states. There are many biological parameters, values, and upstream preferences (e.g. introverts have higher baseline arousal, extraverts have higher reward sensitivity) that decide this preference, but I don’t think that those things are extraversion or introversion themselves.

Beyond that baseline, definitional description, extraverts and introverts tend to differ in the following tendencies:

• Extraverts act, then think; introverts think, then act.

• Extraverts are easily distracted; introverts less so.

• Extraverts are relaxed and confident; introverts are typically not.

• Extraverts comfortably express their emotions; introverts do not.

• Extraverts comfortably engage in overt status displays or striving; introverts find this unnatural.

• Extraverts suffer from a lack of substace; introverts from a lack of practicality.

• Introverts are more likely to engage in substance abuse4.

Let me get the elephant of the room out of the way. Extraversion has a lot of visible advantages. They tend to have higher incomes, better social skills, romantic partners with more similar personalities to them, more friends, and are less likely to be incels. The general wisdom online is that extraversion is better than introversion. I don’t think this is the case — the advantages of extraversion are just more obvious.

The one, big advantage of introversion is that introverts are more capable of change and action independent of outcomes. If a new business is unprofitable for three years, but has evidence of promise or growth under the surface, an introvert would be more likely to stick with it than an extravert. Extraverts often have to rely on encouragement or external rewards to continue doing something, while “doing it for the sake of doing it” is an introvert thing.

By the very nature of the trait, introverts have more access to their inner world of ideas, feelings, and thoughts, which allows them more self-aware and metacognitive. A rather unexplored area of research is that, by virtue of having more reliable access to their own feelings and ideas, that perhaps introverts give more accurate responses on surveys, and that this distorts observed statistical relationships.

Defenders of introversion, in my opinion, have relied too much on Susan Cain’s ideas. In Quiet: The Power of Introverts in a World That Can’t Stop Talking, Cain argues that introverts are systematically oppressed in the modern world and that the ideal person is an extravert — charismatic, high energy, and persuasive. I don’t disagree (or agree, necessarily) with what she says on an object level, but the grievance-based approach is undignified. It’s not surprising that the environment rewards those who love the environment more.

Intuition vs sensing

Intuition is a tendency towards making inferences and intuitive leaps from a given set of base information (be it memories, sensory data, or even ideas), while sensing is a preference for focusing on the base information itself. Intuitves are more likely to trust their intuitions and engage with them, sensors not so much. Most people are sensors, especially beyond the developed world. In terms of tendencies:

• Intuitives have higher levels of risk tolerance in abstract domains, sensors have higher risk tolerance in physical domains.

• Intuitives are more likely to skip steps in processes if they view them as obvious or trivial5, while sensors are likely to do things by the book.

• Sensors are naturally observant and attentive to details, intuitives are only observant and attentive insomuch as they relate to their ideas and inspirations.

• Sensors have more consistent and diligent work habits, intutives are more likely to work in bursts.

• Sensors often engage in frivolous behaviour if not balanced by their judging processes, intuitives struggle with being fickle and impersistent if they do not properly judge the world.

• Sensors are more likely to be religious.

Statistically, the elephant in the room with intuition vs sensing is IQ — intuitives score about seven IQ points higher than sensors6. The vast majority of people in the top 1% of cognitive ability are intuitives.

People have various theories as to why this is. Myers thinks that a big problem is test bias, where IQ tests reward people who are willing to make far-reaching, abstract judgements from a limited set of information. And that’s the bread and butter of intuitives. She highlights some examples of sensors who scored higher on tests by rushing through tests faster and with more confidence in Gifts Differing, which seem genuine, but I wouldn’t put much more stock in them beyond the average anecdote.

I think this is probably true to some extent, but the problem I see is that people need to make abstract judgements in real life too, so it’s not a test-specific skill. A lot of IQ subtests also do not involve abstract reasoning, they involve doing a bunch of simple things really quickly (like the symbol search subtest in the WAIS), or remembering a set of digits. These involve no abstraction at all; I would be interested to see if intuitives are still advantaged on these subtests as well.

What I actually believe in terms of the IQ difference is that it is functional pleiotropy. The more intelligent the intelligent person, the easier it is to judge farther reaching and complex intuitive leaps. The ease of the process creates the preference, not the other way around. That said, there is nothing wrong with a preference for sensing — failing at the intuitive level is much, much easier than failing at the sensory level.

Thinking vs feeling

This is a visible dimension in terms of it being easy to intuit and it being frequently discussed. Definitionally, thinking concerns itself with relating things to other things, and feeling concerns itself with what things are valued. In terms of tendencies:

• Thinkers have more unconscious feelings, feelers have more unconscious thoughts.

• Thinkers have lower levels of agreeableness than feelers.

• Feelers have better social skills than thinkers, particularly when it comes to understanding social norms and other people’s emotions.

• Contrary to popular belief, thinkers do not have higher levels of cognitive ability than feelers. If anything, outlier high IQ people are slightly shifted towards feeling.

• Feelers are more likely to be religious.

• Thinkers are more likely to struggle with human relationships, less with jobs.

This difference is pretty straightforward. The only thing I need to elaborate on is the “decoupling” idea, that some people can separate truth and value — and that perhaps this is consistent with a preference for thinking over feeling. I reject this. Facts and values are conceptually distinct, but ultimately part of the same system. Focusing on the facts causes the valuation process to retreat to the unconscious, focusing on values forces thoughts into the unconscious.

Judging vs perceiving

People often confuse this with the “conscientiousness” facet of the big five. It’s not the same thing. Judgers prefer structure while conscientious people are better at executing it. Concretely speaking: judgers prefer closure and external structure; perceivers prefer internal structure and the ability to keep options open. In terms of tendencies:

• Judgers are more opinionated than perceivers, who have either absent, developing, or uncertain opinions.

• Judgers often decide on a best way of doing something and always do it that way, while perceivers do whatever feels natural.

• Judgers find local maxima and optimise them, perceivers try to search for the global maxima… And often fail. Sometimes, they don’t.

• Perceivers are natural deconstructers, judgers are natural builders.

• Perceivers hate missing information, judgers hate leaving it unexamined.

• Judgers are more comfortable forcing the world to comply with their standards, perceivers are better at accepting it as it is.

• Judgers with bad perception are rigid and incapable of tolerating other people’s perspectives, perceivers with bad judgement devolve into laziness

• Judgers are more likely to be religious.

I think the judging/perceiving difference is the hardest to evaluate in yourself, because there is often a gap between what you think you should do, what you naturally do, and what you do in a given moment. People who naturally prefer external structure, but aren’t good at implementing it, it might look like perceivers; their preference is judging.

Jungian functions

This is where MBTI theory starts to become much more abstract, unfalsifiable, but interesting. Beyond the four preferences, MBTI also theorises that there are eight type functions, which Myers and Briggs took from Jung. A quick rehash:

1. Extraverted sensing (Se): to experience the real world as it appears. Present-focused.

2. Introverted sensing (Si): to draw upon experiences from memory. Past-focused.

3. Extraverted intuition (Ne): to intuit various interpretations of the world as it appears and hold them as alternatives.

4. Introverted intuition (Ni): to focus on one particular interpretation of the world.

5. Extraverted thinking (Te): to judge things according to whether they function.

6. Introverted thinking (Ti): to judge things according to whether they are true.

7. Extraverted feeling (Fe): to judge things according to whether they preserve social harmony.

8. Introverted feeling (Fi): to judge things according to whether they are are subjectively valued.

Myers and Briggs theorise that a type’s dominant function is determined the following way. First, they have their irrational (S vs N) and rational (T vs F) preferences. Then, the judging vs perceiving trait (J vs P) decides whether the main rational function is internal or external. If it is perceiving, it is internal; if it is juding, it is external. The main irrational function works the opposite way: if a person is judging, then their main irrational function is internal; it they are perceiving, it is external.

Introversion vs extraversion decides which of the two main functions dominate — sorting them into a ‘dominant’ and ‘auxiliary’ function. Then, the inferior functions (the opposites of the dominant functions) balance out the dominant functions. Use of only introverted functions leads to solipsism, use of extraverted functions leads to meaningless reactivity. And it also can’t be a judging function too: all judgements and no perceptions leads to nowhere. So if the dominant function is judging, then the auxiliary function is perceiving and vice versa.

Allow me to be more concrete. Let us take my personality type (INTP7) and infer its function hierarchy. The P means that the thinking is internal, and the intuition is external. The I means that the introverted function dominantes the extraverted one. So, we have Ti > Ne. The opposite functions then have to balance out the dominant ones, so then we have Ti > Ne > Si > Fe. Ti is the dominant function, Ne is the auxiliary, Si is the teritary, and Fe is the inferior.

The dominance does not mean that the function is more developed, but in practice, it tends to happen that way — INTPs naturally prefer Ti and Ne, so they develop their execution more completely. On the other hand, Si and Fe are not as developed and focused on, so they retreat into the unconscious. As such, INTPs often struggle from repeating the same mistakes and misplacing things (Si deficits) as well as awkwardness and emotional, validation seeking outbursts (Fe deficit). That… describes me better than I would like to admit.

Essentially, in MBTI, personality development happens by accepting your preferences, and then trying to develop the execution of your inferior functions first; then awareness of your shadow functions if you can.

The logic of which function dominates does make sense and follows cleanly from basic MBTI theory, but the part about the inferior functions balancing out the dominant ones… I don’t really know if that is true.

Traditionally, it has been posited that the dominant emerged in childhood, the auxiliary emerged in teenage years, the teritary emerged in adulthood, and the inferior was almost always never fully developed. Now, people are more skeptical of this, and are not as sure about whether function maturation is the same for all people. I, personally, doubt it.

Criticisms of the MBTI

The most common criticism of the MBTI is that it is not scientific. Scientific… Meaning what? Does it have institutional approval? Is it official? Is it high status? Is it able to systematically make testable hypotheses about the physical world? The answers to the respective questions are: it depends on the insitution, kind of, not really, and yes. It is commonly believed that scientific experts reject the MBTI, when, to my knowledge, there is no survey of expert psychologists’ opinion on the model.

So yes, the MBTI is about as “scientific” as any psychological theory, like IQ or the big five. It’s not scientific in the sense that it involves a lot of abstact constructs, but if you take the constructs for granted, then testing said constructs are the same as testing any other physical thing, like the weight of a human. There is some abstraction and faith that goes into the concept of a body itself, but it is not as big of a leap.

People also criticise it for dichotomising its variables, which reduces their reliability and granularity. This critique is rather confusing, because the point of the MBTI is the dichotomisation and trying to model humans using how different preferences interact to produce different archetypes. And MBTI tests can give continuous scores as well, they just aren’t as commonly used.

People have criticised the MBTI test for being unreliable, sometimes based on a single statistic, or on anecdotes. So, to be clear, let us assume the test is reliable. Does that mean it is good? No — if the thinking/feeling test was simply a bunch of questions asking “do you like computers” with different wording, then it would be bad. And if the test was unreliable, then that wouldn’t mean that the MBTI framework itself is bad, it could just indicate the test is in need of improvement.

So, the “MBTI is unreliable” critique proves itself to be uninteresting. And for those who are interested in it, the official MBTI test’s reliability is within the standards of the statistical community, which is > .70. The dichotomisation makes the statistical unreliability more apparent.

Myers in Gifts Differing noticed issues with the reliability of the MBTI test in children and teenagers, and she attributed this to their preferences not being as defined or developed at a young age; I would also note that self-awareness and self-concept scale with age. So the actual MBTI test being unreliable might not even be an issue with the test or the framework, it could be the nature of the testing circumstance.

The main functional shortcoming of the MBTI, in my opinion, have to do with poorly modelling emotions and actions — it’s missing something along the lines of order/self-efficacy and emotional attachment/neuroticism. In terms of praxis, I also think the MBTI leans too much into institutionalism by having a “main MBTI organisation”, perhaps if there was no official MBTI, then people would be more comfortable researching the model.

Further reading

• Gifts Differing — Isabel Myers

• Psychological Types — Jung

• MBTI manual (v3) — Isabel Myers

3

Relevant meme:

There is, however, one point he made that did hold water. That, when you correlate IQ scores with other outcomes of interest that aren’t test scores, the relationships observed aren’t strong — 25% of the variance in productivity and lifelong income; less of others like divorce rates or political beliefs.

Taleb’s critics pivoted to arguing that he was using the wrong statistic (R^2), and that if he really wanted to know how much IQ matters, he should have used the correlation coefficient (r). Converting from r to R^2 is just a matter of multiplying r by itself, squaring it, so to say.

I think this is an awful argument. Let me put this mathematically: if IQ explains 25% of the variance in productivity, then 75% of the variance is explained by other factors. 75% is a lot bigger than 25%, so it would be fair to conclude that there is a lot more that goes into productivity than just IQ. It’s also literally just the same statistic, just on a different scale.

Sometimes, neither of these statistics are the correct ones to use. Let’s say you want to test how much malaria harms your health. If you were to correlate people’s malaria infection status to their health in the South Africa, the correlation would be close to zero because there’s very few people who are infected with it at a given point. But malaria absolutely does mess you up.

In psychology and statistics, there are guidelines regarding what constitutes a small, medium, or large effect size. These might be helpful for undergraduates, but the tables themselves are made up — whether an effect is “big” or “small” has to do with subjective values, not mathematics. In that regard, the R^2 vs r debate is not helpful, because the salience of a statistic cannot be determined by how big it is.

The standard deviation of income of income in the United States is about $50,000 dollars. Increasing your income by 0.2 standard deviations would be equivalent to $10,000 dollars per year. I’d venture that’s a lot. On the other hand, 0.2 standard deviations in height adds up to only 0.5 inches.

Where to go from here?

When people realise that IQ doesn’t explain that much of the observable universe statistically, this could be due to two reasons.

One of them is that intelligence cannot be measured accurately by IQ tests, and that intelligence is best defined as something else. A popular definition I’ve frequently seen is that “intelligence is the ability to get what you want out of life”. The spirit of the phrase is that your intelligence doesn't matter if it doesn't lead to any outcomes, which I agree with, but it is still false by definition. The realisation helps prevent people from coping with failure by tieing your self worth to your intelligence, but that doesn't personally resonate with me.

I think that this definition, covertly, sneaks IQ determinism back into the equation, just with the aside that it can’t be measured by a test, but with what you do and get. And those things definitely matter, I just don’t think they are that related your thought processess.

The definition of intelligence I've arrived to is the ability to infer information from information. The inference can be difficult because it is far-reaching, unintuitive, requires background knowledge, or mentally tracking lots of involved parts. IQ tests can measure how intelligent people are, because they measure the amount of knowledge they have already accumulated (vocabulary, general knowledge tests), proxies for cognitive ability (e.g. reaction time, processing speed), and making conclusions that are far-reaching and involve tracking lots of parts.

Funny that Taleb’s critique involves arguing that there is no right answer to the question ‘ 1 → 2 → 3 → X ‘ , because the pattern could be something besides 1+1+1+1 that looks like 1+1+1+1 for the first three numbers. In the real world, a lot of conclusions people have to make look like this: no 100% logically correct right answer, but something that “feels right” and works.

I’ve entertained the perspective that IQ tests do not measure intelligence before, and came to the conclusion that they do so pretty well. It’s not really possible to determine how well exactly because intelligence is an abstract, unmeasurable concept, but I think the true correlation between intelligence and IQ is something like .8.

The other reason that intelligence could not be a good statistical predictor of anything besides test scores is that it just doesn’t matter that much. It doesn’t factor in, well, everything else about a person: their personality, physical capabilities, appearance, physical health, or circumstances.

Notes:

I haven’t posted in a while, partly due to having the flu from Jan 2 - 15; and also because I have been cooking two really long pieces: an attempt to explain all personality psychology, and an attempt to build a framework that explains all differences in income between people.

Said flu also led me to reflect on the time I got typhoid fever when I was 19. I did it on my new substack publication Selective Contrarianism, where I just post whatever I think in the moment without regard to what is acceptable, what people would find interesting, or whether it makes sense.

1. Capitalism revealing our preferences.

2. Build-up effects (new hypothesis, I’ll explain this).

3. Faster iterations of news cycles, cultural cycles, and social discourse.

4. Literature becoming less relevant, both in terms of creation and readership.

5. Loss of faith in definitive and long-term vision.

When people talk about the convergent culture of monochrome and minimalism — whether in logos, cars, interiors, clothes, or designs — the blame is often levied at “algorithms” shaping our preferences and making all companies do the same thing. Ignoring definition games about what constitutes an algorithm, computational models are clearly not to blame for the convergent culture.

Take, for example, the change in car colours over time:

The change starts in 1998, before the big data revolution.

How about photos of artifacts in museums?

Constant increase in monochrome and colder colours ever since the 1800s. It seems more reasp, a type of artificial intelligence that assigns incentives and prices based on demand and conditions is a much more explanatory explanation for why culture has converged than computers.

And regardless of what mechanism drove the convergence, the drive to blame the algorithms is interesting. Essentially, what an algorithm does is that it takes a bunch of inputs and transforms them into an output. In the context of culture, this happens at various levels, but conventionally, people are talking about the taste-level. Companies release products, consumers buy them, and then companies adjust their response to the tastes of the consumers.

If so, then all that is occuring is an episode of the masses revealing their preferences. Cultural decline as perceived by an observer, not a god, or the public for that matter.

You could argue that, maybe, this is a molochian problem where the incentives at the individual level are to cater towards the average preference, but it would be better in aggregate if companies did things differently anyway. I find this doubtful, if there really was a burning desire for original television and film, then people would make it.

I think this is a fair case to be made that the problem with cars and interior design is molochian, in the sense that people want to resell their assets for high prices to people who want them — incentives encourage following safe or public preferences. I would ask why somebody wealthy enough to buy a new car and decorate their house would care about how much they sell it for; these are humans we are dealing with after all.

Architecture is a little different, Scott Alexander approached this issue and he thinks that it might have to do with the wealthy wanting to hide wealth in favour of signalling taste, and architects and designers finding the old aesthetics — symmetry, maximalism, and functionalism — too constraining. In that case, it would be appropriate to blame the tastes of the creators | elites and not the masses — most people like traditional architecture more than modern architecture.

Strangely, when we see an increase in drivers of cultural diversity — be it racial types, subcultural fragmentation, or political polarisation: we are afraid. We must manage it with bureaucracy and social fabric, or reduce it by means of limiting immigration or discourse. We don’t seem to want culture to stagnate but we also don’t want it to be diverse either.

There are people who do want different, new things, they are just in the minority, and there are not enough of them to sustain avant garde, ambitious art at scale. Especially when these people who want better things can just pivot to older content; the kind of people who want different things are also more likely to try to find it. Which leads me to my second hypothesis:

Build-up effects

This is not the same as a low hanging fruit effect. A build-up effect is an effect that arises from more fruits being picked, regardless of where they are on the tree.

The low-hanging fruit effect is a good explanation for the decline in productivity in the sciences and perhaps some constrained forms of art. I am, however, skeptical of whether this is the case for the rest of culture and particularly narrative, the form of culture I am most interested in. Most great narrative masterpieces are not low-hanging fruits1, but high-hanging ones, stories that were difficult to conceptualise and execute. Lord of the Rings, for example, took decades of worldbuilding and conception to bring to fruition.

I think that a similar, but functionally different effect is responsible for some of the slowdown in culture we seen: I call it the build-up effect.

Imagine a society with a set population of 100 million people and zero innovation, but possesses modern digital technology. 10,000 works of narrative are released every year. Every year, the number of total works ever written keeps increasing every year relative to the number of new works. Even with no technological or demographic progression, culture “stagnates” because the amount of total work the culture has produced is constantly increasing relative to new output as nothing else changes.

This also drives perception too. As time goes on, even if no sequels or remakes are published, it feels like culture is stagnating because, as time goes on, the best of it is increasingly old. In addition, more of those 10,000 works are going to be remixes, adaptations, sequels, or remakes of the old works.

The catch: this is clearly not the main driving force behind what is happening.

Take films, for example. The amount of new film has skyrocketed starting in the late 90s — from 5000 in 2000 to 17500 in 2020, and the same is true for other forms of art, like anime2 and books3 too.

It’s difficult to quantify the number of remakes and sequels that occur every year, because they need to be labelled manually, so people often evaluate this by looking at the top films by revenue. This will overestimate the number of sequels/reboots, as successful franchises disproportionately continue

Even so, this cannot be the cause of the problem. See the following chart: top grossing films went from 25% sequels in 2000 to 75% in 2020.

If we take these numbers at face value, then we have gone from ~3750 brand new films in 2000 to ~4300 in 2020 — an increase, in fact. The problem is that they are, well, bad.

Personally, the “sequelitis” critique of culture doesn’t land because a lot of my favourite media — Fate/Zero, Skyrim, and Devil May Cry 3 — are all sequels. I do concede, however, that this is behind a great share of the perception behind culture stagnating — not the essence, though.

I think the build-up effect, however, can explain artists not wanting to cater to divergent or “refined” tastes — those with these tastes can just look up the content they want to watch on the internet, and watch it themselves. I don’t believe true art competes with anything, because nothing can replace it, but the shift in incentives remains nonetheless.

Faster cultural iterations

Essentially, a cultural iteration is:

Ideas (e.g. mythology, political philosophy) → content (e.g. films, games) →discourse (e.g. tweets, books)→more ideas→more content

In the past, these things occurred slowly, because distribution channels took their time, attention spans were better, and the content was longer.

Now, it is extremely fast.

This speed makes discourse feel meaningful, impactful, or cool. But said speed actually makes the iterations less impactful: stable changes in conception and belief come from periods of reflection, not an attention-shifting state. I am not blaming only trashy short-form content, but also the speed up in the pace of all content, be it film, television, or books.

These fast news and event cycles give people the illusion of a rapidly changing, impactful discourse, but none of the substance: when one side starts losing face or composure, it disengages and diverts attention; the winning side claims victory, only for the “victorious” argument to be forgotten in mere weeks. The cancelled not only stay cancelled, but irrelevant too. Anti-capitalist films and television like Parasite or Squid Game go viral, disappear, only to be replaced by the enduring soul of utilitarian neoliberalism.

Growing irrelevance of literature

This was the topic of the first post on cultural decline:

I still consider the thesis defensible. I think I was too eager to claim that the best authors would turn away from writing — it’s still materially easy to do, and I think the very best, the transformational talents, are probably still there; perhaps just writing stories in different mediums.

The current mediums: video games, films, and television series, are not as suited to the creation of original and high quality content. These technological mediums serve best as vectors of transmission, not creation. Cultural changes observed elsewhere (e.g. logos, cars) cannot be explained with any of the causes I posited, besides perhaps broad technological stagnation.

Loss of faith in definition

If you look at the greatest of our species — be they artists, statesmen, philosophers, entrepreneurs, scientists — they often have different personalities or backgrounds, but there are two traits that recur:

1. High intelligence.

2. The ability to commit to a definitive, grand, long-term vision, even in the absence of financial or social rewards.

When people speak of the decline of great genuises, I think that some of it is just an artefact (might talk about this later), but I think some of it is a culture that encourages spontaneity, novelty, and “keeping options open” over planning, hard work, and delayed gratification. The former gives us consultants, financiers, polymaths, and generalists; the latter gets us to the moon.

This is a softer and less empirical explanation, but it nonetheless feels real to me. Thiel touches on this issue in Zero to One, the best book I have read to date.

The false explanations

I avoid putting people on blast. I will abide by this standard here, though it will lead to an inevitable loss in context, so I will link the posts but not mention names.

Our first theory posits that there is a general loss in divergence in human behaviour, and that this is causing the great cultural convergence: the monochrome cars, minimalist logos, and athleisure that have been panned to death, but also the lower drug use in the youth, crime reductions, and fertility declines.

The author hypothesises that this decline is driven by longer and more predictable lifespans, which encourage more risk averse behaviour and slow life strategies — less drugs, sex; more studying and reputation-guarding. Once people start doing that, their life experiences homogenise, lives narrow, and worldviews converge. This convergence in experience causes a convergence in artforms, and institutions enable this by penalising failure and documenting reputations.

I object to this analysis on almost every single level.

Regarding the trends in the youth, the elephant in the room is the decline in face-to-face social interaction. I ask, what kind of person spends all their time drinking alone? Smoking alone? A depressed, executively dysfunctional person. The fact that the youth of the day are turning away from the drugs and the crime is not a testament to their weakness, but to their strength and isolation. There is also statistical evidence4 that these trends we see in aggressive behaviour such as unprotected sex, drug use, and crime internationally are driven by declines in social interaction: not phones, the internet, or parents being too vigilant.

The same kinds of people who engage in petty risks — unprotected sex, violence, drug use, or crime — are actually probably less likely to create great art, which requires delaying gratification. Dysfunctional risk-takers are less risk averse, but they are also less intelligent and worse planners. It also doesn’t factor in that the kind of people who take concrete risks (MBTI sensors) are not the same type of people who take abstract risks (MBTI intuitives).

Also, just take a look at twitter, or any internet culture for that matter. Are we really getting less weird, or is people’s weirdness just getting expressed in different ways?

I also object to the cause. Longer lives and less day-to-day death risks encourage behaviours with longer time horizons — which encourage great art.

There is also another theory which states there is no cultural decline, and all of the innovation is hidden in new art forms: tiktoks, tweets, or memes. Now this is a cope.

Many of these advocates of internet culture (not the author, to be fair) never stop to tell us what about it they enjoy; I have no such reticence: I like the naruto AI parody where Naruto’s body is inhabited by an African man, the Skyrim AI parodies of American culture, RWBY fanfiction, and the Sonic fandubs with Alfred in them.

These people never do this because the new culture is, simply and obviously, worse than the old one. It’s not even trying to do the same thing, so maybe it doesn’t even make sense to say it is worse, but it doesn’t function as a replacement. Some of it might be funny or entertaining, but it’s not a substitution for masterpieces like Chinatown, Twin Peaks, or Ghost in the Shell. These creators of the new culture, no matter their popularity, either envy or admire the great artists.

There is this cope that “everybody wants to be a poaster”, that discourse matters or whatever, but real culture comes in serious art forms: anime, video games, film, and books. Any 200k+ twitter or tiktok account would 100% prefer to be making transcendent art or building monopolies than doing whatever they are creating at the moment. The issue is that these online platforms attract a certain neurotype, typically high in insecurity, drive, and disorganisation, and low in executive function and maturity; selecting them into social media and away from more wholesome forms of creation.

A third theorist posts that the world has been ruined by “dopamine seeking” devices which distract us, pacify us, and do a bunch of bad things. Zuckerberg, Musk, and the elites are to blame for all of this. No really, that’s what he thinks:

Do you remember rule two above? It said: Look to the teens, and their digital lives.

When you do that, you see immediately that they are the main victims here. This flattened culture is all they have ever known. It’s now the landscape of their inner lives.

Many of these youngsters lack the skills and tools required to escape. So this flattened world is really their prison—and the billionaire wardens (Mr. Z and Mr. M and all the rest), who get rich from their brokenness, want them held in their digital chains forever.

Now, I am not exactly the biggest fan of short form content. But I think this is the wrong line of attack — who, may I ask, is using phones to look at all this garbage?

Technology might have given us more distractions and meaningless fluff, but earlier generations had these things too, just in forms that had other ends and were delivered in a more palatable form: social interaction, exercise, collecting, television, and having sex with prostitutes. People starting projects and losing focus, lacking discipline, or the ability to delay gratification is a perennial problem.

Technology also gave us more opportunities and tools: easily pirated digital workstations, digital art software, and free platforms. Humankind, instead of being driven to creation, has decided to make cheap, stupid content or sterilise itself with it. The “intellectuals” ignore this obvious fact and divert the bad conscience to technology — the best thing humanity creates.

I will, say, on a positive note, that it seems like the mediums that are stagnating the least (video games, music) are also the ones where people have the easiest time making things on their own without the help of mass audiences, marketing, or institutions. Within music, I see many emerging styles like witch house, emo rap, lofi, or Phonk, they do not tend to hit the top of the charts, but many people still listen top them nonetheless. In that regard, it seems that our artists are doing relatively fine, it is the masses and elites that are flaundering.

Previously, I was concerned that perhaps the problem was that we are getting more content, and it has become harder for the collective intelligence to sort between all of it. Even small changes in the correlation between popularity and quality could change the quality of what rises to the top.

I no longer think this is the case. Strictly speaking, there are two barriers to the creation of culture:

1. The number of people who engage with a form of culture.

2. The ease of creating said culture.

Lots of people watch anime, but only several hundred are created per year, because creating anime requires a studio and capital. Novels aren’t read that often, but are frequently written because it is far easier to write a novel than film a movie.

The raw quantity of film and anime has increased by an order of magnitude in the last 20 years, but 17500 films have been released in 2020 and 300 anime were shipped out (not aired) that year. Those numbers also differ greatly, but I feel like the “rise to the top” effect is pretty similar in both mediums and isn’t affected that much by the raw amount of content. More coal doesn’t hide the gems if they are shiny enough.

People have also highlighted that selection in the past was different: it was institutions that chose whether a book was published or a film was released. Now, computers + social media make distribution of content much easier, which lowers the quality of content by default. This is probably true, but popularity has always been directed by word of mouth, which is deterministic at a high enough scale.

So

Finding good culture is easy. Find a computer, get on the internet, and search for it.

If so, then why does this even matter? To some people, this matters because culture matters to them beyond consumption; I can sympathise with this motivation. Alternatively, one could read discourse regarding cultural stagnation as performative, engaged in to signal “divergent” or “higher” tastes that stand above the mass culture, that you are keyed in to the latest trends and discussions on the internet.

I think the answers that some of these intellectuals give is rather telling. That the problem is the “elites”, that modern life makes us pod people that don’t want to take risks, and that that cheap husk of a culture we call “memes” is a replacement for high art. We would love to blame anybody but us, the people with the right tastes and preferences. Or maybe the problem is that I am not trying hard enough to find the right cultural critics.

In social environments, exposure to mass culture is inevitable. And here’s the thing: the point of these environments is the people, not the culture. I don’t think whether Golden by KPOP Demon Hunters being a good song changes whether I enjoy dancing to it with my 6 and 8 year old siblings.

2

Anime:

3

Books:

4

Let me look at the main source that suggests the decline is due to face to face socialising. Their regression table is pretty unambigious, extremely low p-value:

For the individual-level effects, it’s also pretty unambigious:

The record also does not suggest they are electronically driven either. See Table 1:

Some of it is also just later initiation ages, which goes against the author’s hypothesis:

1. Richard Hanania explains the based ritual: any objection to right wing opinions has to be due to being too right wing. “Repealing the 19th is bad because nobody should vote anyway” or “hating minorities too much is bad because that diverts hate away from women”.

2. Anonymous woman describes her dating experience in the bay area on Scott Alexander’s blog, and describes a few types: “the man who is not”, “the man who is”, “the founder”, among others. A little fluffy (to be expected), but conceptually dense, raw, and original.

Read more

The theory

Empirically, self-reported reading for pleasure has declined in both adults and teenagers over the last 50 years. People also rarely finish the books they read, which can be inferred from the fact people tend to be much more likely to quote passages from the beginning of a book. Using this data, it’s possible to estimate the percentage of people who actually finish books:

If less people are reading, that means that less people are writing, not just due to the lower demand, but also the fact that the skillsets overlap. More importantly, the demographic of individuals who tend to write the most books that become classics — White men — have vanished from major writing awards:

It’s easy enough to trace the decline of young white men in American letters—just browse The New York Times’s “Notable Fiction” list. In 2012 the Times included seven white American men under the age of 43 (the cut-off for a millennial today); in 2013 there were six, in 2014 there were six.

And then the doors shut.

By 2021, there was not one white male millennial on the “Notable Fiction” list. There were none again in 2022, and just one apiece in 2023 and 2024 (since 2021, just 2 of 72 millennials featured were white American men). There were no white male millennials featured in Vulture’s 2024 year-end fiction list, none in Vanity Fair’s, none in The Atlantic’s. Esquire, a magazine ostensibly geared towards male millennials, has featured 53 millennial fiction writers on its year-end book lists since 2020. Only one was a white American man.

This is also true for writing in American television:

…And the film industry:

Some of this is just politics, but I think a lot of it is changes in incentives. The kind of introverted, smart, artistic people (regardless of gender or race) who would have written stuff like A Song of Ice and Fire are not writing anymore. I think most of them went into tech (particularly AI, software, or game development), finance, influencing, or ghostwriting — fields that offer more lucrative opportunities, regardless of how glamorous they are. This talent reallocation has been going on for a long time, maybe as early as the late 18th Century, but it’s intensified with the development of television and the internet.

The kind of talent that makes somebody a good writer does overlap with the talent that makes them a good stock trader or coder. Far from perfectly, but well enough to the point that most people who could write a good novel would also likely be a passable white collar employee. I think that Tolkien-tier talents probably would be doing something creative regardless of their situation, but the same is not true for people who are a tier below him.

It’s also far more difficult to get discovered as a new writer now: people are writing more books, people are reading them less, and the low hanging fruits have been picked. There has been an (at least) 23x increase in books published from 1940 to 2025:

Essentially, even if the talent that makes great fiction was actually writing novels, we can’t discover which ones they are if nobody reads them, and espeically when there are so many of them. Novels also allow for more thematically complex, coherent, and long stories that are more able to exemplify what good narrative is.

I personally might not like the novel as a form of art, but it allows a single artistic mind to enforce their will onto the world. All great vision, all great stories — come from great and industrious geniuses, not institutions or groups. I suspect that part of it is due to the fact creative talent has a right tailed distribution: someone like Aldous Huxley is 10x more generative than the typical 99th percentile creative talent, but also because of the nature of thinking — it comes from one mind.

Because of the monocausal nature of creativity, top creative talent is less likely to find working at an institution attractive. It’s also true that, regardless of field, the best tend to go do their own thing anyway; there is nobody to slow them down or take the surplus of their labour. As such, the top creative talent that was previously writing novels or short stories is unlikely to have gone into the film industry. Can you imagine Franz Kafka working in Hollywood?

You do see good directing talent come out of the film industry — Lynch, Polanski, and Nolan for example. Regardless of their talents and responsibilities, they are unable to generate the same kind of lasting and unique stories that novelists like Tolkien write. They are subservient to their sources of capital, and contrained by their writers, special effects teams, and actors.

If there is less good literature, then that decline inevitably flows from books to film and television, because films and television rely on it for inspiration. A bunch of B tier talent with no drive and overarching vision are not going to make anything interesting. There are a few exceptions of high quality original television, like Breaking Bad1, but the rule remains. Literature also influences film and television beyond mere adaptation.

Culture didn’t tank as soon as people started reading less — the effect is lagged. Technology first made culture better by giving us superior methods of distributing narratives (films and television, based on people’s revealed preferences). As they improved they incentivised the creation of newer, bolder, and better content — CGI gave us Pirates of the Caribbean, technicolour gave us Robin Hood, and multi-camera setups gave us I Love Lucy.

Now that technological innovation is slowing down, there are less incentives to create new and impressive things in film. There is also less great literature to adapt into film, as the classics have gotten adapted already and nobody is writing anything to match them. Eventually, businesses start opting for safer ventures like sequels or remakes due to financial incentives and a lack of good content to test for adaptation. Graphically speaking:

Sequelitis is also massively overstated as a problem, and is better understood as a symptom instead of a cause of decline. Many game sequels, like Half Life 2, Skyrim, Devil May Cry 3, and Vampire the Masquerade were more popular and higher quality than their predecessors. I think that people like to latch on to the sequel problem because it is a legible proxy for cultural decline, which is something that people feel deep in their bones, but find difficult to justify with words or numbers.

If we are talking about television in particular, I think that streaming also contributed to the decline. Platforms like Netflix give people the opportunity to watch anything whenever they want, so television series have to try harder to catch people’s attention. Anecdotally, I’ve noticed that the pace of TV, both Japanese and Western, seems to have drastically increased after 2012, which removes all emotional impact.

Streaming also gutted mid budget films, because the industry could still expect to make some money off of DVD sales if things didn’t go well in theatres. This leaves only indie low budget films or Hollywood blockbusters; very little of the former is any good, and the latter must devalue themselves and appeal to the lowest common denominator to get any profit.

So, that’s it. Those are the causes of cultural decline in narrative-based art forms.

I have conflicting thoughts on the direction of other art. Fashion has gotten worse, mostly because people are too lazy to put any effort into their clothing. I think music has gotten better, if you ignore what rises to the top — electronic music is a richer form of expression than anything that came before it. Multiplayer games have gotten more balanced over time, but most of them are awful anyway. Drawing has improved over time due to algorithmic feeds and software.

Narrative-based art clearly stands out as getting far worse than other forms of art, which are either getting better or worse for their own idiosyncratic reasons. This, in my opinion, shows that narrative-based art must be declining for reasons beyond mere cultural changes, which should theoretially have a global infuence on all art.

Regarding the algorithms: around the 2000s, new data analytic software and compute made it easy for corporations to statistically analyse the predictors of best-selling media, and then try to fit new content to the data. Because algorithms can only adjust to existing preferences, some argue that they promote cultural stagnation.

I find this narrative unconvincing. Algorithmic recommendations could result in people watching more of what they already like and alter the natural ‘rise to the top’ that occurs with good new content, but this would only decrease the correlation between what is popular and what is good. The problem I see is not so much that good content isn’t rising to the top of the popularity hierarchy, it is just straight up not being made.

If I look at the medium I know best, anime, there is not much algorithmic curation because of widespread piracy and there being (relatively) little new content. Most anime are derived from light novels and manga, which are also not subject to artificial curation.

Anime, like other forms of narrative, started to fall off somewhere between the late 00s and early 10s. If you tally down all of the good anime from each period, the decline seems pretty clear:

• 1988-1999: Evangelion, Ghost in the Shell, Princess Mononoke, Perfect Blue, Cowboy Bebop, Serial Experiments Lain, Berserk, Great Teacher Onizuka, One Piece, Akira, Hunter x Hunter, Vampire Hunter D, Legend of the Galactic Heroes, Blue Gender

• 2000-2012: Death Note, Fullmetal Alchemist, Steins;Gate, Spirited Away, Satoshi Kon’s films, Shinsekai Yori, Code Geass, Welcome to the NHK!, Tatami Galaxy, Psycho Pass Fate/Zero, Texhnolyze Bakemonogatari, Kaiba, Nana, Attack on Titan, Ergo Proxy, Samurai Champloo, Howl’s Moving Castle, Ouran High School Host Club, Haruhi Suzumiya, Darker than Black, FLCL, Baccano!, Penguindrum, Monster, Ghost in the Shell: Stand Alone Complex, Gurren Lagann, Soul Eater, Fate/Stay Night, GITS Innocence, Avatar the Last Airbender

• 2013-2025: Mushoku Tensei, Made in Abyss, A Silent Voice, Re:Zero, Your Name, Aggretsuko, My Dress up Darling, Spy X Family, RWBY….

And that’s basically it. I’ve heard Frieren is good but I haven’t gotten into it yet.

I also play a lot of narrative-based games, and I think the decline has started to set in for games too, despite sales largely being a function of word of mouth. The decline is not as stark as it is for other mediums of storytelling, there are definitely some good post-2013 releases like Undertale, Disco Elysium, TCOAAL, and Nier.

Some argue that this decline is due to cultural forces, usually postmodernism or wokeism, constraining the development of art. I couldn’t disagree more, the most popular and impressive artists find ways to dance around social conventions regardless of time. In fact, I think that artists get punished more for being too acquiescent to politics — I count many more instances of studios getting rejected by audiences for being too woke than not being woke enough. Political and religious constraints on art are nothing new.

The timing of this decline in narrative also concords with the advent of the mass internet and smartphones. I, however, think it’s unlikely phones actually caused this. Within the West, games/film/TV have always been the entertainment of the lower classes. The mass internet and piracy expanded this audience internationally, but I doubt that writers and producers are interested in appealing to 14 year old Indonesians who pirate films on their $100 android phones.

I should also restate my view that shifts in average IQ in the last century do not explain… Anything at all. Evidence of people getting dumber or smarter in our times is generally not that good, and it doesn’t survive sophisticated corrections for measurement invariance. Uncorrelated has a nice projection of the world IQ over time:

Cultural progress is not an intrinsic fact of the world. For about 1,500 years, Europe has been telling itself the same stories, worshipping the same religions, and making the same art. Then everything changed when the printing press, camera, and computer attacked. I’d also venture that increases in global intelligence and population enabled the creation of surplus and novel culture. In that respect, it would be better to see cultural decline as a regression to the mean and not a historical contingency.

• It’s not illegal in the United States.

• IQ explains 25% of variance in job performance within occupations, more so for complex and technical professions. It beats out every single predictor of job performance typically used by firms for selection, besides work samples.

• A firm that selects software engineers with >115 IQs would see a 10-30% productivity boost, which would outweight the expenses that come from selecting smarter employees.

• It’s unpopular primarily due to social and practical reasons, not legal reasons.

Legality

First of all, it’s not illegal to do this in the United States. There was a supreme court case (Griggs vs Duke Power), concerning a firm that used IQ tests as a means to discriminate against black employees1. The court ruled that businesses must show that any test used for selection, if it produces ethnic group differences, is “reasonably related to the job.

This is not equivalent to making such testing illegal, especially given the empirical literature showing that more intelligence employees tend to have higher productivity. Furthermore, in a recent case (Ricci vs DeStefano, 2009), the supreme court ruled in favour of 20 firefighters who were selected for management roles based on test scores, but were rejected at the last minute due to concerns over disparate impact.

The combination of these two rulings does make it legally difficult. Firms who select for employees on the basis of IQ test scores, which contain racial differences, open themselves up to litigation if they can’t prove that said tests are relevant to the occupation2. If they discard said scores on the basis of their racial differences, they open themselves to a lawsuit which they would likely lose.

The correlation between IQ and job performance

The best meta-analysis on the relationship between IQ and job performance, conducted by Hunter & Hunter, finds a mean correlation of 0.53. This means that 25% of the variation in job performance can be explained by IQ scores.

This value has been debated in the literature for mainly two reasons3:

1. The value is adjusted for supervisor ratings.

2. They assumed that job applicants and the general US population had the same variance in intelligence4.

Controlling for unreliability in supervisor ratings is sensible, as supervisors evaluate employees in different ways and lack omniscience. In fact, the original Hunter & Hunter meta-analysis underestimated the degree to which supervisor ratings are unreliable — they assumed a reliability of 0.6, when in reality it’s closer to 0.52.

Regarding restriction of range — the idea is that if you calculate a correlation within a sample that is restricted, the relationship will be attenuated in strength:

Critics argued that because job applicants already show reduced IQ variance, correcting for this may exaggerate the incremental value of cognitive tests over existing hiring filters. This is valid as a contextual point, but it does not undermine the interpretation of the corrected validity itself.

The other issue is that H&H assumed that job applicants and the American workforce population were equal5 in terms of variance in intelligence when they corrected for restriction of range. While this asumption sounds ludicrous, it doesn’t turn out to be that big of a problem. Empirically, applicant pools for specific jobs vary only slightly less than the broader applicant pool:

• Sackett, P. R., & Ostgaard, D. J. (1994). Job-specific applicant pools and national norms for cognitive ability tests: Implications for range restriction corrections in validation research. Journal of Applied Psychology, 79(5), 680–684. doi: 10.1037/0021-9010.79.5.680

Correcting validity coefficients for range restriction requires the applicant pool predictor standard deviation (SD). As this is frequently unknown, some researchers use national norm SDs as estimates of the applicant pool SD. To test the proposition that job-specific applicant pools are markedly more homogeneous than broad samples of applicants for many jobs, job-specific applicant pool SDs on the Wonderlic Personnel Test for 80 jobs were compared with a large multijob applicant sample. For jobs at other than the lowest level of complexity, job-specific applicant pool SDs average 10% lower than the broad norm group SDs. Ninety percent of the job-specific applicant pool SDs lie within 20% of the norm group SD, suggesting that reducing a norm group SD by 20% provides a conservative estimate of the applicant pool SD for use in range restriction corrections for other than lowcomplexity jobs.

Given that H&H underestimated the error in supervisor ratings, and overestimated the degree of restriction of range, I calculated a correlation that adjusted for both of these biases6, which turned out to be… 0.52. Turns out the biases cancel out, as they go in different directions. For the sake of transparency, I also posted what each correction does to the effect size:

Hunter & Hunter use supervisor ratings as a proxy for productivity. Presumably, there is some bias that results from this, independent of the statistical error that comes from supervisors giving inaccurate ratings. In a followup paper, Hunter did a path analysis where the effect of cognitive ability on job performance was estimated using work sample tests instead of supervisor ratings; the overall effect was more or less the same (0.54 according to this chart):

The effect of IQ on performance also varies by occupation, where the most complex jobs have the strongest associations (r = ~0.6), while less complex ones have weaker ones (r = ~0.4). In manual labour jobs, psychomotor ability and dexterity are better predictors of performance than cognitive ability.

IQ vs other selection methods

The correlation between job performance and IQ might only be modest, but it should be noted that cognitive ability beats every alternative predictor of job performance except for work samples (r = 0.54).

In most of these cases, it’s not possible to correct for restriction of range, as the distribution of these variables within the reference population is not known. To make the apples to apples comparison, H&H note that the validity of interviews and experience would still be far below that of cognitive ability, even if their validity was corrected for restriction of range.

The key finding for the interview is a mean validity of .14 (in predicting supervisor ratings of performance, corrected for error of measurement). If the restriction in range is as high as that for cognitive ability, then the true mean validity of the interview is .21.

The observed average correlation for ratings of training and experience is .13. If the extent of restriction in range matches that for cognitive ability, then the correct correlation would be .19.

No correction for restriction in range was needed for biographical inventories because it was always clear from context whether the study was reporting tryout or follow-up validity, and follow-up correlations were not used in the meta-analyses.

How effective is test-based selection?

I’m not a fan of the academic literature on productivity, particularly the 10x literature which argues that there are massive differences between the best and worst employees. It is often unclear whether these “10x” estimates refer to the actual difference between the most and least productive workers in a sample, or merely the ratio between the tails (e.g., top 1% vs. bottom 1%). If it’s the former, then the difference will be imprecisely estimated because of sample size variance.

It’s also not clear what constitutes an objective measurement of job performance. Some software engineers might write more lines of code but at a lower quality. This also applies to art; popular films aren’t necessarily good ones.

That said, the idea that the difference between the best and worst employees in complex occupations is an order of magnitude (10x) seems intuitive to me. So much, that I won’t bother trying to justify it with academic literature.

I will be assuming from the get-go that the difference in productivity between the top 1% and bottom 1% within software engineers (just an example) is anywhere from 5x to 25x. I will be using the correlation between job performance and IQ that is adjusted for the reliability of supervisor ratings and restriction in range relative to job applicants. Presumably, the correlation between IQ and job performance could vary anywhere from 0.4 to 0.6 due to the typical heterogeneity and error that occurs in meta-analyses, so said uncertainty will be integrated into the model as well.

I chose a right-tailed gaussian distribution for productivity:

The base case is that the employees are just typical software engineers (SWE). According to Wolfram’s 2023 paper, the average IQ of a software developer is 111. Based on a table in this paper, the standard deviation of IQ within complex professions at the ~111 IQ level is about 12SD, so I will use that as an estimate for the variance in IQ within SWEs. Given that so many people apply for SWE jobs, I think it is plausible that a firm could set a minimum requirement of an IQ of 115 to become a SWE. Without sacrificing for other targets they use for job performance, that is.

Under these parameters, I estimated the percentage improvement in productivity that would result from selecting only SWEs with IQs above 1157, in comparison to normal hiring methods (which lead to SWEs with average IQs of 111). Based on the simulation, selecting for SWEs with IQs above 115 would result in an increase in productivity of 10-30%8.

Which might not sound that large, but for a company as large as Telsa, that would translate to a gain of $1-3 billion in terms of net income every year. Given the smarter employees would be slightly more expensive, and that most occupations lower variance in terms of productivity, I’d wager that the real gain could be anywhere from $100M to $1B per year.

The math at the aggregate level is also supportive of the idea that selection for IQ works. The correlation between IQ and job performance (r = 0.52) is higher than the correlation between the correlation between IQ and income (r = 0.35), especially when you consider that the correlation between IQ and income will be weaker within people who share the same job. There is also more variance in productivity than income, so even if the correlations were the same, IQ selection would still be efficient.

It’s not really possible to estimate the productivity gain if every firm selected employees based on IQ, as talent allocation is zero sum. Presumably, the filtering would result in the higher IQ workers being fed into occupations with larger variance in productivity, which would yield a net economic benefit, though I am not sure how large said benefit would be in practice.

All of these statistics assume that the test involved is a highly reliable test like the GATB or WAIS; in practice a lot of firms that engage in employment testing often have tests that are too short or incomplete, which will diminish the efficacy of testing. Matrix reasoning tests, for example, only correlate with full scale IQ at 0.7. There’s a tradeoff between test length and reliability here; the best tests will be as short as possible and as reliable as possible. For this purpose, I recommend crystalised ability measures like general knowledge, mathematics, and verbal ability.

In real terms

On an emergent level, employees primarily possess four qualities:

1. Cognitive talent: ability to extract information from information, solve problems, and make intuitive judgements. Some talent is also task-specific — some people are good writers but awful mathematicians. IQ will measure most cognitive talent, but not all of it.

2. Energy: ambition, passion, physiological health, and activity. It doesn’t come from personality or even incentives, but a kind of irrational drive that comes from the pursuit of mastering the thing in itself.

3. Character: egolessness, emotional stability, work ethic, and sensitivity to the thoughts and feelings of others. This is analogous to the psychological concept of stability, where there are strong positive intercorrelations between emotional stability, agreeableness, and conscientiousness.

4. Polish: appearance, charisma, and ability/willingness to manipulate situations and perceptions to their advantage. People with polish can pretend to have good character and to a lesser extent talent/energy.

In my opinion, talent > energy > character > polish in terms of productivity, though this varies substantially by occupation. Polish is essential for professions centered around persuasion or performance (e.g., acting), but far less for technical ones (e.g., academics).

I think a lot of the appeal of IQ testing online comes from the fact that it selects people based on their talents and not polish. The problem is that said selection ignores character and energy, leading to the hiring of potentially egoistic or lazy employees who could be hiding their shortcomings with a layer of polish.

One could argue that, in a corporate environment, those kinds of things shouldn’t matter. But evidently they do. In fact, the kind of people who disregard the feelings or thoughts of others when acting or speaking would recoil at the idea of being treated the same by their peers. Tactlessness usually reflects a lack of character and self-awareness, not polish.

References can’t unveil this coat of polish because the incentives for employers to give other employers accurate references don’t exist. If anything, they are perverse: employers might readily recommend employees with poor character or talent to get them off their plate. It’s an unfixable problem; personality tests are too unreliable and easy too game. Ideally workers would be vetted for IQ first, and then when they have the opportunity to work at the firm, they are promoted based on their productivity; this would still gate untalented but potentially productive employees from the system.

Why don’t firms use IQ testing?

People often ask why intelligence testing isn’t popular in firms if it’s supposedly so effective; there is no one answer to this question. It’s often raised in the lens of the “free market”, that perhaps the fact that IQ testing is unpopular demonstrates that it doesn’t work.

There are some occupations where it simply doesn’t make sense — jobs with low demand, low variance in productivity between workers (e.g. assemblyline workers), and where skill is highly legible (e.g. artists, musicians) do not benefit from cognitive testing. Because hiring methods are mimetic, it’s inevitable that managers who would benefit from selecting from IQ might copy the hiring methods of other managers who do not need to do so.

“IQ” is a socially controversial concept, some people believe in it, others don’t, so it’s inevitable that some businesses will not use it even if they are incentivised to.

Beyond being controverisal, IQ tests are also gauche; stigmatised on grounds of being racist, classist, ageist, and nerdy. They assign people a single number that is assumed to measure intelligence, something that is considered to be innate and also valuable, a dynamic which creates resentment and anxiety.

Some people don’t like it when status-associated traits are explicitly measured out in the open. Some of this is just egalitarian drives, but it also has to do with preferences for implicit or ambiguous hierarchies which allow people to preserve their egos.

Interviews, references, and holistic impressions might be less effective at scale, but they also give evaluators a pretense of agency or mastery when selecting employees. IQ tests are cold and lazy.

The effect of selecting employees for IQ presumably varies by company. I doubt Microsoft, for example, would see large gains from test score selection, as most of their value comes from a product that they’ve already built; though I would assume that if Microsoft was more intelligent they would make decisions that result in them maintaining their market share for a longer period of time. Startups would probably see the greatest success from filtering hires based on intelligence, as their value comes from products they need to create in the future.

Disparate impact

By demographic group: men and women have roughly the same IQ scores, and the elderly perform worse than the young, though much better than people would expect. Some ethnic minorities such as blacks and hispanics perform worse on IQ tests in comparison to whites.

Independent of the causes of these associations, IQ tests typically show little evidence racial or sexual bias at the aggregate level — See Jensen 1980 for an extended review of this topic. In summary, bias in intelligence testing is assessed by regressing an outcome variable of interest (e.g. training success, income) onto IQ within two groups. Bias can be assessed in terms of intercept and slope: if one group has consistently better performance in comparison to what is expected based on their IQ, then the test is likely biased against them9.

Example of a specific test of this hypothesis (though not an explicit one):

I should also mention that it’s the majority opinion within intelligence research that IQ tests are not racially biased10.

So

If you feel like you need to select your employees on the basis of IQ, you probably do. The since the goals and situations of employers will differ. If the occupation is one where work samples or job knowledge tests are easy to administer, reliable, and effective, I would advise for using those regardless of situation; otherwise, IQ tests should do just fine.

R code:
#going through every possibility from 0 to 0.53
possible_range <- seq(from=0, to=0.53, by=0.005)
error <- rep(0, length(possible_range))
iteration_product <- data.frame(i_rxy = possible_range, error_term = error)
sd_ratio = 0.67
assumed_unrestricted_sd = 15
assumed_restricted_sd = assumed_unrestricted_sd*sd_ratio
corrected_rxy = 0.53

#R = (rS/s)/ sqrt(1-r^2 + r^2(S^2/s^2)).
#r = R * sqrt(1-r^2 + r^2(S^2/s^2)) * s/S

for(i in 1:length(possible_range)) {
  inferred_rxy_value = iteration_product$i_rxy[i]
  #rearranged correction formula
  
  inferred_rxy_formula <- corrected_rxy * sqrt(1-inferred_rxy_value^2 + inferred_rxy_value^2*(assumed_unrestricted_sd^2/assumed_restricted_sd^2)) * assumed_restricted_sd/assumed_unrestricted_sd
  
  iteration_product$error_term[i] <- (inferred_rxy_formula-inferred_rxy_value)^2
}
iteration_product
#minimised at 0.385
uncorrected_r <- iteration_product$i_rxy[iteration_product$error_term==min(iteration_product$error_term)]

#going from 0.6 to 0.52 supervisor rating rxx
corrected_for_supervisor <- uncorrected_r*sqrt(0.6)/sqrt(0.53)
corrected_for_supervisor
#10% lower than 15 = 13.5

assumed_unrestricted_sd_true = 13.5
assumed_restricted_sd_true = assumed_restricted_sd
true_ratio <- assumed_restricted_sd_true/assumed_unrestricted_sd_true

true_corrected_rxy <- psych::rangeCorrection(r = corrected_for_supervisor, sdu = assumed_unrestricted_sd_true, sdr = assumed_restricted_sd_true, case=2)
true_corrected_rxy

> IQ_vector = rnorm(100000, mean=100, sd=15)
> jobperformance_vector <- IQ_vector*0.53 + rnorm(100000, mean=100, sd=15)*sqrt(1-0.53^2)
> 
> sd(jobperformance_vector)
[1] 15.028
> 
> empirical <- data.frame(IQ = IQ_vector, job_performance = jobperformance_vector)
> 
> pro100 <- empirical %>% filter(IQ > 100)
> rxy <- cor(pro100$IQ, pro100$job_performance)
> sr <- sd(pro100$IQ)
> su <- sd(empirical$IQ)
> 
> psych::rangeCorrection(r=rxy, sdu=su, sdr=sr, case=2)
[1] 0.53679
> cor(empirical$IQ, empirical$job_performance)
[1] 0.53296
> R = (rxy * su/sr)/ sqrt(1-rxy^2 + rxy^2*(su^2/sr^2))
> R
[1] 0.53679

generate_perf <- function(pe, ere) {
  raw_perf <- IQ_vector*ere + rnorm(100000, mean = 100, sd = 15) * sqrt(1 - ere^2)
  raw_perf^pe
}

ratio_error <- function(p, target_ratio, er) {
  perf <- generate_perf(p, er)
  q <- quantile(perf, probs = c(0.01, 0.99))
  ratio <- q[2] / q[1]
  (ratio - target_ratio)^2
}

# Solve for exponent p
solve_exponent <- function(target_ratio, r) {
  optimize(ratio_error, interval = c(0.1, 20), target_ratio = target_ratio, er = r)$minimum
}

p5  <- solve_exponent(5, 0.5)
p10 <- solve_exponent(10, 0.5)
p15 <- solve_exponent(15, 0.5)
p20 <- solve_exponent(20, 0.5)
p25 <- solve_exponent(25, 0.5)

p5
p10
p15
p20
p25

jobperformance_vector <- (IQ_vector*0.5 + rnorm(100000, mean=100, sd=15)*sqrt(1-0.5^2))^p15
q <- quantile(jobperformance_vector, probs = c(0.01, 0.99))
q
###############################
set.seed(1)
IQ_vector <- rnorm(100000, mean = 100, sd = 15)
noise_generator <- rnorm(100000, mean = 100, sd = 15)
people <- data.frame(IQ = IQ_vector, noise = noise_generator)
people$selector <- people$IQ + people$noise


r_variance <- seq(from=0.4, to=0.6, by=0.01)
byx_variance <- seq(from=5, to=25, by=1)
daframe <- data.frame(temp = rep(0, length(r_variance)*length(byx_variance)))
daframe$byx <- rep(0, length(r_variance)*length(byx_variance))
daframe$r <- rep(0, length(r_variance)*length(byx_variance))
it <- 1

for(r_value in r_variance) {
  for(byx_value in byx_variance) {
    p_exp  <- solve_exponent(byx_value, r_value)
    
    people$job_performance <- (people$IQ*r_value + rnorm(100000, mean=100, sd=15)*sqrt(1-r_value^2))^p_exp
    
    mean_111 <- people %>% filter(selector>208)
    plus_115 <- people %>% filter(IQ>115)
    
    ratio115to111 <- mean(plus_115$job_performance)/mean(mean_111$job_performance)
    
    daframe$r[it] <- r_value
    daframe$byx[it] <- byx_value
    daframe$ratio[it] <- ratio115to111
    it <- it + 1
  }
}

daframe

10

Table 3:

1. Identifying a proxy for happiness, like depression diagnoses or self-reported well-being.

2. Correlating said proxy with a trait.

3. The understood conclusion is that the observed correlation is causal and that people should find happiness by optimising for the traits that are correlated with happiness.

Sometimes the methodology is more statistically complex, allowing for a more explicitly causal interpretation, but my criticism here is not methodological or even causal.

The first problem with happiness is the concept of happiness itself, which is murky and difficult to define; often people confuse it with contentment (one’s own life evaluation), nirvana (an absence of suffering), or joy (an emotion). I define happiness as the relative balance of positive/negative emotions that occur within a context-appropriate timeframe. Concretely, if you move away from a location you dislike and start to feel more positively about your life, the context-appropriate time here is after your move.

With regard to contentment, it’s better to think your life is good than bad, but if your life is actually bad, then you should think it is bad — self-delusion will only remove the purpose of negative self-evaluation (self-transformation) and keep the pain.

This is also where I break with conventional wisdom on hedonism. Hedonism is true insomuch as your emotions are what describes your value function, but it’s false insomuch as the emotions themselves should not be optimised. Even if they really are the “ultimate goal” of everything.

Often when people criticise hedonism, they do so arguing that it is good to sacrifice pleasure for the purpose of something else, e.g. avoiding hyper-palatable food to feel healthier. In reality, the example is simply a trade which exchanges one reward for another. Typically, when people propose these examples, the compared rewards are of different natures or time scales, which makes the rebuttal seem legitimate when really it is a misunderstanding of the hedonist thesis.

The conflation of positive/negative emotions with good/bad value is also an issue. Hedonism doesn’t say that positive emotions are good or that negative emotions are bad — pain can be good and pleasure can be bad. Drugs can feel good and ruin your life. People with a congenital insensitivity to pain suffer from their disorder: unnoticed infections, self-inflicted injuries around the mouth from biting, and bone fractures.

Do people really know what they feel?

When people take surveys, they are most likely in a reflective mode and not experiencing any strong emotions, so any response they give will be regarding an assessment of their life as is and not their current emotional state. Sexual activity might bring people joy, but they do not experience said joy when they are filling out a survey and it might not even weigh into their responses.

I think that people have a decent intuitive grasp of how good their life is to live, but I question how accurate these reports are for the purposes of statistical research. The norm is that when different people evaluate different things at a subjective level, their responses do not strongly correlate — whether it’s peer reviewers or raters of personality. I see no reason why happiness should be different.

Researchers often think about happiness in poor theoretical terms; allow me to introduce the example of money and happiness. Let’s be clear here: people feel joy when they receive money. Said joy might be momentary or fleeting, but it is joy all the same. If this is the only emotional thing that money does, then money does cause happiness, just to a limited extent.

One could criticise this argument on the grounds that income statistically tracks life satisfaction more than happiness, but I defer to my criticism of how people report their emotions in these surveys: it’s completely possible that income and resources cause people to feel more positive emotions on a day-to-day basis but said increase is not registered in their resting emotional state, but is reflected in their self-reported life satisfaction.

Then there is also the question of what is done with the money. If the money spent on impulsive purchases, drugs, or other things that don’t matter, then said money is at best a neutral element and at worse a negative one. If said money is spent on things that actually matter and the purchaser consistently values, then it is at worst a neutral element and at best a positive one. Given that income is an instrumental value, it seems odd that this aspect of the debate is so under-emphasised.

What has also been neglected is the massive age interaction that exists in the income ~ happiness association. There is little correspondence between income and happiness in the youth, but a stronger gradient emerges as people age:

My interpretation is that a lot of the appeal of a career is not the work, or the money, but the sense of progression itself. People might be fine with earning $30,000 a year while they are building up their skillset early in their career, but somebody who is making the same amount without the same trajectory will not feel the same way. Also, younger poor people might still have a chance to find a different line of work, but that chance diminishes with age.

The hedonic treadmill is real, insomuch as people feel momentary joy when they upgrade their living standards, but they return to their old resting emotional state after said improvement. I would argue this is true for literally everything that we do — everything is impermanent, as the Buddha says. Most older people I know say running on the treadmill is a bad idea, which seems credible to me, though I can’t say I know firsthand.

That aside, I doubt the reversion to the resting emotional state actually reflects the day-to-day lived experience: if we take two identical lives, and give one person high quality speakers and another low quality speakers, I wouldn’t be surprised if they claimed to experience the same level of happiness, but the fact remains that the person who has higher quality speakers is experiencing a better life, even if the degree is marginal and not subjectively observed.

People who doubt the effect income has on happiness are often well intentioned and are actually correct for the most part, insomuch as money itself doesn’t bring contentment or nirvana, and even when you look at the material aspect, it must be used competently in order to make any difference.

How do you actually find happiness?

Happiness research is poorly framed. It uncritically accepts a universalist frame by asking questions like “does exercise cause happiness?”, when the correct question to ask is “do some people value getting exercise?”.

It’s been observed that, based on meta-analyses of RCTs that control for publication bias, that randomly assigning people to do exercise does not make them less depressed. One could then wrongfully argue that exercise is a waste of time and nobody should do it, when really what should be questioned is the methodology.

In the real world, everybody is exposed to physical activity of some kind. Nothing is stopping them from engaging in it. Naturally, people who value the experience of engaging in physical activity and the rewards it brings them will gravitate towards it, while those who don’t care for them will not. These RCTs needlessly distort this environment and try to make people do things that, based on their revealed preferences, do not want to do.

Most people are overly insecure, and when they are unable or unwilling to do exercise, their bad conscience attributes it to a lack of discipline and effort, when really they might just not care for it. Because exercise is high status and socially desirable, people who would otherwise not care for it feel compelled to do it, and will delude themselves into thinking that they will be happier once they acquire the discipline and aesthetics of a fit person.

Genetics of happiness

All traits are heritable, and life satisfaction is no exception, with a heritability of 33-38%1. Some happiness researchers take that as evidence that people have genetic set points of emotion that people always regress back to when they are rewarded or when their experiences deviate from their expectations. This is not the correct interpretation.

35% is simply not a high heritability, it’s even below the heritability of income (for one year) or education. The heritability of a trait also does not imply that it is directly genetically caused. In the case of income/education, there are no genes that print out dollars or college degrees, but genes can change people’s personalities/levels of intelligence which then have an effect.

I don’t doubt that some people have an innate predisposition to positive or negative emotions, and that said predisposition affects how how they feel on a day-to-day basis. That said, it’s also possible for people to affect their extrnal environment using their own will and learn things that erase the suffering that comes with pain, counter to set point theory. Though I would admit that said ability to be introspective, active, and self-transforming is also heritable and likely unlearnable.

The focus on the “set point” and “resting emotional state” in happiness research seems rather odd in general. It’s not like you feel anything in a “resting emotional state”. Nobody does. You aren’t supposed to. What matters is the relative balance of positive to negative experiences.

It’s possible for people to be in the same situation but with different interpretations of it: one who is fine with it, another who is not and strives to go beyond it. The one who is not content might feel the negativity that comes from being in an unsatisfactory situation, but they might feel a sense of progression or struggle that comes from trying to change, which is arguably a positive phenomenon.

Another misunderstanding I see is that the genetic portion of happiness is somehow outside of your control or this implies that people can’t strive to be happier beyond a certain extent. This is also wrong: you ARE those genes. You ARE the circumstances that shaped you. That conscious “you” that you think is controlling your behaviour independent of your genes and circumstances is completely fake, but that is no reason to give up. If you are unhappy and want to change, DO IT. Don’t let philosophical debates about free will stop you.

Sometimes, researchers bring out the big guns and try using twin controls: they test whether the relationship between a trait and self-reported happiness exists within MZ twins. Technically, it’s still possible for a non-causal correlation between a trait and happiness to exist within MZ twins, but the idea behind the method is that if the relationship doesn’t exist between people who share the same genes, then the relationship is due to genetic confounding.

When people test for whether the association between a supposed cause of happiness and a trait at the genetic level, it almost never exists: not for exercise, homosexuality, and social media use. Though it does for income2. I also suspect most of the supposed causes of depression like pornography, video games, promiscuity, or social isolation would yield similar nulls that we would ignore because we just want to hate degeneracy because it is degenerate.

With regards to depression, the big error I see in the literature on depression is that it assumes it is a bug and not a feature. That depression somehow must reflect a physiological cause like poor nutrition, disease, or a genetic disorder and is not something that happens to functional organisms. I see two types of people who conceive of depression this way: the anti-hedonists who mistakenly believe that you should pursue “meaning” (fake), “status” (fake), or some other higher value (probably, but not certainly, fake) instead of pleasure; then you have the hedonist relativists who don’t actually understand hedonism and think that nothing matters besides positivity, so if depression makes you feel negative, then depression is bad.

The main effect depression has on people is that it reduces their energy levels, willingness to take risks, and the joy they receive from experiences. All of these things, on a superficial level, are bad. But the underlying purpose behind all of these physiological changes is to stop them from engaging in pursuits that lead them nowhere, or inform them of what bad outcomes are.

From a mechanistic point of view, frivolous activity is likely to lead to depression, as depression is caused by doing things that are rewarding in the short term or assumed to lead to rewards, but don’t actually lead to anything in the long-term. I think it’s probably true that most people would be depressed if they played video games for 80 hours a week, but I don’t think that’s the only way people can get depressed and I also think that it’s rare for people to sustain that level of dedication.

People can also get depressed by failing at a non-frivolous activity — an unsatisfying relationship, exercise that leads to no gains or injury, a dead end job, or a friendship that ends in embers. People do actually feel something when they try to accomplish things in life, it’s not the easy pleasure of doing something like eating fast food, but a different kind of reward that comes from effort and struggle. I actually think that people failing at otherwise socially acceptable and long-termist pursuits contibute to much more to depression than the frivolty that everybody loves to scream at, though I admittedly have no evidence for this claim.

So

We don’t need surveys and statistics to find happiness. Maybe we just need to look… Inside. To see if we are happy. If we are, then we don’t need to read any studies because we are already happy. If we are unhappy, then we must find out for ourselves what is causing our unhappiness, and there is no statistic that can identify what is making any specific person miserable.

And even if research on happiness could be helpful, in its present state it is a failure due to its tacit universalism and ignorance of inconvenient null findings. The genetics research on causes of happiness and depression is interesting, and useful for the sake of polemic; even then it is either ignored or misinterpreted by the public.

Further reading:

• Money does not buy much happiness — Maxim Lott. Here he cites a study that leverages data on people who are living their lives in the moment and are asked by an app how happy or unhappy they feel in the moment, which gets past some of the evaluative error observed in studies on the question. The observed effect was linear (no threshold effect) but small:

  

• Politics is worse than video games, porn, and drugs combined — Max. Can’t link this piece enough times.

• Minority Stress Model — East Hunter. In a similar vein to exercise, the link between homosexuality and mental health appears to be genetically mediated.

On my further reading lists — I often include articles that I disagree with on details or even the overall picture if they informed my thinking and consider valuable. I dislike doing disclaimers, but I assume I will be asked about this tendency at least once, so I may as well clarify myself.

2

At a p < .01 level, so just maybe. Perhaps it does for marriage too, but the p-value for the MZ association within men is not very good though (I’m not talking about the MZ-DZ difference:

To predict our economic trajectory, I used projections of national IQs and age demographics of countries to predict their GDPs from 2023 to 2100 using autoregression.

At the moment, there is not enough information to paint a precise picture, but most projections agree that global economic stagnation will set in sometime between 2040 and 2080, and it will get more difficult for nations to retire their citizens. The bulk of variation in predictions is due to misestimated parameters, not variation in projections of population, global IQ, or the use of any specific statistical model.

I estimated the percentage of countries that would have fiscal troubles with pensions by taking 50% of GDP per capita in 2025 to be an estimate of a pensioner’s state-sponsored income throughout the century. I then identified countries that would be projected to spend over 20% of their GDP on their pensions (context: Italy and Greece spend the most on pensions in the world at 18% of GDP), which I deem an excessive amount. Several countries, notably Spain, Greece, Chile, Korea, and Italy are going to have major issues with their finances going forward.

In the case of pensions, variation in population projections have massive influences on the percentage of countries that end up fiscally insolvent:

I consider this to be an underestimate of how much fiscal budgets will be an issue, as pensions run on a hedonic treadmill and aren’t fixed to a specific income. It’s inevitable that some nations will not choose between raising taxes and reducing pensions, resulting in a mounting deficit that will end in a bailout or hyperinflation.

Regionally speaking, East Asia looks awful, Europe looks good or bad depending on the country, and the United States looks fine. I should note that the European countries projected to have the least troubles with pensions are the ones most likely to have lenient immigration policies.

Israel looks like the best nation in terms of wealth and fiscal budget by far. Russia, Indonesia, Mongolia, Iraq, Libya, and Central Asian countries all look good according to the models, though for some of these countries improvements are contingent on them changing their political system. China should look good midcentury, but will fall off if it doesn’t fix its demographics.

Methodology

I use four main sources of data: the UN’s population projections, national IQ data, IQ/education/fertility data, and the Maddison GDP dataset2. I then create a set of synthetic variables that have their uncertainty estimated using various plausible models and simulated scenarios. First come the national IQs, then GDP per capita, then GDP + estimates of retirement burden.

In this study, I use three different population projections: the ‘low’ variant, the ‘medium’ variant, and the ‘zero migration’ variant. All of these labels are self-descriptive, in the sense that the low variant predicts a relatively low population and the zero migration models the world as having no immigration.

To illustrate the differences:

The UN is often criticised for not forecasting properly, particularly for being optimistic and inaccurate. For example, they’ve been predicting South Korean fertility will revert back to sustainable levels for 20 years in a row, despite constant decline:

My friend uncorrelated tried his hand at forecasting fertility trends using machine learning models and was able to beat the UN’s accuracy, but eventually came to the conclusion that the mean-reversion that is observed in fertility forecasts is statistically rational and reflects reversion to the mean. His models, for example, still predicted that South Korea would increase its fertility:

There’s also a lot of historical evidence that suggests the UN has done a good job of forecasting the global population, this is also true at the level of regions, with the UN historically being off by only about 1-5%:

In a similar vein, people often criticise the idea of GDP on the grounds that it is a meaningless metric that can’t be compared across time because of hedonic adjustments and other biases. Here I defer to the defenses made by TotalHealthOptimization and Deep Left Analysis — GDP is not perfect, but it tracks differences in living standards between time and countries very well.

When the economy recedes, GDP drops. When countries adopt market reforms, they get wealthier and their GDP goes up. Poor countries like India, Mexico, and Morocco have lower GDPs than Spain, Japan, and America.

Regarding national IQs — I think they are good enough. If we accept that it’s possible for the average IQ of a country to change, I don’t see what’s wrong with thinking that IQ could vary across countries. They track performance in proxies for intelligence like academic performance across countries extraordinarily well, to the point that PISA/PIRLS/etc tests are now used to measure national IQs. They track differences in economic activity and religious beliefs. I do suspect they have some statistical bias and overestimate difference between nations, though research on this question is unfortunately lacking.

Others may object to the projections that are made on the grounds that some technological advancements like radical life extension or robotics will make these projections moot. Taking the outside view, GDP per capita has grown at a constant rate of about 2% in most industrial economies. No technology, be it cars, vaccines, or the internet has changed this constant rate of growth. That is not to say technology does not have an effect on economic growth, simply that the ones that have come in the past 200 years have not changed the rate at which the economy grows.

With regard to radical life extension, I am skeptical because we don’t even know what causes aging and how it works. There is the goal-direction theory of aging that posits aging reflects a loss of goal direction, there are multicausal damage theories like de Grey’s, immunity theories, programmed-death theories (genes that are good when you are young but bad when you are old are selected for by evolution). I guess you could argue that it only takes one person to be right about aging to make a difference, but I’ll believe it when I see it.

The outside view is also unkind to the idea of radical life extension: the rate at which life expectancy has been improving in developed countries has been slowing down. This is because the death rate exponentially rises with age, so reductions in the death rate lead to increasingly smaller increases in life expectancy.

I didn’t use the high variant because the UN’s population projections are slightly too optimistic as is, both in terms of predicted TFRs and life expectancy. Zero-migration is an untenable assumption, but one could defend the model on the grounds that it does not assume that immigrants will resemble the natives of the countries they migrate to — a more important assumption. As such, I call it the “essentialist” model.

I have my own thoughts on immigration, but I think the idea that it causes global economic growth by taking workers from unproductive countries to productive ones is naive. It’s also an empirical fact that non-western immigrants fiscally constrain the economies they move to and will not make the pension situation any better, so immigration as a functional solution to population decline is dead in the water.

Projecting national IQs forward and backward

I added intelligence as a predictive variable for two reasons: it’s a strong predictor of economic growth between countries, with one IQ point corresponding to an increase in GDP per capita of about 8-10% based on a paper of mine3.

The first thing I did is forecast the world IQ based on the correlations between IQ and fertility by country, average IQ by country, and the world’s population projections. I do not have data for every single country, so occassionally I had to make imputations based on the correlation between education and fertility or values from surrounding countries; a few countries had their NIQs geographically imputed as well. This will bias the results for individual countries, but the direction of the global projection is unchanged.

I built on work I did in a previous paper, with some changes:

1. I added some new data from the latest PIAAC wave, bringing the total to n = 500,000 and k=183.

2. I used a different national IQ dataset: V2 of most accurate national IQs possible.

3. I accounted for uncertainty by calculating forecasts that used different assumptions.

4. In the original paper, I found that the correlation between IQ and fertility varied by source of data, so I added an uncertainty parameter that accounts for the amount of variance observed between sources.

5. The correlation between the mid-parent IQ and their child’s IQ could vary between 0.6 and 0.7 based on my own research4.

6. Varying forecasts by UN population projection.

7. Generational timings can halt or hasten the effects of differential fertility by IQ, so I tried out three different forecasting methods: using the UN’s forecasts of average age of mothers from 2023-2100, assuming they will not change at all, and assuming that all countries will converge to the average over time (28).

Those efforts led to the conclusion that the world IQ should be expected to fall from 85 to 75-79 by the end of the century, depending on which assumptions are made:

Everybody who looks at this chart has more or less the same reaction: it’s over.

…Not exactly. I think this chart overestimates the decline due to changes in fertility within countries — the correlation between education and fertility has decreased in magnitude over the last 50 years5, according to my own data. Income and fertility are also now weakly positively correlated in most European countries.

This is also true for the correlation between national IQs and TFR between countries, as middle and low income countries have started to experience declines in fertility:

I still expect the forecast to be roughly true, just an exaggeration of the magnitude of the effect by about 20%, so the world IQ by the end of the century should be somewhere between 78 and 80. Even if the situation ends up being as bad as my models predict, there is still a possibility that economic growth ends up winning because of how strong compounding is.

Training/testing phase

First, I tested my methodology on an old version of the United Nation’s population projections from 20006 that projected all the way to 2050. I also used the NIQ data and the Maddison GDP per capita dataset to model economic growth. For the sake of simplicity, I stuck with the medium population projection and did not integrate variation in IQ estimates over time into the model.

The method I use to forecast economic growth is fairly standard: autoregression, which involves predicting an outcome from a future year based on a past year, and then doing it over and over again. This method can also integrate covariates — the ones I use are age demographics and national IQ. I used 4 different autoregression methods depending on whether they used fixed or mixed effects7, and whether they used a restricted cubic spline (nonlinear effect) to estimate the effect of past GDP per capita8.

The results were not encouraging. On average, all of the models underpredicted GDP per capita by roughly 10% over the course of the 20 years.

Embarrassingly enough, if you take the observed average global GDP per capita growth from 1950 to 2000 (2.2%), and assume the same amount of growth continues into the future, you would predict the global GDP per capita in 2022 to be 15935, just below the observed value of 16744.

The population projections the UN made in 2000 were reasonably accurate — they predicted there to be 7.6 billion people alive in 2022 in contrast to the observed 8 billion on the planet at that time, so I don’t think they are at fault. All of the models gave roughly the same results, so I don’t think the modelling strategy is at fault either.

The dataset I used to train the model on had only 7334 rows of complete data, which might sound like a lot, but it’s not enough to generate predictions at this granularity. The coefficients for the effects of population ageing aren’t even statistically significant in the fixed-effects models:

To prove this, I used cluster bootstrapping to measure how much error in the model’s parameters contribute to error in predictions (the bootstrap only accounted for the error in the mode, not anything else). Unfortunately, the mixed-effect models could not be bootstrapped because they used country-based effects, so only the normal fixed-effect models were used.

Some of the variance could be attributed to sampling error, but there’s still a residual upwards trend that cannot be accounted by it. The 2000s in particular were a strong decade for growth internationally as China and the Soviet bloc countries were starting to reap the rewards of their market reforms, so it’s not too surprising that the model failed for this particular time period.

Prediction phase

Here I use the same data I used in the prior post, but with the UN’s 2024 population projections instead, so the training dataset has 11,000 rows of information on demographics, IQ, and GDP per capita. The first thing I tested was whether there was a year trend, and there was — growth has been slowing down over time.

However, when one controls for (projected backwards, not measured) declines in IQ and demographic shifts, the year trend is no longer statistically significant and is 77% smaller. This was also true even when I fiddled with the models and introduced splines or different types of effects9.

People have observed this slowdown effect before and have their own theories about it, but I think this one is a good statistical fit. The channels by which this growth slowdown effect operate might not be intuitive, e.g. wealthier economies might increase their regulations and discourage entrepreneurship, but this does mean that any theory of declining economic growth will have to account for demographic changes.

As I did in the previous example, I will be attempting to forecast GDP per capita with four different models based on whether they have fixed/mixed effects and model the effect of prior GDP per capita on current GDP per capita. I will be using three different population forecasts: the low variant, the medium variant, and the essentialist variant. I also model uncertainty in IQ trajectory by forecasting with each individual set of IQ projections that I previously created.

The results suggested that differences in modelling and population scenario had far more bearing than variation in national IQ (which is represented by the width of the individual bars):

As in the previous example, I will use bootstrapping10 to generate CI intervals for the fixed-effect models.

This is the projection for GDP per capita:

This is the forecast for GDP:

Estimating retirement burden

So, the idea is basically that working-age adults have their incomes collected by the government and said resources are then redistributed to retirees. X% is the missing variable which acts as a measurement of retirement burden. Internationally, pensioners recieve about 61% of their income when they retire in OECD countries, though the figure is typically lower in poorer economies, so I will assign a blanket estimate of 50%.

There is no pretense here that it is possible to forecast whether a given country will become fiscally insolvent due to aging populations and lowering GDP per capita. I don’t think that would even be possible with better methods and more data, the issue is that it’s not possible to know what decisions policymakers will make in response to crisis. Some countries like Singapore have private pension systems so they are more robust to the effects of evolving demographics, but that’s besides the point — public systems are the standard and I am not focusing on the fate of individual countries.

Instead, what I intend to do is to estimate the % of countries that will be under stress due to the effects of demographic decline. From what I gather online, spending over 15-20% of GDP on pensions seems to be the figure that most economists and policy-makers cite as unstable; I didn’t look too much into it but it sounds reasonable to me — I’ll stick with 20% for now. For context, the nations that spend the most in the world on their pensions are Italy and Greece, at 18%. These are the percentages by population projection type:

Here estimates vary significantly by population projection: the low fertility variant forecasts that 40% of nations will be fiscally insolvent by 2100 due to pensions, while the medium variant forecasts that only 10% will. The essentialist variant is somewhere in between. Given the conservative bound I used for what constitutes a crisis (20%) and that nations vary greatly in their spending and policies, I think it’s inevitable that several developed countries will face a pension crisis this century.

On a national scale, the countries most likely to face major issues with pensions are South Korea, Chile, Taiwan, Japan, and most of Southern Europe.

I think that fiscal crises will start popping off earlier than 2050 because the modelling strategy — blanket estimates for pension size and no hedonic treadmill — cause the variance in insolvency risk to be vastly underestimated.

What will actually happen

The main reason why aging populations have such a negative impact on GDP per capita is that most people tend to retire when they come of age. The other reason is that most innovation and new technology, which drives long term economic growth, tends to come from people between their 20s and 40s. Aging populations will not forget the old technologies, but they will struggle to create new ones, leading to lower levels of long term growth.

Besides these two effects, I don’t think that aging populations are much of an issue, and that it’s unlikely that we will see the global economy tank. Given that the previous modelling attempt underpredicted growth, and that I predict many elderly people are going to remain working against their wishes, this is my relatively positive prediction:

Regarding fertility, I don’t think the declines are a mystery. Fertility is falling in ~90% of countries at the same time, which is suggestive of a cultural or technological cause rather than an economic one. As such, I think it’s unlikely that policy interventions will be able to control population figures.

Most people only want 2-3 children, if at all, so fertility preferences in most countries are only just above replacement in most countries; in China they are below. This is fertility in an ideal world: a world where people are dating somebody they are satisfied with and feel materially ready to have children11. Which is well, not happening for most people.

It’s also possible to plot the rate at which fertility changes, and it’s clear that fertility started falling once smartphones and the mass internet started taking off.

If you ignore the first fall that came it looks like the long term trend is that the rate at which fertility is changing is approaching zero. Which means that the change in fertility is going to be closer to the medium variant than the low variant, for better or for worse. For reference, see:

If you take an account of all the biases:

1. Old people aren’t some magical curse that causes GDP shrink: they slow down economies by retiring and making less new technology. The former will be an issue if it is not correctly addressed politically, and the latter only leads to stagnation.

2. Global IQ is likely to be higher than predicted.

3. The likely fertility future is somewhere between the medium and low variant, but closer to the medium variant.

4. Improvements to life expectancy will continue to see diminishing returns.

5. Essentialism is true and moving people from country to country leads to no net global economic changes in the short term (and negative ones in the long term).

I think we are going to be fine. Not good, but not collapsing any time soon.

Political implications of this information

Governments facing fiscal troubles have three choices:

1. Raise taxes.

2. Cut pensions.

3. Do nothing and suffer from debt and/or hyperinflation.

3 is obviously the worst outcome here. It would be nice if we still had something like the gold standard, unfortunately economists have brainrot and think that having constant inflation is necessary for growth.

Raising taxes vs cutting pensions involves two tradeoffs: one of them is the tradeoff in labour, where raising taxes results in less time spent working in both the youth and elderly, but cuts economic growth; cutting pensions puts more people in the workforce, but maintains economic growth. The former benefits the old and attracts people with leftist values, while the latter benefits the youth and attracts people with right wing values. I’m not sure who is going to win, I haven’t thought about it too deeply.

Pensions and spending will become the most pressing issue in any country that starts to spend over 20-25% of its GDP on pensions, in some nations like Korea or Spain I predict it to overshadow literally everything else, kind of like how WW2 drowned out every other political concern. Everybody will have a stake in the debate, regardless of their age and income.

Prognosis by nation

Albania looks rough, no matter what happens with demographics.

The United Arab Emirates looks very rough if no labour is imported. All the other oil baron countries look more or less the same.

Argentina could get very bad, depending on how birth rates work out.

Armenia looks iffy.

Australia looks fine.

Austria looks iffy.

Azerbaijan looks OK.

I have no idea what happened with this population projection.

Belgium looks iffy.

Brazil looks iffy.

The essentialist (aka true) projection looks bad for Canada.

Switzerland looks iffy.

Chile is a nightmare.

China looks high variance.

Czechia looks OK.

Germany looks bleak, but passable.

Denmark looks OK.

Spain is toast.

Estonia could get bad.

Finland spends a lot on pensions in the real world, but they presumably could cut back on them.

France is OK.

I’d say Britain would be fine if I wasn’t aware of how awful their politics are.

Greece looks rough.

Croatia could get bad.

Hungary looks OK.

Indonesia is on track to becoming wealthier than Greece.

India looks good relative to where it already is.

Ireland looks OK.

Iran could get really bad.

The model predicts that Iraq will be doing much better at the end of the century. I think this could happen if things improve politically.

Iceland looks iffy.

Israel looks really, really good.

Italy looks awful.

Jamaica could get surprisingly bad.

Japan looks better than I expected.

Kazakhstan looks good.

South Korea looks terrible.

Libya looks good, assuming they fix their political situation.

Lithuania could get bad.

Malta is cooked.

Montenegro could get ugly.

Mongolia looks good.

Malaysia looks good.

Netherlands look OK.

Norway looks iffy.

New Zealand looks OK.

Poland looks bad.

Puerto Rico…

Portugal looks iffy.

Romania looks iffy.

Russia looks far better than I expected.

Singapore looks wild. If I recall correctly, they have a private pension system, which should protect them from a fiscal crisis.

Serbia could get bad.

Sweden looks iffy.

Thailand looks iffy.

Turkmenistan looks good.

Turkey looks iffy.

Taiwan looks bad.

Ukraine, in light of recent events, looks awful.

Uruguay looks bad.

The United States looks decent.

TODO list for V2

1. Use communist history as a past/future covariate, which could perhaps help with correcting under-prediction during the 2000-2022 period.

2. Use the 3rd version of the NIQ dataset for the forecasts, which integrates the countries from the previous datasets that got passed over in data collection.

3. Use ML/DL or other models in addition to standard autoregression to predict fertility and life expectancy, then with those predict population figures, then with said population figures the GDP per capita estimates can be made. I would have to get a better video card first, though. (Currently using RX6600).

4. Integrate multiple sources of GDP per capita into one dataset. I didn’t want to do this here because it turns out that integrating the various datasets lowered the quality of the models, but with ML/DL the different datasets can be labelled and the models could adjust accordingly. The problem here though is that ML/DL have issues generalising outside of their reference bounds and it will be difficult for them to infer what happens when 50% of people are over 65 when the oldest countries in the training dataset have maybe half of that.

5. Only use essentialist models.

6. Use different age categories, I think 0-15, 15-25, 25-50, 50-75, >75 would be best, the categories 15-25 and 50-75 can serve as liminal spaces between dependents and working-age people.

Currently, the training dataset currently includes 11,122 rows and 160 countries; the UN’s population projections contain 235, so the theoretic maximum size of a training dataset that goes from 1950 to 2025 is 17,775. Were this to be combined with superior methodology and communist history, I think the error bars in the projection could be shrunk by 40% or more.

1

That aside, I do think that resource depletion is concerning, especially since renewable alternatives are either expensive (e.g. solar, wind) or politically unfeasible (nuclear).

5

True when controlling for source, cohort, and country:

9

Spline model:

Mixed-effects:

Mixed effects + spline:

Because insecurity is maligned by contemporary society, “total self acceptance” has become the new thing in spirituality and self-help culture. If one searches for the term, they will find a bunch of psychologists and new-age type coaches explaining what it is and how to reach it. This idea has also gained some traction in the rationalist sphere due to the influence of a certain influencer who I will not name; I just want to emphasise that this is not just a normie pathology.

I define insecurity as the state of perceiving that one of our traits might not be in line with our values. ‘Might’, because someone certain they lack a trait cannot be insecure about it. This definition is important, as dictionaries often uncritically conflate insecurity with a lack of self-confidence or feelings of unworthiness. Simply not liking the fact that you are not talented isn’t insecurity – it’s either truth (if you don’t have talent) or delusion (if you do). This uncertainty can arise from four sources:

1. Lack of clarity: the individual might not be sure of what traits they possess, so value judgements cannot be given.

2. Lack of predictability: the individual attaches themselves to a trait that doesn’t change predictably.

3. Lack of implication: a lack of awareness of what a trait can be a means for, so an individual who doesn’t care for a trait in and of itself might still be insecure about it. An introvert may prefer to spend evenings alone, but might be insecure about whether that makes them miss out on business opportunities or relationships.

4. Misaligned values: the individual is not sure whether their values are actually valuable.

Starting with the first cause, it is impossible to be completely self-aware because humans aren’t omniscient. Which may sound obvious, but it also means that you will always be insecure about something. Beyond this, consciousness is also inherently recursive, a function that applies itself to itself, kind of like how Russian nesting dolls contain another doll. As such, there is always an unobserved layer of consciousness that cannot be processed as information.

Being insecure about your own values might seem silly. Sometimes it isn’t; values interact with each other, so the presence of a value can be objectively “bad” or “good” according to the relationships between the values that said value coexists with. Somebody who wants to bedrot all day might question whether they really want to do anything with their lives. And maybe they should, as they will have to choose between these values at some point.

There is a social taboo against having negative perceptions of yourself (that’s unconfident!) and having positive perceptions of yourself (that’s grandiosity!). There are nuances and degrees to this taboo, but I think they are diluted in the cultural telephone game, so the end result is many people being reluctant to evaluate themselves properly. Some people do this by engaging in outright self-delusion, and some try to do it by reframing their weaknesses to be strengths, or downplaying their strengths. I think this is a massive source of a lot of insecurity: if you are not willing to think of yourself in a negative or positive way, then you cannot think of yourself at all.

Insecurity being a symptom rather than an illness implies a radically different treatment: instead of burying insecurities under 500 layers of neural networks, one should face them. This involves figuring out what the cause of insecurity is (perception, instability, means, or values), and finding a solution to the cause or accepting that one does not exist.

Total self-acceptance sounds a lot like an enlightenment to people. I have no idea if “enlightenment” exists or if it resembles anything close to the platonic idea people have of it. But the idea that there is a secret truth out there that can raise people above the chained, unhappy, and ignorant masses into a new state of being is extremely compelling to… the masses. Some people realise that and build things: cults, religions, ideologies, or whatever to satisfy that gnostic yearning. Sometimes people think that the answer lies in money, sex, sports, status, science, or altruism. Most, if not all of these things don’t satisfy that inner gnosticism – either because they are false or impermanent.

I am a fan of the Buddhist doctrine of anattā (noself), the idea that the “self” is not permanent, causal, or coherent, and that identity is false perception. In the context of insecurity, you being insecure about how smart you are could be reframed to be this process: our observational faculties receive feedback that casts doubt on our intellectual faculties are as strong as they think they are, which gives rise to thoughts (“am I not as smart as I think I am?”) and negative feelings that accompany this realisation. During this process, the body can irrationally identify with facets of this process – probably the thoughts or the intellectual faculties that are in question – and experience an additional layer of suffering.

Noself can save somebody from the layer of suffering that occurs afterwards, but it cannot stop them from questioning themselves, or even from the negative emotions that spring from the questioning. During the process of insecurity, the negative emotions are communicating “you need to reevaluate what you are or what you value”, not “haha you suck dude”. There is no evolutionary spandrell at play here. This Buddhist doctrine also deconstructs the idea that there is even a “self” to accept in the first place.

Initially, I was very averse to Buddhism because I associated it with wanting nothing and being some ascetic monk on an island, which I didn’t like. I have been in denial about this until just recently, but I am a very ambitious person and I have almost always rejected anything that I saw as obstructing my goals.

From my admittedly limited understanding of Buddhism, I don’t think Buddhism actually teaches you to stop wanting things, but to stop irrationally craving them. It wants to save you from the unnecessary suffering that stems from a poor cognitive model of the universe: where you are a self that attaches itself to things that don’t actually give you any permanent value. Buddhists in fact have two separate words for want: chanda, which refers to a zeal or desire to act that comes from a clear conscience, and taṇhā, a deluded state of craving where one believes they will escape dissatisfaction by gaining a thing that will only give temporary satisfaction; a state that is actually responsible for dissatisfaction in the first place.

I now accept that anything I accomplish or obtain will never satisfy me permanently, that “I” don’t actually exist in the way my brain tricks me into thinking I do. But I continue to engage with life anyway, like any other person you see on the street. If that’s not Buddhism, then I reject Buddhism, and will call what I believe Buddhism 2.

The closest one can get to totally self-accepting is accepting insecurity and appropriately dealing with it, very different and far from total self-acceptance, but better than nothing.

The biggest trend I see in zoomers anecdotally is that they are more concerned with status than previous generations, even controlling for age. I have no empirical evidence for this being the case, but I do see it anecdotally, especially in the tech world. Most of the gen x or even millennial tech people like Musk or Zuckerberg were just nerds who did stuff and made money, while the younger founders of today like the Cluely guy are usually motivated by attention or status.

In the early phases of the mass post-2012 internet, content creators asking for money was seen as gauche and grifty. Now, that’s totally normal. I think a similar thing is happening with status, where it used to be gauche or weird to talk about status openly, but now people don’t seem to mind as much — “codes as low status”, “countersignal”, “elite”, and “high-agency” weren’t in tech people’s vocabularies 20 years ago.

I don’t think a lot of the data people cite to argue for this being true is valid — some have cited a gallup poll that finds that Americans have begun to value money more, though that could simply reflect a more pragmatic or utilitarian mindset. Some articles talk about how zoomers are starting to see jobs like “influencer” as increasingly attractive, but that could also reflect changes in what is perceived as high status.

The clout focus in zoomers is not some weird neurosis or fad, instead it reflects rational behaviour and responses to incentives. The long term trend behind this is that traditional status markers like virtue, money, and education are falling out of fashion — society is becoming more nihilistic, money is less valuable when people have so much of it, and educational credentials are suffering from inflation. Increases in the size of the global population and the cheapening of international communication, particularly television has also made popularity more attractive.

The arrival of the internet accelerated this trend that was already going on and intensified it1: providing an environment with a low barrier to entry that everybody can participate in regardless of their location/race/class. It fosters a competitive environment where the winners take over and the middle is hollowed out.

The internet makes status fungible, easy to verify, and internationally visible. If you are high status in X community, then that also translates to status in Y community, just to a lesser degree. People are impressed by credentials or titles from institutions that they do not belong to or have never even heard of. Partly because people understand that subcultures assign value to similar kinds of people, but also because we are all just apes that see imaginary numbers over people’s heads.

The internet also makes it so clout isn’t an end, but a means for connections, sponsors, relationships, friendships, and information. To some extent this has always been true, but the internet as an envornment has magnified the effect. People who aren’t temperamentally predisposed towards chasing clout might try to do it anyway because they care about the things status can give them.

My interpretation of zoomer behaviour being driven by incentives is not a tacit endorsement; this is one of the worst developments to come from the internet. Chasing status for the sake of itself is slavish. Even if the people who want status chase it for their own ends, they are still placing the group’s value function over their own. The path of the noble man is to do the thing in itself, for the thing in itself.

The debate on chasing passion vs chasing clout/money/realism is complicated, but this is my view on it: people who are really good at things do them because they like them. Or more accurately, because they receive rewards from doing them, which might come in the form of social status, but frequently does not. I’ve heard it’s common for professional athletes to not be passionate about the sport they play, but I doubt that applies to, say, scientists. I attribute this to extra motivation: the passionate noble is motivated by the thing in itself + money + status, while the striver is only motivated by money and status.

I don’t really believe in authenticity, so I don’t criticise this trend on the grounds that it surpresses our “true selves”, but I do believe in relativity. I don’t think everyone should have the same values or goals, and that they have to create2 them.

Often, when one starts doing a craft, they aren’t good enough to make it on the grounds of their own ability because they are, well, new to it. Chasing passion makes going through the initial phase of getting good at something much easier, since rewards will come from doing the thing in itself. The slave feels no such satisfaction.

Attention span

The main focus of this post is about the status-seeking trend in zoomers, though I figured that I would speak on the other trends that differentiate zoomers from the previous cohorts.

Shortening in attention span in the youth is something I and many others have noticed that can also be empirically proved. The best quantitative evidence of this is that zoomers simply read less than their elders now:

One could argue that perhaps this trend is specific to reading, but if one looks at internet platforms and their users, the same pattern emerges: Gen Z dominates shortform platforms like snapchat, tiktok, and instagram, while media like TV, facebook, and youtube have relatively older userbases.

The attention and status trends are also connected. Status is something that can be communicated easily and quickly, while other characteristics like value, truth, or motivation are harder to parse and require more time to judge.

A more uncommon rebuttal to this narrative is that there is a Flynn Effect in terms of concentration and sustained attention, with recent cohorts seem to be outscoring higher cohorts. This is only a good criticism if one thinks the problem is that zoomers don’t have the intellectual ability to concentrate, the issue could simply be the informational environment and the habits it creates.

I think this is bad. Genuine understanding of anything, be it a trade, skill, or field, must be acquired through longer content and sustained attention. Tiktok might not actually make people dumber, but it will not teach people anything more simple than an internet meme.

Risk assessment

There is no good psychometric evidence for risk assessment having changed in zoomers, but there is a lot of good behavioural evidence. Drinking, smoking, getting pregnant as a teenager, and approaching the opposite sex are all dropping among the recent generation.

What I don’t understand is how exactly risk assessment changed: have zoomers gotten more calculated in terms of their risk assessment or more conservative? The difference here being that conservatives do not want to take risks regardless of how good they are, while calculated people simply take better ones.

One could argue that not wanting to approach the opposite sex is a clear marker of conservatism, “the worse thing they can say is no”. Which is well, not actually true. While it is correct that the social and legal risks of approaching the opposite sex (particularly women) are overblown, approaching the opposite sex carries an energetic and emotional cost that people don’t want to admit exists.

It’s also further confounded by the problem of arrested development: teenagers are working and driving less as well, activities which aren’t really that risky, but require a certain level of advancement and desire which just isn’t there. Given the decline in traditional risk-taking behaviour extends to drug use as well, I’m inclined to think that risk assessment is genuinely changing beyond just the effects of slower maturation.

Acceptance of foreign cultures

Millennials weren’t a particularly racist or xenophobic generation, but the white ones did keep outside culture like anime at a distance. People into anime or games kept those interests to themselves or had to stand up to bullies. Some time around 2010-2015, everything changed and watching anime and listening to KPOP became as normal as watching TV. This is also reflected in zoomers adopting black and nazi/incel slang.

This mainstreaming of foreign cultures is good in my opinion. It’s at worse a symptom of the greater problem which is that culture and art have begun to stagnate everywhere, be it TV series, games, anime, or film3. This can be inferred from the rise in sequels and remakes in the past 20 years and from, well, observation with the naked eye. Anybody who wants to experience art or media that is actually good will be forced to branch out.

The myths

Some have speculated that zoomers have become depressed, autistic, dumb, or lazy. The source of blame for these illusory changes in highly generic traits is always “da fonez”, no matter how much genetically-informed studies suggest social media does not cause mental health issues. Others have written good debunkings of these myths, so I may as well link to them explanations:

• Autism: diagnosis of autism has increased over time, but symptoms for it have not.

• Depression: depression rates have increased in the United States, but this is not true for the rest of the world. There is also no guarantee that this isn’t one of those cases of traits changing over time due to diagnostic drift or some other artefact.

• Test scores: changes in test scores over time rarely pass measurement invariance.

• Laziness: the original FT chart was misleading, and the change in conscientiousness it portrayed was a simple d = .40 effect (analogous to 6 IQ points). It’s also not clear if the effect would survive controls for measurement invariance; zoomers are more likely to stay inside or engage in brainrot hobbies, but that could reflect cultural/environmental changes rather than psychometric ones.

The Verdict

My thesis, stated plainly, is that increases in the global population, international communication, and the devaluation of traditional measures of status like wealth, education, and virtue have resulted in raw popularity rising in importance over the last 100 years. This was accelerated but not caused by the arrival of the internet, which gave people fast and easily verifiable measurements of clout and increased the fungibility of popularity.

Zoomers are looking like a rough generation. I might be more optimistic about us than some, but the clout-chasing fad and short attention spans are going to do in a lot of otherwise talented people. I once thought that zoomer artists would clear out the Millennials in terms of quality, as they weren’t infected with the same authenticity/irony culture, but now I’m not so sure. Making good art requires having a long attention span and an appreciation for the thing-in-itself, things I do not see as often in my generation.

The computer models predict that the fraction of >130 IQ people peaked somewhere between 1990 and 2020, given that most big creative/intellectual work is accomplished by people between the ages of 20-40, an IQ-only model would predict that the most artistically eminent generation of people were the Xers and early Millennials. I do think intelligence and creative ability are correlated, though not to the point that one can deterministically predict artistic achievement across time with this chart.

The Flynn effect has been investigated extensively for IQ, but few attempts have been made to study it in relation to working memory (WM). Based on the findings from a cross-temporal meta-analysis using 1754 independent samples (n = 139,677), the Flynn effect was observed across a 43-year period, with changes here expressed in terms of correlations (coefficients) between year of publication and mean memory test scores. Specifically, the Flynn effect was found for forward digit span (r = 0.12, p < 0.01) and forward Corsi block span (r = 0.10, p < 0.01). Moreover, an anti-Flynn effect was found for backward digit span (r = − 0.06, p < 0.01) and for backward Corsi block span (r = − 0.17, p < 0.01). Overall, the results support co-occurrence theories that predict simultaneous secular gains in specialized abilities and declines in g. The causes of the differential trajectories are further discussed.

This is relevant because the ability to memorise digits backwards is a better indicator of intelligence than the ability to memorise them forwards, so it has been cited as evidence that the Flynn Effect is an artefact of performance changes on specific tests instead of a general improvement in cognition.

I downloaded their data out of curiosity and decided to check for errors. I found one in their 2nd regression table, where I was unable to replicate the statistically significant1 decline in backwards digit span over time.

I was otherwise able to replicate the other coefficients in their model, like the intercept being 7.74 or the effect of country being 0.88, so I’m inclined to think the failure to replicate is not a function of small differences in underlying data or methodology. I was also similarly able to replicate the paramaters in their zero-order regression (16.11 and -0.01) but not the p-values and t-statistics2.

The table is otherwise strange. One intercept is listed as statistically significant (24.89) and another is not (10.52) despite both having large t-statistics. They have one t-statistic listed with one star (15.29) but explicitly labelled as < .01 in the table, which is odd as they claim in Table 2B that one star is only p < .05.

Essentially, my claim is that they made a mistake somewhere along the way and found a null to be a positive finding. If they were fraudulent researchers, they probably would not bother sharing their data.

Doing things my way

Different age groups have different standard deviations in terms of digit span, so this must be adjusted for when calculating the change in performance over time. As the averages may also vary by country, I categorised every single one of the effect sizes by country (all 592!) by searching for the publication using the author/year that they gave. In 22 instances I could not find the original source. I also added a few other uncited publications along the way, bringing up the total number of effect sizes to 599. I also labelled the perceived SES of the sample (higher for professional workers or college students, average for high school students or volunteers, low for unskilled labourers). I weighed by the square root of the sample size instead of the raw number, as that is standard practice.

Fitting a spline to the data and controlling for age/SES/country3 suggested that backward digit span has increased by about 5.5 IQ points (41 x 0.13518) over the 1975 - 2016 time period. The effect was statistically significant4, but not to an impressive degree (p = .0063).

The spread of scores is high because the data is not of particularly high quality. The age-norming and country categorising were attempts to remedy this, but unfortunately they only provided marginal improvements.

It would also be prudent to test whether the same holds in the forward digit span test. It did, with a larger effect (9.9 points) and a much more clear effect (p = .00000023)5.

In all

Both of the increases over time are statistically significant and of similar magnitudes, which leads me to believe that this particular criticism of the Flynn Effect is not valid. I am still skeptical that observed Flynn Effect gains represent true gains in intelligence, though I don’t think this publication and data should be cited as being evidence against the intelligence-gain hypothesis, and my priors have shifted slightly towards FE gains reflecting some increases in real intelligence.

I have the code6 I used, but it’s not very useful because I use a lot of proprietary functions to run it. It’s also illegible because I wrote it for my own purposes. I do have the dataset I used to make my own calculations on the alternative website, which is more useful.

2

Table:

3

Relevant charts:

Mean(Score) ~ Age, controlled for year/country/SES. Peak is 19.5.

SD(Score) ~ Age, controlled for year/country/SES

Same charts but backwards:

Peak is 22.5

4

Table:

5

Table:

qwe <- lm(data=savy, Mean ~ Year, weights=Size)
summary(qwe)

qwe <- lm(data=savy, Mean ~ Year + Age + Male + Type_C + Platform, weights=Size)
summary(qwe)

################
testtempyarfwefe <- allspan


subset <- testtempyarfwefe %>% filter(type==’backward’)
subset$Country[is.na(subset$Country)] <- ‘Unknown’
subset$SES[is.na(subset$SES)] <- 1
subset$SE <- subset$SD/sqrt(subset$Size)
subset$Country[(subset$Country==1 | subset$Country==0 | subset$Country==’‘)] <- ‘Unknown’
unique(subset$Country)

p <- splinechart(datos=subset, var1=’Age’, var2=’Mean’, knots=5, breakn=10, metastyle=F, label=’Age’, labely=’Mean Backward Digit Span’,
                 covariatefunc=’ + as.factor(SES) + Year + Country’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’, Year=2000), outputyes=F)
p

p <- splinechart(datos=subset, var1=’Age’, var2=’Mean’, knots=5, breakn=10, metastyle=F, label=’Age’, labely=’Mean Backward Digit Span’,
                 covariatefunc=’ + as.factor(SES) + Country’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’), outputyes=F)
p

#Yes, this does pass significance testing
p <- splinechart(datos=subset, var1=’Age’, var2=’SD’, knots=5, breakn=10, metastyle=F, label=’Age’, labely=’SD Backward Digit Span’,
                 covariatefunc=’ + as.factor(SES) + Country + Year’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’, Year=2000), outputyes=F)
p

lr <- lm(data=subset, Mean ~ rcs(Age, 5) + as.factor(SES), weights=sqrt(Size))
summary(lr)
metaobj2 <- metafor::rma(yi=Mean, sei=SE, data=subset, mods = ~ rcs(Age, 5) + as.factor(SES))
summary(metaobj2)
lr$coefficients <- metaobj2$b

metaobj32 <- metafor::rma(yi=SD, sei=SE, data=subset, mods = ~ rcs(Age, 5) + as.factor(SES))
summary(metaobj2)
lr3 <- lm(data=subset, SD ~ rcs(Age, 5) + as.factor(SES), weights=sqrt(Size))
summary(lr)
lr3$coefficients <- metaobj32$b

uzi <- seq(from=4, to=92.5, by=.1)
uzi2 <- data.frame(Age=uzi, SES=1)
uzi2$SD_age = predict(lr3, uzi2)

subset$residualscore <- lr$residuals
subset$roundage <- format(round(subset$Age, 1), nsmall = 1)
uzi2$Age_formatted <- format(uzi2$Age, nsmall = 1)

subset2 <- left_join(
  subset,
  uzi2 %>% select(Age_formatted, SD_age),
  by = c(’roundage’ = ‘Age_formatted’)
)

subset2$IQ <- subset2$residualscore/subset2$SD_age*15+100

p <- splinechart(datos=subset2, var1=’Year’, miny=70, maxy=130, var2=’IQ’, knots=5, breakn=5, breakny=5, metastyle=F, label=’Year’, labely=’IQ’, titul = ‘Backward digit span scores over time, controlling for age, sample SES, and country of origin’,
                 covariatefunc=’+ Country + as.factor(SES) + Year’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’, Year=2000), outputyes = T)
p

lr <- lm(data=subset2, IQ ~ Country + Year + SES)
summary(lr)

41*0.13585    


#################################

burndata <- data.frame(
  SES = 1,
  Country = ‘UK’,
  Year = 2000
)

uzi2 <- seq(from=18, to=30, by=0.1)

covariatefunc=’‘

modelt = paste0(’ ‘)
lr <- lm(data=subset, Mean ~ rcs(Age, 5) + as.factor(SES) + Year + Country, weights=sqrt(Size))
summary(lr)


uzi2 <- seq(from=18, to=30, by=.1)
uzi4 <- data.frame(Age=uzi2, burndata)

# Predict
uzi4$fit <- predict(lr, newdata=uzi4, interval=”confidence”)

uzi4


##################
###############
testtempyarfwefe <- allspan

subset <- testtempyarfwefe %>% filter(type==’forward’)
subset$Country[is.na(subset$Country)] <- ‘Unknown’
subset$SES[is.na(subset$SES)] <- 1
subset$SE <- subset$SD/sqrt(subset$Size)
subset$Country[(subset$Country==1 | subset$Country==0 | subset$Country==’‘)] <- ‘Unknown’
unique(subset$Country)

p <- splinechart(datos=subset, var1=’Age’, var2=’Mean’, knots=5, breakn=10, metastyle=F, label=’Age’, labely=’Mean Forward Digit Span’,
                 covariatefunc=’ + as.factor(SES) + Year + Country’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’, Year=2000), outputyes=F)
p

p <- splinechart(datos=subset, var1=’Age’, var2=’Mean’, knots=5, breakn=10, metastyle=F, label=’Age’, labely=’Mean Forward Digit Span’,
                 covariatefunc=’ + as.factor(SES) + Country’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’), outputyes=F)
p

#Yes, this does pass significance testing
p <- splinechart(datos=subset, var1=’Age’, var2=’SD’, knots=5, breakn=10, metastyle=F, label=’Age’, labely=’SD Forward Digit Span’,
                 covariatefunc=’ + as.factor(SES) + Country + Year’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’, Year=2000), outputyes=F)
p

lr <- lm(data=subset, Mean ~ rcs(Age, 5) + as.factor(SES), weights=sqrt(Size))
summary(lr)

metaobj2 <- metafor::rma(yi=Mean, sei=SE, data=subset, mods = ~ rcs(Age, 5) + as.factor(SES))
summary(metaobj2)
lr$coefficients <- metaobj2$b

metaobj32 <- metafor::rma(yi=SD, sei=SE, data=subset, mods = ~ rcs(Age, 5) + as.factor(SES))
summary(metaobj2)
lr3 <- lm(data=subset, SD ~ rcs(Age, 5) + as.factor(SES), weights=sqrt(Size))
summary(lr)
lr3$coefficients <- metaobj32$b

uzi <- seq(from=4, to=92.5, by=.1)
uzi2 <- data.frame(Age=uzi, SES=1)
uzi2$SD_age = predict(lr3, uzi2)

subset$residualscore <- lr$residuals
subset$roundage <- format(round(subset$Age, 1), nsmall = 1)
uzi2$Age_formatted <- format(uzi2$Age, nsmall = 1)

subset2 <- left_join(
  subset,
  uzi2 %>% select(Age_formatted, SD_age),
  by = c(’roundage’ = ‘Age_formatted’)
)

subset2$IQ <- subset2$residualscore/subset2$SD_age*15+100

p <- splinechart(datos=subset2, var1=’Year’, var2=’IQ’, maxy=130, miny=70, knots=5, breakn=5, breakny=5, metastyle=F, label=’Year’, labely=’IQ’, titul = ‘Forward digit span scores over time, controlling for age, sample SES, and country of origin’,
                 covariatefunc=’+ Country + as.factor(SES) + Year’, ws=’Size’, burndata=data.frame(SES=1, Country=’UK’, Year=2000), outputyes = T)
p

lr <- lm(data=subset2, IQ ~ Country + Year + SES)
summary(lr)

41*0.2422    


#################################


burndata <- data.frame(
  SES = 1,
  Country = ‘UK’,
  Year = 2000
)

uzi2 <- seq(from=18, to=30, by=0.1)

lr <- lm(data=subset, Mean ~ rcs(Age, 5) + as.factor(SES) + Year + Country, weights=sqrt(Size))
summary(lr)


uzi2 <- seq(from=18, to=30, by=.1)
uzi4 <- data.frame(Age=uzi2, burndata)

# Predict
uzi4$fit <- predict(lr, newdata=uzi4, interval=”confidence”)

uzi4

2023 — Against full scale IQ fetishism : I consider myself an “IQ lukewarmist”. I think IQ tests are generally decent measurements of intelligence. Said measurements tend to correspond well with financial success (explains ~25% of variance in permanent income and productivity) but not much else; correlations with other variables of interest like divorce risk, happiness, ideological beliefs, and taste tend to be null or disappointingly weak.

Despite the high correlation between IQ and productivity, I don’t think selecting employees for IQ works well because the tests employers use don’t tend to be accurate (such as the raven’s matrices test) and the existing job selection process already filters out people based on IQ, demonstrated by the lower variance in intelligence within a job position in comparison to the applicants. Those who doubt this are free to select people based on tests all they want — literally, it’s legal. Griggs vs Duke Power only discouraged using them.

Even if it were the case that IQ tests did work as selection mechanisms, I doubt people would want to use them anyway. They’re nerdy, boring, and make judgements too explicit and legible, which is something people don’t like. Having a bunch of numbers like IQ scores decide filters makes it more difficult to make looser decisions based on charisma and style, which are valued but might not correlate that highly with productivity. As Robin Hanson notes:

Years ago a NYC based software firm ran some prediction markets, hoping in part to find & promote “diamonds in the rough” employees who predict especially well. They did find such, but then said “Oh, not them”; such folks didn’t have the polish & style they wanted.

Anecdotally, I’ve noticed that the most successful and competent artists and creatives don’t seem to be as gifted in terms of IQ as the top tech titans (e.g. Thiel, Musk, Zuckerberg, Gates) or the greatest scientists (e.g. Einstein, von Neumann). I can even see it in their social backgrounds; scitech titans often attended top universities or came from wealthy families, while creative titans usually do not attend top universities and are only more likely to come from a wealthy family.

Perhaps this is due to the fact that IQ is capable of measuring the cognitive talents associated with science and tech well, but not the talents that are associated with writing narratives, making music videos, or painting pictures. Or maybe these kinds of creative pursuits depend on a range of non-cognitive traits like volition, taste, or openness that are not captured by intelligence. Either way I don’t think IQ is a great signal of artistic ability the way it is for scitech ability.

2023 — Signalling theory of hobbies : I endorse the theory, but I advise against adopting hobbies or activities that are high status because they are high status. I personally choose hobbies based on how pleasurable I find them (e.g. video games) or how talented I am at them (e.g. drawing). Productive hobbies are better than unproductive hobbies, but I feel like deliberately choosing productive hobbies takes the fun out of doing them.

2024 — Taking mutational load theory seriously : a comprehensive refutation of the theory that mutational accumulation due to lowering infant mortality is making us more genetically unfit.

In summary: the biggest theoretical issue I have with mutational load theory is that the more generalized mutations are, the more likely it is that mutations that cause early mortality will be selected out through miscarriages, survivalpregnancy failures, or reproduction. The less generalized mutations are, the less problematic it is that mutations associated with early mortality accumulate in the population.

2024 — Narcissism and selfishness are the human default : I still believe humans are selfish in a fundamental way. Not because of any scientific evidence, but because it’s not actually possible. I also don’t think this is a conclusion that people can arrive at through scientific thinking, it is something that must be personally discovered.

I no longer define narcissism as self-enhancement, but as an identity disorder that involves difficulties with identity formation and self-conception. I’m still outlining my thoughts on self-conception and identity, so I don’t have any concrete thoughts on the matter, but I did note in the article that distorted self-perception is the rule and not the exception.

2024 — The Role of Cultural Drift in Obesity : I will double down on the fact that the social class does not prevent obesity, but I’m not sure if it is cultural either. I think it might be a product of cross-trait assortative mating, where higher SES individuals exhibit a stronger preference for thinner mates, and so over time the correlation between SES and obesity increases.

2025 — Economic inequality increased ever since the dawn of civilisation : my argument is that the Gini coefficient is bad because it measures inequality in terms of proportion and not actual resources. I defend the post insomuch that I think economist’s insistence on using the Gini coefficient to measure inequality is extremely irrational. Otherwise I think the case that economic inequality increased since the 50s (as I claimed in the post) is admittedly thin. Numerically it did, but mass production has made it so resources like computers, food, good clothing, spices, furniture, transportation, housing, and healthcare are now available to most people in developed countries regardless of income. Inequality discourse should ideally include measures of the actual standard of living, but I lack the historical knowledge and life experience to evaluate the problem at that level.

2025 — the answer to the missing heritability problem : although I am right to dismiss the missing heritability problem and “molecular genetics studies” as red herrings, I still think that heritability research is valuable. Public understanding of genetics is surprisingly decent from what I’ve gathered, but behavioural genetics increases the dimensionality and rigor of this knowledge.

Academia

2022 — Top 5 problems with sociology : the problems were overreliance on observational data, genetic confounding, lack of real world testability, unintelligent students can still get good grades, and left wing bias. Not a bad list, but an awkwardly written article (as is the case for most of my early posts).

2023 — Why Ivies should exist — I think I should have made a macro-post on selection and Ivy league universities rather than a few loosely connected ones. My view is that Ivies are not necessary, but work fine as standins for public SAT/ACT scores, and that criticism of their methods of selection are misguided — many claim they’re not focusing enough on non-academic ratings, when in reality those “personality ratings” and “extracurriciulars” hardly predict anything in the real world and they would be better if they just took the top 20k students + some athletes.

2023 — University quality vs Student quality — I statistically prove that statistical measures of “university quality” all correlate highly (r > .9) with the academic quality of the students they admit. Some univeristies are obviously better than others in terms of aesthetics, features, and location, but I don’t think that those things are subject-independent or easy to measure. I’m also not sure how well they would scale with the academic quality of the students.

2024 — Academia’s prestige will nosedive in 50 years — I reaffirm the prediction, but restate it in the form “it will have nosediven in 50 years”.

Philosophy

2021 — Moral Unism: a Case for Objective Morality : here I attempt to construct a theory of objective morality based on the fact that preferences for certain states of existence are subjective but the collective preference for which state of existence maximises people’s preferences is objective and constitutes a valid goal to optimise for.

I see three large problems with this theory. The first is that there is no cosmic justification for why the collective preference should be optimised for at all — one could argue that it is irrational for somebody to value their preferences but not the preferences of others, but this is not the case if they value selfishness.

The second is that the theory doesn’t adequately or explicitly deal with cases where people’s preferences, even if revealed, are bad. Some people may pursue status in the first half of their lives but later discover they don’t actually care about it, while others may do the opposite.

The theory also does not wrestle with the fact that people have different higher values (egalitarianism, libertarianism) beyond different preferences for individual states. As such, they will have different ways of aggregating the value equation. One could argue that these “higher values” devalue themsevles and there is no reason for them to be taken into consideration, but if one acknowledges that is the case then the attempt to create a grand theory of morality is not exactly “the play”.

2021 — In Defense of the Ad Hominem : I argue that the Ad Hominem, commonly considered a fallacy, is indeed a valid argument because a person’s arguments are downstream from their selves. I do detail how genes and motivated reasoning play a role in the construction of beliefs, but I feel like the one line explanation of the idea is sufficient.

2022 — Absolute Monarchy is not a Panacea : around this time I got interested in the neoreactionary movement, particularly Curtis Yarvin’s work. I (sloppily) explained his philosophy and the idea behind his solution, neocameralism: having the government be a corporation governed by a CEO accountable to a board of directors.

The first problem I raised with his solution is that the difference between a corporation and a government is meaningful — a government can control its own currency and run a deficit indefinitely, while a corporation cannot (this point can be easily refuted by noting that the East India Company issued coins).

The other issue is the board of directors. If the board is appointed by the king, then the king is in control (so neocameralism is a dictatorship). If something else (e.g. lottery, public) appoints the board, then the board is in control (oligarchy).

Yarvin’s rebuttal wrt this is that, in monarchies, the public is politically apathetic because they believe they have no influence on politics. I would argue that this should be true about oligarchies (commonly known as democracies) if having no influence leads to no interest, but that’s somewhat beside the point. I’m also not sure if a politically apathetic public can exist in the current media and cultural environment even in a different political system.

I still largely agree with this piece, with the added point that leader-led political systems are unstable and are predicated on the competence of their leader; oligarchy might be stale and opressive, but at least it works consistently.

2022 — the Accelerationist Manifesto: The Eternal Whitepill : In the post, I concede to the opposition that there are many ways technological development has made the world a much more unfree place. Agricultural improvements have led to increases in population sizes, which have encouraged the creation of police (restricted freedom). Industrialisation has led to specialised jobs, which has led to the education system (restricted freedom). Technology facilitates taxation which encourages governments to build massive spending programs that accomplish very little of value (restricted freedom). Markets and a combination of other factors have encouraged the formation of corporations and modern jobs, which involve a lot of forced socialisation that some people aren’t going to like.

One might think that, perhaps, we could rise up and destroy all of this technology because it is bad for us. But nothing ever happens, so that’s not an option.

Rather than mope at this fact, my argument is that accelerating technology further is actually likely to make us more, not less free. If I look at the big technologies of the current day that have yet to run their course, they are:

• Internet

• Embryo selection

• AI

The interent encourages remote work which reduces the amount of forced socialisation we must endure. It also allows people to distribute knowledge more freely, so much that groups and advertisers have to shackle big tech into censoring their users. One could make the case that the internet has led to the creation of a more digitally exposed culture, but I think this is somewhat overplayed and not that much of a concern in everyday life.

Embryo selection encourages higher levels of intelligence and health which should lead to higher human capital, which is a massive boon to society: less criminals, less educational strain, higher productivity, and more desirable areas for housing.

I didn’t specify what the effects of AI would be in the article, as I only started getting into AI in mid 2022. It’s hard to predict what will happen because we don’t even agree on what version of AI we are getting: singularity, strong AI, or just more marginal improvements in currently existing technology.

Personally, I think the idea of iminent AGI is capeshit, because modern AI do not possess a lot of the features you would want in an autonomous, generally intelligent machine: innate values and processing that converts sensory/visual/audio data into information (aka, g). I don’t see how upgrading these machinese gives them those abilities. As long as these features are not striven for, current models will not yield AGI no matter how much training is done.

I think it’s likely that AI will, in the long term, reduce the barrier of entry of most white collar jobs. I’ve seen some make the case that AI will break down the education system the way the printing press broke down monasteries. I really, really, really, really, really, really, really want to believe this but the pessimist in my thinks that professors and educators will find ways to adapt, like with in person testing or oral exams.

In the original article I argued that population decline would also contribute to freedom by reducing population density, pollution, and littering. I still largely agree with this view, but though I’m not that interested in convincing anybody else of it.

2022 — Problems with libertarianism — in summary, I argue that libertarianism is not tenable because it is either framed through deontology (which makes no sense as a theory of morality, because rules must be founded on something or risk being arbitrary) or consequentalism (so liberty isn’t sacred anymore). I also brought up the criticisms raised against unregulated markets (externalities, limited information) which can result in the markets being a net negative for the group. I am not very interested in economics (and never pretended to be, even 3 years ago I admitted as much), but these arguments seem credible enough to me.

With regard to libertarians who are anarchists, I argue that anarchism is untenable because of the problem of national defense — an army that collects income from citizens is subject to a free rider problem where people who don’t pay the military benefit from their services, so there is no incentive for the anarchists to pay their own army. If the army decides to loot their citizens, they are arguably a government at that point. If anarchism is global, then all that will happen is that the political order will devolve into polycentric law, where everybody buys into law systems that benefit themselves, which is obviously unsustainable and eventually leads to one law system winning out.

The strongest case I could make for libertarianism is that we have far too many taxes, far too many regulations, far too many laws; liberty is underrated but not a self-asserting high value. Libertarianism is an emotional reaction to this massive state that should stay as a political movement, but not as an ideology.

2022 — Debate is mostly useless : The “debate mindset” assumes people believe things because they are true. They don’t. They believe in things because they feel good. Changing your opinion on a descriptive belief can change a prescriptive one, but usually the former exists to protect the latter. Some people do care about the truth: those people don’t watch debates, they research at their own speed or consult their peers. They also possess volition that others do not and cannot have.

A lot of times, when people disagree, it’s due to underlying beliefs or values which cannot really be debated on the fly. Good luck kidnapping a progressive and trying to sort out whether “authority” is better than “equality” (meaningless abstract words that don’t mean anything anymore). The specific debates are proxies for the general debate.

If you have to “debate” somebody, something is going wrong. Should I debate my mom on whether we should have pizza or cheese casserole for lunch? Should I debate my father on whether his driving is too slow?

2024 — Statistics vs Words vs Power? — not a very good article, but a decent attempt to counterbalance two irrational forces: the force which discards all verbal argument as “wordcelery” and the force that discards all data as “lying statistics”.

Politics and current events

2022 — is American Education Uniquely Bad? : I make the case that it is not — empirically, American students are in the middle of the developed world when it comes to scholastic performance, and on top of it if one controls for race. I also highlight statistics suggesting that policies that increase school choice and funding for schools are also unlikely to yield better grades.

Not exactly an uncommon opinion on this part of the internet anymore, but it was a solid attempt at answering the question.

2022 — COVID19 Theory Breakdown : I outline different points of contention regarding the COVID pandemic (e.g. lab leak vs zoonic, efficacy of the vaccine) and then map them to whether they are more supportive of the pandemic being planned or unintentional. I argue that a lot of the observations as of now are more consistent with the hypothesis that the pandemic was planned, but I leaned against the plandemic hypothesis anyway because I didn’t see a good candidate for a culprit.

I still dislike the plandemic hypothesis, but my reason for this has more to do with priors for an intentional pandemic being very, very low.

2024 — Does the Right Have a Stupidity Problem : No. There is like a 2-4 IQ difference between Republicans and Democrats in the modern day. The right’s loss of cultural power occurred far before it started getting dumber in the mid 00s.

2024 — the alt-right lost : I argue that the alt-right lost because it didn’t affect public opinion with regard to race or immigration, a perspective which I then debated with Walt Bismarck. Now I feel entirely different: the alt right temporarily lost because of the Charlottesville incident, but then inevitably grew afterwards into what we have now.

It was effective in offering an alternative to people who were skeptical of “the taboos” and wanted a more intense cultural experience, but it couldn’t deliver anything en masse besides memes that were judged by the collective consciousness to be inoffensive enough.

2025 — what happened to the dissident right? : somebody told me in a DM that this post could have been much improved from detailing things out or providing examples, which was definitely true, but I didn’t want to single out sane people who left and erased their tracks or deranged but talented people who insisted on staying.

Although I think the DR is in decline at the moment, I think there will always be a demand for something like it. I do think that the specific brand of alt-right culture that emerged between 2010 and 2020 that was polymathic (interested in philosophy/game/polsci/HBD/history…) and overtly edgy is on its way out due to decreases in literacy, more censorship, and lower levels of intellectual interests in the recent generations.

2025 — left wingers who are not awful — independent of political disagreements, left wing political pundits are almost always boring. They might doubt morality on philosophical grounds but their revealed beliefs betray their moralism. Most of them don’t seem to be very deep thinkers.

Left wing philosophy and punditry all converges towards the same policies and opinions due to a shared culture and value system. Even if individual pundits disagree on individual policies, they are all disagreeing on how to best optimise for those values. The same is not true of the right, where there is a wide variety of political camps with different value systems and outlooks (accelerationist Landians, street safetyist GDP-maxxing LKYites, catholic traditionalists, Fascist bodybuilders).

That said, I refuse to disavow Zizek. He’s charming. Funny. Interesting. I also find that left-right preference often does not track quality when it comes to domain-specialists.

Statistics

2022 — Is there a g-factor in political views? : More or less yes — it’s left wing vs right wing. It doesn’t load on every political question in existence but it loads on 96% of them.

In intelligence research, the “g factor” is a word used to label a hypothesised statistical variable that causes variance in all cognitive abilities (in other words, intelligene). People have also subject political surveys to factor analyses, and the vast majority of questions load onto the first factor: left vs right. It’s not immediately clear why this is: it could be social media echo chambers, it could be genes, or it could be due to how ideological beliefs are constructed. Personally, I lean towards the latter two.

2022 — Data damage in an AI study predicting professional LoL : I proved that a study predicting wins in League of Legends matches suffered from data damage, where the red side player winrates and blue side support winrates are no longer consistent with any of the other starting around row 1860. I tried contacting the authors and predictably got no response.

2022 — Reaction time and gaming skill : I find a low correlation (r = .2) between reaction speed and League of Legends rank based on survey data. I considered this evidence that reaction speed has a weak effect on actual performance, which is dictated more by the ability to anticipate events or react to different possible stimuli.

2023 — Database of IQ Estimations : using a (relatively) uniform methodology, I attempted to estimate the IQs of ~50 different public figures. I think I went a little overboard in terms of effort, but I endorse the implicit message I was trying to send: highly successful people are less intelligent than commonly thought and the >150 IQ figures that people tend to float around are made up.

2024 — Ageism is justified : I reafirrm the idea that people past the age of 30 or so are unlikely to dramatically shift in terms of their competence or social class, but I think I was too ready to dismiss the idea that luck matters.

The heritability of intelligence and big 5 personality traits are all about 75%, presumably the heritability of competence would be similar, but the heritability of income is only 45% (this means only about 60% of income in a given year can be explained by competence). The heritability of long-run income is higher (about 60%), which implies that 80% of long-run income is caused by differences in competence. At least according to my model…

(Note: competence and merit are synonyms, but not perfect ones).

2025 — The art of data analysis : a little navel-gazey and pretentious, but I disavow nothing I wrote here. Nothing can systematise the process of information processing.

Culture

2022 — How to estimate the quality of an anime in 5 minutes : a failed attempt to communicate the true intuition, which is that people can subconsciously predict with decent accuracy whether they are going to like something before they watch it.

2024 — Why do anime bloggers have such bad taste in anime : my argument is that watching things to evaluate them produces a systemtically different experience from watching things for pleasure, which leads to a distorted value system.

Posts I have no opinion on or tacitly endorse

Everything else.

Posts that were mistakes

2022 — Wordcels vs Shape Rotators

2022 — Midwit red flags

2022 — Analysis for TLAU

2023 — Why are Great Intellectuals So Rare : the triple event logic, that multiple traits are necessary to promote good and tasteful ideas, checks out in my head, but I think I ignored the far greater contributor: people with the talent to be good intellectuals also probably have skillsets that let them engage in other endeavours that are more fruitful.

2024 — What’s in a nerd : basically what I said is that stereotypes of intelligent people (unaesthetic, physically weak, socially stunted) have no basis in reality, but that the type of the “nerd” emerged anyway because it embodied a set of traits that distinguish people who perform well in school/work and people who perform better in normal sociological hierarchies.

I have no particular reason for disliking it, just wish I addressed the topic from a better angle and with more detail. There is also definitely a distinct “nerd” type that emerged in modernity that did not use to exist, but that the type itself is not reflective of correlations that exist in the real world (e.g. smart people aren’t more likely to be unathletic even if there is a distinct type of person who is smart and unathletic).

2024 — Does Saturated Fat Intake Cause Mortality? : I argued that the hypothesis that saturated fat causes mortality (particularly CVD) was empirically unsupported, which was actually true, but I’m starting to think that the actual theory itself is true, just to a very limited extent where saturated fat slightly elevates LDL which has an impact on CVD death risk, but the effect itself gets attenuated through the multiplication of effect sizes.

2024 — Midwits as impostors : I think I failed to explain the problem with the term midwit, which is that it unsuccessfully combines Gaussian (linear) and Jungian (typological) ways of categorising people. I also don’t think people with above average but not superlative levels of intelligence define themselves by having… Above average but not superlative levels of intelligence.

2025 — The Case for Utilitarianism : utilitarianism is just morality, but consequentialist and conflating value and utility. As I think value and utility are meaningfully different, I no longer endorse utilitarianism.

Ending thoughts

I’m mostly proud of what I have written. The biggest issue is that I invested too much energy into combatting ideas that were not worth fighting against, usually regarding people’s incorrect ideas on hereditarianism. In fact, I decided to compile a list of all ideas I don’t like that don’t deserve their own blogpost to save my energy for more constructive efforts. I also did the thing where you get interested in things you don’t actually care about that much but you see other people care about so you care about them too (in other words, I am mimetic like all other humans).

This was the case when it came to my interest in health. By nature I am healthy and tend to recover from illnesses, even bad ones, in just a few days. I’ve had my range of health issues (hyperflexibility causing all sorts of issues, varicocele) which I fixed through my own effort and knowledge, but otherwise I feel like a lot of my interest in diet and lifestyle came from seeing other people talking about it.

In terms of ideas, I think that most of my errors have stemmed from being too optimistic, despite being one of the most blackpilled people on the internet. I don’t think I am pessimistic, just asocial — somebody who isn’t interested in keeping up morale or thinking that other people and groups are headed in good directions. I also have a tendency to forget my own opinions due to having so many of them, which leads to my thoughts being less interconnected than they should be.

Other stuff

2024 — Politics of Hereditarianism : I reaffirm my thesis that talking about hereditarianism will not change anybody’s minds. Alex Young’s recent admixture study is also another case of researchers getting a lot of attention in niche internet circles that translates to absolutely zero media attention or real world impact.

The only way the discussion is going to reemerge in public discourse is if a high status and prominent person decides to argue in favour of the hereditarian hypothesis, which could go well (increase in visibility and dialectical advancement of hereditarianism at the cost of station) or badly (loss of station with no increase in visibility or dialectical advancement). I lean towards the latter.

2024 — How common is incest in the west? — I stand by the estimate that 30% of people have engaged in sexual activity with a relative; to those who argue about muh false self-reports, the high figure is partially downstream from the wide definition which includes playing doctor. The fraction who engaged in fondling or sex were a minority of that 30%.

2025 — Contra Lyman Stone on national IQs — I stand by everything I have written here, and it was fun to watch Lyman Stone write a reply that I never read, but my time is worth orders of magnitude more than his, so this post was ultimately a net negative for the world.

2025 — Childhood stories — believe it or not, everything I wrote here was the universe experienced through my eyes.

When people are being sincere, they do what reflects their thoughts and emotional state. Getting mad when the sports team loses. Claiming to enjoy foods that you enjoy. This opens people up to being vulnerable, being attacked for things that are linked to their identity. So people have started being ironic: doing things that do not reflect the self.

My uncle1 gifted me a pair of Gucci sneakers when I was 12, which fit me by the time I was 13. I thought that luxury brands were for dull and showy people, so I did what any teenager would do: I wore them ironically; they were nice shoes after all. But I can’t even wear them ironically anymore because the idea of “me” doing things has been deconstructed. My brain does things, my hands move, and suddenly the shoes are on my feet. “I” didn’t put the shoes on, officer.

The passage of time has led to the emergence of two new states: postirony and metairony. Postirony advances sincere messages through the vehicle of irony, i.e. a postironic welfare reformist arguing “hey, wouldn’t it just be awesome if the government just let homeless people starve on the street?”, instead of ironically arguing “wouldn’t it be awful if homeless people just all starved?”. The stage of irony and sincerity being blurred due to postironists has been dubbed “metairony”.

The frame of irony assumes that there is a coherent and causal (not necessarily permanent) I that does things when it does not. The same is true for thoughts: people don’t choose to have songs stuck in their head or immediate strokes of genius, they merely appear. Although I object to the idea that the consciousness itself is nonexistent, people’s decision to identify with it is unfounded and arbitrary. It’s also more accurately described as the department of the brain that attempts to construct socially safe narratives as to why things occur: “I cheated on my wife because of a lack of will, not love”.

I am told that modern science has largely validated this perspective, with studies finding that brain activity precedes conscious action and that the brain is a collection of modules that carry out distinct tasks, but I can’t say that I stand behind it with any confidence; I have no interest in neuroscience.

In this post, I use the word ‘I’ and make causal statements about my own beliefs and actions. This appears contradictory, but the structure of grammar forces me to do it. In conventional English grammar, a sentence needs to have a subject which does things to something, so we must say things like “I think chess is boring” which makes us believe “we” generate our thoughts, when they’re just things that appear in our heads that we irrationally attach ourselves to. It’s also much faster and clearer to say “I think X” instead of “the network of neurons stored inside the cranium that inhabits the body that is communicating this message has generated thought X”.

Irony gives the ironist the same detachment that spiritual progression does, but at the cost of the soul: the capacity to do things that are reflective of the body’s drives. Consistent ironic action is eventually done reflexively: I once started calling my parents “mother” and “father” ironically, and now do it automatically. There is no evolutionary pipeline that allows us to sort between things we do “sincerely” and “ironically”; it feels the same way to our physiology.

Irony has also been judged in the context of narrative, beyond real life application. In that respect, I am an unashamed, unsophisticated and total advocate of sincerity. I have no deep, logical reasoning for doing this.

Irony just looks ugly.

Frankly… I can’t say I endorse sincerity either. I’ve seen too many sincere people say or do things they 100% believe in and fail spectacularly because they are mediocrities with no talent who don’t think things through. The ideal to me is not being yourself, being ironic, or faking it till you make it, but doing it till you are it.

Becoming yourself.

I also challenge anybody to live a purely sincere life. It’s not fun. Life is a performance: Starbucks constructed with local wood selling lattes made with Brazilian coffee beans, cousins who lie about eating food, and politicians who wear J.Crew but prefer and could afford to wear Louis Vuitton. The ironist embraces this, while the sincerist foolishly rebels.

Sincerity also encourages conformity — if you can’t appear as X and be Y, then you have to be X or risk punishment Z. It’s not a fun game to play. Irony games do eventually get unmasked: ironic racism is as obvious as sincere racism (Hanania seems to have figured out the next step is ironic antiracism).

Irony is overhated and gets blamed for things that it isn’t responsible for. “Hey guys, I believe in nothing and want to seem detached from everything so I am going to go buy a gun, go outside, and kill a bunch of people” — said nobody ever. The influencer push to blame the Charlie Kirk shooting on “irony poisoning” and “terminally online nihilists” was a rather bizarre misdirection from the true culprit: the radical left. Irony and nihilism are sedatives, things that draw people away from grand narratives, religions, or creations. Perhaps this is for the better.