Overcoming Bias

I have long associated with smart nerdy folks with broad interests, especially re tech/future. Groups like “extropians”, “rationalists” and “effective altruists”. While there are many smart nerdy amateur groups who focus on rather concrete topics, like old cars or poker, the folks I’ve like have had a “taste for abstraction”. They like more to reason abstractly, and so over time have collected many abstractions to help them reason. This seems to me a key common element across the diverse topics they like.

When such people are nearer to academia, they tend more to learn established abstractions from academic disciplines. Others tend more to collect abstractions from online thinkers, who more often invent their own new abstractions, instead of using established ones. Such novel abstractions are generative, adding to our innovation in abstractions. But they also tend to be less reliable, leading such thinkers more often astray. Academics, in contrast, are slower to adopt new abstractions, as they hold new proposals to higher standards.

This is my main criticism of the communities collected around these online thinkers. I like them personally, but think they too often go wrong by inventing new abstractions, and then overly trusting these due to their trusting folks inside their community much more than outsiders. In particular, I think such folks have been led astray by new abstractions re AI risk; they’d do better with vetted abstractions from biology, culture, or economics.

I’m now an academic, though I was once an amateur. Over my lifetime, I have been tempted into many diverse topic areas, due to their immediate interest to me. This induced me to learn many new-to-me-but-standard abstractions. As a result I’ve stumbled into a polymath lifetime strategy: the more fields I learn, the more intersections I find where I can apply the tools of one field to the problems of another.

As a result my productivity has increased over time, even though I’m getting old; knowing N fields empowers me to look for N(N-1)/2 intersections between fields. Most of my contributions have been applying stuff we know in some areas to other areas. And note how this approach allows you to be a pretty reliable contrarian. Contrary approaches within a discipline tend to be wrong more often than just applying established abstractions from other disciplines to this one. As folks inside each discipline tend to resist accepting corrections from other disciplines, that will make you a contrarian, at least for a time.

Oddly, few people plan when young to adopt such a polymath life strategy. I think this is in part because we find it hard to believe that other fields besides where we started actually know a lot. When we feel that our intuitions seem adequate to guide practical action in an area of life like romance or physics, we find it hard to see that there could be that much to learn about it. I have been surprised by just how powerful are the abstractions that I’ve learned from areas outside my early life focus areas, and how much more productive I’ve become by learning them.

Academia neglects interdisciplinary work that combines insights from multiple areas. Each field has expert versions which experts use among themselves, and public versions seen by outsiders, and people in field B won’t accept your using the expert version of A if that differs from the non-expert version of A that B folks have in mind. Also, if you hold an academic event on the topic of A intersect B, you’ll usually invite the most prestigious people you can get in A, and in B, but you won’t usually invite people who have specialized in A intersect B, as they will tend to be as prestigious.

Thus humanity’s beliefs on many important topics have long been just inconsistent and incoherent across disparate fields of inquiry. Creating a huge opportunity to learn lots of big stuff fast: search for more contradictions between fields, and resolve them. And as humans have long neglected this opportunity, this may now be a promising option for LLMs, who seem to know quite a lot on a very wide range of topics.

Thus we might get a huge burst of progress soon if only we could get LLMs to look carefully at pairs of distant areas, ask if what they know about those two areas are in conflict, and if so substitute new more consistent views. Use the new better consensus views to lather, rinse, and repeat. Of course I’m sure there will be many obstacles to making this work in practice. Maybe LLMs just aren’t able to reason well enough yet in such cases. But maybe we should try?

Imagine a biotech firm that funds projects to develop new products, and typically bases their projects on one or more academic papers. This firm wants to learn which papers are promising as bases for new projects. But they want any info they induce to be available only to them, and not to rivals.

Here’s a simple way to do this. Pick a pool of people who seem able to judge promising papers, and give them each N tokens. (Some may get more than others, and tokens might be given at some steady rate until N is reached.) Tell them a rough idea of what sorts of projects and papers the firm seeks, and then let participants at any time privately put tokens on particular papers, or move tokens from old papers to new.

When the firm is willing to publicly declare that it is picking or considering a particular project j, then it declares a set of supporting papers i, with paper weights w_ij, such that Sum_i w_ij = 1. Anyone who put a token on paper j then is locked in to get a payment proportional to w_ij * F_j, where F_j is the funding level of project j. Though that actual funding decision might happen later. (Alternatively, they get a % stake in the project, and are only paid later when project success is determined.)

Now only the company can see how many tokens are on each paper, and who those tokens came from, and can use this info advantage to decide which projects to fund. Obviously it is a problem if participants can get info on which projects are being seriously considered before the official announcement.

From a convo with Kati Conen.

Our world consists of many coupled evolving systems, including systems of competing species, nations, political parties, firms, cultures, charities, and even academics. These systems vary in many ways, but a key difference is in their adaption power - how fast can each one search to find and adopt more adaptive alternatives.

If the strength of influence between such systems were symmetric, then systems with stronger adaption power would tend to tame and drive the weaker ones. This would promote overall adaption of our total system, and we’d want to increase the influence of strong systems over weak.

However, in our world today we often see governance and regulatory systems, which are weak adapters, having big and asymmetric influence over strong adapters like capitalism, with the reverse influence being much weaker. In fact, we often actively suppress reverse influence as illicit “corruption” or “conspiracies”.

In general, having weak adaptation systems tame and drive strong ones seems bad for overall system adaption. However, might our specific case be an exception to this general rule?

Historically war has rewarded large scale coordination, which has selected for the social unit of empires, which tax and draft from smaller communities, and resist reverse attempts to interfere with their abilities to prosecute wars. In addition, the effectiveness of law in suppressing destructive conflict has selected for legal systems which can settle legal disputes without being overly influenced by legal disputants. These may plausibly explain why we have weak adaption governments that asymmetrically influence strong adaption systems like capitalism.

More recently, empires found that they could get stronger local support for wars by merging local cultures into national cultures, and this required them to get more involved in shaping and regulating culture. And then people in national cultures became much more interested in using government to regulate each others’ behaviors. Since forager times, that’s what people who strongly feel part of the same community tend to do to each other.

And that’s my view of the status of regulation today. Government regulation is mostly justified in our world as fixing local problems, much like foragers who meddled in their local social worlds to fix what they saw as local problems. Debates about regulation almost never mention the harms of letting weak adaptive systems drive strong ones, and most specific regulations seems to me maladaptive, relative to the private alternatives that would likely arise in their absence.

So regulation likely exists as a result of prior strong selection pressures to create central governments to prosecute big wars, and to create law and national cultures to support them. Excess regulation is a side effect of making such asymmetric powers.

World fertility decline seems the clearest example of a maladaptive cultural trend, as healthy biological species just don’t decline in times of plenty, peace, and health. Two main theories help explain this trend. One is that previously adaptive habits have turned maladaptive by misfiring on cues that no longer track the adaptiveness as they once did. The other is that the cultural evolution process has become much weaker than it was up until a few centuries ago, which both slows the rate at which misfirings can be corrected, and also allows for more maladaptive changes to norms, via random walks and reversion to natural habits encoded more deeply in DNA.

Here are nine suggested misfiring stories:

1. Contraception allows us to satisfy usual norms re fun, mating w/ fewer kids

2. Pursuit of status markers induce urbanity, long education, conflict w/ kids

3. Freedom is a status marker, but having more induces fewer kids

4. Modern media shows high status in detail, raising expectations

5. Pensions replace kids to give old age security

6. Super-stimuli makes fun more engaging, distracts from kids

7. Loss of kin living close makes parenting harder

8. Urban density makes it seem like overpopulation

9. Indoor life messes w/ light, activity rhythms

I asked 5 LLMs to estimate the factor of how much faster such misfirings would be corrected now if our cultural evolution process for group norms was as healthy and robust as it has been through most of human history up until a few centuries ago:

So middle estimate of ~5.5. Stuff that would once been corrected in ~50yrs will now take ~275yrs. Culture is indeed broken.

Consider three sources of opinions or habits:

• (A) Inherit - passed down via DNA or culture, mostly sit in background unquestioned, give assumptions for B,C.

• (B) Consider - personally think own thoughts, conscious or otherwise. Influenced by what hear, debates join.

• (C) Specialize - people sit at niches in a structure, learn skills to contribute there, defer to outputs from other niches. Hear, debate near niche. Different types of structures: hierarchies, professions, speculative markets.

Before big brains, A dominated most everything. Then with big brains, A dominated stuff that was pretty constant over space and time, while B dominated the rest. And as we learned more kinds of abstractions, we collected more kinds of A that could help with B. While C has long been a thing, the modern world arose mainly due to a huge increase in C, mostly in orgs, markets, and professional networks. As our lives started to change faster and to get more specialized, that also induced a big increase in B to help us adapt to local context.

Looking more particularly at morality, norms, and adjacent culture, we see a relatively sudden jump from A to B at the modernism transition ~1900. People felt morality should change as fast as other habits were changing, and youth movements led the charge. But people also rejected C on such topics; it felt important that everyone “think for themselves”.

In adjacent areas of policy, sometimes C has been deferred to, but the ideology of democracy opposes doing too much of this. Over the last half century, we’ve seen a general decline in respect for and deference to C sources, especially near morals and politics, plausibly due to a long slow drift toward forager styles.

Alas, our civilization now plausibly suffers maladaptive cultural drift, in part from this new habit of setting morals and norms via B instead of A. And our civilization will fall unless we somehow fix this. (Even if we make AGI.) Yes, some C-like structures often feed indirectly into this B, but they don’t seem very adaptive. But short of returning to a stable low-tech highly-fragmented pre-modern world, it seems quite hard to return to A. So key question is: can we find an adaptive-enough C to source our morals?

I’ve explored a number of possible options here. While none seem especially promising, at least there’s some hope. But in this post I want to note that all of them will require us to accept no longer sourcing our morals mainly via “thinking for ourselves”. Maybe some people can be fooled into seeing themselves as vibing their morals, but there will in fact have to be a big effective structure that sets and changes morals, where people specialize on their small part and while deferring to other parts.

This is an essay. Like most of my essays, I write it mostly to strangers. And with it, I hope to influence history. Some influence history via words to strangers that show drama, interestingness, impressiveness, or political and moral evocation and bonding. Alas, my best skill is abstract analysis. But the fact that most other approaches hide behind an appearance of abstract analysis gives some hope for my approach.

To influence history, I want to induce my readers to change key factors that shape history. But if my main tool is abstract argument, I should focus on factors that we better understand abstractly, and also on factors with clear levers that motivated readers might predictably find and influence, if so persuaded. Which suggests that I look to factors other than meaning, motivation, aesthetics, and culture, factors which though quite powerful also seem hard to reason about and predictably influence.

The biggest history-making factor that fits my criteria seems to be: institutional structures, rules, and mechanisms. Especially applied to the most important areas of life. I have a Ph.D. on institutions, and have spent a career near this topic area, during which I’ve learned many powerful related abstractions, and also the fact that institutional structures do in fact greatly influence history. Also, there are often clear sharp choice points at which we change institutions, via specific concrete decisions that people can organize to influence. And big choices are often greatly influenced by observed results from much smaller prior tests, tests that can be much cheaper and easier to purposely fund, participate in, and influence. Thus I pick institutions.

However, when I follow this logic and write abstractly on institutions, to inflluence history, my words compete with many words that others write on related topics. And they compete within our shared meta-institutions, i.e., the institutions that shape who listens to and believes whom on what about abstract topics like the consequences of institution choices. (E.g., universities, journals, peer review, tenure, grant panels, newspapers, think tanks, conferences, blogs, podcasts, and social media.) So the effect on history of my abstract writings may depend greatly on the quality of those meta-institutions. Thus the quality of our institutions plausibly depends strongly on the quality of our meta-institutions. Making those meta-institutions especially promising as targets of abstract analysis.

Now, yes, the effectiveness of abstract writings should also depend on culture and many other factors of the contexts where my writings compete with others’. But again, such other factors seem harder to reason abstractly about and to predictably influence. Tipping me toward writing abstractly on the meta-institutions within which we write abstractly to influence history.

One worry: areas of life may vary in how strongly institutional differences there influence outcomes there. So how much does the insight and effectiveness of the world of abstract arguments actually depend on the quality of our meta institutions? Actually, in my judgement the world of abstract arguments seems to be one of the place where better institutions matter most!

First, over the last few centuries our most prestigious intellectuals have steadily pushed away outside accountability, first by replacing prizes with grants, and then by instituting tenure and peer review. They falsely claim that the best institution for their world is a variation on our most ancient human institution of simple gossip and prestige. We are to just trust the most prestigious folks completely by giving them resources to do whatever they want, and letting them pick the new generation of prestigious folks.

Second, this gossip and prestige structure usually results in the folks in each discipline working mainly to look impressive according to local standards. While contributions may be justified in terms of their new insights, the prospect of useful or important insight actually little drives choices of topics or methods. Worse, they tend to belittle those who try to offer insight without meeting their local standards of impressiveness. And as the most prestigious find it hard to judge quality above their own quality level, incentives become quite weak for quality above these levels.

Third, this gossip and prestige system is often taken over by political, ideological, and other factions, who insist that candidates for prestige in their world must first pledge allegiance to key dogmas. Also, common dogmas on acceptable topics and methods leave many, even most, topic-method combinations as taboo in their worlds.

Fourth, the space of possible abstract claims and arguments is vast and high dimensional, with relevant connections possible across vast topic scopes. As a result, the cost-effectiveness of clever creative approaches can be many orders of magnitude higher than that of standard predictable methods. This implies unusually large gains from giving people strong freedoms and incentives to achieve the best outcomes, via whatever methods they can find.

Finally, the key outcome that we want society to accumulate over the long run from our abstract talk, i.e., insights into important topics, seems quite measurable. Making it plausible to imagine using powerful mechanisms like decision markets tied to such aggregate outcomes to make key governance choices about this area of life. It also seems like it might be possible to measure individual contributions to such aggregate outcomes, allowing finer-grain incentives for individuals.

If we would seriously explore the space of possible institutions for our abstract talk, we could plausibly find much better versions, which if widely adopted would let us accumulate abstract insight much faster across most topics, including the topics of institutions for other areas of life. Which could then allow our whole society to run much better, and better understand most important topics. What’s not to like?

Most writing and talking embraces our usual illusions on human motives. In our book The Elephant in the Brain (with Kevin Simler) we instead expose such illusions. Which many have told us feels depressing and demotivating; it’s not what they wanted to hear. It’s right there in the title, an analogy to “The Elephant in the Room”, which is a big topic which people in a room pointedly ignore.

Yet we’ve sold over 60K copies over 8 years, which is quite good for an academic book. We got some pretty high profile early reviews. And have even been on few class syllabi. So there is clearly an audience for our message. But why, if it tells things people don’t want to hear?

The most prestigious intellectuals in our world are writers of op-eds, and givers of TED and keynote talks. And such luminaries often offer policies and stances based on their claims that ordinary people are typically mistaken on key things. For example, this is the usual rationale for paternalism, which justifies over half of government intervention (as well as legal rules of evidence). So there is in fact a big audience for claims that most other people are wrong; that’s why you say the world should let your people take control. As another example, consider how popular was Al Gore’s An Inconvenient Truth, another title that telegraphs such a message.

However, a different kind of deep illusion finds a far smaller audience. Our most prestigious intellectuals are cultural warriors, who to be popular and effective must project a graceful and compelling confidence in their moral stance, a stance that they convince readers is shared between them. Their key culture war stance is that we, our side, correctly feels a clear and compelling impulse to push hard to get our way. As we are obviously morally right, and they are wrong.

Alas, this is the sort of illusion that I must apparently try to expose in order to get people to see our key modern problem of cultural drift. I can explain the logic of this problem easily enough, if I can get people to stand outside of their particular culture, and see the cultural evolution process in the abstract. Yet, alas, from that vantage point, few feel much motivation to care. I haven’t succeeded at all at the key op-ed writer task of projecting a graceful confidence in a supporting moral stance, a stance I convince readers that they share with me, in opposition to an evil other side.

In my last post I reported:

For the last century, … averaging over [3] LLMs, 89% of culture trends that can be classified are toward-forager.

And 81% of such trends can be so classified. For the prior two centuries this explanatory power was weaker (59%,65%), but still substantial. This suggests a way to predict the next century: predict toward forager trend changes.

So I collected 22 future trends that would plausibly be predicted by a continuing toward-forager-style trend. I then set aside these 7 trends as ones that could also be as plausibly predicted by increased wealth, education, or world connection:

↓ Fertility; ↑ Travel, Migration;↓ Nationalism;↓ Religion, ↑ Spirituality; ↑ Emotion Talk, Legitimacy; ↑ Flexible Work Hrs, Places; ↑ Casual Dress, Etiquette.

That left these 15 trends as better tests of the toward-forager hypothesis:

↑ Business Regulation; ↑ Kid Autonomy; ↑ Loose Drug Norms; ↑ Loose Sex Norms; ↑ Nature Sacred; ↑ Redistribution; ↓ Convict, Animal Cruelty; ↓ Family, ↑ Friends; ↓ Gender Roles; ↓ Institution Authority; ↓ Marriage; ↓ Militarism; ↓ Monogamy; ↓ Politics Via Orgs; ↓ Rank/$, ↑ Charisma.

To further consider this hypothesis, I asked poll respondents to rank, and 3 LLMs to predict, the chance that each will be a world trend over the next century. Here are human relative priorities and median LLM chances:

LLMs give a mean chance of 67%, about the fraction they said fit toward-forager trends in 1826-1926. So LLMs foresee a much lower predictive power for the next century, compared to the last century. But the correlation between humans and LLMs here is -0.06, so humans disagree with LLMs lots here. In a century we’ll have actual trend data to more directly see who was right.

For over ten millennia of the farming era, most folks saw themselves as tightly tied to small groups that lived in a largely alien and hostile world, under the thumb of empires and elites selected by tradition and power, elites not embarrassed by their privilege, interested in the general welfare, nor open to persuasion by argument. Few saw grand arcs of history as the sorts of things that they could or should much influence.

Today, in contrast, most people and especially elites see themselves as part of a single big world, with elites selected more by merit, embarrassed by unmerited privilege, interested in general welfare, and especially smart and open to persuasion. So we see world arcs and problems as things to be dealt with by smart elites talking stuff out until they agree, and most everyone is eager to join in such talk to seem like elites.

How did this change? In 2010, I started to explore this explanation: modern values are mainly a reversion to forager values.

[Forager] individuals who otherwise would be subordinated are clever enough to form a large and united political coalition. … the weak combine forces to actively dominate the strong. … They must continue such domination if they are to remain autonomous and equal, and prehistorically we shall see that they appear to have done so very predictably as long as hunting bands remained mobile. … Before twelve thousand years ago, humans basically were egalitarian. They lived in what might be called societies of equals, with minimal political centralization and no social classes. Everyone participated in group decisions, and outside the family there were no dominators. For more than five millennia now, the human trend has been toward hierarchy rather than equality. But the past several centuries have witnessed sporadic but highly successful attempts to reverse this trend. (More)

A lot of today’s political disputes come down to a conflict between farmer and forager ways, with forager ways slowly and steadily winning out since the industrial revolution. It seems we acted like farmers when farming required that, but when richer we feel we can afford to revert to more natural-feeling forager ways. (More)

In the absence of [big] threats, the talky collective was the main arena that mattered. Everyone worked hard to look good by the far-view idealistic and empathy-based norms usually favored in collective views. … When they felt on good terms with the group, people could relax and feel safe. They then become more playful, and acted like animals generally do when playful. Within a bounded safe space, behavior becomes more varied, stylized, artistic, humorous, teasing, self-indulgent, and emotionally expressive. For example, there is more, and more varied, music and dance. New possibilities are explored. (More)

We [today] … have a strong world culture of regulators, driven by a stronger world culture of elites. Elites all over the world talk, and then form a consensus, and then authorities everywhere are pressured into following that consensus. … This looks a lot like the ancient forager system of conflict resolution within bands. Forager bands would gossip about a problem, come to a consensus about what to do, and then everyone would just do that. … This world system [is] new … this looks like another way in which our world has become more forager-like over the last few centuries, as we’ve felt more rich and safe. (More)

Weak cultural selection pressures have allowed a drift back to forager habits and attitudes, which DNA makes still more natural than farmer alternatives. Our increased wealth, health, and peace now makes us unusually willing and able to indulge forager-style moral preferences. The usual forager view is this: we must coordinate via norms and governance to prevent dangerous competition from undermining our precious stable shared human values. (More)

I don’t claim to be totally original here. Let me credit sources who explored related ideas: Joshua Meyrowitz (1986) No Sense of Place, Friedrich Hayek (1988) The Fatal Conceit, Ernest Gellner (1994) Conditions of Liberty; Christopher Boehm (1999) Hierarchy in the Forest; Ronald Inglehart, Christian Welzel (2005) Modernization, Cultural Change, and Democracy; Peter Turchin (2105) Ultrasociety; Ian Morris (2015) Foragers, Farmers, and Fossil Fuels; James Suzman (2020) Work.

To test this basic idea, I asked 3 LLMs to find 100 cultural changes in the West in each of the periods 1400-1726, 1726-1826, 1826-1926, and 1926-2026, and then to score each change as more toward a forager style, more toward a farmer style, or hard to classify and thus neither. Here are their results:

For the last century, we see a strong correlation: averaging over LLMs, 89% of culture trends that can be classified are toward-forager. Making this return-to-forager-styles theory quite explanatory for that period. However, over the prior two centuries the correlation seems real but weaker, with 59% and then 65% of trends being toward-forager. For the earliest period of 1400-1726, the tendency was the opposite, with only 37% of trends were toward-forager.

To explain recent trends even better, let’s add in two more key changes: the world got both better connected and more educated. Increasing talk, travel, and trade made us intuitively feel part of much larger communities. So when our elites try to act like forager sitting around the campfire pontificating on their band’s problems, they see much larger social units as their “band”, often the whole world. And being better educated, elites now use much higher levels of abstraction and other mental tools of the educated when pontificating on big arcs and problems. Also, putting our young elites together in school has created strong youth cultures, which have for the last century driven rapid change in core cultural values.

This return to forager styles has created the intellectual world that I have known and loved all my life. The world in which I love to read, listen, write, and speak. And which sits adjacent to the songs, movies, art, etc. that I love. A world where, at its best, smart young people talk abstractly and idealistically about big issues and problems, and then greatly influence policy and culture. In the last few decades I’ve been associated with new groups like rationalists and effective altruists who have arisen in this mold.

Alas, I recently learned that forager-style elite talky collectives seem to be contributing to our civilization’s key problem of decline due to insufficient evolutionary pressures for dimensions of behavior not greatly under the control of capitalism, but instead subject to strong individual conformity pressures. Not only have youth movements been rapidly changing key cultural values with little regard to their adaptiveness, but our forager elite intellectuals have been overconfidently inducing over-regulation, severely limiting the scope of strong evolutionary pressures.

You see, ancient forager elites didn’t just consider in general how to promote their groups, they instead focused mostly on the possibility that some of group members might gain and use dangerous powers. Since then, people thinking like foragers have similarly focused on identifying and reigning in what they see as the dangerous potentially-ineqalitarian powers of their world. In the last few centuries, such dangers have included alien ideologies and militaries, capitalist owners and firms, and technologies like nuclear, genetic engineering, and AI. A lifetime of detailed examination of such things allows me to say with some confidence: we have consistently greatly over-regulated such things.

It is likely that our civilization will fall, to be replaced by much less forager-like versions. Like civs built by descendants of today’s Amish and Haredim. But I see a chance to save a lot, a chance I want to explore. Yes, this would require substantial compromise; we just can’t keep on relying on simple forager intuitions as naively as we have. But I do see a potential way out.

First, we’d need to adopt far more effective and accountable institutions for creating consensus on claims about the concrete consequences of policies. Institutions like policy decision markets or academic prestige futures. These could cut much of the bias in our policy choices, relative to our values. Second we’d need to either directly or indirectly show far more respect for adaptiveness when expressing our deep values. Either have big polities hold to sacred goals inconsistent with civ collapse, or smaller polities hold directly to their long term adaptiveness, both via rather competent governance institutions. Big asks, I know, but at least I see a chance here.

Sometime in the last few million years, our ancestors began to get better brains, use tools and weapons, speak language, and live in larger groups in a wider range of environments. A big key to all this was cultural natural selection. Though at first DNA and cultural evolution often pushed in different directions, the fact that culture could drive change so much faster let culture tame DNA, and induce it to make us especially plastic and receptive to culture.

Early on, sufficient brains, culture, weapons, and language let us create social norms, i.e., “good” and “evil”. (I use scare quotes to point to social concepts that may not guide my choices.) At first, our main use of norms was to suppress the often violent internal competition that had previously limited feasible primate group size. Our norms said to help and share, and not hit, threaten, brag, or form subgroup coalitions. “Good” was following moral instincts and prestige incentives to take collective actions and enforce norms to prevent dangerous competition, while “evil” was conspiring in the shadows to compete for power, often by evading norm enforcement.

Funny thing though, while norms did help foragers avoid the worst scenarios of destructive conflict, foragers actually evolved more due to selection pressures that favored doing “evil” well, compared to “good”. That is, foragers mostly got smarter by learning to pretend to do “good” for the whole group while actually conspiring with allies to compete. Non-violently, but fiercely and cleverly. And this has been a consistent historical trend: our strongest selection pressures, inducing the most evolution, have long appeared in relatively “evil” harsh, destructive, norm-violating areas of life, relative to areas we see as driven more by “good”. Our evolutionary engines tend to be “evil”, not “good”, which is why “good” has found it so hard to defeat “evil”, even when everyone gives it such enthusiastic praise.

For example, before humans, predatory animals grew bigger more innovative brains, compared to prey animals and plants. Human foragers evolved more from hidden politics and competition than from cooperating to do “good”. In the farming era, war most drove cultural evolution, even though war was quite destructive, and made us do things we usually consider quite “evil”. In our industrial era, capitalism has driven evolution more than anything else, even though it is widely considered close to “evil” due to selfishness, competition, inequality, creative destruction, and indifference to sacredness. Today “social Darwinists”, who try to make their nations or groups win at Darwinian competition (either DNA or cultural), are now widely seen as max evil.

However, just as the stronger force of culture tamed the weaker DNA force, these harsh “evil” areas of life with stronger selection pressures have often tamed “good” areas. For example, collective forager talk and norm enforcement habits evolved to be manipulatable by covert political coalitions. (Just as in the politics of most small orgs today.) In the farming era, religions and norms evolved to support and not oppose wars. And in the early industrial era, capitalist pressures induced norm changes in many areas of life, to allow more money and capitalism there. “Good” behavior tends to become a hypocritical cover for “evil” forces.

However ~1900 competition between nations became a stronger selection force, with nations more controlling and limiting both capitalism and culture. And since WWII, activist-driven fast-changing culture has surged in strength, coming to control and limit both nations and capitalism. Over the entire industrial era, areas of life not run by capitalism and under strong conformity pressures have plausibly come to suffer from cultural drift into maladaption due to a lack of sufficiently powerful evolution. Eventually, such maladaption will plausibly get fixed by “evil” capitalism, with its stronger power, vitality, and selection pressures, taming conflicting forces of “good”, and then inducing norms that support a wider use of capitalism.

But before then we may suffer a long painful transition period during which much of what we cherish about our civ may be lost. For example, our civ might fall to be replaced by insular fertile subcultures like the Amish, with future civs maybe also rising and falling several times. Even human level AI doesn’t directly solve cultural drift, though the fact that capitalists now make, own, and shape AIs offers hope of a faster cleaner transition to a capitalism-dense AI world.

Why has culture been able to defy and limit capitalism so well over the last few centuries? I’ve suggested that weak cultural selection pressures have allowed a drift back to forager habits and attitudes, which DNA makes still more natural than farmer alternatives. Our increased wealth, health, and peace now makes us unusually willing and able to indulge forager-style moral preferences.

The usual forager view is this: we must coordinate via norms and governance to prevent dangerous competition from undermining our precious stable shared human values. For foragers in a small band, the dangerous competition came from sub-band coalitions. And all my life I’ve heard excess regulation justified in such terms, and heard futurists talk similarly, except that their envisioned dangerous competition comes from capitalism, genetic engineering, population explosion, or AI.

However, as our culture’s shared values today are not at all stable, but instead have been drifting fast into maladaption, they are not so precious. So making a “good” world government to control “evil” competition in their name thus seems bad. The only way to long preserve anything unusual about our civilization (e.g., open inquiry) is to mix it into an adaptive cultural package. And as capitalism is now our most powerful adaptive engine, that means a package where capitalism runs most things. (Other fixes seem variations on this.) Such as via big for-profit governments, capitalists paying parents to make profitable kids, sacred capitalists investing in sacred ventures, or foundations reinvesting all returns to drive interest rates down to growth rates.

Once “evil” capitalism has tamed the “good” norms of culture, we will still have norms that we enforce, norms which may on average mitigate real harms from excess competition. But which still allow strong selection pressures to keep our descendants adaptive. And which, if we are lucky, preserve some of what we today find precious about our civ.

Added 18May: Note the similarity of cooperative explicit good vs passionate powerful evil to near-far theory distinction of weakly-motivated abstract far to strongly-motivated concrete near.

Capital, culture, and states are three key powers in the world. Which ones influences the others more, and how has that changed over time? I asked ChatGPT (5.5), Claude (4.6), and Gemini (3) to estimate pairwise influence each way on a 0-10 scale these over four time periods. The following table shows medians for the 3 LLMs for each period:

I’ve marked in green the more reliable entries, where the range across the 3 LLM estimates is 2 or less, and in red less the reliable, where that range is 4 or more. Note that estimates seem less reliable in more recent periods.

Below the main table I show the median estimates over all times. Oddly, these values are consistently 6 or 7. Maybe all the time-specific LLM estimates given are normed to be relative to this time-independent reference point? In which case, these numbers are mostly about changes over the periods, not constant over time effects.

To the right of the main table I show the net (sum out minus in) influence for each power at each period. The story told here is that before industry culture dominated, states were much weaker, and capital was much weaker still. Then in the early Modern period all three had about equal influence, though capital might have had a bit more. In the middle Modern period states dominated, with capital much weaker, and culture much weaker still. But then in the most recent Modern period, culture has returned to now dominate, with capital and states much weaker.

The part of this I feel most confident in is that the influence of capital, culture, and state on each other did change over this period, and it is worth trying to figure out how. I’m also pretty confident that the 1900-1970 period was the peak of state influence, and that culture had its peak influence both long ago and recently.

Humanity has broken its superpower of cultural evolution, at least at the level of large cultural units, the units that set our game theoretic equilibria of key norms, values, and status markers. 300yrs ago these units had great variety, were under strong select pressures, and had slow rates of change of environment and internal drift. But since then, all four of these key control parameters have since gotten much worse.

Unless we achieve human level AI soon, our dominant world civ’s population seem likely to decline, to be replaced by fertile insular religious subcultures like the Amish and Haredim, who have been doubling every 20yrs for over a century. (Like how Christians took over Roman Empire.) Human extinction seems unlikely, if our declining civ continues to tolerate their norm deviance. But we do risk the end, at least for a while, of many novel treasured features of our current civ, such as democracy, pacifism, gender equality, sexual freedom, legal due process, open inquiry, and modern artistic genres.

I’ve been pondering our options, and want to report my current thinking. I see four.

Fertile Cults - We might plausibly try to create more fertile durable insular subcultures, ones that save more of our treasured cultural features. This is quite hard, however, as only a tiny fraction of cults ever achieve this package. As the strongest cultural divides in the world today are along religious lines, the few successes here are likely to be religious. And this only puts off the problem; replacement civs, including AIs, would still suffer cultural drift until they found deeper solutions. Very small groups can try this, though alas few seem interested in the key insularity feature.

Max Capitalism - For-profit firms still seem to be sustaining a healthy cultural evolution, with the set of all firms improving over time even as typical firms decay. The decaying dimensions of our behaviors seem to be those we don’t let for-profit firms control. So we might fix those dimensions by removing such limits. For example, allow large-scale for-profit governments, let capitalists pay parents to make profitable kids, let sacred capitalists invest in sacred ventures, and let foundations reinvest all returns to drive interest rates down to growth rates. This must be tried at the scales where laws now forbid such ventures. While many are passionately against this, some are passionately for, an energy one could build on.

Adaption Policy - If we could commit to measuring the actual adaptive influence (both via DNA and culture) of groups today in a century or two, we could make futures markets in such measures, and then use changes in current price estimates of group adaption as metrics to reward and punish group leaders. This requires such people to overcome the now widespread taboo against “Social Darwinism” to value adaptiveness greatly, and enough to use adaption as a main criterion when choosing group leaders and policies. (Futarchy might help here.) Modestly small groups can try this, though very few now have much passion for the adaption goal.

Sacred Policy - While few have much passion for the direct goal of adaption, many more can find passion for goals that cultural maladaption might block. For example, the goals of having a million people living in space, or achieving physical immortality for humans, might take centuries and also take longer if our civ falls due to maladaption. Many might treat such goals as sacred, being proud to sacrifice for them and ashamed to abandon them. A group big enough to have substantial influence on when the world achieves such goals might make futures markets estimating such dates, and use price changes to reward and punish group leaders. (Futarchy might help here.) Alas, this requires rather large groups, and requires them to, when they achieve sacred goals, keep setting new goals also in conflict with civ decline.

For years, cybersecurity experts have been warning about the chaos that highly capable hacking bots could usher in. … Claude Mythos Preview appears to represent not an incremental change but the beginning of a paradigm shift. … Perhaps more concerning than the reported capabilities of Mythos Preview is that other companies are not far behind. (More)

Finding bugs was also hard, so the worst flaws stayed hidden, sometimes for decades. It wasn’t a great system. But the difficulty on both sides created a kind of détente that held. Now, thanks to new A.I. tools, anyone can write code. Soon, bad actors could use those same tools to find out what’s wrong with code. The détente is over. (more)

Use strong passwords that are unique across every site, preferably through a trusted password manager. Better yet, when a site offers a passkey, take it. … For accounts without passkeys, use an authenticator app for two-factor authentication, not text messages. Always keep all your software up to date, and uninstall unnecessary apps. (more)

OK, I’m a few weeks late to this party, but not too late to give many of you news: We may soon face a period (a few years?) of greatly reduced software availability.

For many decades, we have known how to write pretty secure software. It takes a bit longer, and security considerations must be central to early design efforts, but it is possible. However, developers have usually been in too much of a rush to market to do this. So most software systems today are riddled with security holes. What has saved them so far is that it takes humans a lot of work to find and exploit such holes.

However, there now exist powerful AI systems that are far better at finding and using such holes. Soon (within a year or two?) many AI firms will have such tools, and they will spread to be widely available. Yes, such AI systems can also work to patch such holes, but computer security experts tell me that the nature of insecure systems is to make it much easier to find and use than to patch such holes. Attack beats defense.

Software firms would then more eagerly rewrite their code to use more secure designs, and AI could help them to do this. But this takes time, and as there isn’t a lot of secure software out there now, AI hasn’t had big datasets ready to help them learn how to do this well. So it will take some time to replace weak with strong software.

So there may soon be a period, starting within a few years, maybe lasting a few years, when most actual software systems can cheaply be hacked. This will make such software firms vulnerable to ransomware, and make customers wary of using their products. Customers, firms, and App stores, will respond by cutting back on what software systems they offer, and by simplifying them by dropping many features.

As our world has come to rely on software for a great many things, it seems quite concerning that we might soon have to make do with substantially less software. How vulnerable are crucial systems like electricity, cars, traffic lights, voting systems, and payment systems? I don’t think we know. Beware the coming Hackastrophe.

Note: such an event would likely make the public much more willing to regulate AI. And if credit card firms get overwhelmed with false sales, that could make crypto more attractive.

The key innovation that has powered the modern era is: organizations. We solve a great many problems by creating an org, setting it tasks, giving it powers and resources, and putting some key “masters” in charge.

Besides participating as suppliers, customers, employees, or targets of such orgs, there are two other key ways we engage such orgs: politics and governance. In politics, we take sides among the different alliances of masters and tasks, struggling for who will dominate. In governance, we try to hold masters accountable for achieving tasks, and seek new better ways to choose, reward, and monitor them.

Low status folks have long been advised to keep their head down and stay out of both politics and governance. Higher status folks, in contrast, are somewhat encouraged to do politics, if they are willing to risk suffering repression when their allies lose. We like democracy as more of us can more safely be political, and thus see ourselves as high status, though politics becomes less safe as political polarization rises.

However, most folks are well advised to stay out of governance, at least when that involves any substantial chance of holding masters more accountable, and thus cutting into their spoils. Masters coordinate to block cuts to their spoils. (Yes, some spoils come via achieving promised tasks, but most don’t.) In contrast, masters don’t mind and even like governance changes that don’t risk stronger accountability. Such as making it more popular, inclusive, decentralized, more intensive participation, etc.

How much should you fear masters displeased by your meddling in governance? Greatly! Org masters, and their allies and wannabes, are the fiercest predators of our world. Smart, energetic, and well-connected, they are wolves in sheep’s clothing, smiling broadly, speaking gently and grandly, but holding their fangs and claws ready in shadows to strike when ready.

Alas, our world has long suffered from poor governance. So much so that for most problems we know how to solve, we don’t actually solve them. We got better enough at governance to allow the modern world to have big orgs, but just barely.

Today, our civilization faces problems so huge that we will mostly likely fall, as did the Roman Empire, to be replaced by insular fertile cultures like the Amish and Haredim. Better governance seems our best hope here, and promising alternatives do exist, ones that can be tested at small scales before deploying on larger scales. Alas such efforts are mainly blocked by spoil-protecting masters. Will enough of us risk their displeasure to force such innovation experiments in time?

We vary in our motives and priorities in thinking. For example, some try to impress, some try to sell others on pre-existing positions, some try to show loyalty and support to teams, and some try to figure stuff out. As we have norms against the other motives, when asked, many of us claim to have this last widely admired motive.

Yet, strikingly, few in public discussions present themselves as trying to figure things out together with their convo partners. Such as by posing problems and questions, reframing these to avoid sloppiness, offering alternative options and answers, noting puzzling or contrary consequences, and admitting when one’s prior convo moves are undermined by new points made.

Yes, presenting a figuring-stuff-out-together convo persona often imposes some costs relative to other possible personas. But the more eager that we are to suppress other possible interpretations of their motives, the more eager we should be to pay such costs, to assert our preferred persona.

I have to conclude that while we usually don’t want to directly admit that we seek to impress, sell, or support, we don’t actually much mind observers inferring such motives in us. Few actually have that much respect for people those who try to figure stuff out together.

(This is my comment re CFTC call for comments on prediction markets.)

As an economist, not a lawyer, I write here on public interest, not what is legal.

Like all financial markets, prediction markets can serve many functions, such as moving and cutting risk, collecting and sharing information, and the fun of action and proving yourself in competition. For decades, that risk function was the only one U.S. regulators allowed as a justification, but I’ve long argued for a huge potential info value, far more than what we now realize. I want these markets to grow toward that potential. While I personally don’t mind people having fun, I see that others mind, and we might have to compromise there.

Focusing on that info function, prediction markets have many issues in common with other info institutions, like gossip, academia, and journalism. All info institutions can induce folks to (A) reveal info better kept secret, (B) reveal secrets people promised to keep, (C) waste time and money that could be used productively, (D) make misleading contributions to get favorable treatment, (E) change the world to get favorable treatment, and (F) reward participants unequally.

I admit these are real issues, but I say we should treat the various info institutions similarly, unless we find specific reasons to treat them differently. For example, if you wouldn’t forbid govt employees from talking to reporters, for fear they’ll reveal govt secrets, also don’t forbid them from trading just due to similar fears.

On (A), an example is election-day who-wins predictions, which many say discourage voting. But as the risk of over-regulation here is severe, the first amendment should protect prediction markets as an info institution, especially markets on politics and policy. Just as protests are protected, since there are things you can say via protests you can’t say via mere words, trades should also be protected, as there are things you can say with trades you can’t say via words or protests. Putting your money where your mouth is adds punch to your words.

On (B), orgs have legit interests in keeping secrets, but outsiders often have legit interests in exposing them. Many of history’s most lauded journalism stories were enabled by org leaks. There’s a tradeoff here, and requiring everyone to work to help all orgs keep their secrets goes too far. We have strong rules on the books now re prediction market “insider trading”, but note that such rules for stocks have had limited effects. At public firms announcements, half of the price change happens beforehand, and half of that is from insider trading. We shouldn’t expect prediction market rules to succeed much better, or to result in much worse harms.

On (C), other financial markets already allow as much pure “gambling” as anyone could want, and compared to prior ages we today let people devote great time and money into non-productive fun of many sorts, including news, making risky choices of who to date, and making risky choices of careers like acting, music, or athletics.

On (D), speculative markets are actually far more resistant to manipulation than other info institutions. When traders expect more efforts to manipulate a price, they respond so that prices on average become MORE accurate. Also, in head-to-head comparisons with other info institutions, with the same question, time, participants, and resources, speculative markets have been consistently about as accurate or much more accurate.

On (E), life insurance has big enough stakes and easy enough personal influence that we reasonably regulate it to prevent murder for money. But we see almost no cases of traders successfully sabotaging firms to profit from stock trades; firms seem too hard for individuals to influence compared to the stakes. And when prediction markets have been made on events that individuals can influence, it seems traders have been well aware of this fact, and saw this fact as adding to their fun.

On (F), other info institutions also give unequal rewards for intelligence, education, effort, and good social connections. Yes, we could create amateur-only markets, but few would want to trade there; most want to try their hand competing with the best.

Due to their great info potential, let’s approve prediction markets by default, especially when they can inform topics that matter, and only restrict them when we see clear evidence of harm, applying similar standards and scrutiny as we do for other info institutions.

What are you the most wrong about? You know the least about stuff far away from you in distant galaxies, but as you have few opinions about that, and it hardly affects you, who cares?

But what are you the most wrong about where you do have opinions, and where they are consequential for you? Consider seven factors that say when you are BLINDED:

• [B]ound: When you are judged by your group on your confident and unthinking belief in and loyalty to particular claims, you won’t study them well.

• [L]ow-Impact: When you are wrong about factors relevant for collective choices, your vote barely moves them, and so you have little incentive to think about them to make them better.

• [I]ndefinite: When concepts come from a high dimensional space where it seems hard to pin them down, separate them, or to define or measure them.

• [N]on-Connected: When you see relevant concepts as coming from a whole separate realm that has no logical connections to all the usual realms where you know things.

• [D]evalued: When you declare yourself to be largely indifferent to the consequences for you, as something else matters much more to you.

• [E]vidence-Poor: When you actually have little relevant data to draw on, and the best data that you have supporting your opinion is the mere fact that some groups like yours have continued to exist and while holding this opinion.

• [D]ynamic: When the topic is about what changes to be making to your group’s collective choices, either recently or in the near future, the mere fact that your group exists no longer offers even weak evidence for those choices.

The max mistake topic area, with all of these factors, is: the adaptiveness of your morals.

Your group suspects that you are evil if you do not see their morals as obvious, and even suspects you if you had to think to come to agree with them. Morality is a collective choice, where you are punished for deviating, so to have an impact you’d have to change your group’s shared moral opinions. Moral concepts tend to be hard to pin down, and today most see moral claims as sitting in a disconnected realm where all our usual non-moral claims are not relevant.

On the topic of the cultural and DNA adaptiveness of your group’s morality (and norms and status markers), most people say they care much less about the adaptiveness of their morals than about the “moral truth” of their morals. Figuring out theoretically which morals are more adaptive is actually quite hard, and so our best evidence is empirical: which successful societies have had which morals. But the fact that your society seems inclined to change its morals lately in a particular direction is far weaker evidence for the adaptiveness of that direction.

The topic where you most need careful thought is also where your community most punishes such thought. This is our big blind spot on which our civ will likely fall.

Consider the social ranking of who is how much of an intellectual. Think of this ranking as made by a weighted average of the opinions of other intellectuals. If we look at how this weighting changes across intellectual levels, there will be a median level, where half of the weight comes from opinions above that level, and half below.

I asked ChatGPT (5.5) and Claude (4.7) to give percentile estimates for the median level who judges who are the very best intellectuals, for the West in various years. They gave median 99%,99.5% for year 1000, median 96%,97% for year 1750, median 93%,90% for 1900, and median 88%,80% for 2025.

We have thus seen an increasing populism in who among us judges who are our very best intellectuals. Which is plausibly a source of intellectual decay. Especially as it is often noted that we usually find it hard to distinguish between mental quality levels above our own.

Many (Poincaré 1908, Schumpeter 1911, Ogburn 1922) have said that, as there are so many good ideas out there, most innovation is just simple combos of prior good ideas. This seems true of my best idea.

April 25, 1996, thirty years ago today, I first posted my best idea: decision markets, i.e., speculative markets that advise specific decisions by estimating decision-conditional outcomes. A.k.a., “futarchy” as applied to governance. It’s not my deepest, grandest, beautiful, or hardest won insight, just the one with the biggest expected impact.

My idea was a simple combo of two other long-well-known ideas.

The first prior idea I built on is that speculative markets do quite well at aggregating info. This was explored in theory (Emory 1896, Gibson 1889, Bachelier 1900) and in data (Cowles 1933, Working 1934). Even so in 1996, US regulators in practice only allowed risk-hedging, not info aggregation, as an “economics rationale” to allow markets to exist. (The allowed “price discovery” rationale was tied to helping other markets hedge risks.)

In 1984 I left grad school in physics and philosophy of science at U Chicago to go to Silicon Valley to do AI research, and on the side work with Xanadu, trying to invent the World Wide Web. Around 1988 I first started to have doubts about the Xanadu vision of reforming public convo by making criticism easy to find, and wondered what else we could do instead. So I started to think and write about the big potential of making speculative markets to aggregate info on far more topics. Like most everyone who first enters this space, I was first thinking mainly in terms of markets on the usual topics we see in mass media, punditry, and public policy debates.

The second prior idea I built on is that info is mainly valuable by informing specific decisions. For many centuries we’ve seen calculations of the value of certain specific info for specific decisions. And then we developed more general theory (Ramsey 1928, Hosiansson 1931, Blackwell 1951, Savage 1953, Schlaifer 1959). At Caltech social science grad school 1993-1997, I learned decision theory and the standard value of info calculation. Then wondering where speculative markets could add the most info value, ~1996 I realized that this would likely come from markets estimating specific outcomes given specific decision choices.

As I was one of the first to write on the big potential of prediction markets, many who entered this space over the years approached me. At which point I usually pitched this decision market concept. Which usually pushed them away, as they were focused, as I was initially, on those mass media and punditry topics. But I have doggedly persisted.

Most all innovations combine simple elegant ideas with messy details that make those ideas work. Mine is no different. To find the right messy details, one needs concrete trials and experiments trying different detail versions. It has been hard to find orgs willing to do this, as org decision making is usually quite political. But in the last few years we’ve thankfully started to see some trials.

As an econ professor who specialized in governance, I can assure you that the world is greatly structured by the fact that we typically have pretty incompetent governance. Imagine a governance that, when assigned a goal, would reliably achieve that if it is in fact feasible. This would radically reshape our whole world. (Yes, even if we soon get powerful AIs.) As decisions markets plausibly enable such competent governance, this is why I estimate their expected impact to be so very great.

Human action plans are often organized around goal hierarchies, with lower-level subgoals helping to achieve higher-level goals. And many parameters correlate simply with this high-to-low goal axis. For example, lower-level goals and actions tend to take less space, time, and other resources. They are less likely to conflict with other goals, and more likely to be time-consistent. They are more easily evaluated for success, better described by simple abstractions, more reliably controlled, and more easily optimized by hill-climbing. They seem more observable, reversible, and substitutable, give faster feedback, and are more easily automated.

However, other related parameters depend on this key high-to-low goal axis in less simple ways; they instead peak at some mid-level, and fall away from that in both directions. For example, we have more conscious awareness of, give more conscious attention to, and make more deliberate choices re mid level goals. We can more clearly articulate them and their relations to other goals, and we can more easily teach others to manage them. People coordinate with each other more here, and our blame, credit, norms, and laws focus more here. There is more cultural variety of behaviors at these mid levels; other behaviors are more set by DNA.

A noteworthy exception is that such mid-peaking parameters often peak at much higher levels in large for-profit orgs, and in other large orgs, like militaries, with strong incentives tied to concrete goals. Such orgs often can and do articulate, measure, credit, and blame the behaviors of top people who mange high-level goals.

A simple interpretation of these patterns is that cultural evolution of coordinated behaviors faced a key tradeoff. Let me explain.

As thinking and talking takes time, there is a lowest level of goals and actions where we can discuss them as we choose and do them, so that such talk greatly influences those actions. While humans can and do watch and learn details of others’ behaviors that are at much lower-levels, we mostly do this non-verbally and unconsciously.

However, to enforce norms, including the norms that say that we should keep our promises, we humans need to be able say to others in sometimes-verifiable words what we and others have or have not been doing lately. So that we can complain about such actions, and recruit others to exert social pressures toward norm enforcement. To defend ourselves against such accusations, our conscious minds were created to manage key stories of what we’ve been doing lately and why.

So cultural evolution got into the habit of having us think and talk consciously about goals near this lowest-articulable level, and also to notice, copy, and teach chunks of behavior near these levels. And in addition, we mostly manage our norms, status markers, and key coordination mechanisms near such levels. As this cultural evolution process is pretty random and uncoordinated, efforts to abstract these norms and chunks most naturally expressed at these mid levels into higher level goals don’t usually achieve much clarity or coherence. Also, we seem reluctant to explicitly name cultural adaption itself as a big higher level goal.

So why didn’t we instead define and manage our social coordination using much higher levels goals? The simple correlations above say that such higher goals would tend to be less modular, less observable, and less easily described using abstractions. Making it harder for us to see and describe them, and to enforce norms about them.

However, with the invention of money and for-profit orgs, the world has now found new ways to use modular observable goals at quite high-levels. When we allow such orgs to manage key areas of life, they have shown remarkable abilities to effectively coordinate our behaviors. The problem is that, in many minds at least, their wider use would violate other key norms that we have inherited from cultural evolution.

Notice that cultural natural selection of individual behaviors seems insufficient to evolve better norms and status markers, as these are features of key game-theoretic equilibria, where individuals deviations are punished. We need instead to have collective deviations of entire cultures, i.e., units with much stronger internal than external conformity pressures.

Alas this process has been greatly hindered in the last few centuries by decreasing variety and selection pressures, and increasing rates of environmental change and internal cultural drift. Which is plausibly causing such norms to decay, plausibly leading to civ collapse and replacement in a century or two.