Imagine a distant planet full of eyeless animals. Evolving eyes is hard: they need to evolve Eye Part 1, then Eye Part 2, then Eye Part 3, in that order. Each of these requires a separate series of rare mutations.
Here on Earth, scientists believe each of these mutations must have had its own benefits – in the land of the blind, the man with only Eye Part 1 is king. But on this hypothetical alien planet, there is no such luck. You need all three Eye Parts or they’re useless. Worse, each Eye Part is metabolically costly; the animal needs to eat 1% more food per Eye Part it has. An animal with a full eye would be much more fit than anything else around, but an animal with only one or two Eye Parts will be at a small disadvantage.
So these animals will only evolve eyes in conditions of relatively weak evolutionary pressure. In a world of intense and perfect competition, where the fittest animal always survives to reproduce and the least fit always dies, the animal with Eye Part 1 will always die – it’s less fit than its fully-eyeless peers. The weaker the competition, and the more randomness dominates over survival-of-the-fittest, the more likely an animal with Eye Part 1 can survive and reproduce long enough to eventually produce a descendant with Eye Part 2, and so on.
There are lots of ways to decrease evolutionary pressure. Maybe natural disasters often decimate the population, dozens of generations are spent recolonizing empty land, and during this period there’s more than enough for everyone and nobody has to compete. Maybe there are frequent whalefalls, and any animal nearby has hit the evolutionary jackpot and will have thousands of descendants. Maybe the population is isolated in little islands and mountain valleys, and one gene or another can reach fixation in a population totally by chance. It doesn’t matter exactly how it happens, it matters that evolutionary pressure is low.
The branch of evolutionary science that deals with this kind of situation is called “adaptive fitness landscapes”. Landscapes really are a great metaphor – consider somewhere like this:
You pour out a bucket of water. Water “flows downhill”, so it’s tempting to say something like “water wants to be at the lowest point possible”. But that’s not quite right. The lowest point possible is the pit, and water won’t go there. It will just sit in the little puddle forever, because it would have to go up the tiny little hillock in order to get to the pit, and water can’t flow uphill. Using normal human logic, we feel tempted to say something like “Come on! The hillock is so tiny, and that pit is so deep, just make a single little exception to your ‘always flow downhill’ policy and you could do so much better for yourself!” But water stubbornly refuses to listen.
Under conditions of perfectly intense competition, evolution works the same way. We imagine a multidimensional evolutionary “landscape” where lower ground represents higher fitness. In this perfectly intense competition, organisms can go from lower to higher fitness, but never vice versa. As with water, the tiniest hillock will leave their potential forever unrealized.
Under more relaxed competition, evolution only tends probabilistically to flow downhill. Every so often, it will flow uphill; the smaller the hillock, the more likely evolution will surmount it. Given enough time, it’s guaranteed to reach the deepest pit and mostly stay there.
Take a moment to be properly amazed by this. It sounds like something out of the Tao Te Ching. An animal with eyes has very high evolutionary fitness. It will win at all its evolutionary competitions. So in order to produce the highest-fitness animal, we need to – select for fitness less hard? In order to produce an animal that wins competitions, we need to stop optimizing for winning competitions?
This doesn’t mean that less competition is always good. An evolutionary environment with no competition won’t evolve eyes either; a few individuals might randomly drift into having eyes, but they won’t catch on. In order to optimize the species as much as possible as fast as possible, you need the right balance, somewhere in the middle between total competition and total absence of competition.
In the esoteric teachings, total competition is called Moloch, and total absence of competition is called Slack. Slack (thanks to Zvi Mowshowitz for the term and concept) gets short shrift. If you think of it as “some people try to win competitions, other people don’t care about winning competitions and slack off and go to the beach”, you’re misunderstanding it. Think of slack as a paradox – the Taoist art of winning competitions by not trying too hard at them. Moloch and Slack are opposites and complements, like yin and yang. Neither is stronger than the other, but their interplay creates the ten thousand things.
Before we discuss slack further, a digression on group selection.
Some people would expect this discussion to be quick, since group selection doesn’t exist. These people understand it as evolution acting for the good of a species. It’s a tempting way to think, because evolution usually eventually makes species stronger and more fit, and sometimes we colloquially round that off to evolution targeting a species’ greater good. But inevitably we find evolution is awful and does absolutely nothing of the sort.
Imagine an alien planet that gets hit with a solar flare once an eon, killing all unshielded animals. Sometimes unshielded animals spontaneously mutate to shielded, and vice versa. Shielded animals are completely immune to solar flares, but have 1% higher metabolic costs. What happens? If you predicted “magnetic shielding reaches fixation and all animals get it”, you’ve fallen into the group selection trap. The unshielded animals outcompete the shielded ones during the long inter-flare period, driving their population down to zero (though a few new shielded ones arise every generation through spontaneous mutations). When the flare comes, only the few spontaneous mutants survive. They breed a new entirely-shielded population, until a few unshielded animals arise through spontaneous mutation. The unshielded outcompete the shielded ones again, and by the time of the next solar flare, the population is 100% unshielded again and they all die. If the animals are lucky, there will always be enough spontaneously-mutated shielded animals to create a post-flare breeding population; if they are unlucky, the flare will hit at a time with unusually few such mutants, and the species will go extinct.
An Evolution Czar concerned with the good of the species would just declare that all animals should be shielded and solve the problem. In the absence of such a Czar, these animals will just keep dying in solar-flare-induced mass extinctions forever, even though there is an easy solution with only 1% metabolic cost.
A less dramatic version of the same problem happens here on Earth. Every so often predators (let’s say foxes) reproduce too quickly and outstrip the available supply of prey (let’s say rabbits). There is a brief period of starvation as foxes can’t find any more rabbits and die en masse. This usually ends with a boom-bust cycle: after most foxes die, the rabbits (who reproduce very quickly and are now free of predation) have a population boom; now there are rabbits everywhere. Eventually the foxes catch up, eat all the new rabbits, and the cycle repeats again. It’s a waste of resources for foxkind to spend so much of time and its energy breeding a huge population of foxes that will inevitably collapse a generation later; an Evolution Czar concerned with the common good would have foxes limit their breeding at a sustainable level. But since individual foxes that breed excessively are more likely to have their genes represented in the next generation than foxes that breed at a sustainable level, we end up with foxes that breed excessively, and the cycle continues.
(but humans are too smart to fall for this one, right?)
Some scientists tried to create group selection under laboratory conditions. They divided some insects into subpopulations, then killed off any subpopulation whose numbers got too high, and “promoted” any subpopulation that kept its numbers low to better conditions. They hoped the insects would evolve to naturally limit their family size in order to keep their subpopulation alive. Instead, the insects became cannibals: they ate other insects’ children so they could have more of their own without the total population going up. In retrospect, this makes perfect sense; an insect with the behavioral program “have many children, and also kill other insects’ children” will have its genes better represented in the next generation than an insect with the program “have few children”.
But sometimes evolution appears to solve group selection problems. What about multicellular life? Stick some cells together in a resource-plentiful environment, and they’ll naturally do the evolutionary competition thing of eating resources as quickly as possible to churn out as many copies of themselves as possible. If you were expecting these cells to form a unitary organism where individual cells do things like become heart cells and just stay in place beating rhythmically, you would call the expected normal behavior “cancer” and be against it. Your opposition would be on firm group selectionist grounds: if any cell becomes cancer, it and its descendants will eventually overwhelm everything, and the organism (including all cells within it, including the cancer cells) will die. So for the good of the group, none of the cells should become cancerous.
The first step in evolution’s solution is giving all cells the same genome; this mostly eliminates the need to compete to give their genes to the next generation. But this solution isn’t perfect; cells can get mutations in the normal course of dividing and doing bodily functions. So it employs a host of other tricks: genetic programs telling cells to self-destruct if they get too cancer-adjacent, an immune system that hunts down and destroys cancer cells, or growing old and dying (this last one isn’t usually thought of as a “trick”, but it absolutely is: if you arrange for a cell line to lose a little information during each mitosis, so that it degrades to the point of gobbledygook after X divisions, this means cancer cells that divide constantly will die very quickly, but normal cells dividing on an approved schedules will last for decades).
Why can evolution “develop tricks” to prevent cancer, but not to prevent foxes from overbreeding, or aliens from losing their solar flare shields? Group selection works when the group itself has a shared genetic code (or other analogous ruleset) that can evolve. It doesn’t work if you expect it to directly change the genetic code of each individual to cooperate more.
When we think of cancer, we are at risk of conflating two genetic codes: the shared genetic code of the multicellular organism, and the genetic code of each cell within the organism. Usually (when there are no mutations in cell divisions) these are the same. Once individual cells within the organism start mutating, they become different. Evolution will select for cancer in changes to individual cells’ genomes over an organism’s lifetime, but select against it in changes to the overarching genome over the lifetime of the species (ie you should expect all the genes you inherited from your parents to be selected against cancer, and all the mutations in individual cells you’ve gotten since then to be selected for cancer).
The fox population has no equivalent of the overarching genome; there is no set of rules that govern the behavior of every fox. So foxes can’t undergo group selection to prevent overpopulation (there are some more complicated dynamics that might still be able to rescue the foxes in some situations, but they’re not relevant to the simple model we’re looking at).
In other words, group selection can happen in a two-layer hierarchy of nested evolutionary systems when the outer system (eg multicellular humans) includes rules that the inner system (eg human cells) have to follow, and where the fitness of the evolving-entities in the outer system depends on some characteristics of the evolving-entities in the inner system (eg humans are higher-fitness if their cells do not become cancerous). The evolution of the outer layer includes evolution over rulesets, and eventually evolves good strong rulesets that tell the inner-layer evolving entities how to behave, which can include group selection (eg humans evolve a genetic code that includes a rule “individual cells inside of me should not get cancer” and mechanisms for enforcing this rule).
You can find these kinds of two-layer evolutionary systems everywhere. For example, “cultural evolution” is a two-layer evolutionary system. In the hypothetical state of nature, there’s unrestricted competition – people steal from and murder each other, and only the strongest survive. After they form groups, the groups compete with each other, and groups that develop rulesets that prevent theft and murder (eg legal codes, religions, mores) tend to win those competitions. Once again, the outer layer (competition between cultures) evolves groups that successfully constrains the inner layer (competition between individuals). Species don’t have a czar who restrains internal competition in the interest of keeping the group strong, but some human cultures do (eg Russia).
Or what about market economics? The outer layer is companies, the inner layer is individuals. Maybe the individuals are workers – each worker would selfishly be best off if they spent the day watching YouTube videos and pushed the hard work onto someone else. Or maybe they’re executives – each individual executive would selfishly be best off if they spent their energy on office politics, trying to flatter and network with whoever was most likely to promote them. But if all the employees loaf off and all the executives focus on office politics, the company won’t make products, and competitors will eat their lunch. So someone – maybe the founder/CEO – comes up with a ruleset to incentivize good work, probably some kind of performance review system where people who do good work get promoted and people who do bad work get fired. The outer-layer competition between companies will select for corporations with the best rulesets; over time, companies’ internal politics should get better at promoting the kind of cooperation necessary to succeed.
How do these systems replicate multicellular life’s success without being literal entities with literal DNA having literal sex? They all involve a shared ruleset and a way of punishing rulebreakers which make it in each individual’s short-term interest to follow the ruleset that leads to long-term success. Countries can do that (follow the law or we’ll jail you), companies can do that (follow our policies or we’ll fire you), even multicellular life can sort of do that (don’t become cancer, or immune cells will kill you). When there’s nothing like that (like the overly-fast-breeding foxes) evolution fails at group selection problems. When there is something like that, it has a chance. When there’s something like that, and the thing like that is itself evolving (either because it’s encoded in literal DNA, or because it’s encoded in things like company policies that determine whether a company goes out of business or becomes a model for others), then it can reach a point where it solves group selection problems very effectively.
In the esoteric teachings, the inner layer of two-layer evolutionary systems is represented by the Goddess of Cancer, and outer layer by the Goddess of Everything Else. In each part of the poem, the Goddess of Cancer orders the evolving-entities to compete, but the Goddess of Everything Else recasts it as a two-layer competition where cooperation on the internal layer helps win the competition on the external layer. He who has ears to hear, let him listen.
Why the digression? Because slack is a group selection problem. A species that gave itself slack in its evolutionary competition would do better than one that didn’t – for example, the eyeless aliens would evolve eyes and get a big fitness boost. But no individual can unilaterally choose to compete less intensely; if it did, it would be outcompeted and die. So one-layer evolution will fail at this problem the same way it fails all group selection problems, but two-layer systems will have a chance to escape the trap.
The multicellular life example above is a special case where you want 100% coordination and 0% competition. I framed the other examples the same way – countries do best when their citizens avoid all competition and work together for the common good, companies do best when their executives avoid self-aggrandizing office politics and focus on product quality. But as we saw above, some systems do best somewhere in the middle, where there’s some competition but also some slack.
For example, consider a researcher facing their own version of the eyeless aliens’ dilemma. They can keep going with business as normal – publishing trendy but ultimately useless papers that nobody will remember in ten years. Or they can work on Research Program Part 1, which might lead to Research Program Part 2, which might lead to Research Program Part 3, which might lead to a ground-breaking insight. If their jobs are up for review every year, and a year from now the business-as-normal researcher will have five trendy papers, and the groundbreaking-insight researcher will be halfway through Research Program Part 1, then the business-as-normal researcher will outcompete the groundbreaking-insight researcher; as the saying goes, “publish or perish”. Without slack, no researcher can unilaterally escape the system; their best option will always be to continue business as usual.
But group selection makes the situation less hopeless. Universities have long time-horizons and good incentives; they want to get famous for producing excellent research. Universities have rulesets that bind their individual researchers, for example “after a while good researchers get tenure”. And since universities compete with each other, each is incentivized to come up with the ruleset that maximizes long-term researcher productivity. So if tenure really does work better than constant vicious competition, then (absent the usual culprits like resistance-to-change, weird signaling equilibria, politics, etc) we should expect universities to converge on a tenure system in order to produce the best work. In fact, we should expect universities to evolve a really impressive ruleset for optimizing researcher incentives, just as impressive as the clever mechanisms the human body uses to prevent cancer (since this seems a bit optimistic, I assume the usual culprits are not absent).
The same is true for grant-writing; naively you would want some competition to make sure that only the best grant proposals get funded, but too much competition seems to stifle original research, so much so that some funders are throwing out the whole process and selecting grants by lottery, and others are running grants you can apply for in a half-hour and hear back about two days later. If there’s a feedback mechanism – if these different rulesets produce different-quality research, and grant programs that produce higher-quality research are more likely to get funded in the future – then the rulesets for grants will gradually evolve, and the competition for grants will take place in an environment with whatever the right evolutionary parameters for evolving good research are.
I don’t want to say these things will definitely happen – you can read Inadequate Equilibria for an idea of why not. But they might. The evolutionary dynamics which would normally prevent them can be overcome. Two-layer evolutionary systems can produce their own slack, if having slack would be a good idea.
That was a lot of paragraphs, and a lot of them started with “imagine a hypothetical situation where…”. Let’s look deeper into cases where an understanding of slack can inform how we think about real-world phenomena. Seven examples:
1. Monopolies. Not the kind that survive off overregulation and patents, the kind that survive by being big enough to crush competitors. These are predators that exploit low-slack environments. If Boeing has a monopoly on building passenger planes, and is exploiting that by making shoddy products and overcharging consumers, then that means anyone else who built a giant airplane factory could make better products at a lower price, capture the whole airplane market, and become a zillionaire. Why don’t they? Slack. In terms of those adaptive fitness landscapes, in between your current position (average Joe) and a much better position at the bottom of a deep pit (you own a giant airplane factory and are a zillionaire), there’s a very big hill you have to climb – the part where you build Giant Airplane Factory Part 1, Giant Airplane Factory Part 2, etc. At each point in this hill, you are worse off than somebody who was not building an as-yet-unprofitable giant airplane factory. If you have infinite slack (maybe you are Jeff Bezos, have unlimited money, and will never go bankrupt no matter how much time and cost it takes before you start earning profits) you’re fine. If you have more limited slack, your slack will run out and you’ll be outcompeted before you make it to the greater-fitness deep pit.
Real monopolies are more complicated than this, because Boeing can shape up and cut prices when you’re halfway to building your giant airplane factory, thus removing your incentive. Or they can do actually shady stuff. But none of this would matter if you already had your giant airplane factory fully built and ready to go – at worst, you and Boeing would then be in a fair fight. Everything Boeing does to try to prevent you from building that factory is exploiting your slacklessness and trying to increase the height of that hill you have to climb before the really deep pit.
(Peter Thiel inverts the landscape metaphor and calls the hill a “moat”, but he’s getting at the same concept).
2. Tariffs. Same story. Here’s the way I understand the history of the international auto industry – anyone who knows more can correct me if I’m wrong. Automobiles were invented in the early 20th century. Several Western countries developed homegrown auto industries more or less simultaneously, with the most impressive being Henry Ford’s work on mass production in the US. Post-WWII Japan realized that its own auto industry would never be able to compete with more established Western companies, so it placed high tariffs on foreign cars, giving local companies like Nissan and Toyota a chance to get their act together. These companies, especially Toyota, invented a new form of auto production which was actually much more efficient than the usual American methods, and were eventually able to hold their own. They started exporting cars to the US; although American tariffs put them at a disadvantage, they were so much better than the American cars of the time that consumers preferred them anyway. After decades of losing out, the American companies adopted a more Japanese ethos, and were eventually able to compete on a level playing field again.
This is a story of things gone surprisingly right – Americans and Japanese alike were able to get excellent inexpensive cars. Two things had to happen for it to work. First, Japan had to have high enough tariffs to give their companies some slack – to let them develop their own homegrown methods from scratch without being immediately outcompeted by temporarily-superior American competitors. Second, America had to have low enough tariffs that eventually-superior Japanese companies could outcompete American automakers, and Japan’s fitness-improving innovations could spread.
From the perspective of a Toyota manager, this is analogous to the eyeless alien story. You start with some good-enough standard (blind animals, American car companies). You want to evolve a superior end product (eye-having animals, Toyota). The intermediate steps (an animal with only Eye Part 1, a kind of crappy car company that stumbles over itself trying out new things) are less fit than the good-enough standard. Only when the inferior intermediate steps are protected from competition (through evolutionary randomness, through tariffs) can the superior end product come into existence. But you want to keep enough competition that the superior end product can use its superiority to spread (there is enough evolutionary competition that having eyes reaches fixation, there is enough free trade that Americans preferentially buy Toyota and US car companies have to adopt its policies).
From the perspective of an economic historian, maybe it’s a group selection story. The various stakeholders in the US auto industry – Ford, GM, suppliers, the government, labor, customers – competed with each other in a certain way and struck some compromise. The various stakeholders in the Japanese auto industry did the same. For some reason the American compromise worked worse than the Japanese one – I’ve heard stories about how US companies were more willing to defraud consumers for short-term profit, how US labor unions were more willing to demand concessions even at the cost of company efficiency, how regulators and executives were in bed with each other to the detriment of the product, etc. Every US interest group was acting in its own short-term self-interest, but the Japanese industry-as-a-whole outcompeted the American one and the Americans had to adjust.
3. Monopolies, Part II. Traditionally, monopolies have been among the most successful R&D centers. The most famous example is Xerox; it had a monopoly on photocopiers for a few decades before losing an anti-trust suit in the late 1970s; during that period, its PARC R&D program invented “laser printing, Ethernet, the modern personal computer, graphical user interface (GUI) and desktop paradigm, object-oriented programming, [and] the mouse”. The second most famous example is Bell Labs, which invented “radio astronomy, the transistor, the laser, the photovoltaic cell, the charge-coupled device, information theory, the Unix operating system, and the programming languages B, C, C++, and S” before the government broke up its parent company AT&T. Google seems to be trying something similar, though it’s too soon to judge their outcomes.
These successes make sense. Research and development is a long-term gamble. Devoting more money to R&D decreases your near-term profits, but (hopefully) increases your future profits. Freed from competition, monopolies have limitless slack, and can afford to invest in projects that won’t pay off for ten or twenty years. This is part of Peter Thiel’s defense of monopolies in Zero To One.
An administrator tasked with advancing technology might be tempted to encourage monopolies in order to get more research done. But monopolies can also be stagnant and resistant to change; it’s probably not a coincidence that Xerox wasn’t the first company to bring the personal computer to market, and ended up irrelevant to the computing revolution. Like the eyeless aliens, who will not evolve in conditions of perfect competition or perfect lack of competition, probably all you can do here is strike a balance. Some Communist countries tried the extreme solution – one state-supported monopoly per industry – and it failed the test of group selection. I don’t know enough to have an opinion on whether countries with strong antitrust eventually outcompete those with weaker antitrust or vice versa.
4. Strategy Games. I like the strategy game Civilization, where you play as a group of primitives setting out to found a empire. You build cities and infrastructure, research technologies, and fight wars. Your world is filled with several (usually 2 to 7) other civilizations trying to do the same.
Just like in the real world, civilizations must decide between Guns and Butter. The Civ version of Guns is called the Axe Rush. You immediately devote all your research to discovering how to make really good axes, all your industry to manufacturing those axes, and all your population into wielding those axes. Then you go and hack everyone else to pieces while they’re still futzing about trying to invent pottery or something.
The Civ version of Butter is called Build. You devote all your research, industry, and populace to laying the foundations of a balanced economy and culture. You invent pottery and weaving and stuff like that. Soon you have a thriving trade network and a strong philosophical tradition. Eventually you can field larger and more advanced armies than your neighbors, and leverage the advantage into even more prosperity, or into military conquest.
Consider a very simple scenario: a map of Eurasia with two civilizations, Rome and China.
If both choose Axe Rush, then whoever Axe Rushes better wins.
If both choose Build, then whoever Builds better wins.
What if Rome chooses Axe Rush, and China chooses Build?
Then it depends on their distance! If it’s a very small map and they start very close together, Rome will probably overwhelm the Chinese before Build starts paying off. But if it’s a very big map, by the time Roman Axemen trek all the way to China, China will have Built high walls, discovered longbows and other defensive technologies, and generally become too strong for axes to defeat. Then they can crush the Romans – who are still just axe-wielding primitives – at their leisure.
Consider a more complicated scenario. You have a map of Earth. The Old World contains Rome and China. The New World contains Aztecs. Rome and China are very close to each other. Now what happens?
Rome and China spend the Stone, Bronze, and Iron Ages hacking each other to bits. Aztecs spend those Ages building cities, researching technologies, and building unique Wonders of the World that provide powerful bonuses. In 1492, they discover Galleons and start crossing the ocean. The powerful and advanced Aztec empire crushes the exhausted axe-wielding Romans and Chinese.
This is another story about slack. The Aztecs had it – they were under no competitive pressure to do things that paid off next turn. The Romans and Chinese didn’t – they had to be at the top of their game every single turn, or their neighbor would conquer them. If there was an option that made you 10% weaker next turn in exchange for making you 100% stronger ten turns down the line, the Aztecs could take it without a second thought; the Romans and Chinese would probably have to pass.
Okay, more complicated Civilization scenario. This time there are two Old World civs, Rome and China, and two New World civs, Aztecs and Inca. The map is stretched a little bit so that all four civilizations have the same amount of natural territory. All four players understand the map layout and can communicate with each other. What happens?
Now it’s a group selection problem. A skillful Rome player will private message the China player and explain all of this to her. She’ll remind him that if one hemisphere spends the whole Stone Age fighting, and the other spends it building, the builders will win. She might tell him that she knows the Aztec and Inca players, they’re smart, and they’re going to be discussing the same considerations. So it would benefit both Rome and China to sign a peace treaty dividing the Old World in two, stick to their own side, and Build. If both sides cooperate, they’ll both Build strong empires capable of matching the New World players. If one side cooperates and the other defects, it will easily steamroll over its unprepared opponent and conquer the whole Old World. If both sides defect, they’ll hack each other to death with axes and be easy prey for the New Worlders.
This might be true in Civilization games, but real-world civilizations are more complicated. Orson Welles said:
In Italy, for thirty years under the Borgias, they had warfare, terror, murder and bloodshed, but they produced Michelangelo, Leonardo da Vinci and the Renaissance. In Switzerland, they had brotherly love, they had five hundred years of democracy and peace – and what did that produce? The cuckoo clock.
So maybe a little bit of internal conflict is good, to keep you honest. Too much conflict, and you tear yourselves apart and are easy prey for outsiders. Too little conflict, and you invent the cuckoo clock and nothing else. The continent that conquers the world will have enough pressure that its people want to innovate, and enough slack that they’re able to.
This is total ungrounded amateur historical speculation, but when I hear that I think of the Classical world. We can imagine it as divided into a certain number of “theaters of civilization” – Greece, Mesopotamia, Egypt, Persia, India, Scythia, etc. Each theater had its own rules governing average state size, the rules of engagement between states, how often bigger states conquered smaller states, how often ideas spread between states of the same size, etc. Some of those theaters were intensely competitive: Egypt was a nice straight line, very suited to centralized rule. Others had more slack: it was really hard to take over all of Greece; even the Spartans didn’t manage. Each theater conducted its own “evolution” in its own way – Egypt was ruled by a single Pharaoh without much competition, Scythia was constant warfare of all against all, Greece was isolated city-states that fought each other sometimes but also had enough slack to develop philosophy and science. Each of those systems did their own thing for a while, until finally one of them produced something perfect: 4th century BC Macedonia. Then it went out and conquered everything.
If Welles is right, the point isn’t to find the ruleset that promotes 100% cooperation. It’s to find the ruleset that promotes an evolutionary system that makes your group the strongest. Usually this involves some amount of competition – in order to select for stronger organisms – but also some amount of slack – to let organisms develop complicated strategies that can make them stronger. Despite the earlier description, this isn’t necessarily a slider between 0% competition and 100% competition. It could be much more complicated – maybe alternating high-slack vs. low-slack periods, or many semi-isolated populations with a small chance of interaction each generation, or alternation between periods of isolation and periods of churning.
In a full two-layer evolution, you would let the systems evolve until they reached the best parameters. Here we can’t do that – Greece has however many mountains it has; its success does not cause the rest of the world to grow more mountains. Still, we randomly started with enough different groups that we got to learn something interesting.
(I can’t emphasize enough how ungrounded this historical speculation is. Please don’t try to evolve Alexander the Great in your basement and then get angry at me when it doesn’t work)
5. The Long-Term Stock Exchange. Actually, all stock exchanges are about slack. Imagine you are a brilliant inventor who, given $10 million and ten years, could invent fusion power. But in fact you have $10 and need work tomorrow or you will starve. Given those constraints, maybe you could start, I don’t know, a lemonade stand.
You’re in the same position as the animal trying to evolve an eye – you could create something very high-utility, if only you had enough slack to make it happen. But by default, the inventor working on fusion power starves to death tomorrow (or at least makes less money than his counterpart who ran the lemonade stand), the same way the animal who evolves Eye Part 1 gets outcompeted by other animals who didn’t and dies out.
You need slack. In the evolution example, animals usually stumble across slack randomly. You too might stumble across slack randomly – maybe it so happens that you are independently wealthy, or won the lottery, or something.
More likely, you use the investment system. You ask rich people to give you $10 million for ten years so you can invent fusion; once you do, you’ll make trillions of dollars and share some of it with them.
This is a great system. There’s no evolutionary equivalent. An animal can’t pitch Darwin on its three-step plan to evolve eyes and get free food and mating opportunities to make it happen. Wall Street is a giant multi-trillion dollar time machine funneling future profits back into the past, and that gives people the slack they need to make the future profits happen at all.
But the Long-Term Stock Exchange is especially about slack. They are a new exchange (approved by the SEC last year) which has complicated rules about who can list with them. Investors will get extra clout by agreeing to hold stocks for a long time; executives will get incentivized to do well in the far future instead of at the next quarterly earnings report. It’s making a deliberate choice to give companies more slack than the regular system and see what they do with it. I don’t know enough about investing to have an opinion, except that I appreciate the experiment. Presumably its companies will do better/worse than companies on the regular stock exchange, that will cause companies to flock toward/away from it, and we’ll learn that its new ruleset is better/worse at evolving good companies through competition than the regular stock exchange’s ruleset.
6. That Time Ayn Rand Destroyed Sears. Or at least that’s how Michael Rozworski and Leigh Phillips describe Eddie Lampert’s corporate reorganization in How Ayn Rand Destroyed Sears, which I recommend. Lampert was a Sears CEO who figured – since free-market competitive economies outcompete top-down economies, shouldn’t free-market competitive companies outcompete top-down companies? He reorganized Sears as a set of competing departments that traded with each other on normal free-market principles; if the Product Department wanted its products marketed, it would have to pay the Marketing Department. This worked really badly, and was one of the main contributors to Sears’ implosion.
I don’t have a great understanding of exactly why Lampert’s Sears lost to other companies even though capitalist economies beat socialist ones; Rozworski and Phillips’ People’s Republic Of Wal-Mart, which looks into this question, is somewhere on my reading list. But even without complete understanding, we can use group selection to evolve the right parameters. Imagine an economy with several businesses. One is a straw-man communist collective, where every worker gets paid the same regardless of output and there are no promotions (0% competition, 100% cooperation). Another is Lampert’s Sears (100% competition, 0% cooperation). Others are normal businesses, where employees mostly work together for the good of the company but also compete for promotions (X% competition, Y% cooperation). Presumably the normal business outcompetes both Lampert and the commies, and we sigh with relief and continue having normal businesses. And if some of the normal businesses outcompete others, we’ve learned something about the best values of X and Y.
7. Ideas. These are in constant evolutionary competition – this is the insight behind memetics. The memetic equivalent of slack is inferential range, aka “willingness to entertain and explore ideas before deciding that they are wrong”.
Inferential distance is the number of steps it takes to make someone understand and accept a certain idea. Sometimes inferential distances can be very far apart. Imagine trying to convince a 12th century monk that there was no historical Exodus from Egypt. You’re in the middle of going over archaeological evidence when he objects that the Bible says there was. You respond that the Bible is false and there’s no God. He says that doesn’t make sense, how would life have originated? You say it evolved from single-celled organisms. He asks how evolution, which seems to be a change in animals’ accidents, could ever affect their essences and change them into an entirely new species. You say that the whole scholastic worldview is wrong, there’s no such thing as accidents and essences, it’s just atoms and empty space. He asks how you ground morality if not in a striving to approximate the ideal embodied by your essence, you say…well, it doesn’t matter what you say, because you were trying to convince him that some very specific people didn’t leave Egypt one time, and now you’ve got to ground morality.
Another way of thinking about this is that there are two self-consistent equilibria. There’s your equilibrium, (no Exodus, atheism, evolution, atomism, moral nonrealism), and the monk’s equilibrium (yes Exodus, theism, creationism, scholasticism, teleology), and before you can make the monk budge on any of those points, you have to convince him of all of them.
So the question becomes – how much patience does this monk have? If you tell him there’s no God, does he say “I look forward to the several years of careful study of your scientific and philosophical theories that it will take for that statement not to seem obviously wrong and contradicted by every other feature of the world”? Or does he say “KILL THE UNBELIEVER”? This is inferential range.
Aristotle supposedly said that the mark of an educated man is to be able to entertain an idea without accepting it. Inferential range explains why. The monk certainly shouldn’t immediately accept your claim, when he has countless pieces of evidence for the existence of God, from the spectacular faith healings he has witnessed (“look, there’s this thing called psychosomatic illness, and it’s really susceptible to this other thing called the placebo effect…”) to Constantine’s victory at the Mulvian Bridge despite being heavily outnumbered (“look, I’m not a classical scholar, but some people are just really good generals and get lucky, and sometimes it happens the day after they have weird dreams, I think there’s enough good evidence the other way that this is not the sort of thing you should center your worldview around”). But if he’s willing to entertain your claim long enough to hear your arguments one by one, eventually he can reach the same self-consistent equilibrium you’re at and judge for himself.
Nowadays we don’t burn people at the stake. But we do make fun of them, or flame them, or block them, or wander off, or otherwise not listen with an open mind to ideas that strike us at first as stupid. This is another case where we have to balance competition vs. slack. With perfect competition, the monk instantly rejects our “no Exodus” idea as less true (less memetically fit) than its competitors, and it has no chance to grow on him. With zero competition, the monk doesn’t believe anything at all, or spends hours patiently listening to someone explain their world-is-flat theory. Good epistemics require a balance between being willing to choose better ideas over worse ones, and open-mindedly hearing the worse ones out in case they grow on you.
(Thomas Kuhn points out that early versions of the heliocentric model were much worse than the geocentric model, that astronomers only kept working on them out of a sort of weird curiosity, and that it took decades before they could clearly hold their own against geocentrism in a debate).
Different people strike a different balance in this space, and those different people succeed or fail based on their own epistemic ruleset. Someone who’s completely closed-minded and dogmatic probably won’t succeed in business, or science, or the military, or any other career (except maybe politics). But someone who’s so pathologically open-minded that they listen to everything and refuse to prioritize what is or isn’t worth their time will also fail. We take notice of who succeeds or fails and change our behavior accordingly.
Maybe there’s even a third layer of selection; maybe different communities are more or less willing to tolerate open-minded vs. close-minded people. The Slate Star Codex community has really different epistemic norms from the Catholic Church or Infowars listeners; these are evolutionary parameters that determine which ideas are more memetically fit. If our epistemics make us more likely to converge on useful (not necessarily true!) ideas, we will succeed and our epistemic norms will catch on. Francis Bacon was just some guy with really good epistemic norms, and now everybody who wants to be taken seriously has to use his norms instead of whatever they were doing before. Come up with the right evolutionary parameters, and that could be you!
Last part of “4. Strategy Games” seems related to the end of Guns, Germs, Steel (see last paragraph of Synopsis -> Outline of Theory). https://en.m.wikipedia.org/wiki/Guns,_Germs,_and_Steel I think Jared Diamond’s argument there is that less slack due to geography-induced competition led to critical bad policy decisions being limited in duration, among other things
Yeah, I thought of that too.
Slack: Getting Past Burnout, Busywork, and the Myth of Total Efficiency
As I recall, this is more about how much competition a company is expecting rather than the actual level of competion, but it’s about the fear of competition getting so extreme that people in the company don’t have time to think about their decisions or provide quality products.
The first example is a bit unsatisfying, since an actual eye is far too complicated to evolve by chance, even if you have all the evolutionary slack in the world. Still, the insight that slack lets you get out of a local minima is a good one. In physics, temperature plays the same role, allowing systems escape to lower energy minima.
An important ingredient many of the other examples seems to be good intentions. We can imagine a completely selfish scientific researcher. With no slack, they will be forced to churn out trendy paper after trendy paper in order to keep their jobs. If they have a lot of slack, perhaps bulletproof tenure with no chance of being fired, they will spend their time playing video-games. If the amount of slack is intermediate, they will churn out enough trendy papers to keep their jobs, and spend the remaining time playing video-games. The only time that groundbreaking research is a possibility is when we have a scientist who is intrinsically motivated to produce good science. That is when adding more slack starts to produce better outcomes. Similarly, while an enlightened monopolist might choose to invest in R&D, other monopolists will instead choose to pay themselves a hefty bonus and buy a yacht. The correct amount to slack to have depends on how enlightened your monopolists tend to be. It seems like slack is playing a very different role here than in the evolutionary case, where it is channeled into pure randomness.
Which kind of eye ? I was under the impression that the evolution of vision was fairly well understood, but there are many different kinds of eyes out there, so I could be wrong. But, as Scott says, the actual eye is still a poor example, because each step of its evolution does confer an advantage — unlike the steps required to build the (hypothetical) giant airplane factory. So, real eyes require very little slack compared to airplane factories.
I assume the three “eye parts” are more something like “photoreceptive chemical” and “two expression sites on two sides of the organism” and “differential behavior to turn towards the light”. I’d guess IRL this was bypassed by having a preexisting turn-towards-chemical-that-indicates-food behavior. Maybe they use a different food-seeking mechanism that can’t be reused like that.
But of course the actual eye did evolve by chance, if we mean a series of random mutations that eventually led to what we’ve got. Our eyes are different than the eyes of a housefly or a squid, and no entity intentionally designed any of them.
Scott’s example is satisfying, because he’s asking us to imagine that instead of the intermediate steps conferring a small benefit (as they did on Earth, which is why they stuck around long enough to step by step become what we’ve got), they would only be a burden.
The notion that evolution works by pure chance is a common misconception. Selection for various traits is a vitally important ingredient. Take that away, as Scott does, and you won’t end up with an eye. Maybe if evolving an eye only required 3 single-letter mutations, you could get there by chance, even if the first two were deleterious, but in real life the required number of mutations is much larger.
Wait, what distinction are you making here? Scott doesn’t ignore selection — hence “Here on Earth, scientists believe each of these mutations must have had its own benefits”.
I think I get your point: eyes are too complex to evolve without incremental fitness benefits; if you assume they are only useful when complete, then the odds are prohibitively against evolution ever discovering them, slack notwithstanding. (The ‘common misconception’ bit threw me, as I don’t think Seth or Scott are making that mistake.)
The eye example is just a simplified metaphor, though. To make it more realistic, you could increase the resolution: let’s say that milestones 1-1000 on the road to an eye are individually fitness-increasing, but each milestone requires multiple (though not an impossibly large number of) mutations that are individually useless. Now slack has a plausible role to play.
sethgodin makes it sound like the road to an eye is just as likely as any other road. While chance played a role, it was not the sole driver.
There are real-world examples of such hillocks which evolution cannot overcome. Staying with the eye example: Evolution will never fix our retina which is sitting the wrong way: The nerve ends don’t come out at the back, towards the brain, but in the front, and we need the blind spot of Mariotte to let them pass through. Squids don’t have this problem (which by the way indicates that their eye seems to have evolved independently). Evolution is unable to turn the whole retina around!
Another example: Evolution has never invented the wheel. There are tumbleweeds or some rolling bugs and caterpillars, but no wheels turning around an axis. This is a concept which is hard to invent by evolution. Of course the concept of irreducible complexity is unscientific, because it is an argument ex post: If there were wheeled animals, we wouldn’t assume that they are impossible.
The problem with this example is that wheels are actually not very adaptive. Even in today’s world with many pre-existing man-made roads there aren’t many organisms you would purposefully design with wheels instead of legs. Think about how annoying it is to get around in a wheelchair and now imagine you need the chair to catch prey, flee from predators, or navigate a plant-rich environment.
It’s also not at all clear that evolution would be incapable of producing a wheel if there were appropriate selection pressure. The Flagellum is remarkably similar to an actual rotor and that has been produced by evolution.
This is such absolute and total horseshit you should be ashamed to have even thought it, much less posted it on a public forum.
The evolution of vision is extremely well documented, numerous cases of EXTANT intermediate forms exist, the developmental biology is far simpler than you know (which is obvious, since you clearly know zero biology), and every step does, in fact, produce an advantage.
Photoreceptive pigments are extremely common throughout life, even in bacteria, mediating biased random walk patterns to avoid or stay in light. Distributed photoreceptors give gradients, making motion more efficient. Concentrated patches allow extremely rudimentary image formation (though some species with whole-body photoreception can still form images, like some echinoderms). Making the patch concave improves focus, until you eventually get a pinhole camera (a widespread form in many worms, and convergently evolved in the “second eyes” of vipers, i.e. their heat pits). A supporting body of fluid in the core can, with easy modification, become a lens, and bingo, the eye, simple and easy. The fact that eyes seem to have evolved multiple times independently shortly after the origin of multicellular life is proof enough that, far from impossible, it’s quite easy to evolve an eye – it’s evolved more times than powered flight, after all.
I’m not positive, but I’m pretty sure that phi is not disputing this.
This is the key point. I believe in phi’s statement that “an actual eye is far too complicated to evolve by chance,” the emphasis is not on “evolve”, but on “by chance.” An eye could evolve by natural selection, just not by chance alone, as in Scott’s example. Because the eye has many intermediate stages, not just three, it couldn’t evolve without each of those stages conferring some advantage of their own; getting all of them at once just by chance would be unlikely enough that it would never happen. Because each state does, in the real world, confer some advantage, the eye can, of course, evolve in the real world; it’s just that it makes Scott’s example a bit forced, because in his example he postulates that the stages don’t confer any advantage until you have all of them. At least, that’s how I read phi’s comment.
“Evolution” does NOT mean “spontaneous occurrence of mutations”. It means “change in allele frequency in a population over time”. Either your interpretation is wrong and phi’s statement is as stupid as I think, or phi mis-used the word so badly it’s like calling a train a boat.
Less of this, please.
I think a careful reading and ten seconds of thought about phi’s comment will reveal that they aren’t actually trying to argue that IRL eyes were created by divine intervention, as you seem to thing they’re saying. The point phi’s trying to make is that, if each individual part of an eye did not confer an advantage (i.e. in Scott’s hypothetical alien species), then complex eyes would not evolve even on evolutionary timescales due to their improbability.
And even if they were advocating creationism, saying “you should be ashamed to have even thought it” is…at odds with the culture we try to foster here. “I’m astounded you actually believe that, could you explain why?” tends to lead to more interesting discussions.
I don’t think you need any mystical concept of “intrinsically motivated to produce good science”. All you need is the idea that a certain number of trendy papers can keep your job, while a slightly larger number gets you a bit of a promotion, and an individual revolutionary paper gets you nothing, while a revolutionary paper that gets followed up by a bunch of trendy papers on its trend gets you a named research chair at Caltech. If you tune the “you’re fired” parameter too close to the margins, then everyone does just trendy papers. If you tune it too low, then everyone does just a few trendy papers and then spends all the rest of the day attempting their solitary revolutionary things, and no one gets the boost of other people’s trendy papers. If you tune it just right though, then everyone attempts a few revolutionary papers and then does enough trendy papers that some people are able to strike the jackpot.
Companies don’t evolve, though. If they did, they probably wouldn’t be so commonly dysfunctional as they are…
I don’t find this a very interesting disagreement. Corporations clearly do something evolution-like, but it clearly isn’t exactly the same as biological evolution. Whether or not you call that “evolution” is a stylistic choice, and I think mine is appropriate here, especially since everyone now seems to agree that saying “cultural evolution” is okay.
This is a great post, Scott, worth the effort you put into it. Twenty years ago, I spent a year of my life writing an entire book on the topic, which is my least successful: https://www.amazon.com/Survival-Not-Enough-Shift-Happens/dp/0743221230
People have a hard time understanding the massive time scale associated with biological evolution and their eyes glaze over (I’ve seen it from the stage, almost every time) when it’s talked about.
I think that memetics, red queens, sexual selection and the rest are fascinating and accurate metaphors for so much of what builds our culture. Thanks for highlighting it here.
I don’t think that’s so clear at all. As Eliezer points out, the entire descent part is missing. Companies’ descendants don’t really manage to replicate their parents, because so much of what makes a company tick is really hard to transmit! So, it isn’t transmitted. And, of course, “more successful” for a company means more money, not more descendants.
On the other side of things, of course, companies do, like, try to optimize themselves, which is also quite un-evolution-like.
I think the resemblance to evolution is wholly superficial. It just really isn’t evolution. There’s some optimization going on, and some competition, but those are basically the only two aspects that match. Evolution’s whole mechanism for gradual improvement is gone.
And like — I think this is why large companies are still so crap. If corporate evolution were a real thing, I don’t think this would be such a consistent problem. But instead we have to rely on the more legible sorts of optimization, which normally I like but in this case don’t seem to do very well, because people don’t really know how to write down or transmit a corporate culture, including mechanisms to prevent a company from falling into mazedom that won’t themselves be perverted by the suits to drive the system to mazedom more quickly.
Cultural evolution obviously isn’t the same as biological evolution either, but I think of “cultural evolution” as more of just a phrase describing how cultures change rather than by a claim that the mechanism is actually similar. Cultures do seem better at replicating themselves into their descendant cultures than companies do (because cultures don’t discretely fission like that). But cultural evolution as a parallel to biological evolution? Yeah, that doesn’t happen. Once again, you have competition, and this time you have something more like descent with modification, but the other aspects are still missing (again, more success doesn’t mean more descendants).
But it isn’t. New corporations are not generally formed by fresh-out college graduates (or dropouts), but by people who have worked for existing corporations. They take the best practices of the firms they have worked for and duplicate them in the new companies they found.
And for that matter, existing companies often attempt to duplicate the best practices of their own competitors, or of firms in related but not directly competing industries, when they feel that their own practices are lacking in some respect. So you get Darwinian evolution, Lamarckian evolution, and Intelligent Design all working in parallel.
Sounds more like a memetic evolution of business practices, rather than of companies.
A somewhat analogous claim would be saying that organisms don’t evolve, genes do.
Corporations do horizontal gene transfer.
But the selection pressure is not measured simply in profits. Sure, that’s important, but humans are very picky and diverse group, and they can keep many kinds of corporations alive. From Amazon to Patagonia, from the sweatshops of Bangadlesh and the semi-robotized paramilitary Foxconn campuses to the super-exclusive Koenigsegg automotive of Sweden.
But even if we just look at Samsung, Apple and Google, they all have phone brands, they all have phone serious phone software and hardware development departments, they all have a lot of other businesses that make them money, yet basically all are completely different. (Samsung is missing from FAANG, because it’s not US based, Apple is not though of as an Internet business but more as a device maker, Samsung is not a pure tech business, because it’s more like Korea’s engineering department that fall in love with rounded corners.)
Just as human minds are incredibly diverse corporations are too, that doesn’t mean there is no evolution, just means that the causal pathways are long and chaotic.
(Reproduction, heredity, variation in fitness, variation of traits are the required phenomena. We obviously have variation in both categories, and we can say that we have heredity too, but this doesn’t require the corporation to die and reproduce, it’s enough if it changes, incorporates new ideas, or the board replaces the CEO, or the board approves a new approach to doing business; and we have reproduction too, successful corporations grow and copycats emerge inevitably, and they even usually enter into new market segments, acquire competitors, merge with them, and now we have more of the same. That’s reproduction even if it does business as one big entity.)
I regret not expanding upon it at the time, but this is the exact point (and link, even) that I was alluding to at the end of my comment on BR:SooS.
The difference is critical, maybe enough to undermine the entire thesis. As the engineer’s saying goes, a difference in magnitude is a difference in kind – these different selectors may all be called “evolution”, but I’m counting five or six orders of magnitude between the timescales at a minimum.
DownUpthread John comments that “you get Darwinian evolution, Lamarckian evolution, and Intelligent Design all working in parallel” and I agree, but if you’re intuiting how selection pressures produce adaptation then those three do not belong in the same bucket.
I really don’t get what that article is on about. Even if you take the worst case assumption that corporate culture is utterly inflexible after creation (which is really isn’t, companies reinvent themselves all the time) there’s still room for evolution in the corporate world. No one is going to copy Juicero’s business model but everyone is copying Uber’s. That is evolution and heritability, even if the genes in question are business memes.
What? The article isn’t talking about how corporate cultures don’t change. It’s talking about how corporate cultures don’t replicate themselves. There’s change, sure, but the optimization process of the successful ones replicating themselves doesn’t happen; at most, other companies try to imitate the successful ones — but the problem is, so much of what makes a company successful is hard to transmit.
I mean… humans don’t replicate themselves and we still evolve. I’m not really following this analogy. Sure corporations don’t obey strict Mendelian principals but neither does 99% of the natural world.
The eye evolution is actually an equivalent of simulated annealing.
Yeah, I kept expecting that to come up given that Scott lives in the very-ML-literate Bay Area.
Yeah, also expected that to be mentioned.
Or, indeed, actual annealing.
Feels like another great place to insert the complete stance. We can slice the cake and come up with many 2 dimensional slices that imply a tradeoff between several competing tensions, some cleaner than others. One question is, why isn’t this stance obvious? Why do thousands of pages need to be written about it with only some people getting it even then? When we ask what is the ideal balance point and get back an answer of ‘it depends’ why does it bother us so much? Because the payoff for finding an actual invariant is so damn high. If you do manage to find metastability you get compression and modularity, which then lets you abstract away that particular tradeoff and build much more complicated things. Things like commodity futures markets that prevent drastic swings of over and undersupply of agriculture in your civilization because farmers now get pricing signals. Things like being able to manufacture complex goods with long supply chains. You have probably heard that premature optimization is the root of all evil. Abstraction is a form of optimization. Premature abstraction seems to be how we make progress, despite there being a hundred false alarms for every fire, because if it’s a false alarm you just go back to work, but if it’s a fire it spreads. Occasionally we abstract away human suffering and get monstrous results. Increasingly suggestive hints from biology that cancer happens not because cells get ‘old’ but because intercellular signaling breaks down, undermining the cooperate-cooperate equilibrium. Making our suffering legible to one another can also get coopeted by moloch, but the payoff if we succeed in extracting invariants would be so damn high.
Slight correction: the cuckoo clock speech wasn’t written by Greene (though it really isn’t out of voice for him at all), but rather added by Orson Welles during shooting when they found they needed another sentence for timing. One of the all-time great films.
And of course, the longer speech it’s part of is one of the most evil speeches in all fiction.
– Have you ever seen any of your victims?
– Do you know, I don’t ever feel comfortable on these sort of things… Victims?
(He opens the door of the Ferris wheel carriage.)
Don’t be melodramatic. Look down there… would you feel any pity if one of those dots stopped moving forever? If I offered you £20,000 for every dot that stopped – would you really, old man, tell me to keep my money? Or would you calculate how many dots you could afford to spare? Free of income tax, old man, free of income tax. It’s the only way to save money nowadays.
I think that it’s a bit inaccurate to refer to dialogue that someone writes for one of their characters as something they “said”. Just because you have one of your characters say something, doesn’t mean you’re endorsing it.
About Switzerland producing only a Cuckoo clock… Switzerland has the most Nobel prizes per capita among decent-sized countries. Einstein lived and worked in Switzerland when he wrote his most famous works.
Also Cuckoo clocks were invented in Bavaria.
The Swiss also used to be Europe’s most in-demand soldiers during the early modern period. And they didn’t have only brotherly love for each other.
Cuckoo clocks stereotypically are produced in Schwarzwald. Which sounds sort of similar to Switzerland, and that’s probably the cause of this mistake.
You can’t look at modern state boundaries when you’re talking about these things. They’re more a reflection of Napoleonic and Bismarkian machinations than actual culture or history.
Augsburg, germanophone Swizerland and the Schwarzwald were all part of the stem dutchy of Schwabia, centred on the Bodensee, under the early HRE. This area was mostly inhabited by the Alemanni/Suebi, who broke through the Limes in late antiquity.
So Augsburgers are culturally (and linguistically) closer to the Swiss Germans, Baden-Württembergers and Alsatian Germans than Bavarians.
Even today, Schwabia is an important region for engineering. It’s the home of Mercedes-Benz/Daimler, Porsche and Bosch.
Also, five hundred years of democracy, peace and brotherly love has got to be worth something by itself.
Prior to salt iodization Switzerland had a cretinism problem.
This concept is why I am usually always in favor of people trying new things and experimenting – no matter how good I think the actual idea is. Uniformity scares me more than anything.
Freeman Dyson has this really interesting bit in one of his books where he says that research of space programs and nuclear programs stalled completely because they were solely government controlled and the government cannot afford to take risks and lose face on “big important things” – it has no slack. The private sector is much better suited for research in a novel field where lots of things need to be tried before we have a good idea of what works.
That’s interesting, because I would have assumed the government has more slack since it can just get into debt endlessly and doesn’t need to be profitable. The government can “lose face” for decades on end but keep doing the same thing anyway. On the other hand, corporations that get bailed out by the government don’t necessarily have to be profitable either. There are a lot of just-so type arguments we could make here.
I think slack creates the opportunity for big important things and big stupid things, everything from impressive marvels of infrastructure, to complete boondoggles that cost billions upon billions but fail to work properly. Slack creates the opportunity for smart people to not have to worry about the shorter time horizon of surviving, but simultaneously you have to wonder about the competence of someone who hasn’t ever faced constraints. Maybe this means that the government should be the slack component and use the endless money bag for long timeframe projects, but it should hire those tested by the constraints of profitability.
On the other other other hand, I do recall something posted here on SSC about how mixed public-private partnerships are actually bad since they corrupt motives. It concerns me that on this topic we could just other hand all day, and there’s no natural isolated experiment to appeal to. All the evidence says we need some compromise between the two factors, but there’s absolutely no telling what that compromise looks like. It seems kind of hopeless.
The government has less financial pressure, but requires more acceptance. Politicians want to be re-elected, just like CEOs want to keep their jobs, but the requirements to keep their job are different.
Even financially, the pressures are different, because people get upset over how the government is spending our money, while people care way less about how companies are spending their money. So the government loses face when they mess up an IT project and waste money, but companies can mess up whatever they want as long as their prices stay reasonable, although they do lose face when they mess around with our data.
So I would say that you are both right, the government both has more and less slack, depending on what slack you look at. Slack is not something you have more or less of, but is is something that you have more or less of in a certain dimension.
You can compare it to a Jewish person having more slack to make Jew-deprecating jokes and a black person having more slack to make black-deprecating jokes, but the Jewish person better not make those same black-deprecating jokes.
To use this theory as a guide to behavior is going to either require plotting out this multi-dimensional slack matrix (in which case: what if the Office of Slack becomes too slack?), or accepting that it subjectively depends on the lens you use what even counts as slack to begin with, making the whole concept less useful.
On the “acceptability” vs “costs” metric. This means its often much easier for a government to plow more and more money into a program that’s already approved/popular, than to do a new program
What do you mean by “the government” in this context? Because short of a major war, nothing is ever done by “the government” as a whole. And even in a major war, no decision is made by “the government” as a whole.
The administration, has to avoid losing face in the eyes of its supporters at least, or they’ll be voted out of office at the next election. And the bureaucrats making operational decisions, if they lose face, will see their career paths hit a brick wall and their departments’ budget and scope diminished at least in relative terms.
But it’s a nestled thing where slack on one level provides slack for another. You go on to say that the civil servants can see budget cuts, but the degree to which this happens is dictated by the administration. It’s not particularly important whether the administration directly runs everything, which would be silly.
That depends on if voters are able to not vote for that party or even that incumbent. In the American system, most disillusioned voters still vote for their party. Liberals pull the lever for Democrats, and conservatives pull the lever for Republicans, while they both try to motivate some portion of the independents. This means there’s a very high bar for policies and leaders becoming untenable. Sure if a Republican or Democratic President is bad enough, the voters from the other party might mobilize slightly more than they otherwise would, but this is happening at the margins, since voters from the same party will largely keep voting for the terrible President because of “the lesser of two evils” logic. This creates a high bar for mass rejection of a leader, and then add in incumbency advantage, and you have a large amount of slack.
In theory, but Republicans rarely slash and burn as much as they say they’re going to. They increase the national debt the same as Democrats do (and before the stimulus under Obama, their record was worse). That’s not to say that things won’t get cut back in one area while the DoD is given even more money, but overall things don’t get obliterated by cuts that often, and this is when the party that supports a competition based worldview is in power.
What you’re talking about are factors that relatively speaking wobble the amount of slack up and down a bit, but the government of the USA and most Western countries are operating with an incredible total amount of slack, in which finances practically don’t matter at all, because mostly voting somebody out doesn’t constrain the government to a scarcity respecting regime. There is a large degree of continuity between parties.
Obviously there’s a limit, but I think it’s a lot higher than you are giving credit for, and this better explains why so many modern governments have in fact been incredibly loose with deficit spending. You could say that they chose this option instead of higher taxes, which is an example of a pressure changing their behavior, but it just means that they found a get out clause. It doesn’t matter if a lion was initially hunting gazelle if its behavior over the last decade has involved having food thrown at its face by keepers. You had competition and it relaxed completely, so now you have slack.
Possibly I’m missing something, but it looks like your entire response is about the willingness of governments (in whole or in part) to spend lots of money they don’t have. Which, yes, they are. But that’s not the problem I am talking about, and I don’t think it is what Scott etc are talking about.
The problem is that “the government” is unwilling to take risks , or at least risks whose downside involves significant loss of face. That’s where there isn’t enough slack, and government action is constrained to doing things that have proven safe in the past. Spending ten billion dolllars on something where we’re guaranteed to muddle through is OK, spending one billion on something that will either succeed or fail spectacularly, not OK.
Given five billion-dollar proposals that each have a 50-50 chance of spectacular success or spectacular failure, where the successess will exceed the ten-gigabuck muddle, and we’ll spend the ten gigabucks. The other plan has a 97% chance of giving better results at half the cost, but it requires five people to wager their prestigious and lucrative careers on a coin toss. You’ll get people who say they are willing to do that, but really they’re each going to hit you up for ten billion and then muddle safely through.
From my experience of talking to people who work in government, there’s a pretty strong selection pressure not financially but for “justifiability”. For a new program to be funded it needs to be the sort of thing that you can convince people (depending where in the system you are that might mean management, politicians, interest groups or the public writ large) that it’s the sort of thing that you should do. And it’s always much easier to justify the status quo than any change, however good it is in theory.
Education is a good example of this. There’s lots of research on ways to do it better, (I’m going to avoid mentioning any specifics so thus doesn’t get derailed, but insert your favorite here) but any of them would require a major change to the status quo of “what schools look like” and its difficult to convince the relevant stakeholders (eg parents, government) that they are worth doing, even if the experts agree they are, think of the massive backlash to any change made in the American education system in the last few decades. Education is particularly bad because it has a large stakeholder group (parents and the public in general) who aren’t esperts, but think they understand the system and how it should work due to having spent 10+ years in it. And the outcomes are long term and hard to measure. (If you institute “magic new curriculum x” even if its better on every metric, you won’t see the results for years or decades). And people have strong feelings about anything that affects their children. So large scale change is very difficult. Only happening with either broad public support or a big top down effort from government willing to sacrifice short term political benefit for the long term outcome.
Your example is rather poor, since the ‘experts’ on education reform seem to typically be extremist ideologues, with extremely little evidence that their proposed reforms are better (let alone much better), yet with very high confidence that they are.
This is not true (e.g. https://eric.ed.gov/?id=ED397535 ). Talking heads aren’t experts – everyone knows this at some level.
It’s a bit politically incorrect, but wealth inequality is a major source of slack. A private company that’s held by millions of investors who are all relying on the stock for their retirement has little slack. A company wholly owned by an eccentric billionaire has lots.
But it isn’t necessary that the eccentric billionaire own the company outright, or even that he have a majority stake, So long as it’s clear that it would take an implausibly coordinated shareholder revolt to divert the company from the eccentric billionaire’s chosen path, the rest of the investors will be people who are happy with eccentric-billionaire management.
iPhones exist because Steve Jobs was a billionaire. With just pension funds and their conservative CEO picks, you’d all be making due with Blackberries.
Have space programs really stalled? Seems that we keep doing the important things (GPS, meterology, research satellites) and we just abandoned the flag-waving part (sending humans to distant celestial bodies).
We were doing all those things forty years ago. We’re doing them somewhat better now, but only by small marginal improvements. What we are conspicuously not doing, is anything whose failure would represent a conspicuous loss of face for the people in charge. GPS satellites are useful, but if one of them fails you’ll probably never notice it. If an entire block of satellites turn out to be lemons, you’ll probably never notice.
See also the James Webb Space Telescope. Originally proposed as a quick $500E6 project because with fancy modern tech we can way outdo Hubble at bargain prices – but it would mean taking “unnecessary” technical risks with a high-profile flagship program. So, enter plan B where we spend ten billion dollars and run the schedule out an extra fifteen-plus years until all the people who set it up are safely retired.
Also, count the number of “return to the Moon” proposals that have had their budget and schedule grown to the point that they are cancelled before anyone has to take the risk of launching an astronaut on a new spaceship.
The cost per kg to orbit, and the cost and time to build a new launch vehicle, did not improve much in quite a few decades (and has sometimes gone backwards, e.g. the Space Launch System). Several companies in the U.S. tried to improve things and all failed, some asserting that government policy made it impossible to succeed.
SpaceX shows how much room there was to improve. First they got to orbit on a shoestring. Then they became competitive in just a few years. Then they developed reusable orbital-class boosters and dominated the market. Now they’re building a fully-reusable Apollo-class vehicle for $2-3 billion and a few years of R&D in tents, and projecting 100 tons to orbit for $2M per flight.
So yes, we have maintained a space capability, but it seems a case study in stagnation until SpaceX came along.
I agree whole heartedly with your comment, but when one says “SpaceX came along” that really means “Elon Musk risked half his large fortune against everyone’s advice and worked really hard with lots of brilliant people for 15 years” (the other half went toward Tesla). The human race could have very easily seen no advancement in space launch capabilities for the foreseeable future. Maybe China?
Elon Musk’s companies have never been first to market. This is probably very important, in that they didn’t have sunk costs on ideas that failed previously (or merely on old tech that worked), and could see market ‘pain points’ (I hate that term) in advance, and directly address those points.
Did Scott just coin the term “inferential range”? I think that’s a keeper.
If you tell him there’s no God, does he say “I look forward to the several years of careful study of your scientific and philosophical theories that it will take for that statement not to seem obviously wrong and contradicted by every other feature of the world”? Or does he say “KILL THE UNBELIEVER”?
He’s probably likely to say “Who do you think you are, Peter Abelard?” and then refer you to the Cluniacs 🙂
“Inferential distance” has been a term used on Less Wrong for a while
There’s an important limitation to the fitness-landscape model – it assumes that evolution-as-a-dynamical-system has a potential function. In other words, it assumes that any given point in state space has an innate “stability”, with less-stable states yielding to more-stable ones. But this need not be the case (and in mathematical terms, it would be kind of surprising if it did).
Consider a system with two (self-interested) agents, A and B. A and B have come into possession of a cursed crown. While wearing it, one feels intense agony, but can compel others to put on the crown instead. Once the crown is off of you, the agony goes away, but so does the power to compel others.
The crown begins on A’s head. A does not want to be in pain, so A uses the crown’s power to compel B to put it on instead. Now A’s pain is relieved. B is now in agony, so B uses the crown’s power to put it on A’s head. And so on and so forth for eternity.
Actually, this is just a simplified version of foxes and rabbits. In a world with no mutations, Moloch (here interpreted as simply the god of dynamical systems) leads the foxes-and-rabbits system around in circles for eternity: high foxes, low rabbits -> low foxes, low rabbits -> low foxes, high rabbits -> high foxes, high rabbits -> repeat. This system happens to have an equilibrium (a population of foxes and rabbits that perfectly balance forces out), but some systems (like the cursed-crown one) don’t. Some systems need not even have stable cycles.
The implication of this is that unlike a true fitness landscape, the amount of work to get from point A to point B in such a system’s state space is (potentially unboundedly) path-dependent. And I don’t just mean in the sense that the “humps” you have to cross are path dependent, I mean in the sense that the height-difference is in some sense path dependent. Like an Escher drawing, there can be a “downslope” from A to B and from B to C *and from C back to A*, while the A -> C -> B -> A route is entirely uphill, something that is impossible in a true fitness-landscape model.
Relatedly covering lack of stable cycle, Nisan’s excellent book report on Theory of Games and Economic Behavior.
It is true that potential-based views can be misleading, but even if attractors are not fixed points, they can still have basins of attraction. Will you end up in the A-C-B cycle (or strange attractor or whatever), or the D-E-F, or somewhere else, and can you jump from one to another?
So it’s not so clear-cut, and you can use ideas like Morse decomposition to separate a dynamics into “potential-like behavior far from the attractors” (falling into a basin), and “non-potential-like around the attractors” (A-C-B-A)
What you’re talking about is well-understood in evolutionary biology, particularly in the context of frequency-dependent selection, in which the rare phenotype is always favored. These type of systems tend to be either a) sexual preference, b) exploiting fluctuating food types, or c) immunological arms races with parasites or other pathogens.
In contrast, fixed fitness landscapes (or mostly fixed) tend to occur with more mechanistic systems, such as locomotion, feeding, armor, etc., where the underlying landscape is mediated not by other biological factors, but by physics.
“particularly in the context of frequency-dependent selection, in which the rare phenotype is always favored”
I think you mean “particularly in the context of frequency-dependent selection in which the rare phenotype is always favored”
I’m skeptical about your analogy in Part 1.
In the early days of machine learning, people worried a lot about local minima. You optimize 10 parameters one step at a time, you might not reach the absolute best configuration (the ‘global minimum’), same as the picture with the ‘puddle’ and ‘pit’ you showed.
But nowadays ML has stopped worrying about local minima. Why? Because we’re not fitting 10 parameter models, we’re fitting 10 million parameter models. And the 2D or 3D intuitions don’t quite carry over.
Imagine pouring a bucket of water, but not in 2D, but in 10 million D. Most probably, the water will indeed end up at the lowest point. A puddle, or local minimum, is extremely unlikely.
Why? A puddle means that locally, there is a hill or moat in every direction. In 2D, you just need hills on the X axis to stop the water. In 10 million D, you need a 10 million hills. Since getting a hill in 10 million directions is quite unlikely, you will end up with very few local minima. (See here)
(Note that high D spaces are not without challenges, but I don’t want to get into that now).
So in high dimensional spaces, Moloch wins over Slack. With close to infinite possibilities, you’ll always find a direction to improve the status quo.
Hm, do you feel like the eye example is something that could never happen? What about the example where nobody competes with Boeing because even if they could eventually be better, they would be outcompeted at intermediate stages? If those could happen, how are they different from the machine learning example?
I think the important difference is brought up in Inadequate Equilibria; you need at least two sides that are locked into some bad equilibrium.
The modern ML problems were we don’t worry about local minima are usually only one sided: eg detect cat in a picture. Or, drive a car.
Not: compete with other people for research funding on one side, ans decide on how to hand out research funding on the other side.
While it is true that high-D spaces have very weird properties and many low-D intuitions don’t apply, there is unfortunately an entire field of physics devoted to the fact that in 10 million D, you can get exp(10 million) local minima.
That’s called disordered systems, or glassy physics, and that’s why glass doesn’t flow and also why there are NP-hard problems (including finding Nash equilibria of many-player games for instance).
See Mezard and Montanari’s great book “Information, Physics, and Computation” or this seminar for instance.
The fact that some algorithms might be rescued from this problem doesn’t suggest to me that it is not a relevant picture of the world, very sadly for us all!
I have to admit, I know absolutely nothing about glassy physics. I know that when training neural networks, this issue doesn’t really come up, and there are attempts at theoretically explaining why that isn’t the case.
Do you know how to reconcile these two? Are training NNs a special subset of high D problems where local minima are a non-issue? What am I missing?
Thanks for the refs!
I’ve been going quickly through Sagun et al, Ben Arous is definitely a glassy person so the authors are probably well aware of the issues.
I think the crux is this: under conditions which I need to understand (but may well be general), there is a whole bunch of local minima, but getting into any of them already takes you into a “fairly good” part of parameter space. Not optimal perhaps, but still much better than almost everything you’d get at random.
It’s true that it happens, in spin glasses, that your many local minima have somewhat similar statistics in some respects (though not in others).
In the same spirit, there was a quite controversial evolution experiment on yeast where they deprived it from its food source and replaced it by something inedible.
They saw the population crash, then quickly go back up, and every time they repeated the experiment, the (epigenetic) “solution” found to process the bad resource was different, some definitely better than others, but all allowed you to survive.
Thanks for the help! The more I read about the topic the more confused I get 🙂
I actually encountered the view you wrote in terms of neural network training as well (that there are multiple local minima, but each one is ‘fairly good’).
I think the practical point for not worrying about local minima in NN training is fairly robust (at least for supervised models; GAN training can be fiddly), but I’m not sure what to think of the underlying theory…
Neural networks for supervised learning really seem to be a special case.
In reinforcement learning bad local minima are a real issue. This is fundamentally caused by the exploration-exploitation tradeoff, which does not exist in supervised learning.
In Scott’s terminology, exploration is Slack and exploitation is Moloch. If you have too much of either then you stop making progress, and even with the right amount you are ultimately in the hands of Fortuna.
when training neural networks, this issue doesn’t really come up
What about the effect described in this very interesting paper from Japan? Does it describe a way of avoid a local minimum of the loss function, or a way to find a model with a slightly higher value of the loss function but better generalization? Either way, I think it’s closely related to the problem of avoiding local minima, and I like the way the name “flooding” uses the same water metaphor in a creative way.
Since existing regularizers do not directly aim to avoid zero training loss, they often fail to maintain a moderate level of training loss, ending up with a too small or too large loss. We propose a direct solution called flooding that intentionally prevents further reduction of the training loss when it reaches a reasonably small value, which we call the flooding level. Our approach makes the loss float around the
flooding level by doing mini-batched gradient descent as usual but gradient ascent if the training loss is below the flooding level. With flooding, the model will continue to “random walk” with the same non-zero training loss, and we expect it to drift into an area with a flat loss landscape that leads to better generalization.
The ability of data scientists to manipulate hyperparameters (e.g. regularization parameters) helps resolve the apparent conflicts between physical observations where local optima are inevitable and ML techniques where they are vanishingly rare. Physicists can only observe the fundamental properties of their materials; they cannot change them. It’s feasible to create local optima in a neural network if you do a bad job.
Indeed. Neural network practitioners have developed over the decades an arsenal of tricks to make their models converge to good local minima: residual connections, normalized initializations, normalization layers, adaptive gradient descent with momentum, and so on.
It is true though that just making the model bigger helps. This is essentially because typical neural network architectures become Gaussian processes or something similar in the limit of infinite width, and Gaussian processes have a convex training problem.
Interesting point. This would go in the same direction as William Bialek’s argument (in his book Biophysics), that biological networks within an organism are typically neither glassy nor fine-tuned — understand, neither a landscape with a billion billion minima, nor clockwork with a single well-defined working state and range of mechanical tolerance.
Typical example: useful proteins can fold in a few shapes, not all great. Artificial random polymers of comparable length can have a hundred thousand folding states.
So, at a glance, cell (or organism)-level evolution playing with the hyperparameters of the fitness landscape for protein foldings seems to match what neural network people do.
Never is a strong word. I’m sure there are examples. But how relevant are they practically?
I don’t know the details of the Toyota case, but maybe that fits. Still, is it the rule or the exception? If advising a rising 3rd world dictator on economic policy, would you say that ‘protect your domestic industry & you’ll be rich’ is a good course of action?
So why aren’t people competing with Boeing? Well, there is one startup building supersonic passanger planes, but why aren’t there more?
To be honest, I’m not sure. My guess: Elon Musk could build a better than Boeing company. But we don’t have 1000s of Elon Musks, and the ones that exist work on more pressing problems. I’m skeptical that there are 1000s of Musks whose only obstacle is that they will be competed away at the intermediary stage.
Here is another way to think about it. Under the too-much-Moloch theory, if an asteroid hit the Boeing headquaters, destroyed all equipment, we would be better off (as that would lessen the competitive pressure). I highly doubt that.
The one area where I do see this effect: signaling industries. The diamond business or higher ed / academia. There probably are 1000s of people who could make a ‘startup university’ that’s much better (much cheaper!) than the existing model, but it’s hard for them to get accepted as non-weird (Lambda school may be an exception here).
If an asteroid surgically destroyed all academic institutions, the world may indeed be better off!
They are. Not just Airbus, but also a couple of other countries are trying to break into the passenger jet market.
There are actually two. The problem is that building passenger aircraft is really hard. Not just from an aerospace engineering perspective, but from a regulatory one. I’ve heard that it’s harder to put a part into a human than it is to put (a different) one onto an airliner. I used to be involved with the latter, and the claim is at least plausible.
And when you are competing with Boeing and Airbus, you are not just competing with the companies, but also the USA/France/Germany and their secret services. So you better have your own big country backing you.
Yeah, you need to have solid backing from your country. Bombardier was trying to compete with Boeing and Airbus on medium-range airplanes with the CSeries, which by several accounts was a very promising product. But then Boeing and Airbus both tried to attack the CSeries by cutting prices, lobbying for tariffs, etc., and Canada was probably not big and/or willing enough to really give Bombardier the support they needed. It’s been speculated that it’s because Bombardier doesn’t have a very good reputation outside of Quebec. The government of Quebec did try to help, but was certainly not big enough. In the end, the CSeries was given essentially for free to Airbus and became the A220.
If advising a rising 3rd world dictator on economic policy, would you say that ‘protect your domestic industry & you’ll be rich’ is a good course of action?
See my comment re: Ha-Joon Chang. This was essentially what most advanced economies did – used protectionist policy to grow nascent industries until those industries were powerful enough to compete in a freer market. Samsung and Toyota were specifically protected by their countries in this exact way. The US and UK were very protectionist and only became standard bearers for free markets when they were convinced they would be dominant in those free markets.
See also the Chinese Internet with its Great Firewall, whose primariy purpose was censorship, domestic surveillance and prevention of foreign espionage, but it had the effect of creating a thriving domestic market largely isolated from the American companies. Today China has Internet megacorporations with top-tier technology such as Tencent, Baidu, Alibaba.
Contrast with Europe. There were quite a few promising Internet startups in Europe in the 90s and early 2000s but they have long since folded, now the market is completely dominated by American companies which pay little taxes and employ few people there compared to the profits they make, and of course let the US government access their data as it sees fit.
On the other hand, if you isolate yourself too much (e.g. modern North Korea, or historically, Edo period Japan), you’ll get stuck with obsolete shit-tier technology.
For a country to be “dominant” in one area, other countries have to be dominant in others. There’s no such thing as being dominant in free markets as a whole.
It’s worth noting that some systems, particularly systems operating in physical environments or with developmental constraints, really are constrained to low dimensionality – e.g. lever arms in jaw muscles.
What if you’re designing organisms, and your “fitness” criteria is how close they can get to the Moon? Your algorithm is busy creating birds that can fly to the highest possible altitude. How does your multidimensional optimization get from that to organisms that can build rockets instead?
I’ve trained some neural networks, and my experience is that this is just not the case. Maybe because I’ve mostly been working in reinforcement learning. In that field neural networks get stuck in all kinds of bad local minima that you can’t get out of. Like when playing a video game, the neural network loses points when it dies. And at the beginning of the training, when it is really bad at playing the game, every time that it leaves the first screen it dies to the first enemy. So it learns to just always stay standing still on the first screen because zero points is better than negative points. You have to get really creative to get it out of that local minimum and directly encourage exploration. (oh and you have to start over from scratch. The neural network calcifies in the bad local minimum, and only a random restart can get you to a better place) The same network can represent much better behaviors and actually learn to play the game somewhat well, but it will never get there unless you get really creative while training it.
And, at least in my experience, you find many more local minima than you find ways to get to the global minimum. Most of your work on neural networks is trying to find ways to avoid these countless local minima that you get stuck in.
Fair enough. I was thinking more in terms of supervised learning.
Why not simply reward the network for the number of actions it can complete before it dies, and not penalize it for dying? Staying on the starting screen counts as 0 actions. Leaving the starting screen lets it take some actions. If there’s a game state that lets you move indefinitely without dying or advancing, then add another reward criterion to incent not staying in that state.
Then it learns to take meaningless actions that don’t put it in danger but also don’t get it any closer to actually winning the game.
If the object of the game is to get to the other end of the stage I suppose you could grade it on how close it gets to the other end, though a level design with dead ends would screw that up.
Surely “very few local minima” doesn’t necessarily mean that ending in a puddle is “extremely unlikely”? If you just have 3 local minima, you would naively expect there to be just 1/3 to end up at the global minimum. Since deeper minima are often wider, the probability is probably somewhat greater, but it seems far from guaranteed that you’d end up at the global minimum.
Also, I think it’s extremely rare for big neural networks to actually end up at global minimum. If this was common, you’d expect models to end up with exactly the same behaviour every time you trained them, regardless of the initialization. Do you have an opinion of why this is, if not for local minima? Is it only because we have too little compute?
I think that in many cases, people don’t know the actual global minimum (and why would they?), so if the AI stops improving, they call that the global minimum, while it may just be a local minimum.
For a vivid demonstration of a local minimum that is not a global one in a very-high-dimensional space, consider the giraffe’s recurrent laryngeal nerves.
And you’re deliberately setting them up so that all ten million parameters have a priori equal weighting in the outcome. Reality doesn’t work that way. Reality is, some parameters are more equal than others. Once you’ve optimized for e.g. “Macedonia can support a modestly large army”, “Macedonia has developed a high level of military professionalism”, and “The Macedonian aristocracy occasionally spits out genius-level conquerors”, it hardly matters what the liturgical practices of the Macedonian religion or the growing season of the Macedonian turnip are.
I don’t think think this is true at all.
Rather, any good modern algorithm has considered the problem of local minima and included tools for avoiding getting stuck in them. This doesn’t mean the problem disappeared. It just means that plenty of useful and effective solutions exist.
According to Andrew Ng (one of the pioneers and experts on neural networks), the above commenter is correct – local minima don’t matter with high dimensional models. In sufficiently high dimensional space the odds of a local minima even existing are vanishingly small. Intuitively to get a true local minima there needs to be one along every dimensional axis simultaneously, otherwise you get a saddle point. Saddle points can behave like local minima but there are techniques for getting around them.
Your argument for why the probability for a particular point being a local minimum sounds convincing, but the number of points, and thus the opportunities for a local minimum, increases massively with the number of dimensions. Also, your argument just as well to *global* minima, and suggests that there are no interior global minima. If we’re constrained to the boundary to find minima, then we’re back to a lower dimensional space.
Btw, you’re still playing Civ 4???
Civilization IV is the best game in the series (fite me). Why play a worse game just because it is newer?
In my opinion, the best game is whichever one my friends are playing, which is why I have Civ V.
It’s also an example of local minima: Civ V is the best one for me because it’s the only one that I know the systems well enough to make intelligent decisions. The others have a >10 hour learning curve to understand that risk/reward pay-offs over the course of a game. In the others, I’m just guessing.
Civ IV does clearly have the greatest music. And the best tech quote readings (outside Alpha Centauri).
I had a similar problem switching from Civilization III to Civilization IV, but Sullla’s tutorial got me over the hillock.
My wife got Civ 6 for the Switch. Neither of us has managed to finish a game.
Our most common Civs are the classic Civ 1, and Civ Revolutions. Lots of people hate Civ Rev, but you can play a full game in one night, which is nice.
I’ve been impressed by Civ VI since the Gathering Storm expansion. V was kind of lame for me, but this one is killing it.
Absolutely. And the best Civ IV mod is Dawn of Civilization.
Can you please explain to me the trade-offs between squares and hexes?
I grew up jealous of my friends who had civ 4, but by the time I got to pick games Civ V was out and hexes just seemed much better.
The problem with Civilization V is not the hexagons, it’s One Unit Per Tile. Based Sullla can explain it much better than I can.
Interesting as I’d have said the one unit per tile thing made the game much better, as it removed doomstacks. I suspect this comes down in the end to people wanting fundamentally different kinds of strategic game experiences. Something like 1upt means that decisions made in an individual turn are far more impactful. Which I prefer because it makes those turns more interesting, as they contain a bigger element of risk. Others would say the opposite because it means a single turn can override a large number of turns of strategic gameplay
*Edit* Occurs to me that the total war games are a more extreme example of this difference. Where good play in the battle element can ovvrride bad play on the campaign map, and vice versa.
Sid Meier’s Civilization is the best, because you can choose the “Play on Earth” option and 4 players (so that the Aztecs are available but the Americans don’t exist) so you get the entire Americas to myself, then amuse yourself by colonizing the continents and rushing tech as fast possible in peace.
As you can see, Scott’s aside brought back a lot of memories for me.
Civ IV was the peak of the Civ formula developed in the earlier games. Most of the changes since then have made it clunkier, more tedious, and less streamlined.
I think this post could use the perspective of “the selfish gene”. Basically, if you think that evolution optimizes individuals you fall into a similar trap as the people who think group-evolution is a thing.
Think of a gene in birds that causes them to throw their siblings out of the nest. In the first generation, such a bird with such a gene would have an advantage (more food from parents), but the bird would have a hard time to reproduce (only one offspring per year), and thus such a gene cannot survive. Exept it does, in cuckoos.
Or take a gene that would cause mice to seek out cats. Exists, in toxoplasmosis.
So, at the bottom level evolution “is about” reproducing genes, and everything else, including other genes on the same chromosome, is just environment. A gene that limits fox population in the abundance of food could only evolve in rabbits.
So, to find an optimal balance between competition and slack, you would need an out-group actor that can create a mutually benifical environment by introducing slack. Investors are a good example. Someone who is already rich cares much more about maintaining wealth long-term than increasing wealth short-term.
In the company context, it would be a CEO that wishes to be famous for reforming a struggling company to be ready for the future, rather than just increasing the ROI by 3%, but who also knows they will find a job somewhere else if the board isn’t happy with their approach.
Not so clear. A lot of rich people got that way by being obsessed with getting richer. They are unsatisfied by their first billion, just as they were unsatisfied by their first million.
Great post (so far), but the example of Italy is… really, really bad.
The Borgias do not represent Italy’s flourishing. They represent the
countryregion wasting away its humongous civilizational and economic advantage acquired in centuries prior. (Wasting it so thoroughly, in fact, that historical GDP reconstructions suggest Italy did not return to its late-middle-ages heights until early XX century.) And Da Vinci and other Renaissance icons were not a product of the ongoing collapse around them. They were a product of slack awarded to them by their filthy rich patrons and their large conspicuous consumption budgets.
Not to mention, clocks are wonderful, complicated mechanisms and pinnacles of then-contemporary technology.
It is perhaps worth noting that Welles puts his line in the mouth of a character who has made a fortune by stealing medicine, diluting it to the point of uselessness and reselling it, leading to a hospital ward full of dying children, has committed multiple murders to cover up his activities, will soon be shot dead in a sewer, and is currently making a recruitment pitch for his criminal organisation to the addressee.
Harry Lime is charming and exciting and a wonderful character, but we should probably listen to his advice at least a little sceptically.
There is a very nice (and veeery long) blog series by a historian on why Sparta was different (way worse) than how we imagine it and why they failed to be successful despite starting as the biggest and strongest Greek polis.
The most damning part relevant to this claim is that Spart weren’t really great at war – they won around 50% of battles they fought.
(The blog also explains why the pop-culture perception of Sparta is so different from modern understanding of the historical record)
I’ve written about this before at https://slatestarscratchpad.tumblr.com/post/163974181741/femmenietzsche-tanadrin-spartan-power-as-an
I’d suggest reading the actual post. It talks about how the Spartans appear to have had a slight edge in tactics, but were terrible at every other aspect of war (in particular logistics). Meanwhile the quotes you provide basically seem to be about how badass the Spartans are. But being badass isn’t the same thing as actually being good at war (or even at winning battles).
I read the full series of blog posts, and holy shit, Sparta seems awful. Like, a strong contender for Worst Ever Society. I guess competitors could be flash-in-the-pan badness like the Khmer Rouge and Nazi Germany, but they didn’t last long enough to impose that scale of immiseration. Maoist China and the USSR could compete, and probably come out as causing a greater amount of suffering just because they’re so much bigger.
But as awful as they treated their people, I don’t think they got quite as bad as the overwhelming majority getting hunted for sport, and the relatively lucky few getting taken from their families at age 7, and tortured and raped until they’re ready to continue the cycle. Maybe Belgian Congo?
I am just getting started on the series and holy crap, this is great. Thanks for the link!
Nitpick: You are supposed to win 50% of the battles you fight. Even if the Spartans were the greatest warriors on earth we would expect them to win 50% of their battles. This is since battle is only fought when both sides have an expectation of victory, so the result should be 50:50. If you believe that you’re likely to lose a battle, you don’t fight it: you flee or surrender instead. If the Spartans won 80% of their battles, their enemies would adapt their strategy to avoid the less favorable battles until the percentage went down to 50% again.
Imagine that Spartans were inhuman supersoldiers: that each Spartan could defeat 100 normal Greeks. Now a Spartan army of 100 soldiers march up and is met by an Athenian army of 2000 soldiers. What happens? Well, the Athenians know they don’t have a chance since they need more than 100:1 numbers and only have 20:1, so they flee or surrender without a battle. Ok, let’s say that the Athenians have an army of 20.000 instead. Now the same happens with the Spartans: since they know they need more than 1:100 to win and only have 1:200, they flee or surrender. Battle will only take place when the ratio is about 100:1 and that gives the Spartans even odds of victory.
This assumes that your opponents have an accurate view of your capabilities and that they consider retreat/surrender an option. The absence of those factors is how spectacular generals like Alexander or Napoleon were able to have much better than a 50% battle win-rate.
The post also mentions a factor that may have helped the Spartan’s numbers. The way armies lined up was the most prestigious polis’s phalanx was on the right, and then from right to left in descending order of prestige. So when you have two armies facing each other, who are the supremely-prestigious Spartans going to be lined up against? The least prestigious members of the opposing army, who are going to be fairly intimidated by the Spartan’s reputation.
All true, but A: the Spartans were renowned for their actual military capabilities and B: the battles their opponents chose to fight were in fact the 50:50 ones and C: I don’t recall the Spartans massacring enemies who surrendered or fled before battle(*). So I think all of those conditions apply.
I did toy with the idea of going through the cited battles and plotting the Spartan win rate as a function of numerical superiority/inferiority, but never got around to doing so. That would probably be more indicative of martial superiority than just counting wins.
* The idea that you get to surrender during a battle and live, is a very recent invention and one often ignored by people actually fighting battles.
FWIW I thought the list of battles was the weakest part. What was more compelling to me was that a) the Spartans engaged in pretty much the same sort of fighting as everybody else did, and hoplite battle seems to have been the sort of thing you could pick up with pretty minimal training – there is no evidence the Spartans actually practiced much drill or other combat tactics, b) to the extent they had an advantage, it was more “indoctrination” (unit cohesion) and the fact that Spartiates were probably fitter and better fed than other Greeks who had to work for a living, c) the Spartans May have been better at battles but they seemed to suck at war (really crappy logistics, even for the time, and simplistic strategy)
The bigger nitpicks for me:
1. he includes a bunch of naval battles in his scoring. Sparta didn’t have a navy for a long time, due to being landlocked, and only built one during the Peloponnesian War out of necessity, so of course they weren’t very good at naval combat, since there’s a very definite learning curve involved with all the rowing this way and that in tactical maneuvering to ram enemy ships while they’re trying to ram you (or avoid being rammed).
2. Why does the tale of the tape start at 500 BC? The Spartans conquered the Messenians and reduced them to helot status (thus beginning the era of Spartan militarism) in the 700’s. Seems like one could amass a pretty impressive record in the 200+ years between then and when this chap starts his tabulating. I don’t know enough to say whether that actually happened or not, but still, starting the scoring at 500 BC seems a bit arbitrary.
3. Sparta (along with most of the rest of Greece) was in decline after the Peloponnesian War, so one would expect poorer results after 404 BC, so that’s no surprise. In general, I’m inclined to think ancient Greeks had a clearer picture of who was good at fighting and who wasn’t than people alive today, so I’m skeptical of this kind of revisionist thinking. You’re not gonna get any argument from me with the larger point that Spartan society was not a pleasant one for any strata.
It may have been pleasant (by ancient-world standards) for citizen women on account of when the menfolk were busy oiling up and slaughtering people they left their women mostly alone to run everything else. That’s not the part of Spartan society that everybody glorifies, of course, but I wouldn’t mind a good story told from that perspective (Gorgo’s bit in “300” might be at least a nod in that direction, but I want the version where the women are more pragmatically cynical about the murdery distractions).
The post series covers this. Spartiate women didn’t get to “run things” outside their households (they weren’t allowed in the government). But they did have pretty pleasant lives, because unlike most other Greek women (even relatively noble / well off ones apparently) they were not expected to engage in any sort of productive labor like cweaving, and in fact scorned other Greek women for engaging in those types of activities.
Of course Spartiates were only a tiny fraction of the Spartan population.
1. He addresses this. It doesn’t change the percentages much if you remove the naval battles.
2. He addresses this too. For one thing, we don’t have a lot of actual non-legendary information from this period of Spartan history. For another, smashing up the locals isn’t nothing, but it’s not that impressive because Sparta was significantly larger than all its neighbors. Finally, the authors thesis is not “Sparta sucks at war” it’s “Sparta gained a fearsome reputation early (with a big helping of favorable propaganda via Herodotus) and then coasted on this reputation for a couple centuries where their actual results were middling”
3. But Sparta’s reputation as super tough warriors does not seem to have helped them outlast their neighbors during this decline. If anything Sparta declined a lot harder – Athens stayed relevant much longer, Sparta became a backwater (a literal tourist attraction by the Roman era)
1. I realize that; the Spartans’ record at sea is better than I would have expected, but why include them at all? He spent 18 paragraphs prattling on about phalanxes, then muddies the waters.
2. Okay, but if we don’t have great info, isn’t a more agnostic stance more appropriate? The idea of the Spartans beating up on locals who were apparently small fry seems a bit dismissive, also, because how do you suppose Sparta got to be larger than its neighbors? It didn’t start off that way. The Messenians, if I’m not mistaken, were several times more numerous than the Spartans. And yet, who spent several centuries subservient to whom? Which leads me to another point: not all victories and defeats are equal. Losing at Sphacteria is a bummer, but the Spartans still won the war.
3. That’s fair. That point was mostly aimed towards his comments about how the Spartans didn’t put up a fight against the Macedonians. The jig was largely up at that point, for Sparta, and Macedonia was clearly the New Power to be reckoned with.
On the Sears example, it’s been a while since I read this but I believe P&G were able to find a competitive equilibrium within their own firm. P&G is a massive firm with thousands of different brands, and it is my understanding that they have encouraged their own brands to compete with each other, rather than just those of their competitors, and this was presented as a factor in P&Gs own strength in th FMCG industry.
Unfortunately I can’t remember where I read this so no source, but perhaps there’s an MBA or similar here who has read the same and can back me up
Scott, on Sears, read up on Transaction Costs (Coase). Having departments perform their functions efficiently is great, but they could just be separate firms then. Unless, organizing within a single firm has transaction cost benefits. It’s critical to the decision to do things in-house or outsource. If the benefits are large, having departments strike out on their own is quite literally giving up your organizational advantage. Though to your point, it’s possible that having a temporary period of competition might shake out the cobwebs (unfortunately, this is also the misunderstanding of the business cycle and “creative destruction”). To sohois’s P&G example, it’s about striking the right balance- Tide and Bounty (or however their SBUs are organized) have their own markets to tend to, but for things that they have in common, it’s easier to just ask daddy.
It also relates to your broader point- if you have a bunch of firms transacting with each other, sometimes it might be more efficient (vs. other firms) to organize as a single firm to avoid those transaction costs. If you have a bunch of organisms competing with each other, sometimes it might be more efficient (vs. other groups) to organize as a collective to avoid those competition costs.
There are many companies that have units that sell services internally to other units.
Sears was in an incredibly weak position and retail (especially big box retail) is dying everywhere. Blaming the death of Sears on that particular transformation is a stretch it’s possible that the attempt killed it faster than it would have normally died through many complementary reasons – but blaming internal competition explains entirely too much.
Came here to comment about Coase’s paper as well. Really worth a good read and sad that Coase is more known for The Problem Of Social Cost and not The Nature of the Firm.
I’m not sure that the original “insect-cannibalism” paper entirely supports the conclusions given here or in the lesswrong post.
Specifically when you say they “…killed off any subpopulation whose numbers got too high, and “promoted” any subpopulation that kept its numbers low to better conditions. They hoped the insects would evolve to naturally limit their family size in order to keep their subpopulation alive. Instead, the insects became cannibals…“, this would seem to correspond most closely with “treatment B” in the paper (“group selection for low numbers of adults per population“) which did not have a higher cannibalism rate. Other treatments (the random ones) did produce higher cannibalism rates, and the paper mentions that “some of the B populations enjoy a higher cannibalism rate than the controls while other B populations have a longer mean developmental time or a lower average fecundity relative to the controls”, i.e., sometimes cannibalism, sometimes other factors.
Overall, on a first reading it sounds to me like the conclusion is more “it’s complicated”… but I’m not sure I’ve completely absorbed and understood the paper, maybe I’ve just missed something basic here. I don’t think it makes a big difference to the contents of this particular post but I do think having a clear exposition of experimental support is important, so if anyone with a better understanding of this topic could set me straight that would be useful!
Yeah, this paper is very unconvincing, particularly because their “control” changed so massively, indicating that something else was going on (insufficient nutrients leading to cannibalism?). Add in the small population sizes (prone to drift and inbreeding), and there’s all sorts of trouble. That line B declined in adult population could simply be because the author was unintentionally selecting the messed-up, inbred populations, and what they thought was group selection was just that population circling the mutational drain.
“enjoy a higher cannibalism rate” interesting phrasing
The deep issue with the “group selection problem” is that it sounds a lot like “atoms should generally be found alone, unless they can somehow gain energy by making a molecule”.
That statement is true, but it is also highly misleading as to how many atoms are noble gases. It terribly overstates the unlikelihood of mechanisms that create decidedly collective behavior in chemistry.
Although we (roughly, ecologists and evolutionary biologists) all agree obviously that group selection cannot violate some strict bounds created by individual selection, how often are you close to those bounds? Is it like saying “human language cannot violate the laws of physics”, where really, you’re not looking at the most relevant constraints at all?
I think it is an open and entirely non-trivial question to know whether natural selection gives you mostly noble gases, mostly ocean-sized polymers, 50/50, or something else.
The reasons why the mainstream has alternated between absurdly overemphasizing one or the other are much more sociological than mathematical.
I think there is a conceptual dead end that arises when the statement “evolution doesn’t act on the level of groups” is taken to mean “evolution acts on the level of individuals”. The former may be true, but the latter doesn’t follow. Individuals don’t evolve. Genomes evolve. A gene that kills its host but makes other hosts containing its copies multiply and prosper will win against a gene that prioritizes its current host over anyone else.
That’s just one more turtle on the way down, honestly. You can replace “group and individual” by “organism and gene”, or by “species and group”, or “ecosystem and species”. Or even, if I’m being cheeky, by “gene and atoms”.
All these levels are being selected upon at any given time, the question is “which is the most important to determine current dynamics?”
One naive but helpful way of seeing it is as a matriochka: everything that physics permits > everything that gene selection permits > everything that individual selection permits > everything that group selection permits > …
So, sure, group selection can never violate gene selection or physics. But how close are you to the boundary of each domain? Are you unlikely to evolve a given feature because of thermodynamic bounds, because it would allow selfish genes to take over, because it creates cancer, because it will eventually kill your family or species or planet?
I mean, the amount of biology we can explain without having to resort to group selection has, IMHO, led to the question of whether or not it even matters? If we don’t even need it to explain eusocial insects, it’s either nonexistent, so weak as to be a rounding error, or only occurs in such restrictive circumstances that it’s mostly uninteresting. And the failure to turn up any examples of the latter case, however restrictive or rare, strongly suggests the former two.
I wish I were as optimistic as you are about how much biology we are explaining 😉
My best guess (as someone working in the field, not a naysayer) is that we understand roughly nothing of the main selective forces applying on most species in most ecosystems, and I suspect that it has to do with the fact that we have no idea how to really measure multilevel selection.
4th paragraph: spend -> spent
I have always thought the Greene quote from The Third Man was adapted from Whistler’s 10 O’Clock Lecture:
– but there the Swiss are used as an example of the opposite of too much slack, as people accustomed to fighting for their freedom (Gessler, Tell), who are less favored by art than are the languid opium eaters.
I’ve been thinking about the Japanese car industry, and how perhaps the biggest protectionist step the Japanese government took was to have traffic drive on the left (which obviously discourages importing cars from the US with their steering wheel on the left!).
I’m also looking at the UK and Continental Europe as comparisons. In both cases there were non-tariff barriers that made importing cars directly from the US difficult. The most important one in the UK was left-hand traffic (as in Japan), but there were also factors all over Europe that meant that people preferred smaller cars with smaller engines- they fit better in narrow streets, fuel is more expensive, and many countries had high taxes on heavier or more powerful cars.
The response of Ford and GM was to have subsidiaries in Europe producing vehicles aimed at the European market, largely using European-produced parts. They went about it differently- Ford set up Ford of Britain and Ford of Germany, while GM took over pre-existing manufacturers Vauxhall and Opel- but the end result was pretty much the same.
I was wondering why no American companies tried this in Japan. Might it just be an issue of timing?
Ha-Joon Chang often uses Toyota as an example (Samsung in South Korea in another) to show that, despite the laissez faire camp’s insistence that totally free markets makes the spice flow, advanced economies are often examples of protectionist policies being used to grow key industries until the companies are powerful enough to compete in an open market. The United States and Great Britain are good examples of countries that were fiercely protectionist until it was beneficial for them to prefer free markets.
It would be great if the two sides were “all protectionism is bad” and “actually, protectionism is sometimes good in developing countries” and we could compromise on no tariffs in rich countries without attempts to ban them in poor ones. Unfortunately, in the real world the main side is “no opinion” and the runner up is “protectionism only for the rich countries that don’t need it”.
There’s no such thing as entirely one-sided protectionism. If we’re selling things to poor countries, they must be selling things to us to pay for it. And whatever that is, is being protected. For instance, suppose the US is trying to sell cars to Japan and use the money to buy rice. If Japan imposes laws protecting their car industry, those laws will also serve to protect the US rice industry.
The relationship between protectionist policies and growth rates is fairly controversial and Ha-Joon Chang treatment of economic history is not always the greatest. If people want to know more Pseudoerasmus has a fairly good rundown things here:
In How Asia Works, Joe Studwell shows many examples of how protectionism helped kickstart industrialization in Asian countries. But he argues it’s not good enough on its own. Protectionism must favor companies that export and are therefore subject to the pressures of the international market. Japan, Korea, and Taiwan did this well. In Indonesia, Malaysia, and Thailand, protectionism created too much slack; industrialists were happy (and rich) producing inferior products exclusively for local markets.
His arguments strike me as cherry-picking and post-hoc. “Here’s a country that had protectionist policies followed by positive results”. That doesn’t establish a causal relationship, and even if you could establish that particular policies benefited their countries, that wouldn’t do much against anyone arguing against a *different* policy. If someone points at a particular protectionist policy and says “this is bad for all the parties”, it’s not much of an argument to simply say “Well, beneficial protectionist policies have existed”.
Thanks to danculley downthread: They did. Ford and GM both set up Japanese subsidiaries in the 1920s, at the same sort of time that they were doing so in Europe. The Japanese capped the production of foreign-owned auto manufacturers in the mid-1930s, and outright banned them a few years later.
Weird piece of trivia that this reminds me of- Hubertus von Hohenlohe was born in Mexico City in 1960, the son of a German prince who had founded Mexico’s first Volkswagen dealership and would open the Mexican VW factory a few years later. His parents decided that he should be born in Mexico, and therefore be a Mexican citizen, because of worries that Mexico might restrict foreign ownership of its car industry.
A couple of decades later, Hubertus founded the Mexican Ski Federation. He was the sole member of the Mexican alpine ski team at several Winter Olympics, competing for the last time in 2014 aged 55 against athletes many of whom hadn’t been born when he went to his first Olympics.
Great article! This is the kind of insightful, interdisciplinary, grand-theory-of-everything stuff I read SSC for.
I think there’s a minor error here:
It should be either “lower to higher fitness” or “higher to lower ground” (because high/low is inverted in the landscape metaphor relative to the evolutionary reality).
Was about to point out the same error. Glad I ctrl-f’d before doing so! In a highly competitive environment, you can’t afford to sacrifice fitness to invest in future fitness, so you can only locally raise your fitness not lower it. So it should indeed say “only go from lower to higher fitness”
This was a fun article to read on the day I finished law school.
It is incorrect to say that group evolution is entirely wrong. It’s just mostly wrong, and there’s a gap between mostly and entirely there that is very important.
In your solar flare world, depending on the frequency of solar flares, a group that evolved such that there is no trivial way to lose shielding might eventually take over; maybe the proteins responsible for the shielding also became involved in having an effective respiratory system.
The key to understanding this is to think of genome in which a gene operates as part of its environment; namely, other genes can change the topology of the landscape. If a particular topology is critically useful – say, the jump from “shield” to “no shield” is too hard – that can become a fixture. This is a form of group selection, albeit a very specific case, which just happens to be important to understanding this topic.
But that’s still not group selection. Group selection is defined VERY strictly and narrowly. In your example, you have a developmental constraint or historical contingency that, by sheer accident, led to the persistence of a negative trait for the individual until it was beneficial. The idea that a developmental or genetic constraint can become useful later is not group selection.
– In a sense, yes.
– Not in that framing, no. However, the idea that a group with such a constraint can be selected over a group without that constraint, is a (very specific kind of) group selection.
It’s a very subtle distinction, which my example may not be doing much for.
Perhaps a better example would be two groups, one of which has a genetic complex that means growth over a certain size results in death. Assuming there is local pressure (as seems historically common among fauna) for species to grow larger, and given there are periodic incidents (again, as seems historically common) which cause the disproportionate extinction of larger fauna, there will be a kind of long-term group selection for the group that has the genetic complex that kills individuals that grow over a certain size.
Now, this is not to say that group selection of this kind overrides or invalidates individual (and in particular individual gene) selection – individual selection never stops, certainly not “in favor” of group selection. However, it does meet the criteria for group selection, in that species considered as a whole can have a kind of selective pressure.
Of relevance to this discussion, this kind of selection – in a sense, the evolution of evolvability, both in terms of additional “options” for evolving (for example, redundancy, permitting more complexity, or better or worse error checking, which may affect the rate of evolution) and in terms of constraints – can adjust slack itself, increasing or decreasing it over very long time-frames.
I’m unconvinced of the utility of Slack. Why is the marginal benefit of Eye Part 1 lower on this hypothetical planet even if the total benefit of eyes is supposed to be similar? A priori the benefit of Eye Part 1 on our own planet doesn’t seem that high, but evidently it was enough. You mention islands as places with more slack, but I’m unaware of useful features like eyes appearing on islands first. Instead when there’s long separation between a small population like and island and a large population like a continent, an eventual crossover typically results in the species from the larger population outcompeting those of the island. And as people have noted with reference to Guns, Germs and Steel, the Aztecs hardly outcompeted the Europeans, and it wasn’t because of competition with the Incas.
I am using a certain kind of $20 on the sidewalk logic: evolutionary biologists would have come up with something like Slack and used in models if it actually helped to explain anything, rather than Zvi. They’ve already devoted a lot of work to group-selection even though the math weighs against it.
I’m also confused by your inconsistentcy in determining Slack in real-life civilization. You say “Others had more Slack” because Greece wasn’t unified while Egypt was, but shouldn’t competition between Greek city states mean LESS slack? After all, later in the same paragraph you describe Egypt as without much competition. I had also never heard that Scythia was more competitive than Greece.
My prediction is that little will come of the Long Term Stock Exchange because the common story about publicly listed corporations overly discounting the future is simply wrong. The decline in IPOs is due to regulation, and this new exchange probably won’t be able to get around that.
They already do. Mutation-selection balance introduces a level of “noise” into fitness landscapes, and sexual reproduction allowing massive recombination of genes allow individuals to “jump around” on fitness landscapes (in some cases). The idea that if a trait is highly variable, individuals can jump fitness valleys is well-established in evolutionary biology.
Is there an existing term they use instead of “slack”?
The most common I’ve heard is “standing variation”, representing the typical phenotypic or genotypic diversity in a population (maintained by various factors like mutation, gene flow, etc.)
“Standing variation” isn’t really an equivalent to “slack” or the opposite of “competition”. A larger population will have more mutations for variation, and also more competition.
“Genetic drift” is probably the closest. It’s maybe more of a population genetics term than an evolutionary biology term, but I think most biologists would understand what you meant by “drift” if you used it instead of “slack”.
I read the idea of the Aztecs outcompeting the Eurasian societies as purely for the purpose of the hypothetical.
It also matches how Civ 1 works under certain settings. (The Americans only get added with 7 players, so otherwise the Aztecs have the entire Americas to themselves).
It’s probably worth considering that this X/Y ratio is most likely highly specific to the business in question. I can imagine in a car dealership the best ratio is heavily weighted to the individualistic side of things, as most of your staff are directly shifting product and no one really needs to support each other in order to do their jobs. However, if you tried to put the same incentive structure into a web-development studio you’d just end up with six different code bases, all of which are missing critical features and none of which can be sold to anyone.
Perhaps there are industries for which the extremes are actually the best option, certain co-operative supermarkets work quite well, but it seems Seers was not one of these.
This is a super interesting subject. I’m not an expert but there is a mathematical framework that deals with exploring multi dimensional multi modal function spaces. https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo. Lots has been written about the optimal size of the jumps, as well as how probably you should be accepting a certain amount of bad jumps while exploring the space so as not to get stuck in local minimums (see https://en.wikipedia.org/wiki/Metropolis%E2%80%93Hastings_algorithm) (I think Andrew Gelman proved some results here). Getting stuck too long is called “bad mixing”. There are newer algorithms inspired by physics such as https://en.wikipedia.org/wiki/Hamiltonian_Monte_Carlo that attempt to introduce what I would describe as unbiased biases into the jump patterns, so that the algorithm explores greater space but still in proportion to the function (for example instead of exploring one side of a multidimensional peak first and then the other, the jump pattern is biased to kinda circle and spiral around peaks allowing it to more quickly discover other peaks.
I know little about genetics but reading about the different monte carlo methods has made me wonder if the dominant-recessive gene scheme as something to do with keeping some genes dormant because they may be detrimental by themselves but might be useful if they later appeared in combination with other dormant genes. It could be a way to provide increase likelihood for spontaneous larger jumps, or provide “slack” as you call it.
Edit: Here is an interesting thread on Hamiltonian Monte Carlo: https://twitter.com/betanalpha/status/1234576972132626445
Also here is the more approachable website that got me interested in the subject: https://probmods.org/ (and I think it originates from a Department of Psychology, not Mathematics).
Slack is unstringing the bow (and when I went to look this up to check that I was correct, there seems to be a weird number of religious sites using this as a metaphor and guide of discipline).
Sounds like Lampert should have read St. Paul rather than Rand. Competition between individual organisms is beneficial, competition between your internal organs is decidedly not so.
Your 3-player Civ example isn’t really accurate, Or rather it is accurate only when both Old-World players are equally bad at the game. Otherwise, there are two possibilities:
A) One player is worse than the other. He will be swiftly conquered and the good player will use this extra territory to overwhelm the Aztecs. The Aztecs can do nothing to stop this.
B) Both players are equally good. They go through the same considerations you described in the 4-player example, and they both agree to cooperate before the missing 3rd player can steal the game. Tech trading alone allows them both to completely outpace Aztec science. The Aztecs can do nothing to stop this.
For this reason, starting alone in your own continent in Civ is a major DISadvantage.
I know this wasn’t the explicit intent, but this is the first argument I’ve read that convinced me that Malthusian Competition and the Repugnant Conclusion, are actually bad states for humanity to be in. All the other arguments focus on how bad it would be to live in those times, but with total utilitarian beliefs, I was unconvinced. This makes a strong argument that a society in total competition might be good in the short term, but it would lose out on long term gains. Worse, we may never know what long term gains we missed. Some slack in the system is best for the long term.
I think Ibn Khaldun would disagree that societies with Slack will outcompete ones without it.
This is exceptionally good even by SSC standards.
Since nitpicking is compulsory around here, I’ll point out that Soliloquies on Slack would have been a slightly better title.
This marginally reduces my expectation of being turned into paperclips. The maximizer should experiment with which types of matter to utilize for what, and would probably find that giving humans some slack (so they can invent new stuff) while not giving slack to rocks outcompetes the opposite strategy.
It seems very unlikely that the insights humans could offer a superintelligent paperclip-maximizer would be worth expending tons of precious non-paperclip matter to support them. It’d be like humans spending ages reading randomly-generated text strings on the off chance one of them randomly contains insight, or spending millions on a university for gorillas and chimps who speak sign language.
If they were worth it, it’d probably look more like “simulated humans trapped in a paperclip-themed skinner-box universe where they have to find ways to maximize paperclips for food, running in the corner of a server somewhere” than “not destroying the Earth”.
Great, fascinating and enlightening post as usual. I believe the Revolutions podcaster Mike Duncan suggested that King Charles I (beheaded in England) ignored everyone’s advice and stubbornly went his own way, while King Louis XVI (beheaded in France) took everyone’s advice and didn’t know his own mind.
It reminds me of Acemoglu and Robinson’s “narrow corridor” between authoritarianism and anarchy.
I wonder if the Catholic monk of the 12th century might be easier to convince than you think? I was under the impression that the medieval Latin Church was relatively open to allegorical interpretations of the Old Testament. Wikipedia tells me that St Augustine, for example, rejected the idea that the world was made in literally seven days.
I don’t think “slack” is good way to analyze Louis XVI’s behavior.
If we really want to narrow the French Revolution to a single cause, it would be that the one policy that could have ended the economic crisis was opposed by the entire ruling class (because that policy was to tax the ruling class).
But realistically, there’s a thousand different factors that went into the revolution, and Louis XVI being an indecisive ruler was only one of them.
Comparing this to Acemoglu & Robinson’s Narrow Corridor just makes me even more skeptical. I think institutions are a useful explanation for North vs South Korea, but treating malaria as a proxy for colonial institutions and assuming it can’t have any independent effects really seems like begging to be wrong.
I didn’t like the evolution analogy. Specifically, I don’t think relaxed selection would make evolution better at evolving complex machinery. The space of possibilities is so vast, and the space of multistep complex machinery so tiny, that I don’t think the math works out. You would do better to have stronger selection, and evolve complex machinery where every step is beneficial. (This is based on intuition, not direct simulation, so could be wrong.)
Another issue is that in evolution selection doesn’t just help you build new machinery, it helps to maintain the existing machinery. A big problem is mutational load. Purifying selection keeps load down, and enables more precise and complex machinery to function.
(A possible counterexample is the evolution of human intelligence if it is a case of Fisherian runaway, which requires some slack to work. Personally I don’t believe this hypothesis. All other cases I know of Fisherian runaway have been bad.)
This is a bit different from the case of intelligent agents like humans who can construct multistep plans in our minds. Now having enough “slack” to allow long-term plans to bear fruit might be a good thing.
Anyway, keep up the good posting.
I hereby commit to not commenting further on this post.
Slack is better known as “temperature” in simulated annealing, suggesting the optimal strategy is to start with lots of slack, and gradually reducing it (provided the fitness landscape is static).
Regarding the “landscape” metaphor – local optima in the “free energy” landscape, like the puddle vs. pit comparison, seem inevitable when plotted out in two dimensions as above. However, in a complex multidimensional landscape, local optima become much rarer.
Think of it this way: if there’s a 50-50 chance of the free energy gradient being either up or down in any given direction at any given point, there’s a 25% chance of being at a local optimum at any given point in a 2-D landscape. Sounds like you’re going to get stuck, right? However, each additional dimension you add to the landscape divides the probability of any given point being a local optimum in half. Once you have a 10-D landscape, the odds of any given point being a local optimum are less than 0.1%. Instead of local optima, you end up with a bunch of saddle points, and eventually, the agent in question (algorithm, organism, ecosystem, whatever) will iterate its way out of the saddle point.
In nature, we see this kind of effect in heterogenous nucleation of crystals in supercooled liquids – for example, ice. The bulk of the cooling liquid is in a metastable thermodynamic equilibrium (local optimum) where crystal nucleation seems unlikely. However, the parts of the cooling liquid that are in contact with the surfaces of the mold in which it is contained provide nucleation sites, knocking the liquid out of its equilibrium and forcing it to crystallize. Considering only the bulk, the liquid appears to be at a local optimum where it will never crystallize. Considering the liquid as a whole, it is in reality at a saddle point where crystallization just takes a little extra time.
Edit: Damn it, @Krisztian made this point already.
Quite a bit there. Talking about evolution without talking about cooperation with eco systems, I can understand as a way to focus on a specific aspect of evolution but when you pull it all together you have to deal with the whole theory. I’m uncomfortable, as a systems biologist, with the arguments being made. That said, the history of Japanese imports to the Unites States, was people in US started buying, the UAW insisted on tariffs. Imports nearly stoped. Goldman Sachs presented a plan to Japan Inc to build plants in the US and Goldman would funded them. Being vastly superior to the domestic product, they Japanese succeeded wildly. That may also have been the last time Goldman ever did any useful in the real world.
You’re worried that your local sub population is going to be outcompeted by some slightly better but not very good outside population before you have the chance to get really good. So you build a wall. Great! Now your sub population can flourish with local competition, stimulating but not fatal, allowing you to “evolve” new and powerful systems that are now ready to crush that population you built the wall to keep out. Great!
But there are a few problems:
1) You better be darn sure the local optimum inside the wall is better than the one outside it. Consider the car industries – Japan successfully protected itself long enough to create a globally competitive industry with innovative processes and a quality product. The United States protected itself long enough to stagnate, ossify, and optimize for goals other than “produce high quality affordable cars”. So when the Japanese started showing up with cars good enough to compete despite tariffs, the competition was nearly fatal. Slightly lower walls may have been beneficial, to force the Americans to adapt when they were a little behind instead of significantly inferior.
Or consider the Aztecs. The Atlantic Ocean protected them from competitors from the Med and Europe, allowing them to build a powerful Mesoamerican empire. But when the competition finally got good enough to cross the Atlantic, the Aztecs were unprepared and crushed. Had the interchange started when the respective civilizations were more “on par”, perhaps the Aztecs (or their predecessors) could have adapted and survived. Rome crushed various barbarian tribes, but coexisted with the Parthians and Sassanids. Both Rome and the Persian empires were replaced, but replaced by near-peers that absorbed a lot of Roman and Persian culture, while the Aztecs were basically wiped away.
2) Walls have two sides, and you need to make sure you really don’t care about anyone outside the wall. Consider a country that has a very strong labor movement and gets laws passed that make it very hard to fire people. This is good for the currently employed, but very bad for people trying to break into the labor market. You end up with a good stable working class with plenty of slack to innovate, but a growing and probably restless underclass.
Also, the Japanese protectionism was good for the auto makers, and good long term for consumers, but lousy for consumers in the short term, forcing them to live with more expensive and/or crappier cars than necessary for some time. You better make sure the long term trade is actually worth it.
3) Walls promote competing inside the walls, and ignoring the world outside the walls. Consider Westeros – a massive Wall protected them from a supernatural threat that would crush them if allowed inside. But rather than use the resulting slack to build up a powerful unified culture and new technology with the ability to beat the external threat, they engaged in petty squabbling amongst themselves and were completely unprepared when the Wall failed.
To some degree this happened to Rome as well – they wasted a lot of resources on civil wars while the scattered tribes on and outside their borders started unifying and becoming more state-like, eventually becoming powerful enough to challenge Roman authority and hack off bits until the Western empire fell apart.
Basically, walls give you slack. Slack can give you room to innovate, but it can also give you room to stagnate. Or, even worse, give you the room to forget the real competition and waste resources on destructive internal competition. You might protect yourself from smallpox, but be more susceptible to old age and cancer.
Just a side point. Inferential range – it occurs to me you can short-circuit a lot of the conversation with the monk if you just say “I don’t know”, and maybe bring Occam into the discussion. This way you can skip everything related to evolution.
And I think that’s a skill. Of rhetoric, of psychology, of… sales? Finding a shorter inferential distance on a given topic, and a good way to bridge it. This makes me a bit optimistic – I don’t think there’s such a thing as a fixed “inferential range”, as much as I like the concept.
Not sure this is true – the monk has what looks like a knock-down argument against your claim. If you say you don’t know why it’s wrong, he’d be correct to doubt you. If I gave you a perpetual motion blueprint, and you said “Why doesn’t that violate thermodynamics?” and I said “I don’t know”, you would throw it out, and rightly so.
No no, “I don’t know how the world came to be, and neither do you, not for sure”. Then Occam, with showing that accepting the bible multiplies entities without solving the issue. It’s not a simple argument, but it’s one that a medieval monk is prepared to understand (Occam was a medieval monk, after all). Bringing evolution into the discussion is a very roundabout way of making the point, and to be honest one I don’t actually see working. I don’t think even an educated contemporary understands evolution well enough to prove it from first principles, without going to the Galapagos Islands for proof or spending a decade gardening.
So evolution doesn’t make the best path to closing the inferential distance (but it does make a good example for your point – I’m not criticising that). And if there are multiple paths to get there, there’s no fixed inferential range to speak of. And also there’s a skill/art to closing that distance.
Boeing seems like a weird example of a monopoly, given the existence of Airbus. If anything, it’s a pretty good example of what it takes to overcome an effective monopoly (McDonnell Douglas was kind of a basket case from the early 80s on). The combined governments of Europe have more slack than even Jeff Bezos, and today, their company has about 50% of the market and makes pretty good planes. (I’ll leave the argument of which one is better for another day.)
Yeah, I was about to post that too.
Boeing isn’t an example of an organic monopoly, it’s a government-enforced monopoly, with both subsidies (in the form of defense contracts) and importation tariffs.
I don’t know how much that impacts the article’s “everything is about slack” metaphor, but I think Scott’s model really kind of breaks down once we consider entrenched interests.
Boeing isn’t a monopoly of any sort. US airlines are generally free to buy any planes they want, and quite a few have found it worthwhile to pay the tariffs for Airbus planes. I’m not sure I agree with this because Delta has beaten the protectionist drum enough I think they should be forced to buy from Boeing, but that’s an exception to my general thoughts on free trade. The only time recently when Boeing tried to get heavy tariffs on a (semi) competing plane it backfired spectacularly, with Airbus scooping up what is now the A200 and building it in Alabama.
I’d also argue that defense contracts aren’t a subsidy. Boeing Defense and Boeing Commercial are separate inside the company, and each side is expected to be profitable in its own right. Yes, there’s some overlap, particularly of Boeing Defense selling converted airliners, (the only serious monopoly the company has) but those are products that have been in production for a long time and earned their keep on the commercial market first. Also, the biggest of those recently (the KC-46) has been something of a disaster, so they’re probably not making bank off of it.
The biologist John Tyler Bonner argued that this has been kind of a linear process where slack is needed to evolve the mechanisms that reduce slack and accelerate evolution. Single-celled organisms had very little competition, which gave them enough slack that they eventually evolved sex, which seems like one of those things wouldn’t have been selected for in the short term. Sex then drives intraspecies competition and thus more rapid evolution, but there’s still very little interspecies competition, which gives enough slack for multicellular organisms to evolve–so now you have large, fast-moving predators and most of the slack gets literally eaten. And now human cultural evolution means the world changes more rapidly still, and other multicellular species face even more brutal selection pressure.
One point that is perhaps so obvious you didn’t feel the need to point it out. Slack doesn’t always produce long-term benefits. To return to the drawing of the puddle, the water will never find the pit if it starts climbing the hillock in the wrong direction. And of course it may be a puddle that’s nowhere near any kind of pit. As such, it’ll only be the rare slack civilization that thrives in the long-term.
This is one of my favorite topics, and you reminded me of Kenneth Stanley’s work on this. He gave a great talk here:
In his book on the topic he introduces the concept of “local competition” to get around the problems of too much competition. In his view the diversity produced by evolution is not a product of competition, but a product of trying to escape from competition. If there was global competition among all animals, there would be little diversity and one animal would soon win out. But if one animal manages to escape into a new niche, suddenly it only has to deal with local competition within that niche. Like escaping from the ocean onto land. Or into the air. Or over into the next valley. (or to a colder/hotter latitude) Or how giraffes grew taller necks to not have to compete with other grazing animals.
You can see the problems of global competition all over the place: Reddit is more successful than digg was in part because the subreddits allow local competition. The frontpage will always turn into a lowest-common-demonitator mess of global competition, but subreddits can help you escape from that.
The theory of economic disruption is also one of escaping into local competition: You make a new product and instead of competing with the existing market leader head-on, you compete in a smaller market that they don’t care about, like for the lowest price products. Then once you had time to develop there, you can challenge them in more markets.
Or an example of where this failed is mobile phone games: When they first came about, there was widespread optimism that we would see great new innovative games come out of mobile phones. There were similarities to browser games or to the Nintendo DS: low-powered environments where entering the market was cheap and you saw lots of innovation. But the difference between mobile phones and browser games is one of local competition vs global competition: The Android Play Store has very limited space and only displays the most popular games. So everybody has to compete for that in global competition. If you compare that to websites for old browser games, you see that those made it easy to discover lots of games. And there wasn’t just one page, but there were many pages dedicated to different niches. (like websites dedicated to Room Escape games, which became so popular that they spilled over into real life) In local competition like that you see diversity flourish, in global competition like on the mobile phone marketplaces you see it die out in a sad mess that leads to lowest-common-denominator games that use gambling mechanics and psychological tricks to earn as much money as possible.
I think the theory of local competition fits really well with your theory of required slack: Local competition gives you slack, at least until your new local niche becomes crowded.
I think he also had a concept of “gentle competition” which is probably exactly what you mean with slack, but my memories about that part are more vague. Or maybe he just didn’t have much to say about it in the book…
Oh also I wrote a related blog post a while ago:
Ah, this post made me realize something!
At first, I was confused by its relationship to the Moloch post — it seemed as if the latter had already taken the former into account. As I understood the Moloch post, the gist was essentially “optimization eventually destroys all value not perfectly aligned with the objective function.” And this post just seems to recap some feature that characterize good strategies for doing optimization.
Yes, these strategies may feel counterintuitive, in that they optimize X (the outer objective) well by saying “don’t optimize Y (an inner objective)!”. But at the end of the day, no one asked you to optimize Y anyway, they asked you to optimize X, and this is how you do it . . . and, if optimization eventually destroys all value not perfectly aligned with the objective function, then this still destroys all value eventually by trading it for more X.
However, that just assumes that “value” can always be traded off for X indefinitely so long as the amount of value is nonzero. One way of reading this post is as a series of examples showing how contingent this assumption is.
If value lives on the outer layer, it competes with X (if it isn’t just precisely “X”). But if it lives on the inner layer, X’s implications for value are less determinate and the two can be relatively harmonious.
And when we think about where value intuitively seems to live, it can really be in either place, depending on the situation. In multicellular life, we might imagine it’d be “nice” to be the cells if it were like anything at all to be the cells, but (most of us believe) the cells have no experiences; the experiences happen in the organisms, for whom the phenomenon is not so nice. In the theory of the firm as internally cooperative, the experiencers are the individuals inside (and it’s nice for them); it might be unpleasant to be the firm, but in fact it’s not like anything to be a firm, so that’s fine. And in the case of protectionism, neither the inner layer (companies) nor the other layer (national economies) have experiences.
In other words, we can’t analyze “what does optimization do to value?” without having some account of what value is, where it lives. This is not immediately obvious, because it seems to take us far afield from this self-contained game-theory stuff into a very different kind of philosophy. But once we’ve said the word “value,” we’re doing that kind of philosophy too. For Moloch to be recognizably bad, we need a positive account of what it means for anything to be bad — but once we bring that into the picture, the apparent inevitability of Moloch’s badness seems in danger of collapse.
Wow! Well worth the 2 hours I spent reading it! There’s a whole lifetime’s worth of wisdom here.
RE 6. That Time Ayn Rand Destroyed Sears.
I haven’t read it, but it sounds exactly like they took Econ 101, and then implemented some policies before getting to econ 201 and realizing what they did wrong. Based on how you described it, they failed to consider the profit maximizing operation of vertically integrated firms. Vertically integrated firms can be more efficient and increase profits for both the firm, and increase supply to consumers at a lower cost, because they can avoid the problem of double marginalization. I wont get into a long explanation (because I cannot recall enough from my intermediate micro economics course) but basically the firm profit maximization will call for pricing at marginal cost for one (or more) division (for upstream or, input divisions). This would not happen if divisions are “competing” with each other. I also recall it differs a bit based on how much outside competition there is in the market for inputs, but I cannot recall enough to explain how it changes.
So, I would disagree that this particular example fits with the others about finding the right “balance” of competition vs cooperation. Basically you just have to do some microeconomics to figure out how to maximize profits.
It is more that they hired the CEO to try a desperate gamble to save a dying company and it didn’t work. It is like why most of the restaurants that Gordon Ramsay helps on his show fail, once a company is going down it is very hard to turn it around so even good ideas are unlikely to work. Walmart and Target had turned the department stores business model into an impossible situation, and the real estate that was once there primary asset became an chain around their necks. They have been in decline since 1972 and have survived since 2000 by selling off parts of their business to keep the lights on.
The randian CEO may have done a bad job, but the ship was sinking before he got on.
I think it’s both true that Sears was already dying and that Lampert’s internal markets did not work out well. The authors of The People’s Republic of Walmart also mention that Sears had not been turning a profit for two years when Lampert took over (in 2013). Here are some passages from that book, which I recommend to anyone who is not put off by Left literature:
I think it’s important to note that whatever else Lampert intended to do with Sears, he also intended to play a game at the end of which Lampert’s left hand through Sears would have sold all Sears’ property to Lampert’s right hand through ESL Investments, Lampert’s personal hedge fund, so that Lampert was left owning lots of valuable retail real estate and Sears was left holding lots of expensive leases payable to Lampert. That Lampert ran both companies and stood to personally benefit from this arrangement is the subject of some legal dispute at the moment. Perhaps selling off everything not nailed down would have looked less favorable had Lampert managed Sears better in the years leading up to the eventual bankruptcy, but that seems to have been of secondary importance. He did manage to make sure he was also the #1 secured creditor when the house of cards began to tumble. Arranging to be the CEO, board chairman, lender, and landlord all at once sounds just about right for a former Goldman Sachs employee with a yacht named “Fountainhead”. If he’d been intending all along to set employees against each other so no one was looking as he stripped the flesh from the carcass and left the bones behind, what would he have done differently?
I agree that Sears was dead before Lampert showed up. It had survived a few very significant changes in industry — it was the Amazon of three generations ago, doing mail order for the entire country, without the hassle of storefronts. Then they muscled into the storefront market. They couldn’t re-adapt yet again.
If you read this in Popeye’s voice the typo becomes a beautiful nautical theme.
capitalist economies beat socialist
On capitalist metrics, which is the inherent question begging that always rides shotgun on this argument.
Which metrics do socialist economies excel at?
I think socialist countries claim to care about the standard of living of their people, which is why ostensibly socialist governments will often act like capitalist ones.
I think the way to compare countries without choosing “capitalist” or “socialist” metrics is to look at how people “vote with their feet”.
Yeah, I would agree. The walls around socialist countries always seemed to point inwards. I am wondering what Freddie says though.
As always, Scott is presuming that “socialism” doesn’t include the self-described socialist parties of western and northern Europe who implemented high levels of state ownership, resulting in what most people would consider “success”.
I’m honestly not too hung up on this. If he wants to insist, in an ahistorical and highly US-centric manner, that the term “socialism” should be reserved for countries like the USSR and Maoist China, that’s fine. Just so long as he doesn’t turn around and use “opposition to socialism” it as a cudgel against implementing economic regulations and state ownership.
Speaking of slack….
Thomas Kuhn was wrong about Heliocentrism vs Copernicus. Frank Tipler:
“There has been a tendency among theoretical physicists, particularly string theorists, to downplay the importance of experimental confirmation in recent years. Many have even claimed that Copernicus was not superior in predictive power over Ptolemy. I myself decided to check this claim, by looking at Tycho’s notebooks. I discovered that between 1564 and 1601, Tycho compared Copernicus’s predictions and Ptolemy’s predictions with his own observations 294 times. As I expected, Copernicus was superior. So Copernicus’ theory was confirmed as experimentally superior to Ptolemy long before Galileo. So I have put the Copernicus-was-no-better-than-Ptolemy idea to the (historical) experimental test, and found that it is false: Copernicus Trumps Ptolemy.”
It would be more accurate to claim that Copernicus’ theory was NOT more parsimonious. It even had more epicycles! But it got rid of the equant, which Copernicus hated. I think their accuracy was relatively similar, but as observations got better Kepler’s superior theory managed to win out.
Rome and China spend the Stone, Bronze, and Iron Ages hacking each other to bits. Aztecs spend those Ages building cities, researching technologies, and building unique Wonders of the World that provide powerful bonuses. In 1492, they discover Galleons and start crossing the ocean. The powerful and advanced Aztec empire crushes the exhausted axe-wielding Romans and Chinese.
Okay, but why not this in the real world? I know the Aztecs had technological limitations, but they weren’t stupid, they were organised well above the ‘living in a hole in the ground’ level and they were living in a resource-rich continent.
Any takers for Explaining To Idiot Why Not The Aztecs?
My explanation (as well as an explanation supported by a sizable portion of those looking into the explanation of the “Great Divergence”) is that some of those in the Old World entered an era of partially CONSTRUCTIVE COMPETITION. This involved a constant arms race, not just for arms, but for technological, institutional and economic power. This allowed a few of the lucky ones to partially overcome the intrinsic tendency of societies to become lethargic, bureaucratic, rent seeking and change resistant.
The rest followed the examples of the current leader of the arms race, with new leaders occasionally taking the baton as the older leader decayed and fell to stagnation (Italy, Netherlands, Britain, US).
Have you read Guns, Germs, and Steel?
Assuming she hasn’t, here’s my recollection of the book’s argument:
1. Crops spread north or south slowly, because they have to keep adapting to different climates. But they can spread east and west very quickly.
2. Eurasia plus the north coast of Africa are an enormous region where crops could spread quickly, creating several connected civilizations each of which acquired new crops, livestock, and technology from the others. The rest of Africa is smaller and mostly oriented north-south, as is America. (Asia is easily bigger than both American continents put together.) America was also less connected for other reasons that I don’t remember. (The Aztecs and Mayans were at about the same latitude and about as close together as Greece and Rome, but had no connection as far as I know.)
3. Eurasia and Egypt lucked out and got nearly all the useful livestock. America got llamas, alpacas, and small dogs. (What about American bison? I don’t know.)
4. The New World caught Old World diseases to which they have no resistance, but not the other way around. Why? Because Eurasia and North Africa were a giant disease-pit, thanks to their big trade network, crowded cities, and livestock that like to crowd together. (Much earlier, Bantu-speaking peoples took over much of Africa thanks in part to farming practices that spread malaria.)
6. I don’t think this is in the book, but it makes sense to me: the Old World got a big head start. There were people in the Middle East an awfully long time before Central America, and I think the Middle East got crowded enough for agriculture a long time before Central America did. So it doesn’t surprise me that the Aztecs had technology comparable to the Middle East thousands of years earlier. (Corn and kings, but no metal or writing.)
According to that book, almost all big mammals are very hard to breed in captivity, with only around a dozen exceptions the vast majority of which happen to be native to Eurasia.
Lots of deserts and north-to-south mountain ranges further limiting east-west diffusion of crops/civilizations.
I don’t think #2 applies much to central America. When the Columbian exchange began, crops flowed west to east across the Atlantic, rather than vice versa. IE, Europeans started growing potatoes, corn and tomatoes, rather than the Aztecs all rushing to plant wheat and barley. Meso-American crops were generally more efficient per acre planted than the European alternatives. #3 is just wrong, I think. 4 and 6 were the most important factors, I believe.
Re: #4 and diseases, IIRC a big factor is that the Old World has Africa, where humans originated and many diseases co-evolved to target us, and where warm weather makes it easier for microorganisms to grow. Parts of the Americas have equally warm weather, but migrants to the Americas first had to pass near the North Pole, so they had freezing-climate-typical levels of infectious microrganisms. There wasn’t time for equally-deadly diseases to evolve in the Americas even where conditions were favourable. (Although note that the Columbian Exchange wasn’t totally one-sided disease-wise, just one-sided enough to be crippling.)
I have read dozens of books on the Great Divergence. And hundreds of articles. I have been studying it for about twenty years. GG&S wasn’t one of the more enlightening, but it is well written and interesting.
Again, if there is anything remotely close to a consensus on the issue, it would be that Europe entered an extended period of competition where instead of leading to consolidation and empire, or massive annihilation, we got an arms race that delivered science, effective state institutions and relatively free markets. These added to the discovery of “ghost acres” of recently “unpopulated” continents and usable coal led to technology, economic advance and an industrial revolution, which then led to lower birth rates, more education, higher productivity, higher living standards, better health, etc.
I think the Jared Diamond-level explanation is that the Old World got all the cool animals.
Like horses,donkeys and oxen to draw ploughs. And a jungle fowl that had evolved in an environment where the food supply suddenly spikes every decade or so (when the bamboo reproduces). So you can feed them and they keep laying eggs, and eventually you selectively breed chickens.
The Aztecs faced plenty of competition too; we don’t live in a world with exactly three cultures alotted by a videogame designer.
In fact, the Aztecs were an especially brutal empire who had recently risen to the top of the heap in their region, and their brutality and aggressiveness was arguably a big factor in their conquored peoples’ and neighbours siding with the invaders against them. They were literally the guys who conquored their area with stone axes in brutal war of all against all, only to be steamrolled by an opponent who had built up more advanced technology through cooperation. (Not that more peaceful cultures in more peaceful regions did much better, it’s just a coincidence that they resemble the analogy so well.)
I seriously enjoyed reading this and will be mulling over the ideas for a while, I feel like it’s helping me get un-stuck on a couple things I’ve been banging my head against for a while:
1. Education. I’ve been working in an urban charter school for the last year and have been amazed at how thoroughly and relentlessly the school (and system it’s embedded in) optimizes and competes for higher test scores. Teachers are required to give miniature assessments and the end of every lesson and re-teach to areas of weakness, a ton of focus on detecting and correcting misconceptions, etc. And still, even the “best”, most relentlessly optimized are barely able to boost performance by a few percentiles. I’ve had a nagging feeling that somehow by trying to optimize/compete so hard we shoot ourselves in the foot, given that the very best performing schools seem to be much more experimental and hands-off in their approaches and dedicate a hell of a lot more time in the day to things that don’t have any obvious connection to test scores (Finnish schools, whole-child private schools, etc). There are obviously a ton of variables at hand that play a role but the absence of slack in the high-competition new urban schooling model has to be part of it.
2. Entertainment. It’s been supremely bizarre watching TikTok rise in prevalence these past several months – other social media platforms have of course risen and fallen, but TikTok has managed to carry out a rise that feels inevitable and at the same time almost universally loathed, even by its users. People haven’t “jumped on board” with it so much as they have succumbed to it. It specializes in extremely short-form but high-stimulation entertainment, Moloch’s social media platform of choice. It’s incredibly easy and tempting to open up but also obviously unsatisfying – the opposite of long-form entertainment like television series, 80-hour games or novels where you have to endure a health amount of grind and moseying along but are rewarded with more meaningful revelations in the end.
It seems like education is an area where there has been lots of slack for a long time. Lots of school systems with big budgets and no meaningful competition have not produced any leaps forward in pedagogy but rather administrative bloat and great benefits for employees.
Situations with intense competitions are relatively new and don’t seem to be producing great leaps either in test scores but they do seem better on other metrics. My explanation is that there is room to make the awful mediocre, but there is a limit on how much schools can improve otherwise.
Central to my argument is that things like charter schools can’t move the needle much because they are running up against the limits of the natural talents of students, that our distribution of academic success is precisely what we should expect to find if we believe that there is such a thing as natural academic talent and that it is distributed more or less normally.
So maybe a little bit of internal conflict is good, to keep you honest. Too much conflict, and you tear yourselves apart and are easy prey for outsiders. Too little conflict, and you invent the cuckoo clock and nothing else. The continent that conquers the world will have enough pressure that its people want to innovate, and enough slack that they’re able to.
Insightful post! I read this paragraph and thought of Britain in the 18th and 19th centuries. It’s got a big moat around it, so it doesn’t have to maintain a large standing army, like the continental powers do. Therefore, it can use the resultant slack to invest in a big, capital-intensive navy that eventually outcompetes the hell out of everyone else. Thus, even though Britain is smaller and less wealthy than many of its continental rivals and they all have access to basically the same technology, Britain defeats France pretty handily in the Second Hundred Years War, and in the real life version of Age of Empires, it builds an empire many times the size of any of the other European colonial powers in the 19th century (unless you count Russia).
Yes, that makes for a world changing application of Slack. Thank you for the comment.
I would add that a lot of what Britain used to win the Second Hundred Years War are outgrowths of the 17th century.
• A broad tax base that successfully collected taxes with, ah, less resistance
• A great credit rating (you might say a sterling credit rating) that allowed for more and cheaper borrowing so that a country with less current income (Britain) could outspend France. I wonder if it is fair to say that being the world’s best credit provides Slack in Scott’s model?
• The naval building program got started right after the Civil War
• The ground forces were smaller but of higher quality than the French, which were also high quality, in the 18th century. Also, in the 19th century with the probable exception of the post Camp of Boulogne Grand Army for a few years
• The ending of the Dutch wars with the Glorious Revolution (call it the Dutch conquest of Britain, call it a merger as Niall Ferguson does)
The “basically the same technology” is true if you don’t count some social and manufacturing technologies.
I guess first you would have to grant me that the idea of a social technology is meaningful. The Admiralty ran on partially professional, partially meritocratic lines which was a great help in managing a multi ocean navy. The French aristocratic approach had more failure modes, though it had its successes too.
For manufacturing technologies, by the Napoleonic wars the British navy was able to mass produce blocks for much less cost than the French, though if you say superior seamanship was the secret of the Royal Navy’s success, I would not argue.
Yeah, you won’t get any argument from me about the value of social technology. I like Tom Ricks’ line that in military contexts, amateurs study tactics, professionals study logistics, but experts study personnel policy. But I also think you could consider the Brits’ ability to collect taxes and borrow money more efficiently than the French, as you mentioned, a kind of cultural or social technology as well. Thanks for the reply.
I wonder if current society has too much slack or not enough? Societies seem to generally tend toward more individual slack: socialized healthcare, social safety nets, various types of welfare, childcare, perhaps a UBI in the future etc. but also to some degree less slack in the form of regulations, minimum standards, two income families becoming the norm etc. (or are these better though of as changing the fitness landscape?). In particular, a bunch of arguments I’ve heard around UBI are phrased in terms of adding slack at the individual level, and there’s a lot of debate around whether that would lead to more or less human flourishing/fitness. I wonder if time varying UBI (alternate years?) or ones targeted substantially lower (the Schelling points seem to be 0$ or poverty line level income, but what about something around the global poverty line, say $2ppp/pp/day, that’s about the level of Alaska’s PFD, how does that look from slack perspective) would prove more optimal (for some notion of optimal). I guess FIRE individuals are also building personal slack (or for that matter, so is retirement in general), what do they end up doing?
It strikes me as kind of hard to tell between too much slack and not enough (realistically probably has too much in some places and too little in others). In the US for ex. new company formation has been on a downward trajectory. Is that from not enough slack reducing opporunities, changing fitness landscape, or too much slack leading to stagnation?
I don’t think looking at what FIRE individuals do is a great guide, there are some really strong selection pressures at play there. If your entire early life plan is to stop working, you’re probably not going to do that and be like “great, now I’ve got all this spare time I can use to work”
I think that raises an interesting question about the distinction between “work” and “productivity.” From my observation, FIRE-type people are generally trying to avoid stuff that looks like “work,” as in “working for the man.” But as far as I can tell, a majority of them are *very* productive. They build websites, or grow crops, or practice various crafts at a high level. They do lots of things that people get paid to do, but they do them on their own terms. Personally, I would bet that they’re more productive, on average, than the median employed person, if that were measurable…
The technical innovation space or entrepreneurial landscape provides an analogy of this as well (with a nod to concepts from The Innovator’s Dilemma).
Even a hypothetically very well run corporation that is at the top of its game is vulnerable to disruptive technologies. Disruptive technologies are not profitable in their early stages and trying to develop them is a huge gamble. A well-run corporation maximizing short term and even medium term profits, especially in tight competition, may be unable to devote any resources to such technologies.
Their future competition though, will come from one of dozens of entrepreneurs trying to develop the disruptive technologies. There is slack in this system because the entrepreneurs and the venture capitalists funding them can gamble on total losses as set against potential massive returns.
“Aristotle says that the mark of an educated man is to be able to entertain an idea without accepting it.” Does anyone know where he says this?
He didn’t. Real quote:
“for it is the mark of an educated person to search for the same kind of clarity in each topic to the extent that the nature of the matter accepts it”
“It is right that we ask [people] to accept each of the things which are said in the same way: for it is the mark of an educated person to search for the same kind of clarity in each topic to the extent that the nature of the matter accepts it. For it is similar to expect a mathematician to speak persuasively or for an orator to furnish clear proofs!
Each person judges well what they know and is thus a good critic of those things. For each thing in specific, someone must be educated [to be a critic]; to [be a critic in general] one must be educated about everything.”
– Aristotle, Nicomachean Ethics, 1 1094a24-1095a
I think the real quote is different enough from the one quoted to justify a small note of correction.
Thank you, that is very helpful.
I’ve read about group selection in a few contexts (I think first in The Righteous Mind) and I’m still not sure what its definition is precisely. My understanding was that group selection is when an organism evolves a behavior that hurts the survival of the organism’s genes but benefits the survival of the genes of some group the organism is a part of.
Since being cancerous doesn’t benefit even the cancerous cells, does it really count as group selection? Just because not being cancerous also happens to benefit nearby cells?
Taking the stricter definition of “it has to be bad for the individual”: imagine a group of organisms where, occasionally, one of them will go crazy and eat all available food, starving out the rest of the group. The rest of the group then dies, but the one that went crazy keeps reproducing and is fine (this is the important distinction from the cancer example). Then imagine there’s a gene that causes the organisms to sense when they’re about to go crazy and self-banish themselves. Such organisms starve in their banishment, but the rest of their group lives on.
I think this gene would get selected? Anyone who has this gene increases their chances for certain death by self-banishment, so for any given individual, having this gene is bad. But eventually, the groups that lack this gene dwindle in number, whereas the groups that have this gene survive. So you’ll eventually get a bunch of groups that have this gene. This seems closer to what I imagined “real” group selection was: strictly bad for the individual but good for the group, in a tragedy of the commons kind of way.
This ranks as one of my favorite SSC posts. Brilliant. Gets at some crucial things that seem so rarely comprehended when it comes to large-scale things, even though a lot of people probably intuitively notice similar patterns in situations more immediately relevant to them (different kinds of competitions exist, etc.)
The example of the car industry benefiting from slack ignores a historical point: Japanese cars began outcompeting American ones because during the oil shock in the 70s fuel economy became more important, this is pressure not slack.
As always, the answer is it’s both. All pressure all the time keeps you stuck in local equilibrium and keeps you from reaching a global equilibrium. All slack all the time and you probably never go anywhere at all.
Of course, the point is that it wasn’t just about efficient methods of car manufacturing gradually cultivated during a period of slack but about a previously minor fitness criteria suddenly becoming more selective.
Not sure either of these really disturb the points of your article, but…
Auto tariffs. This history sounded off to me and agreed doing some searching I’m not seeing much support for it. I see that in 1936 Japan passed a law kicking out foreign manufacturers. According to the all-knowing Wikipedia, Ford and GM were the major producers in Japan at the time and Ford was about to build a huge export factory in Japan. In any case, the story seems to be that after the war there were huge tariff barriers on pretty much everything, through some mix of the occupation being concerned about re-armament and corporatism. The genesis of the hyper-efficient manufacturing seems to have been intense competition between Japanese domestic car makers. It’s not clear why the story would have been any different without the tariffs, because becoming more efficient manufacturers would have been locally optimizing in either case.
My confidence level that I have this story right is low, but more generally I worry about the lesson. Sure, it’s possible that if you insulate firms from competition they will drift and break out of a local minima. But most of the time they will just earn more rents and you will be worse off.
investment horizons. That investors are myopic is one of those things everyone seems to say and accept as true, but without any evidence. There is no a priori reason why an investor intending to hold shares for a short period or a long period will have any different evaluation horizon for the company’s profits. Even if every investor held shares for only day and sold them the next, Day 1 investors will care what Day 2 investors are going to be willing to pay, who in turn will care about what Day 3 investors are willing to pay, and so on, forever, so that the Day 1 investors all still care about the expected value of the present value of the profit stream out to infinity.
And, indeed, we don’t observe any shortage of public companies that make losses quarter after quarter but have high stock prices in anticipation it is an for some future gains. For example, Amazon until recently, Uber, and the like.
Of course, in any present value, you will naturally care more about things that happen soon than you will things that happen later. And in any expectation value, you will also likely care more about things that happen sooner because you are more certain of them, and because there tend to be more ways plans can go wrong than they can go right. Add on top of that agency problems — is the CEO doing this grand project to generate some long run reward or just to boost his ego by empire building? Put all that together, and there is ample reason for investors to, in ordinary cases, focus much more on short-term profits. There’s not evidence they would actually do better if they took a longer run view given the circumstances.
That one I have much higher confidence in. (Though I think there are very separate and real benefits from being private, in particular that your investors are highly concentrated and have good incentives to give you advice and use their connections to help you, and that you can be more open in describing your future plans because they aren’t broadcast to your competitors. But those will be a problem in a longer-term exchange too.)
The Sears story is not one of competing business theories. Lampert is a hedge fund guy who bought Sears with borrowed money, pillaged its assets, piled on debt, made a fortune himself while driving the company into the ground. See for example https://www.reuters.com/article/us-sears-lawsuit/sears-sues-lampert-claiming-he-looted-assets-and-drove-it-into-bankruptcy-idUSKCN1RU1V3
Lampert did not invent this process. He is neither the first nor the last to do it. As a group, they bear great responsibility for the hollowing out of the American economy.
“If our epistemics make us more likely to converge on useful (not necessarily true!) ideas, we will succeed and our epistemic norms will catch on.“. I’m confused by this sentence. How is usefulness more important than truth?
I take it as a factual assertion, not a statement about relative importance. Being correct doesn’t necessarily make people want to copy you, in part because they may not be able to judge if you are correct, or because it doesn’t make a difference under the circumstances. Demonstrating something useful is very likely to make people want to try it for themselves. Useful things are usually true in some sense, but a lot of true things aren’t very useful to the average person.
Thanks that helps!
If you reduce a species to an abstraction and smear it out over time I can see how you can deny essences. But when I consider a species in the concrete here and now essences are clearly obvious. Individual members of a species don’t evolve for instance. Is there anyone writing about the distinction between abstraction and reality?
The average Joe in the first example fails to overtake Boeing in the first example, even given sufficient slack, because his original perception of the supposed better minima (where he can capture more customers) does not account for dynamic external factors. This is another reason why there needs to be a happy medium between competition and slack, whereas pure slack will leave you aimlessly wandering. Competition helps you understand the system’s current state with respect to your x-axis position on the landscape. As time progresses, competition may help you realize that your minima is not actually better, because of a system’s direct response to your current position (Boeing cutting prices), or because other players have simply gotten better over time (suppose the US invented flying cars while Japan was busy creating their cars). So there’s always risk that the minimum you originally wanted isn’t actually better once you’re there, even after spending the activation energy.
Regarding the fall of Sears: there is a company that successfully runs itself as an internal market: Koch Industries.
I vaguely recall that Koch Industries does some double counting in the system to give in house services an edge over outside contractors.
Studying their system in depth might be worthwhile.
Yeah, it’s not like Koch has lots of friends among the regulators… their system must be pretty good.
From what I’ve been able to gather Amazon as an internal market as well. To the point that every internal service has to treat everyone else as a consumer and once it reaches a level of maturity it’s released to the public at large and sold as a service to the broader public.
As far as I know, in Amazon, although different teams are responsible for creating and maintaining services, these are not actually bought and sold internally. They are provided for free for the rest of the company. So I think that’s an example of decentralisation, perhaps, but not of internal markets. I’m sure there are some Amazon employees here who can correct me if I’m wrong.
The authors of the article about Sears have a whole chapter on Amazon. Specifically they discuss distribution of goods, which seems to be centrally planned. They argue that Amazon and Walmart are examples of large organisations that effectively collect and organise information and distribute goods to where they need to be. Here are some passages:
They go on to mention chaotic storage and Amazon’s recommendation systems as examples of planned solutions for distribution and information problems, respectively.
Man, this is such a great post!
I wonder if the explore vs exploit trade-off might be an even better fit than the ‘competition’ frame?
In a static fitness landscape, the optimal solution is to start out doing a ton of exploration, and then gradually shift to exploitation over time. The point of exploring (i.e. slack) is only ever to get into a better position to exploit.
In a dynamic scenario, the optimal solution changes: you always want to keep some slack on hand to keep exploring, and avoid getting stuck in local minima. The corollary is that the less stable the environment is, the more valuable slack becomes (and vice versa).
Arguably we see this trend throughout history! For very long stretches of time, the fitness landscape barely changed. The fact that most people/institutions/countries had hardly any slack was optimal under those conditions.
So we can model the growth of civilization as a sort of recursive bootstrapping—there’s no point having slack until some other bastard has some, which makes the fitness environment a tiny bit less stable, which makes it slightly more worthwhile for you and your tribe to gather some slack, which changes the world a tiny bit faster, and makes it more adaptive for that other guy’s tribe to devote more resources away from pure exploitation, etc.
Now we’re at the point where history is being foisted upon us at an obnoxious rate, our cultural traditions contain unprecedented levels of slack. For example, the whole idea of ‘education’ is wild by the standards of almost all human history—a totally indulgent exploratory decade at the expense of your best crop-planting years!— let alone tenure, or bankruptcy, or free speech, or all our other crazy exploratory traditions.
I think this is more-or-less what we see: a mix of exploring and exploiting that happens both serially, and in parallel. On the national level: ‘fund a bunch of crazy stuff during good times; make cutbacks when the economy is doing bad’. On the family level: ‘you do your startup/artistic dream; I’ll support you with my boring accounting job’. On the individual level: ‘work hard for several years, then take a sabbatical to upskill/try a bunch of crazy shit’, etc. (I’m finishing up a book on the importance of individuals having slack, although I call it ‘optionality’).
The interesting political implication here is that as the world becomes more volatile, presumably we really should be prioritising whatever it is that gives people the slack to be boldly exploratory (maybe free speech, UBI or other wealth redistribution, etc).
Re: Sears being a competing group
A socialist group (i.e., a group working all towards one thing) will outdo a capitalist group (i.e., a group where people need to be bargained with to work towards one thing) if everyone in the first group can stay focused.
A good marriage is two people working towards a common goal. We’ve probably all seen marriages where the two parties compete against each other. They fail spectacularly.
I’ve seen some really good start-ups where there are a small group of people all go for one thing and grab it super-fast. I’ve also seen start-ups where one founder has a different end goal than everyone else and works and breaks the thing. The more people you have as founders, the more likely to hit this failure mode.
Large families can often work very well. Cults are extreme examples. Of course, cults also show the problem, in that groups can become abusive and work not towards things that are good for the group but towards things that are good for individual members.
Really good companies are often very socialist internally, keeping people from fighting each other.
Eventually, some people see the above idea and say “what if we got everyone working together,” and no matter how hard you explain to them how that doesn’t work and at best becomes the cult failure mode, they insist on trying anyway. Because wouldn’t it be awesome if it worked?
Imagine if it did though – A real life dragon’s den! That’s a heck of a premise for a fun video game.
Switzerland during the Renaissance had soldiers who were so awesome that they rented them out to everyone else on the continent and still guard the Pope to this day. Seems like the Build strategy paid off for them.
This is a great article.
While I’m not very familiar with the notion of “slack” specifically, the analogy to group selection reminds me of a paper by Terence Deacon:
Deacon, T. W. (2010). A role for relaxed selection in the evolution of the language capacity. Proceedings of the National Academy of Sciences, 107(Supplement 2), 9000-9006. (link to paper)
In general, there’s an emerging theory in research on the evolution of language that some of the seeds for the biological/physiological prerequisites for language may have been planted by “self-domestication”, which created what essentially amounts to what you describe here as slack––thereby allowing certain mutations to flourish that would ordinarily be selected against.
I also don’t think this implies that selection operates over groups per se. Natural selection can still operate at the level of genes (assuming that’s what evolutionary biologists tend to endorse). But groups are simply seen as a kind of ecosystem in which those genes exist.
This concept of “slack” as the ability to temporarily accept worse solutions to get out of local minima has a direct analogue in machine learning: simulated annealing. The “temperature” parameter (when it’s >0) allows it to move to a worse solution than the current one. How this works is that the acceptance function causes the state to move (in expectation, and in the limit as T -> 0) along the gradient of a smoothed version of the objective function. A similar thing happens in SGD (stochastic gradient descent): the stochasticity of the gradient estimate causes the state to change, not along the gradient of the objective function, but in expectation along the gradient of a smoothed objective. (A more explicit connection between SGD and SA is made in Mollifying Networks.)
This is similar to cyclical learning rates: higher learning rates amplify the noise in the gradient estimate. When they’re high, they allow it to break out of local minima (or narrow minima that don’t generalize; in ML the objective function we have is only an estimate of the true thing we want minimized), and when learning rates are low, it can actually converge instead of bouncing around.
There is an argument in here that fewer resources implies more competition, and more competition implies less variance, less variance means more likely to be stuck in a local minima. I’m not sure I buy the first step, or at least the definition of competitive needed forthe first step doesn’t match the definition needed for the second step.
Let’s take sports as an example. Having a large lead (having plenty of resources), will be non-competitive and will lead to high variance play like putting in back ups to see if they’re any better. Checks out. But having a large deficit will also lead to high variance play. In sports terms this is described as less competitive, though you could also say that the selection pressure is ‘stronger’ in some sense.
A more biological example are flatworms, certain species of which can reproduce either by low-variance asexual reproduction or high-variance sex. A slack theory might predict that in good times worms will tend to sex it up, and use their reprieve from competition to shoot for that super planarian. But in reality, flat worms are more likely to produce sexually when they’re feeling stress, presumably because if times are good that means their genes are good enough for the environment, whereas having more diversity could be useful to deal with challenges.
Anyway, one vote against a term that means both ‘has few constraints’ and ‘explores high variance strategies’ because a lot of systems have figured that gambling is only worth it when they’re desperate.
Yes, but who is that more likely to work out for? My sports knowledge is kind of weak so forgive me if I misunderstood your point. Assuming I didn’t:
The team that’s down a lot could try something new and have it pay off, but in a strictly competitive world, if they’re chronically down a lot, they probably are going to “die out,” or at least not go very far. And they bring in the high variance stuff in a desperate attempt to figure out a way to win. Whereas a team that regularly has a lead can regularly experiment with a whole host of things, and give somebody not all that promising some play time to see how it goes, and all that. They don’t have to optimize for a win at that point, because they already have it. There’s a bit more flexibility, a bit less pressure to conform to the immediate survival objective, etc. The team with the lead would seem to be a lot more likely to escape local minima, in terms of odds over time.
But, more than that, I don’t think it’s really about a strategic increase in variance under stress. Sure, that happens, and you get this variety of mutations, including some with initial eyeparts. But those are useless, even detrimental, and they die before getting the second eye part or the third. It’s more about having enough wiggle room that weird things can just continue to survive without their weirdness being an impediment to that. It’s just having a bunch of somewhat “sub-optimal” diversity around because there’s not strong pressure to be exactly one way. That takes enough resources for almost everyone to eat, not just the most efficient; to retain some level of unfitness long enough that it has time to actually become a survival advantage (a complete eye).
Did you ever read “Glory Season” by David Brin? It applies this concept to slightly bio-engineered humans on a colony planet. Children conceived in winter are exact (female) clones of their mother, but children conceived in summer are “vars” (what we consider normal). Society is dominated by clans of clone women who specialize in an economic niche, and smaller nomadic groups of men. Female vars are more-or-less destined for unpleasant jobs or entrepreneurship, with the most successful accumulating enough wealth to start a clan of their own. The story follows young identical twin vars, who start out planning to ‘seek their fortune in the outside world’, which for them includes running scams based on using their twinship to fool people into thinking that they’re part of a respectable clan… 😉
I’m immediately reminded of Bill Bryson’s observation that the 19th century English clergy was a hotbed of invention, from Bayesian reasoning to the power loom, by people who were in no meaningful sense employed to be inventors. It seems that if you take a bunch of very well-educated but somewhat eccentric people, give them a job with basically no meaningful obligations and nearly perfect job security, and wait, they’ll eventually start churning out world-changing ideas basically out of boredom.
Yes! This is a highly unappreciated thing–we need some sort of patronage system like this. Historically, it was mostly done by royalty and churches. They had resources to spare on retaining a group of brilliant eccentrics, who had the freedom and resources for independent creation. The results can’t be meaningfully planned, but history shows it to be a productive strategy.
That sort of total freedom is pretty hard to find in the modern world. DeepMind is the closest I can think of – a place where AI research do pretty much whatever they want with no requirement to progress to an end goal. Boston dynamics was pretty similar for a time – they were a bit more application oriented, but they were definitely geared more towards building cool robots than useful ones. Mathematicians have a great deal of freedom after tenure, to a large part because their research is so cheap to fund, but it’s been a long time since pure mathematics has produced world changing ideas.
A big problem is that it takes more resources to produce results in the modern world now that a lot of the low hanging fruit has been snatched.
Yeah, this must play a big role. I suspect that we’re missing some things right in front of us because so few people are free to really think about them in an independent manner. I think it is a mistake to try and get this sort of thing done almost solely by monetary incentives and team work. Seeing overlooked connections and figuring out the pattern often comes from individual obsession.
Plants developed light sensitivity in order to harness light energy for photosynthesis.
We usually think that animals’ eyes evolved to eventually be able to see. But I’m wondering to what extent initial light sensitivity in animals was driven by the path of warmth/energy rather than the path of vision. This may not be an original thought at all, but initial light sensitivity would have benefited animals by enabling them to move in the direction of better “basking” locations (like plants), increasing their metabolic speed and physical growth and therefore despite the “metabolic costliness” of light sensitivity development it would be actually be a net metabolic benefit. Light=warmth sensitivity then led to light=vision sensitivity to protect against environmental dangers (or to find prey).
A thought occurs: what’s the potential relationship between slack and cost disease?
“Slack” certainly exists in evolution but it needs to be no more than random chance. A fledgling organism carrying a weak advantage can be wiped out by random events very quickly and there is a whole theory on island biogeography that thrives on this. Similarly, incumbents can be wiped out by random events and can give originally weak challengers with a chance to prove their designs.
Furthermore the idea that the eye evolves part 1 with no or weak advantage, then has to wait for part 2, 3, 4 etc. to evolve in the same organism’s germ line to produce better and better results is exactly how it does not work in evolution – and one of the many reasons sex was invented. Sex creates recombination and allows with one stroke of the … well let’s not go there, to combine two advantages “developed” by chance and independently – in different organisms. Technological evolution works the same way of course. Evolutionary algorithms are based on recombination as well. Recombination by some accounts is far, far more important than random mutation in evolution, not the least because of Muller’s ratchet (most mutations are bad and if the genome gets long enough, any act of reproduction creates a worse outcome than the original on average, hence complex organisms limit the amount of mutations their genome allows and are stuck with recombination – but I disgress).
The most important feature Scott you did not mention, is called neutrality. Neutrality in evolution means that a whole bunch of changes (mutational or recombinatorial) are generally neutral to selection – they do not matter, because of built-in slack (redundancy) of genetic information. This allows complex genomes to “explore” neighboring areas of the fitness landscape. They effectively change the internal genetic information quite a bit while maintaining the same or similar fitness overall. Eventually, a small extra mutation happens and the fitness of the entire combination of previous changes is seemingly suddenly much higher – this explains radical evolutionary jumps that would have needed a lot of successive mutations or changes, and in fact have seen them, just not in an outwardly visible way. Kinda like in a country where seething resentment would lead to a revolution but all is quiet on the surface. Everybody goea about their same old ways without expressing their thoughts. Then, a single small event, and everything just suddenly switches to a new form of equilibrium / configuration / revolutionary movement, and no one saw it coming.
Economically and generally speaking, competition vs cooperation: competition is costly, but it is the only pressure that will lead to evolution. The main failure of communism was not brutality or less-than-perfect leaders – goodness knows those exist in democracies too – but stagnation. So competition is a first order cost that produces higher order advantages. Another facet here is that competitive adaptation usually produces efficiency advantages but not radical innovation. Radical innovation at first is usually less performing than the incumbents. So radical innovation needs situation of less competition (asteroid trike wiped out all your competitors, lots of empty niches; accidental oversupply of resources, for example from insane monopolist profits, allowing the monopolist to splurge on otherwise useless ideas. etc). So we have 2 forms of evolutionary mechanisms: Darwinian, under scarcity, leads to efficiency improvements of proven designs. Non Darwinian, under abundance or absence of competition. leads to radical innovation.
As a note, my first thought was, o wow finally this is being addressed – because I had my own set of thoughts about slack, including a book project of the same name… turns out you use the word in a more narrowly focused way on on bridging gaps in the fitness landscape. BTW – (most of the time, the fitness landscape is thought of as a space where the peaks are the highest fitness and the valleys are the low fitness areas needed to be bridged; the inverted low energy model with balls rolling downhill is usually used by physicists.
My thoughts on slack are more general, on the importance of tolerance (as in, mechanical tolerance), and I’d use slack as a metaphor for the need for tolerance width or intervals for any system to function. Biology is full of such slack too, so are economics and technology evolution, but it is not just the external slack that you are talking about, where the process of selection “allows” a small amount of “maladaptive” evolution. Rather, it is the internal, built-in slack, for example, the redundancy of the genetic code, that leads to neutrality or near neutrality. Neutrality in genetics (internally generated) has first been addressed by Kimura in 1968 . Neutrality in ecology (in essence, getting different species assemblages in the same environment depending on luck) was put forward most prominently by Hubbell 2001 , although building on previous models, especially island biogeography, in this context what matters most is his radical null hypothesis “maybe all species are equally fit” and how hard it is to show that they aren’t. Finally let me link also to genetic algorithms, Holland 1960, which often use both recombination and mutation to generate change. Both allow to jump over gaps in the fitness landscape btw – it is the visually appealing, Darwinian model of smooth and gradual fitness change that does not. But phenotypic jumps may well be generated by small genotypic changes, and recombination, as above, combines several advantages gained independently. Again to drive home the point of recombination. Sexual reproduction in humans, e.g., combines 2 times 23 parental chromosomes into a daughter organism. The number of possible chromosomal variants in sperm and egg is 2^23 respectively, through chromosome selection during meiosis, for a total number of possible genetic combinations in the offspring of (2^23)^2 , ca 70 trillion possible genetic combinations in the children from two same parents in humans, and that without adding a single mutation yet.
I don’t think this slack theory really applies to business and economics because there is a financial sector that can fund companies to get over the hump and into the deeper valley. Amazon made no profits for a decade by investors kept giving it money knowing that it had a strong long-term outlook and now it’s one of the world’s biggest companies.
Scott explicitly addresses that scenario.
Maybe (drawing here on the framework proposed in Dune) the best antitrust framework is one that allows monopolies to develop but breaks them up into a diaspora when they become sclerotic.
At first, the the monopoly functions as an incubator: it attracts a lot of smart people and surplus funding, and sets them to work on long-term projects. But as inventions accumulate the monopoly starts to function as a trap. The monopoly is in no particular rush to bring these technologies to market, especially when the technologies aren’t aligned with—or might even undermine—the company’s core business. And there’s no pressure on the monopoly to do so. So then we need to break the monopoly up, send the individual patents and engineers to different companies that will be under tremendous pressure to implement, release, and sell the handful of inventions they got in the breakup.
The traditional US mode of slow, adversarial antitrust may be unusually well suited to this! Rather than preventing monopolies from emerging, the antitrust system lets them emerge, gives them some decades to produce a lot of brilliant innovations—and then, when the monopoly is large, stagnant, and unpopular enough, the antitrust hammer comes down, it shatters the seedpod, and the innovations burst out and seed a lot of secondary companies throughout the market.
Of course, the system wasn’t designed for that purpose—it was an emergent result of antitrust reformers who wanted zero monopolies, individual monopolists fighting to hold onto their monopolies, and the underlying adversarial structure of US regulation and law. And the system itself may have collapsed—it’s hard to imagine Alphabet or Amazon knuckling under to a consent decree in the next decade or so—although perhaps it’s metastable on a longer timeframe.
This is an awesome mental model to assimilate, thanks for crafting it!
My company is a prime example of benefitting from
Slacker, slack. In 2008 I started a marketplace (bonanza.com) that was gradually refined into a revenue-creating engine over years. In 2015, I started wondering if evolving the main product (which competes against Amazon) was the most efficient use of the resources it generated. I determined it was not, and so started incubating two new products, GitClear and Amplenote. Both are classic “long uphill walks.” In the case of GitClear, we’re trying to weave a thread through every line of code to a single ancestor and kin line of code, which will allow us to group commits arbitrarily and save the 30% of time currently spent reviewing code that didn’t actually change (just got moved, find/replaced, etc). It’s taken us five years thus far, during which time our code interpretation has moved from 90% broken to about 10% broken.
Meanwhile, the world’s biggest richest companies (e.g., GitHub, GitLab, Bitbucket) are still stuck with v1 diff viewer/directory browser tools as they compete viciously against each other on price and feature parity. I can’t imagine they would ever try to build something like GitClear, because it takes an awful lot of slack to pursue what is essentially a 5 year research project.
This post inspires hope that even as we continue to toil away in anonymity year after year, the uniquely large amount of slack we’ve been afforded ought to become a differentiator on a sufficiently long time scale.
@scott – wouldn’t symbiotic lifeforms be an example of this? Each creature creates a bit of slack to the other in ways that don’t impact its own survival chances?
Great post! I really liked it and felt it was very thought provoking.
I have one criticism (which should in no way detract from my overall review of the piece, which I give a RottenTomatoes score of 93% – certified fresh). As always, Scott is too focused on Mistake Theory to recognize the usefulness of Conflict Theory as a solution to epistemic failure mode – namely, weaponizing new ideas and using them to destroy people who refuse to update to a more accurate paradigm.
That monk who refuses to listen to the time traveller and instead screams “Burn the heretic?” Well, if you shoot him, set fire to his church, and totally wipe out any of the townsfolk who support him, then not only are you solving the problem of this one asshole who refuses to update their epistemic beliefs, but you are also making it less likely that any other dumb primitives will yell “Burn the heretic” when you are trying to update them, because they saw exactly what happened to the last guy who tried that. Furthermore, from both a consequentialist and a utilitarian perspective, this is a very righteous thing to do. The monk is not just an asshole, but also a bad human being. His backwardness and refusal to open his mind to new perspectives causes a lot of damage to society. Kids die of preventable diseases because his backwards perspective means that cures cannot be invented. Peasants labor in hardship because people like him view labor-saving scientific advancement as heresy. So if you REALLY want to be a good person and advance society, making a horrible example out of people who refuse to question their own epistemic beliefs is overall just a really great policy. Sure, it’s not too pleasant for the INDIVIDUAL in question, but it’s really great for SOCIETY. And remember, the individual deserves to get hurt, because they are prioritizing their own selfish needs at the expense of society. By your own definition, they are cancer cells.
Does a cancer cell think of itself as bad? Probably not. Probably the cancer just wants to raise a family, have good relationships with its fellow cancer cells, and live a long and prosperous life. But that doesn’t change the fact that cancer is cancer, and needs to be excised if you care about the patient’s overall health. Similarly, people who act like cancer within the body of society – whether that is sociologists who damage the integrity of science by politicizing their work, social justice warriors who refuse to accept any scientific data that contradicts their left-wing views, NSA operatives who try to suppress truth in the name of “national security”, religious fanatics who believe that God forbids certain types of scientific advancements, or politicians who refuse to accept scientific data when making policy – well, we need to accept that all those types of people are cancerous, and deal with them appropriately. Anybody who tries to interfere with scientific progress is basically cancer, regardless of their motives or intent.
I suppose it’s unrealistic to expect that a group of rationalist aspies (and I number myself among such people) are going to “rise up” and initiate a revolution – and I’m certainly not calling for violence on this forum. But I view the rationalist community as a group where a lot of scientific advances are going to come from. And science can very easily be weaponized. AI, superforecasting, memetics – all of these tools are likely to emerge organically from the rationalist community, since we tend to be best at adapting to new paradigms. So all I’m saying is that when somebody in this community eventually DOES make a groundbreaking advance like this, we should put some thought into whom we allow to get their hands on this new technology. Because we all know that the NSA and various corporate interests are going to rush to seize control, and whomever gets control over this is going to have a lot of advantages over the people who don’t. So maybe instead of rolling over to the normies and letting them tell us how to use our knowledge for THEIR benefit, with no concern to what WE want or what WE feel is best for society, we should use our knowledge to force the normies to roll over to US and tell THEM what the new shape of society is going to look like. Because at the end of the day, a lot of normies in power are like that clueless monk – they THINK that they’re being good people, but their willingness to silence any controversial opinions that differ from their own effectively makes them a cancer on society. And hey, maybe we should be allowed to admit that fact and talk about it publicly, regardless of how uncomfortable it makes the cancer FEEL.
That monk who refuses to listen to the time traveller and instead screams “Burn the heretic?” Well, if you shoot him, set fire to his church, and totally wipe out any of the townsfolk who support him
Thank you for this efficient summary of why utilitarianism has been intuitively rejected by people for several centuries.
Yeah, this. Utilitarians ought to consider the utility of coming up with a whole new set of thought experiments that don’t involve deliberately killing people, and more generally developing rhetorical and analytical techniques that are robust against the temptation to easily justify killing people the thinker would rather not have to deal with.
For such allegedly rational people, both of you are making pretty irrational arguments. The second that monk screamed “burn the heretic,” he turned dialogue into conflict, and at that point he deserves everything he has coming. You should never feel ANY guilt at using retaliatory violence against anyone who initiates it at you.
Are either of you seriously arguing that you would not defend yourself against somebody who attacked you? Even if I were to believe that you are so meekly submissive (which, for the record, I do not), what right do you have to push that self-defeating ethical paradigm onto others? As Kanye would say, “that’s slave mentality.” I will be perfectly honest here: if somebody attacked me with violent intent, I would kill the shit out of them and then take proactive measures to minimize the chance of that ever happening again. I make no apology for that, nor am I at all embarrassed at saying so. The United States was built on that principle of self-defense – we even have it enshrined in law. So how are either of you two qualified to judge me for standing up for my right to defend myself against some violent backwards savage who doesn’t believe in science and wants to kill me because I won’t mindlessly parrot his views? That is literally the example Scott gave. Am I misrepresenting the scenario?
Be honest with me: are you really stigmatizing self-defense rights because you genuinely do not believe in them, or are you just virtue-signalling that intent because advocating self-defense rights is socially taboo in the blue state societies that most rationalists run in?
This is a pretty classic motte-and-bailey maneuver: in your first post you assert it’s right to kill the monk because of his “backwardness and refusal to open his mind to new perspectives”, then when challenged you assert that it’s a mere exercise of self-defense rights.
And all the townsfolk deserve it too, I guess? And you knew up front that this was an outcome with a significant probability attached. There are ethical systems where “look what you made me do!” is a legitimate defense, but from a utilitarian/consequentialist standpoint you just made a decision where the util ledger includes (p>>epsilon * one massacred town) and that’s on you.
Really, you made two lethally bad decisions, because if you can massacre the townsfolk you can just as well escape without killing them all. So this isn’t even one little bit “I had to kill them in self-defense”, this is “I wanted to kill them to stamp out the WrongThink”. Which was rather explicitly cited as one of the benefits of this plan.
If your ethical system winds up telling you to massacre people who disagree with you, you need a new ethical system.
First of all, I specified in my example that you should only massacre the specific townsfolk that supported the monk in his attempt to use violence against you. So when you claim that I am advocating for massacring ALL of the townsfolk, you’re deliberately misrepresenting my position. All I’m advocated is a pretty standard interpretation of Stand-Your-Ground laws. Whether you believe in Duty to Retreat is your call and many states have different opinions. Personally, I do not believe in them.
For the sake of the argument, let’s say that the whole town decides to rush me when the idiot monk stirs up a lynch mob. Then yes, they all deserve to die. In that particular thought experiment, my life is worth more than the entire population of that backwards town because THEY made the decision to initiate violence in response to dialogue, and I simply responded appropriately to defuse the threat. Whether I enjoyed exercising my legal rights in such a thorough way is completely irrelevant to the fact that I operated entirely within the parameters of self-defense law.
I think what makes your ethical system defective is that you are assuming every life has the same value. That’s manifestly untrue. Different lives have different values. Civilized people who operate within the boundaries of the law and attempt to resolve conflict through dialogue have a much higher value that backwards primitives who try to destroy anything that they don’t understand.
Isn’t that the point? The purpose of all those utilitarian thought experiments is to train people to accept doing evil today on the promise of benefits down the line. How are you going to get people to accept pointless wars of choice and hurting others in the name of properly aligning their incentives, if they hold to outdated beliefs like the golden rule?
Why would you want to, when it is so demonstrably easy to get people to accept pointless wars of choice, etc, for God or Patriotism or Revenge or any of the other usual reasons? I’m no big fan of utilitarianism, but people had been managing to justify bloody useless wars for at least fifty centuries before John Stuart Mill and Jeremy Bentham came along.
This post overlaps a great deal with my own series on this subject (Part 1 2 3 4), & I think some of the open questions you still have are addressed there.
I think the subject of the importance of Slack has already been adequately covered by these guys who I definitely never knew:
The Civilization digression sure brings back memories. As a kid, I played a lot of Sid Meier’s Civilization, and I would always choose the “Play on Earth” option and 4 players (so that the Aztecs are available but the Americans don’t exist) so I could get the entire Americas to myself. Then I’d amuse myself by colonizing the continents and rushing tech as fast as I could (hello, 3000 BC gunpowder) in peace. Although, around 1000 BC, barbarians started showing up, so you couldn’t quite forgo a military entirely.
Venkat Rao discusses similar themes in “Fat Thinking”: https://www.ribbonfarm.com/2016/07/28/fat-thinking-and-economies-of-variety/
But wait a moment. A lot of inventions were created during World War II. And the United States urged its nuclear bomb project out of fear that Germany might develop a bomb first. Isn’t that a very competitive environment? And then you could say the same about the space race during the Cold War. Isn’t that evidence against that you need slack for R&D?
Not really, who paid for the development of the bomb? The US government. They gave researchers, physicists and engineers a ton of slack to follow through with a project that might or might not work. Perhaps slack too general a concept.
I think it’s a perfect example of the need for slack. Note that it was the US who produced the manhattan project, and not any of the other belligerents. Only the US was rich enough (and untouched by war) to spend massive amounts of money on a speculative research project. Everyone else was just barely trying to survive and fund their war efforts, but the US could afford to do both.
Note in particular that the Manhattan Project was started while the United States was still technically at peace.
In that case, why would they be afraid that Germany gets its hand on a nuclear bomb before then? Was that just an unrealistic scare?
It was in fact an unrealistic scare, but Germany at the time did have a reputation for being at the forefront of science, technology, and engineering. And they were winning the sort of quick, decisive victories that made it look from the outside like they might have a fair bit of economic slack on the home front.
Hindsight is 20/20. Germany was never close to developing a bomb, but they couldn’t have known that at the time. They didn’t even know how hard it would be when they started. And Germany was a world leader in science before anti-semitism kicked out many of the top scientists.
Could the reason be that Lampert’s Sears isn’t quite analogous to actual capitalist economies? It seems like actual capitalist economies, rather than being 100% free-market, are some % competitive and some % cooperative, more analogous to the “normal businesses” Scott supposes would out-compete both Lampert’s Sears and the straw-man communist collective.
Excellent post as always, although I’m concerned that the monk story might be using an unnecessarily controversial assumption (i.e. mindkiller) as an example. Maybe consider replacing “atheism” with “biblical fallibility/non-literalism”?
This is the best argument in favor of tariffs that I’ve ever seen. I’m going to have to rethink the extent to which I favor free trade.
Almost every economic argument is much more nuanced in reality than the Econ 101 view would suggest.
That being said, you can’t just slap tariffs on things willy-nilly and hope for a miracle. And politicians have a poor track record on industrial policy and incentives to mess things up (tariffs are likely to be kept long beyond the point of usefulness due to the usual cronyism, status quo bias and the like).
A political factor is that a lot of people in your society might get angry about superior foreign products costing more while they wait for you to get your ass in gear, on the promise you’ve made that this is what will actually happen.
The biologist John Tyler Bonner argued that this has been kind of a linear process where slack is needed to evolve the mechanisms that reduce slack and accelerate evolution. Single-celled organisms had very little competition, which gave them enough slack that they eventually evolved sex, which seems like one of those things wouldn’t have been selected for in the short term. Sex then drives intraspecies competition and thus more rapid evolution, but there’s still very little interspecies competition, which gives enough slack for multicellular organisms to evolve–so now you have large, fast-moving predators and most of the slack gets literally eaten. And now human cultural evolution means the world changes more rapidly still, and other multicellular species face even more brutal selection pressure.
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First I’d like to include an actual example of enforced monopolies from the biological world. Bees, some wasps and some ants engage in reproductive enforcement. https://en.wikipedia.org/wiki/Worker_policing
This seems to follow a similar logic of enforcing the good of the species over that of individuals.
Systems that are in full “Moloch” mode and are optimized for efficiency in their local conditions are actually very fragile. They reach a Malthusian saturation and any change in conditions means that many will perish (individuals, species, companies… whichever you are looking at). The more variable the conditions, the more slack is needed, but events that occur once in a few generations will probably not be in taken into account. Slack allows capacity that is usually unnecessary to be maintained for emergencies (think Army Reserves, or Respirators).
“Japan had to have high enough tariffs to give their companies some slack.” Not so. Another possibility: a deep-pockets investor kept funding Toyota as it ran up losses, allowing it to sell its cars cheaper than foreign models, until it achieved its eventual level of competence. The tariffs imposed the temporary losses on Japanese consumers, instead of their being borne by the hypothetical deep-pockets investor.
In case anyone still thinks that the Swiss had 500 years of peace and bortherly love, from 1450-1950 we had wars in 1474-77 against Burgundy, 1499 against the Holy Roman Empire, civil war in 1529 following the reformation in some cantons, war against Milan in 1531, civil war again the same year, then a long period of relative “catholics and protestants agree not to kill each other” until another civil war in 1653 (this one more of a city-vs-countryside thing), then another civil war over religion in 1656 and again in 1712, then in 1798 we got pulled into the whole French revolution thing, but still found the time for another civil war amongst ourselves in 1802 until Napoleon had enough and took over running the country and gave it a French-style constitution. In 1847 we had one last civil war (admittedly not with a huge amount of fighting) which some see as an advance warning of the unrest that was to cover Europe in 1848. In between that, we worked as mercenaries for anyone who would hire us.
The picture you should have in your head for the medieval Swiss is roughly the Borderers from Albion’s seed – originally we were on what passed for a border between the Holy Roman Empire and Austria, after all. Quick to anger, fiercely protective of their honour, and loving nothing more than a good bloody fight. As for all the civil wars, some part or other of the country used to secede around once a generation over some issue or another (usually religion). One of the stories from the early days of the Swiss Confederacy is that the Swiss were peacefully invited to market in a town belonging the the Emperor, but someone important in the town made an ill-timed joke about the Swiss being a bit rustic and they thought it was a perfectly reational response to restore some honour by burning the town to the ground and slaughtering half the inhabitants.
I thought Austria was part of the Holy Roman Empire.
The Empire versus Austria bit that I remembered turned out to be that in the early 14th century, Frederick I of Austria and Louis IV of Bavaria were in conflict to become the next Emperor after a long interregnum; Switzerland backed Louis against Frederick so of course we’d say he’s the One True Emperor and Frederick an Austrian rebel. Eventually they reached a compromise where Frederick would be king and Louis the emperor. Along the way we showed the Habsburgs in 1315 that despite being outnumbered something like 4 to 1, we were willing to fight for our freedom, and our spears were longer than theirs.
We never really liked the Habsburgs as they had lands next to ours, and they coveted ours. The problem was eventually solved by Switzerland conquering the Habsburg core territory (now the canton of Aargau) and the Habsburgs moved to today’s Austria instead.
#6. The strategy of exposing a company’s internal divisions to competition is one of the strategies Amazon has used to become the colossus it is. So Amazon initially built AWS to provide its own computer services and then opened it up to its competitors and it has become the major cloud computing vendor (with a larger market share than Microsoft and Google). Netflix (Amazon’s major competitor in the video streaming market) uses AWS. And then there’s FBA (fulfillment by Amazon) which allows business to do its own selling but then have Amazon handle all the warehousing and shipping.
And Sears? All of large the mall-based department stores have been struggling for years. Neiman-Marcus and J C Penny finally declared bankruptcy and Macy’s has been shrinking (they announced a big round of store closings in February before the Covid crisis). I really doubt there was any strategy that Eddie Lampert could have pursued that would have kept Sears healthy and profitable.
About Amazon, @smilerz made the same point here, if you’re interested in the comments.
About Sears, @sourcreamus made the same point here, again if you’re interested in the comments.
“… even though capitalist economies beat socialist ones”
That’s not true at all. Development and societal advancement require government intervention. It’s Friedrich List’s early 19th century playbook. As you noted, things work best when there is a second layer that creates slack. No nation has ever industrialized without an active government industrial policy, at least not on this planet.
Another thing to remember, all of those monopolist research labs were a result of anti-trust pressures back when our government slapped down companies like Kodak and Standard Oil. AT&T styled itself as a good corporate citizen because it accepted heavy regulation and funded a brilliant research lab. Xerox was similar. Without the government second layer, the laser and graphical user interface would have been dividends and stock buybacks.
Just try playing a few rounds of civilization where your nations are under the control of mortal kings trying to maximize their own reigns. Good luck on an alliance with Rome. Hell, good luck on inventing pottery or the stone axe.
Regarding this—there’s a Chinese company called Haier (pronounced ~higher) that seems to be doing something like this very successfully! It has split the company into thousands of “microenterprises” (MEs), most of which have 10-15 employees, and each of which is considered to have its own customers, some of which are external to the company and some of which are internal (aka nodes).
Article called “The End of Bureaucracy”, detailing how it works.
Emphasis mine—seems to parallel the structure here quite precisely. If this isn’t working for certain organizations (eg Sears) they’re probably missing one of the layers (probably the collaborative container).
This is a very interesting concept, but I’d like to add my voice to those of several other biologists who are uncertain that evolution is a useful way of thinking about this phenomenon.
The eye example is a good one for illustrating how morphological change through “drift” (the biologists’ term of art for genetic changes in a population brought about by forces other than natural selection) might help a population of organisms cross a fitness valley into sunlit uplands beyond. However, it is an open (and probably unanswerable) question whether this phenomenon is a common (or is ever an) explanation for morphological innovation. As some commenters point out above, it is perfectly possible that all the complex structures we see today got that way via a series of selective intermediates. This isn’t to say that “slack” doesn’t explain how structures like eyes came to be, only that we need not invoke it. (Scott would be on better ground if he stuck to molecular innovation; the role of genome duplications in permitting proteins to change function seems like it probably falls under the umbrella of “slack”, and it’s pretty well accepted among biologists).
The cancer example is basically fine.
But then we get into the social examples: monopolies, Japanese car manufacturers, Aztecs, etc. As some commentators pointed out, these are entities that don’t have the characteristics that we associate with things that experience natural selection: they do not have heritable characteristics passed along to their offspring with very high (but not-quite-perfect) fidelity. One commentator says in defense of this claim: “New corporations are not generally formed by fresh-out college graduates (or dropouts), but by people who have worked for existing corporations. They take the best practices of the firms they have worked for and duplicate them in the new companies they found.”
So, sure, we could call this inheritance if we wanted to; in a non-biological context, it would be perfectly comprehensible to talk about “the inheritance of Judeo-Christian ethics” or suchlike. The problem is that is sort of inheritence JUST ISN’T GOOD ENOUGH for evolution. Look at how organisms reproduce: you simply do not see any organisms that are chimaeric mishmashes of different parents like this. Corporation inheritance is like if you got your left arm from one parent, your torso from a second, your right arm and leg from a third, your lungs from a fourth, etc, etc. Organisms simply don’t reproduce in this way: they inherit all of their traits from one or at most two parents, and even in cases where two parents share inheritence (like us!), the inheritance is shared equally in every cell in the body (yes, yes, fine, I know about marmosets and slime molds and calico cats and paternal genome elimination, and if you want to get involved in a long sidebar about none of these support Scott’s point, we can do that).
Now, there are entities that reproduce in the way that Scott says businesses reproduce. Populations! A population is *exactly* this–an amalgam of different inheritances from many, many parents, in which successful parents are disproportionately represented. But as Scott has lucidly explained in the OP, evolutionary dynamics simply don’t work on populations-considered-as-individuals. This is group selection, and except in a handful of very contrained edge cases, the math just doesn’t work. The subentities that make up the individual are simply too different, and have interests too varying, for evolution to kick in at this higher level.
But wait, you might say, isn’t that the point of the cancer example!? Your body is a “population” of cells which has managed to unify its members’ interests sufficiently that it can get around the dismal math of group selection. OK, sure, but that’s not at all what we’re talking about in the human-culture examples. It’s not the “Grand Unified Japanese Auto Industry” that managed to compete in the United States, but individual Japanese car companies, like Honda and Toyota, which are still competing with each other. It’s not “Europe” or that colonized much of the rest of the world in the modern era, but individual European countries. Unless my history is very much wrong, I don’t really recall anyone in France saying, “well, we really wanted control of the Suez canal, but the British got there first, and that is just as good because what is good for any member of Europe is good for all of us!”. Of course not: the whole modern period is one long, grim proof that these nations had radically different interests. When the parts have different interests, like the countries of Europe had different interests, you can’t invoke evolution in describing the dynamics of the whole. That’s the whole point of “group selection”.
What really puzzles me about the invocation of evolution here is that it is not only not useful, but also not necessary. We HAVE a science that describes the behavior of non-reproducing entities seeking to maximize their own benefits under situations in which their interests are often partially aligned with others. Why does Game Theory get such sort schrift here, when it seems like the obvious way of thinking about all the cultural examples Scott mentions? I’m not a game theorist, so I’m open to correction, but I suspect that zero-summedness will get you more or less where you want to go, with “high-slack” environments being totally non-zero-sum and “no-slack” environments being perfectly zero-sum.
Thanks Scott for the great article.
I see “slack” sort of like “entropy”- not as a passive form of “wiggle room” but as an active force that pushes things towards diversification and complexity. Treating markets or biomes like machines for “creating the best species/ best company” assumes that they naturally move towards a single outcome- a monopoly or a dominant, human-like omnivore. But many times markets and biomes do not reach this outcome (or if they do seem to reach this outcome it is not sustained). In both markets and biology, this evolution towards a “rainforest” rather than an “apex species” seems to be more the rule than the exception.
So I think the standard approach to evolution as a Hegelian force that drives towards a single outcome (in that the more evolutionary pressure there is, the more likely that single outcome will be reached) is incorrect. Or at least it needs to be offset by some other more entropic evolutionary force that drives towards greater speciation/ variety in the corporate landscape, rather than less.
Anyways, those are my jumbled thoughts. Great article/ concept, I’m just trying to think about how this all actually works-
I just wrote a blog post examining your first scenario of evolving an eye in detail. I don’t believe the idea of “low evolutionary pressure” really makes sense in the way you’re describing, and in particular it’s highly unclear if the scenarios you purport produce slack really improve the chances of evolving eyes in your hypothetical.
This is a great post! I liked how you drew the parallels between the ways these different systems balance competition and slack and how it affects the entities involved. I just really like this essay sees through the different situations and shows that they are all manifestations of the same phenomenon.
“Francis Bacon was just some guy with really good epistemic norms, and now everybody who wants to be taken seriously has to use his norms instead of whatever they were doing before. Come up with the right evolutionary parameters, and that could be you!”
Nobody can end an essay quite like you.
(I read this post when it came out, but only now came back to comment after having a conversation about corporate research labs with a friend that reminded me of this post.)