“DNA builds products with a purpose. So do people.” –Auerswald, The Code Economy
McDonald’s is the world’s largest restaurant chain by revenue, serving over 69 million customers daily in over 100 countries across approximately 36,900 outlets as of 2016. … According to a BBC report published in 2012, McDonald’s is the world’s second-largest private employer (behind Walmart with 1.9 million employees), 1.5 million of whom work for franchises. …
There are currently a total of 5,669 company-owned locations and 31,230 franchised locations… Notably, McDonald’s has increased shareholder dividends for 25 consecutive years, making it one of the S&P 500 Dividend Aristocrats. …
According to Fast Food Nation by Eric Schlosser (2001), nearly one in eight workers in the U.S. have at some time been employed by McDonald’s. … Fast Food Nation also states that McDonald’s is the largest private operator of playgrounds in the U.S., as well as the single largest purchaser of beef, pork, potatoes, and apples. (Wikipedia)
How did a restaurant whose only decent products are french fries and milkshakes come to dominate the global corporate landscape?
In The Code Economy, Auerswald suggests that the secret to McDonald’s success isn’t (just) the french fries and milkshake machines:
Kroc opened his first McDonald’s restaurant in 1955 in Des Plaines, California. Within five years he had opened two hundred new franchises across the country. [!!!] He pushed his operators obsessively to adhere to a system that reinforced the company motto: “Quality, service, cleanliness, and value.”
Quoting Kroc’s1987 autobiography,
“It’s all interrelated–our development of the restaurant, the training, the marketing advice, the product development, the research that has gone into each element of the equipment package. Together with our national advertising and continuing supervisory assistance, it forms an invaluable support system. Individual operators pay 11.5 percent of their gross to the corporation for all of this…”
The process of operating a McDonald’s franchise was engineered to be as cognitively undemanding as possible. …
Kroc created a program that could be broken into subroutines…. Acting like the DNA of the organization, the manual allowed the Speedee Service System to function in a variety of environments without losing essential structure or function.
McDonald’s is big because it figured out how to reproduce.
I’m not sure why IKEA is so big (I don’t think it’s a franchise like McDonald’s,) but based on the information posted on their walls, it’s because of their approach to furniture design. First, think of a problem, eg, People Need Tables. Second, determine a price–IKEA makes some very cheap items and some pricier items, to suit different customers’ needs. Third, use Standard IKEA Wooden Pieces to design a nice-looking table. Fourth, draw the assembly instructions, so that anyone, anywhere, can assemble the furniture themselves–no translation needed.
IKEA furniture is kind of like Legos, in that much of it is made of very similar pieces of wood assembled in different ways. The wooden boards in my table aren’t that different in size and shape from the ones in my dresser nor the ones in my bookshelf, though the items themselves have pretty different dimensions. So on the production side, IKEA lowers costs by producing not actual furniture, but collections of boards. Boards are easy to make–sawmills produce tons of them.
Furniture is heavy, but mostly empty space. By contrast, piles of boards stack very neatly and compactly, saving space both in shipping and when buyers are loading the boxes into their cars. (I am certain that IKEA accounts for common car dimensions in designing and packing their furniture.)
And the assembly instruction allow the buyer to ultimately construct the furniture.
In other words, IKEA has hit upon a successful code that allows them to produce many different designs from a few basic boards and ship them efficiently–keeping costs low and allowing them to thrive.
The company is also looking for ways to maximize warehouse efficiency.
“We have (only) two pallet sizes,” Marston said, referring to the wooden platforms on which goods are placed. “Our warehouses are dimensioned and designed to hold these two pallet sizes. It’s all about efficiencies because that helps keep the price of innovation down.”
In Europe, some IKEA warehouses utilize robots to “pick the goods,” a term of art for grabbing products off very high shelves.
These factories, Marston said, are dark, since no lighting is needed for the robots, and run 24 hours a day, picking and moving goods around.
“You (can) stand on a catwalk,” she said, “and you look out at this huge warehouse with 12 pallets (stacked on top of each other) and this robot’s running back and forth running on electronic eyebeams.”
IKEA’s code and McDonald’s code are very different, but both let the companies produce the core items they sell quickly, cheaply, and efficiently.
The difficulty with evolution is that systems are complicated; successful mutations or even just combinations of existing genes must work synergistically with all of the other genes and systems already operating in the body. A mutation that increases IQ by tweaking neurons in a particular way might have the side effect of causing neurons outside the brain to malfunction horribly; a mutation that protects against sickle-cell anemia when you have one copy of it might just kill you itself if you have two copies.
Auerswald quotes Kauffman and Levin:
“Natural selection does not work as an engineer works… It works like a tinkereer–a tinkerer who does not know exactly what he is going to produce but uses… everything at his disposal to produce some kind of workable object.” This process is progressive, moving form simpler to more complex forms: “Evolution doe not produce novelties from scratch. It works on what already exists, either transforming a system to give it new functions or combining several systems to produce a more elaborate one [as] during the passage from unicellular to multicellular forms.”
The Kauffman and Levin model was as simple as it was powerful. Imagine a genetic code of length N, where each gene might occupy one of two possible “states”–for example, “o” and “i” in a binary computer. The difficulty of the evolutionary problem was tunable with the parameter K, which represented the average number of interactions among genes. The NK model, as it came to be called, was able to reproduce a number of measurable features of evolution in biological systems. Evolution could be represented as a genetic walk on a fitness landscape, in which increasing complexity was now a central parameter.
Local optima–or optimums, if you prefer–are an illusion created by distance. A man standing on the hilltop at (approximately) X=2 may see land sloping downward all around himself and think that he is at the highest point on the graph. But hand him a telescope, and he discovers that the fellow standing on the hilltop at X=4 is even higher than he is. And hand the fellow at X=4 a telescope, and he’ll discover that X=6 is even higher.
A global optimum is the best possible way of doing something; a local optimum can look like a global optimum because all of the other, similar ways of doing the same thing are worse.
Some notable examples of cultures that were stuck at local optima but were able, with exposure, to jump suddenly to a higher optima: The “opening of Japan” in the late 1800s resulted in breakneck industrialization and rising standards of living; the Cherokee invented their own alphabet (technically a syllabary) after glimpsing the Roman one, and achieved mass literacy within decades; European mathematics and engineering really took off after the introduction of Hindu-Arabic numerals and the base-ten system.
If we consider each culture its own “landscape” in which people (and corporations) are finding locally optimal solutions to problems, then it becomes immediately obvious that we need both a large number of distinct cultures working out their own solutions to problems and occasional communication and feedback between those cultures so results can transfer. If there is only one, global, culture, then we only get one set of solutions–and they will probably be sub-optimal. If we have many cultures but they don’t interact, we’ll get tons of solutions, and many of them will be sub-optimal. But many cultures developing their own solutions and periodically interacting can develop many solutions and discard sub-optimal ones for better ones.
Life constantly makes us take decisions under conditions of uncertainty. We can’t simply compute every possible outcome, and decide with perfect accuracy what the path forward is. We have to use heuristics. Religion is seen as a record of heuristics that have worked in the past. …
But while every generation faces new circumstances, there are also some common problems that every living being is faced with: survival and reproduction, and these are the most important problems because everything else depends on them. Mess with these, and everything else becomes irrelevant.
This makes religion an evolutionary record of solutions which persisted long enough, by helping those who held them to persist.
This is not saying “All religions are perfect and good and we should follow them,” but it is suggesting, “Traditional religions (and cultures) have figured out ways to solve common problems and we should listen to their ideas.”
Back in The Code Economy, Auerswald asks:
Might the same model, derived from evolutionary biology, explain the evolution of technology?
… technology may also be nothing else but the capacity for invariant reproduction. However, in order for more complex forms of technology to be viable over time, technology also must possess a capacity for learning and adaptation.
Evolutionary theory as applied to the advance of code is the focus of the next chapter. Kauffman and Levin’s NK model ends up providing a framework for studying the creation and evolution of code. Learning curves act as the link between biology and economics.
Will the machines become sentient? Or McDonald’s? And which should we worry about?
Make no mistake: Nichols is annoyingly arrogant. He draws a rather stark line between “experts” (who know things) and everyone else (who should humbly limit themselves to voting between options defined for them by the experts.) He implores people to better educate themselves in order to be better voters, but has little patience for autodidacts and bloggers like myself who are actually trying.
But arrogance alone doesn’t make someone wrong.
Nichols’s first thesis is simple: most people are too stupid or ignorant to second-guess experts or even contribute meaningfully to modern policy discussions. How can people who can’t find Ukraine on a map or think we should bomb the fictional city of Agrabah contribute in any meaningful way to a discussion of international policy?
It was one thing, in 1776, to think the average American could vote meaningfully on the issues of the day–a right they took by force, by shooting anyone who told them they couldn’t. Life was less complicated in 1776, and the average person could master most of the skills they needed to survive (indeed, pioneers on the edge of the frontier had to be mostly self-sufficient in order to survive.) Life was hard–most people engaged in long hours of heavy labor plowing fields, chopping wood, harvesting crops, and hauling necessities–but could be mastered by people who hadn’t graduated from elementary school.
But the modern industrial (or post-industrial) world is much more complicated than the one our ancestors grew up in. Today we have cars (maybe even self-driving cars), electrical grids and sewer systems, atomic bombs and fast food. The speed of communication and transportation have made it possible to chat with people on the other side of the earth and show up on their doorstep a day later. The amount if specialized, technical knowledge necessary to keep modern society running would astonish the average caveman–even with 15+ years of schooling, the average person can no longer build a house, nor even produce basic necessities like clothes or food. Most of us can’t even make a pencil.
Even experts who are actually knowledgeable about their particular area may be completely ignorant of fields outside of their expertise. Nichols speaks Russian, which makes him an expert in certain Russian-related matters, but he probably knows nothing about optimal high-speed rail networks. And herein lies the problem:
The American attachment to intellectual self-reliance described by Tocqueville survived for nearly a century before falling under a series of assaults from both within and without. Technology, universal secondary education, the proliferation of specialized expertise, and the emergence of the United States a a global power in the mid-twentieth century all undermined the idea… that the average American was adequately equipped either for the challenges of daily life or for running the affairs of a large country.
… the political scientist Richard Hofstadter wrote that “the complexity of modern life has steadily whittled away the functions the ordinary citizen can intelligently and competently perform for himself.”
… Somin wrote in 2015 that the “size and complexity of government” have mad it “more difficult for voters with limited knowledge to monitor and evaluate the government’s many activities. The result is a polity in which the people often cannot exercise their sovereignty responsibly and effectively.”
In other words, society is now too complex and people too stupid for democracy.
Nichols’s second thesis is that people used to trust experts, which let democracy function, but to day they are less trusting. He offers no evidence other than his general conviction that this change has happened.
He does, however, detail the way he thinks that 1. People have been given inflated egos about their own intelligence, and 2. How our information-delivery system has degenerated into misinformational goo, resulting in the trust-problems he believes we are having These are interesting arguments and worth examining.
A bit of summary:
Indeed, maybe the death of expertise is a sign of progress. Educated professionals, after all, no longer have a stranglehold on knowledge. The secrets of life are no longer hidden in giant marble mausoleums… in the past, there was less tress between experts and laypeople, but only because citizen were simply unable to challenge experts in any substantive way. …
Participation in political, intellectual, and scientific life until the early twentieth century was far more circumscribed, with debates about science, philosophy, and public policy all conducted by a small circle of educated males with pen and ink. Those were not exactly the Good Old Days, and they weren’t that long ago. The time when most people didn’t finish highschool, when very few went to college, and only a tiny fraction of the population entered professions is still within living memory of many Americans.
Aside from Nichols’s insistence that he believes modern American notions about gender and racial equality, I get the impression that he wouldn’t mind the Good Old Days of genteel pen-and-ink discussions between intellectuals. However, I question his claim that participation in political life was far more circumscribed–after all, people voted, and politicians liked getting people to vote for them. People anywhere, even illiterate peasants on the frontier or up in the mountains like to gather and debate about God, politics, and the meaning of life. The question is less “Did they discuss it?” and more “Did their discussions have any effect on politics?” Certainly we can point to abolition, women’s suffrage, prohibition, and the Revolution itself as heavily grass-roots movements.
But continuing with Nichols’s argument:
Social changes only in the past half century finally broke down old barriers of race, class, and sex not only between Americans and general but also between uneducated citizens and elite expert in particular. A wide circle of debate meant more knowledge but more social friction. Universal education, the greater empowerment of women and minorities, the growth of a middle class, and increased social mobility all threw a minority of expert and the majority of citizens into direct contact, after nearly two centuries in which they rarely had to interact with each other.
And yet the result has not been a greater respect for knowledge, but the growth of an irrational conviction among Americans that everyone is as smart as everyone else.
Nichols is distracting himself with the reflexive racial argument; the important change he is highlighting isn’t social but technical.
I’d like to quote a short exchange from Our Southern Highlanders, an anthropologic-style text written about Appalachia about a century ago:
The mountain clergy, as a general rule, are hostile to “book larnin’,” for “there ain’t no Holy Ghost in it.” One of them who had spent three months at a theological school told President Frost, “Yes, the seminary is a good place ter go and git rested up, but ’tain’t worth while fer me ter go thar no more ’s long as I’ve got good wind.”
It used to amuse me to explain how I knew that the earth was a sphere; but one day, when I was busy, a tiresome old preacher put the everlasting question to me: “Do you believe the earth is round?” An impish perversity seized me and I answered, “No—all blamed humbug!” “Amen!” cried my delighted catechist, “I knowed in reason you had more sense.”
But back to Nichols, who really likes the concept of expertise:
One reason claims of expertise grate on people in a democracy is that specialization is necessarily exclusive. WHen we study a certain area of knowledge or spend oulives in a particular occupation, we not only forego expertise in othe jobs or subjects, but also trust that other pople in the community know what they’re doing in thei area as surely as we do in our own. As much as we might want to go up to the cockpit afte the engine flames out to give the pilots osme helpful tips, we assume–in part, ebcause wehave to–that tye’re better able to cope with the problem than we are. Othewise, our highly evovled society breaks down int island sof incoherence, where we spend our time in poorly infomed second-guessing instead of trusting each other.
This would be a good point to look at data on overall trust levels, friendship, civic engagement, etc (It’s down. It’s all down.) and maybe some explanations for these changes.
Nichols talks briefly about the accreditation and verification process for producing “experts,” which he rather likes. There is an interesting discussion in the economics literature on things like the economics of trust and information (how do websites signal that they are trustworthy enough that you will give them your credit card number and expect to receive items you ordered a few days later?) which could apply here, too.
Nichols then explores a variety of cognitive biases, such a superstitions, phobias, and conspiracy theories:
Conspiracy theories are also a way for people to give meaning to events that frighten them. Without a coherent explanation for why terrible thing happen to innocent people, they would have to accept such occurence as nothing more than the random cruelty either of an uncaring universe or an incomprehensible deity. …
The only way out of this dilemma is to imagine a world in which our troubles are the fault of powerful people who had it within their power to avert such misery. …
Just as individual facing grief and confusion look for reasons where none may exist, so, too, will entire societies gravitate toward outlandish theories when collectively subjected to a terrible national experience. Conspiracy theories and flawed reasoning behind them …become especially seductive “in any society that has suffered an epic, collectively felt trauma. In the aftermath, millions of people find themselves casting about for an answer to the ancient question of why bad things happen to good people.” …
Today, conspiracy theories are reaction mostly to the economic and social dislocations of globalization…This is not a trivial obstacle when it comes to the problems of expert engagement with the public: nearly 30 percent of Americans, for example, think “a secretive elite with a globalist agenda is conspiring to eventually rule the world” …
Obviously stupid. A not-secret elite with a globalist agenda already rules the world.
and 15 percent think media or government add secret mind controlling technology to TV broadcasts. (Another 15 percent aren’t sure about the TV issue.)
It’s called “advertising” and it wants you to buy a Ford.
Anyway, the problem with conspiracy theories is they are unfalsifiable; no amount of evidence will ever convince a conspiracy theorist that he is wrong, for all evidence is just further proof of how nefariously “they” are constructing the conspiracy.
Then Nichols gets into some interesting matter on the difference between stereotypes and generalizations, which segues nicely into a tangent I’d like to discuss, but it probably deserves its own post. To summarize:
Sometimes experts know things that contradict other people’s political (or religious) beliefs… If an “expert” finding or field accords with established liberal values, EG, the implicit association test found that “everyone is a little bit racist,” which liberals already believed, then there is an easy mesh between what the academics believe and the rest of their social class.
If their findings contradict conservative/low-class values, EG, when professors assert that evolution is true and “those low-class Bible-thumpers in Oklahoma are wrong,” sure, they might have a lot of people who disagree with them, but those people aren’t part of their own social class/the upper class, and so not a problem. If anything, high class folks love such finding, because it gives them a chance to talk about how much better they are than those low-class people (though such class conflict is obviously poisonous in a democracy where those low-class people can still vote to Fuck You and Your Global Warming, Too.)
But if the findings contradict high-class/liberal politics, then the experts have a real problem. EG, if that same evolution professor turns around and says, “By the way, race is definitely biologically real, and there are statistical differences in average IQ between the races,” now he’s contradicting the political values of his own class/the upper class, and that becomes a social issue and he is likely to get Watsoned.
Jordan Peterson isn’t unpopular or “silenced” so much as he is disliked by upper class folks and liked by “losers” and low class folks, despite the fact that he is basically an intellectual guy and isn’t peddling a low-class product. Likewise, Fox News is just as much part of The Media as NPR, (if anything, it’s much more of the Media) but NPR is higher class than Fox, and Fox doesn’t like feeling like its opinions are being judged along this class axis.
For better or for worse (mostly worse) class politics and political/religious beliefs strongly affect our opinions of “experts,” especially those who say things we disagree with.
But back to Nichols: Dunning-Kruger effect, fake cultural literacy, and too many people at college. Nichols is a professor and has seen college students up close and personal, and has a low opinion of most of them. The massive expansion of upper education has not resulted in a better-educated, smarter populace, he argues, but a populace armed with expensive certificates that show the sat around a college for 4 years without learning much of anything. Unfortunately, beyond a certain level, there isn’t a lot that more school can do to increase people’s basic aptitudes.
Colleges get money by attracting students, which incentivises them to hand out degrees like candy–in other words, students are being lied to about their abilities and college degrees are fast becoming the participation trophies for the not very bright.
Nichols has little sympathy for modern students:
Today, by contrast, students explode over imagined slights that are not even remotely int eh same category as fighting for civil rights or being sent to war. Students now build majestic Everests from the smallest molehills, and they descend into hysteria over pranks and hoaxes. In the midst of it all, the students are learning that emotions and volume can always defeat reason and substance, thus building about themselves fortresses that no future teacher, expert, or intellectual will ever be able to breach.
At Yale in 2015, for example, a house master’s wife had the temerity to tell minority students to ignore Halloween costumes they thought offensive. This provoked a campus wide temper tantrum that included professors being shouted down by screaming student. “In your position as master,” one student howled in a professor’s face, “it is your job to create a place of comfort and home for the students… Do you understand that?!”
Quietly, the professor said, “No, I don’t agree with that,” and the student unloaded on him:
“Then why the [expletive] did you accept the position?! Who the [expletive] hired you?! You should step down! If that is what you think about being a master you should step down! It is not about creating an intellectual space! It is not! Do you understand that? It’s about creating a home here. You are not doing that!” [emphasis added]
Yale, instead of disciplining students in violation of their own norms of academic discourse, apologized to the tantrum throwers. The house master eventually resigned from his residential post…
To faculty everywhere, the lesson was obvious: the campus of a top university is not a place for intellectual exploration. It is a luxury home, rented for four to six years, nine months at a time, by children of the elite who may shout at faculty as if they’re berating clumsy maids in a colonial mansion.
The incident Nichols cites (and similar ones elsewhere,) are not just matters of college students being dumb or entitled, but explicitly racial conflicts. The demand for “safe spaces” is easy to ridicule on the grounds that students are emotional babies, but this misses the point: students are carving out territory for themselves on explicitly racial lines, often by violence.
Nichols, though, either does not notice the racial aspect of modern campus conflicts or does not want to admit publicly to doing so.
Nichols moves on to blame TV, especially CNN, talk radio, and the internet for dumbing down the quality of discourse by overwhelming us with a deluge of more information than we can possibly process.
Referring back to Auerswald and The Code Economy, if automation creates a bifurcation in industries, replacing a moderately-priced, moderately available product with a stream of cheap, low-quality product on the one hand and a trickle of expensive, high-quality products on the other, good-quality journalism has been replaced with a flood of low-quality crap. The high-quality end is still working itself out.
Accessing the Internet can actually make people dumber than if they had never engaged a subject at all. The very act of searching for information makes people think they’ve learned something,when in fact they’re more likely to be immersed in yet more data they do not understand. …
When a group of experimental psychologists at Yale investigated how people use the internet, they found that “people who search for information on the Web emerge from the process with an inflated sense of how much they know–even regarding topic that are unrelated to the ones they Googled.” …
How can exposure to so much information fail to produce at least some kind of increased baseline of knowledge, if only by electronic osmosis? How can people read so much yet retain so little? The answer is simple: few people are actually reading what they find.
As a University College of London (UCL) study found, people don’t actually read the articles they encounter during a search on the Internet. Instead, they glance at the top line or the first few sentences and then move on. Internet users, the researchers noted, “Are not reading online in the traditional sense; indeed, there are signs that new forms of ‘reading’ are emerging as users ‘power browse’ horizontally through titles, contents pages and abstracts going for quick wins. It almost seems that they go online to avoid reading in the traditional sense.”
The internet’s demands for instant updates, for whatever headlines generate the most clicks (and thus advertising revenue), has upset the balance of speed vs. expertise in the newsroom. No longer have reporters any incentive to spend long hours carefully writing a well-researched story when such stories pay less than clickbait headlines about racist pet costumes and celebrity tweets.
I realize it seems churlish to complain about the feast of news and information brought to us by the Information Age, but I’m going to complain anyway. Changes in journalism, like the increased access to the Internet and to college education, have unexpectedly corrosive effects on the relationship between laypeople and experts. Instead of making people better informed, much of what passes for news in the twenty-first century often leaves laypeople–and sometimes experts–even more confused and ornery.
Experts face a vexing challenge: there’s more news available, and yet people seem less informed, a trend that goes back at least a quarter century. Paradoxically, it is a problem that is worsening rather than dissipating. …
As long ago as 1990, for example, a study conducted by the Pew Trust warned that disengagement from important public questions was actually worse among people under thirty, the group that should have been most receptive to then-emerging sources of information like cable television and electronic media. This was a distinct change in American civic culture, as the Pew study noted:
“Over most of the past five decades younger members of the public have been at least as well informed as older people. In 1990, that is no longer the case. … “
Those respondents are now themselves middle-aged, and their children are faring no better.
If you were 30 in 1990, you were born in 1960, to parents who were between the ages of 20 and 40 years old, that is, born between 1920 and 1940.
Fertility for the 1920-1940 cohort was strongly dysgenic. So was the 1940-50 cohort. The 1900-1919 cohort at least had the Flynn Effect on their side, but later cohorts just look like an advertisement for idiocracy.
Nichols ends with a plea that voters respect experts (and that experts, in turn, be humble and polite to voters.) After all, modern society is too complicated for any of us to be experts on everything. If we don’t pay attention to expert advice, he warns, modern society is bound to end in ignorant goo.
The logical inconsistency is that Nichols believes in democracy at all–he thinks democracy can be saved if ignorant people vote within a range of options as defined by experts like himself, eg, “What vaccine options are best?” rather than “Should we have vaccines at all?”
The problem, then, is that whoever controls the experts (or controls which expert opinions people hear) controls the limits of policy debates. This leads to people arguing over experts, which leads right back where we are today. As long as there are politics, “expertise” will be politicized, eg:
Look at any court case in which both sides bring in their own “expert” witnesses. Both experts testify to the effect that their side is correct. Then the jury is left to vote on which side had more believable experts. This is like best case scenario voting, and the fact that the voters are dumb and don’t understand what the experts are saying and are obviously being mislead in many cases is still a huge problem.
If politics is the problem, then perhaps getting rid of politics is the solution. Just have a bunch of Singapores run by Lee Kwan Yews, let folks like Nichols advise them, and let the common people “vote with their feet” by moving to the best states.
The problem with this solution is that “exit” doesn’t exist in the modern world in any meaningful way, and there are significant reasons why ordinary people oppose open borders.
Conclusion: 3/5 stars. It’s not a terrible book, and Nichols has plenty of good points, but “Americans are dumb” isn’t exactly fresh territory and much has already been written on the subject.
Local optima–or optimums, if you prefer–are an illusion created by distance. A man standing on the hilltop at (approximately) X=2 may see land sloping downward all around himself and think that he is at the highest point on the graph.
But hand him a telescope, and he discovers that the fellow standing on the hilltop at X=4 is even higher than he is. And hand the fellow at X=4 a telescope, and he’ll discover that X=6 is even higher.
A global optimum is the best possible way of doing something; a local optimum can look like a global optimum because all of the other, similar ways of doing the same thing are worse. To get from a local optimum to a global optimum, you might have to endure a significant trough of things going worse before you reach your destination. (Those troughs would be the points X=3.03 and X=5.02 on the graph.) If the troughs are short and shallow enough, people can accidentally power their way through. If long and deep enough, people get stuck.
The introduction of new technology, exposure to another culture’s solutions, or even random chance can expose a local optimum and propel a group to cross that trough.
For example, back in 1400, Europeans were perfectly happy to get their Chinese silks, spices, and porcelains via the overland Silk Road. But with the fall of Constantinople to the Turks in 1453, the Silk Road became more fragmented and difficult (ie dangerous, ie expensive) to travel. The increased cost of the normal road prompted Europeans to start exploring other, less immediately profitable trade routes–like the possibility of sailing clear around the world, via the ocean, to the other side of China.
Without the eastern trade routes first diminishing in profitability, it wouldn’t have been economically viable to explore and develop the western routes. (With the discovery of the Americas, in the process, a happy accident.)
West Hunter (Greg Cochran) writes frequently about local optima; here’s an excerpt on plant domestication:
The reason that a few crops account for the great preponderance of modern agriculture is that a bird in the hand – an already-domesticated, already- optimized crop – feeds your family/makes money right now, while a potentially useful yet undomesticated crop doesn’t. One successful domestication tends to inhibit others that could flourish in the same niche. Several crops were domesticated in the eastern United States, but with the advent of maize and beans ( from Mesoamerica) most were abandoned. Maybe if those Amerindians had continued to selectively breed sumpweed for a few thousand years, it could have been a contender: but nobody is quite that stubborn.
Teosinte was an unpromising weed: it’s hard to see why anyone bothered to try to domesticate it, and it took a long time to turn it into something like modern maize. If someone had brought wheat to Mexico six thousand years ago, likely the locals would have dropped maize like a hot potato. But maize ultimately had advantages: it’s a C4 plant, while wheat is C3: maize yields can be much higher.
Teosinte is the ancestor of modern corn. Cochran’s point is that in the domestication game, wheat is a local optimum; given the wild ancestors of wheat and corn, you’d develop a better, more nutritious variety of wheat first and probably just abandon the corn. But if you didn’t have wheat and you just had corn, you’d keep at the corn–and in the end, get an even better plant.
(Of course, corn is a success story; plenty of people domesticated plants that actually weren’t very good just because that’s what they happened to have.)
Japan in 1850 was a culturally rich, pre-industrial, feudal society with a strong isolationist stance. In 1853, the Japanese discovered that the rest of the world’s industrial, military technology was now sufficiently advanced to pose a serious threat to Japanese sovereignty. Things immediately degenerated, culminating in the Boshin War (civil war, 1868-9,) but with the Meiji Restoration Japan embarked on an industrialization crash-course. By 1895, Japan had kicked China’s butt in the First Sino-Japanese War and the Japanese population doubled–after holding steady for centuries–between 1873 and 1935. (From 35 to 70 million people.) By the 1930s, Japan was one of the world’s most formidable industrial powers, and today it remains an economic and technological powerhouse.
Clearly the Japanese people, in 1850, contained the untapped ability to build a much more complex and advanced society than the one they had, and it did not take much exposure to the outside world to precipitate a total economic and technological revolution.
A similar case occurred in 1821 when Sequoyah, a Cherokee man, invented his own syllabary (syllable-based alphabet) after observing American soldiers reading letters. The Cherokee quickly adopted Sequoyah’s writing system–by 1825, the majority of Cherokee were literate and the Cherokee had their own printing industry. Interestingly, although some of the Cherokee letters look like Latin, Greek, or Cyrillic letters, there is no correspondence in sound, because Sequoyah could not read English. He developed his entire syllabary after simply being exposed to the idea of writing.
The idea of literacy has occurred independently only a few times in human history; the vast majority of people picked up alphabets from someone else. Our Alphabet comes from the Latins who got it from the Greeks who adopted it from the Phoenicians who got it from some proto-canaanite script writers, and even then literacy spread pretty slowly. The Cherokee, while not as technologically advanced as Europeans at the time, were already a nice agricultural society and clearly possessed the ability to become literate as soon as they were exposed to the idea.
Likewise, contact between Europeans and groups like the Australian Aboriginees did not result in the Aboriginees adopting European technology nor a new and improved fusion of Aboriginee and European tech, but in total disaster for the Aboriginees. While the Japanese consistently top the charts in educational attainment, Aboriginee communities are still struggling with low literacy rates, high dropout rates, and low employment–the modern industrial economy, in short, has not been kind to them.
Along a completely different evolutionary pathway, cephalopods–squids, octopuses, and their tentacled ilk–are the world’s smartest invertebrates. This is pretty amazing, given that their nearest cousins are snails and clams. Yet cephalopod intelligence only goes so far. No one knows (yet) just how smart cephalopods are–squids in particular are difficult to work with in captivity because they are active hunter/swimmers and need a lot more space than the average aquarium can devote–but their brain power appears to be on the order of a dog’s.
After millions of years of evolution, cephalopods may represent the best nature can do–with an invertebrate. Throw in a backbone, and an animal can get a whole lot smarter.
And in chemistry, activation energy is the amount of energy you have to put into a chemical system before a reaction can begin. Stable chemical systems essentially exist at local optima, and it can require the input of quite a lot of energy before you get any action out of them. For atoms, iron is the global–should we say universal?–optimum, beyond which reactions are endothermic rather than exothermic. In other words, nuclear fusion at the core of the sun ends with iron; elements heavier than iron can only be produced when stars explode.
So what do local optima have to do with diversity?
The current vogue for diversity (“Diversity is our greatest strength”) suggests that we can reach global optima faster by simply smushing everyone together and letting them compare notes. Scroll back to the Japanese case. Edo Japan had a nice culture, but it was also beset by frequent famines. Meiji Japan doubled its population. Giving everyone, right now, the same technology and culture would bring everyone up to the same level.
But you can’t tell from within if you are at a local or global optimum. That’s how they work. The Indians likely would have never developed corn had they been exposed to wheat early on, and subsequently Europeans would have never gotten to adopt corn, either. Good ideas can take a long time to refine and develop. Cultures can improve rapidly–even dramatically–by adopting each other’s good ideas, but they also need their own space and time to pursue their own paths, so that good but slowly developing ideas aren’t lost.