War is Code for the Production of Corpses

Quoting Richard Rhodes’s The Making of the Atomic Bomb:

“The end result of the complex organization that was the efficient software of the Great War was the manufacture of corpses.

This essentially industrial operation was fantasized by the generals as a “strategy of attrition.” The British tried to kill Germans, the Germans tried to kill British and French and so on, a “strategy” so familiar by now that it almost sounds normal. It was not normal in Europe before 1914 and no one in authority expected it to evolve, despite the pioneering lessons of the American Civil War. Once the trenches were in place, the long grave already dug (John Masefield’s bitterly ironic phrase), then the war stalemated and death-making overwhelmed any rational response.

“The war machine,” concludes Elliot, “rooted in law, organization, production, movement, science, technical ingenuity, with its product of six thousand deaths a day over a period of 1,500 days, was the permanent and realistic factor, impervious to fantasy, only slightly altered by human variation.”

No human institution, Elliot stresses, was sufficiently strong to resist the death machine. A new mechanism, the tank, ended the stalemate.”

Big Data describes another war of attrition:

McNamara epitomized the hyper-rational executive who relied on numbers rather than sentiments, and who could apply his quantitative skills to any industry he turned them to. In 1960 he was named president of Ford, a position he held for only a few weeks before being tapped to join President Kennedy’s cabinet as secretary of defense.

As the Vietnam conflict escalated and the United States sent more troops, it became clear that this was a war of wills, not of territory. America’s strategy was to pound the Viet Cong to the negotiation table. The way to measure progress, therefore, was by the number of enemy killed. The body count was published daily in the newspapers. To the war’s supporters it was proof of progress; to critics, evidence of its immorality. The body count was the data point that defined an era.

McNamara relied on the figures, fetishized them. … McNamara felt he could comprehend what was happening on the ground only by staring at a spreadsheet—at all those orderly rows and columns, calculations and charts, whose mastery seemed to bring him one standard deviation closer to God.

In 1977, two years after the last helicopter lifted off the rooftop of the U.S. embassy in Saigon, a retired Army general, Douglas Kinnard, published a landmark survey called The War Managers that revealed the quagmire of quantification. A mere 2 percent of America’s generals considered the body count a valid way to measure progress. “A fake—totally worthless,” wrote one general in his comments. “Often blatant lies,” wrote another. “They were grossly exaggerated by many units primarily because of the incredible interest shown by people like McNamara,” said a third.  — Viktor Mayer-Schönberger and Kenneth Cukier, Big Data

Humans are reasonably smart creatures, but we so easily get stuck in terrible modes of thinking.

On a battlefield men die quickly, they fight back, they are sustained by fellowship and a sense of duty. Here I saw people dying in solitude by slow degrees, dying hideously, without the excuse of sacrifice for a cause. They had been trapped and left to starve, each in his home, by a political decision made in a far-off capital around conference and banquet tables. […] The most terrifying sights were the little children with skeleton limbs dangling from balloon – like abdomens. Starvation had wiped every trace of youth from their faces, turning them into tortured gargoyles; only in their eyes still lingered the reminder of childhood. Everywhere we found men and women lying prone, their faces and bellies bloated, their eyes utterly expressionless. Anger lashed my mind as I drove back to the village. Butter being sent abroad in the midst of the famine! In London, Berlin, Paris I could see with my mind’s eye people eating butter stamped with a Soviet trademark. “They must be rich to be able to send out butter,” I could hear them saying. “Here, friends, is the proof of socialism in action.” Driving through the fields, I did not hear the lovely Ukrainian songs so dear to my heart. These people had forgotten how to sing. I could hear only the groans of the dying, and the lip-smacking of fat foreigners enjoying our butter… — Kravchenko, Victor. I Chose Freedom: The Personal And Political Life Of A Soviet Official

Like human sacrifice and cannibalism:

The word tzompantli is Nahuatl and was used by the Aztecs to refer to the skull-racks found in many Aztec cities; The first and most prominent example is the Huey Tzompantli (Great Skull-rack) located the Aztec capital of Tenochtitlan and described by the early conquistadors. … Excavations at Templo Mayor in the Aztec capital Tenochtitlan have revealed many skulls belonging to women and children, in addition to those of men, a demonstration of the diversity of the human sacrifices in Aztec culture.[15] After displaying severed heads, many scholars have determined that limbs of Aztec victims would be cannibalized [16]

… based on numbers given by Taipa and Fray Diego Durán, Bernard Ortiz de Montellano[18] has calculated that there were at most 60,000 skulls on the “Hueyi Tzompantli” (Great Skullrack) of Tenochtitlan. … There were at least five more skull racks in Tenochtitlan but by all accounts they were much smaller. —Wikipedia

All of the individual parts of a system can seem logical, and yet the end result can still be grotesque, inhuman, and insane.

I am on holiday so your normal Book Club post will resume next Wednesday.

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Book Club: The Industrial Revolution and its Discontents, Code Economy, ch. 5

1. The Industrial Revolution and its consequences have been a disaster for the human race. They have greatly increased the life-expectancy of those of us who live in “advanced” countries, but they have destabilized society, have made life unfulfilling, have subjected human beings to indignities, have led to widespread psychological suffering (in the Third World to physical suffering as well) and have inflicted severe damage on the natural world. The continued development of technology will worsen the situation. It will certainly subject human beings to greater indignities and inflict greater damage on the natural world, it will probably lead to greater social disruption and psychological suffering, and it may lead to increased physical suffering even in “advanced” countries. –Kaczynski, Industrial Society and Its Future

The quest to find and keep a “job for life”–stable, predictable work that pays enough to live on, is reachable by available transportation, and lends a sense of meaning to their daily lives–runs though every interview transcript, from those who are unemployed to those who have “made it” to steady jobs like firefighting or nursing. Traditional blue-collar work–whether as a factory worker or a police officer–has become increasingly scarce and competitive, destroyed by a technologically advanced and global capitalism that prioritizes labor market “flexibility”… Consequently, the post-industrial generation is forced to continuously grapple with flux and contingency, bending and adapting to the demands of they labor market until they feel that they are about to break. –Silva, Coming up Short: Working-Class Adulthood in an Age of Uncertainty

The historical record confirms that the realities of the ongoing processes of mechanization and industrialization, as noted early on by Lord Byron, were very different from the picture adherents to the wage fund theory held in their heads. While the long-term impact of the Industrial revolution had on the health and well-being of the English population was strongly positive, the first half of the nineteenth century was indeed a time of exceptional hardship for English workers. In a study covering the years 1770-1815, Stephen Nicholas and Richard Steckel report “falling heights of urban-and rural-born males after 1780 and a delayed growth spurt for 13- to 23-year old boys,” as well as a fall in the English workers’ height relative to that of Irish convicts. By the 1830s, the life expectancy of anyone born in Liverpool and Manchester was less than 30 years–as low as had been experienced in England since the Black Death of 1348. –Auerswald, The Code Economy

On the other hand:

Chapter 5 of The Code Economy, Substitution, explores the development of economic theories about the effects of industrialization and general attempts at improving the lives of the working poor.

… John Barton, a Quaker, published a pamphlet in 1817 titled, Observations on the Circumstances Which Influence the Condition of the Laboring Classes of Society. … Barton began by targeting the Malthusian assumption that population grows in response to increasing wages. … He began by noting that there was no a priori reason to believe that labor and capital were perfect complements, as classical economists implicitly assumed. The more sensible assumption was that, as wages increased, manufacturers and farmers alike would tend to substitute animals or machines for human labor. Rather than increasing the birth rate, the higher wages brought on by the introduction of new machinery would increase intergenerational differences in income and thus delay child-bearing. Contrary to the Malthusian line of argument, this is exactly what happened.

There’s an end note that expands on this (you do read the end notes, right?) Quoting Barton, 1817:

A rise of wages then does not always increase population… For every rise of wages tends to decrease the effectual demand for labor… Suppose that by a general agreement among farmers the rate of agricultural wage were raised from 12 shillings to 24 shillings per week–I cannot imagine any circumstance calculated more effectually to discourage marriage. For it would immediately become a a most important object to cultivate with as few hands as possible; wherever the use of machinery, or employment of horses could be substituted for manual labor, it would be done; and a considerable portion of existing laborers would be out of work.

This is the “raising the minimum wage will put people out of work” theory. Barton also points out that when people do manage to get these higher-paid jobs, they will tend to be older, more experienced laborers rather than young folks looking to marry and start a family.

A quick perusal of minimum wage vs. unemployment rate graphs reveals some that are good evidence against minimum wages, and some that are good evidence in favor of them. Here’s a link to a study that found no effects of minimum wage differences on employment. The American minimum wage data is confounded by things like “DC is a shithole.” DC has the highest minimum wage in the country and the highest unemployment rate, but Hawaii also has a very high minimum wage and the lowest unemployment rate. In general, local minimum wages probably reflect local cost of living/cost of living reflects wages. If we adjust for inflation, minimum wage in the US peaked around 1968 and was generally high throughout the 60s and 70s, but has fallen since then. Based on conversations with my parents, I gather the 60s and 70s were a good time to be a worker, when unskilled labor could pretty easily get a job and support a family; unemployment rates do not seem to have fallen markedly since then, despite lower real wages. A quick glance at a map of minimum wages by country reveals that countries with higher minimum wage tend to be nicer countries that people actually want to live in, but the relationship is not absolute.

We might say that this contradicts Barton, but why have American wages stagnated or gone down since the 60s?

1. Automation

2. Emergence of other economic competitors as Europe and Japan recovered from WWII

3. Related: Outsourcing to cheaper workers in China

4. Labor market growth due to entry of women, immigrants, and Boomers generally

Except for 2, that sounds a lot like what Barton said would happen. Wages go up => people move where the good jobs are => labor market expands => wages go down. If labor cannot move, then capitalists can either move the businesses to the labor or invest in machines to replace the labor.

On the other hand, the standard of living is clearly higher today than it was in 1900, even if wages, like molecules diffusing through the air, tend to even out over time. Why?

First, obviously, we learned to extract more energy from sources like oil, coal, and nuclei. A loom hooked up (via the electrical grid) to an electric turbine can make a lot more cloth per hour than a mere human working with shuttles and thread.

Second, we have gotten better at using the energy we extract–Auerswald would call this “code.”

Standards of living may thus have more to do with available resources (including energy) and our ability to use those resources (both the ‘code” we have developed and our own inherent ability to interact with and use that code,) than with the head-scratching entropy of minimum wages.

Auerswald discusses the evolution of David Ricardo’s economic ideas:

By incorporating the potential for substitution between capital and labor, Ricardo led the field of economics in rejecting the wage fund theory, along with its Dickensian implications for policy. He accepted the notion the introduction of new machinery would result in the displacement of workers. The upshot was that the workers were still assumed to be doomed, but the reason was now substitution of machines for labor, not scarcity of a Malthusian variety.

Enter Henry George, with a radically different perspective:

“Like a flash it came over me that there was the reason of advancing poverty with advancing wealth. With the growth of population, land grows in value, and the men who work it must pay more for the privilege.” …

George asserted that increasing population density, (not, as Malthus claimed, population decline) was the source of increased prosperity in human societies: “Wealth is greatest where population is densest… the production of wealth to a given amount of labor increases as population increases.”  The frequent interactions among people in densely populated cities accelerates the emergence and evolution of code. However, while population growth and increased density naturally bring increased prosperity, they also, just as naturally, bring increasing inequality and poverty. Why? Because the fruits of labor are inevitably gathered by the owners of land.

In other words, increasing wages => increasing rents and the workers are right back where they started while the landlords are sitting pretty.

In sharp contrast with Karl Marx, … George stated that “the antagonism of interest is not between labor and capital… but is in reality between labor and capital on the one side and the land ownership on the other.” The implication of his analysis was as simple as it was powerful: to avoid concentrating wealth in the hands of the few, it was the government’s responsibility to eliminate all taxes on capital and laborers, the productive elements of the economy, and to replace those taxes with a single tax on land.

Note: not a flat tax on land, but a tax relative to the land’s sale value.

I was glad to see Henry George in the book because I enjoy George’s theories and they are under-discussed, especially relative to Marxism. You will find massive online communities of Marxists despite the absolute evidence that Marxism is a death machine, but relatively few enthusiastic Georgists. One of the things I rather appreciate about Georgism is its simplicity; the complication of the tax code is its own, additional burden on capitalists and workers alike. Almost any simplified tax code, no matter how “unfair,” would probably improve maters a great deal.

But there’s more, because this is a dense chapter. Auerswald notes that the increasing complexity of code (ie, productivity) has lead to steadily increasing standards of living over the past two centuries, at least after the Industrial Revolution’s initial cataclysm.

Quoting economist Paul Douglas, some years later:

“The increased use of mechanical appliances in offices has tended to lower the skill required. An old-fashioned bookkeeper, for instance, had to write a good hand, he had to be able to multiply and divide with absolute accuracy. Today his place is taken by a girl who  operates a book-keeping machine, and it has taken her a few weeks at mot to become a skilled bookkeeper.” In other words, the introduction of machinery displaced skilled workers for the very same reason it enhanced human capabilities: it allowed a worker with relatively rudimentary training to perform tasks that previously required a skilled worker.

…”Another way of looking at it, is this: Where formerly the skill used in bookkeeping was exercised by the bookkeeper, today that skill is exercised by the factory employees who utilize it to manufacture a machine which can do the job of keeping books, when operated by someone of skill far below that of the former bookkeeper. And because of this transfer of skill form the office to the factory, the rewards of skill are likewise transferred to the wage-earner at the plant.”

This is a vitally important pint… The essence of this insight is that introducing more powerful machines into the workplace does more than simply encode  into the machine the skills or capabilities that previously resided only in humans; it also shifts the burden of skill from one domain of work to another. … A comparable shift in recent decades has been from the skill of manufacturing computing machines (think IBM or Dell in their heydays) to that of creating improved instructions for computing machines’ the result has been a relative growth in programmers’ wages. The underlying process is the same. Improvements in technology will predictably reduce demand for the skills held by some workers, but they also will enhance the capabilities of other workers and shift the requirements of skill from one domain of work to the other.”

The problem with this is that the average person puts in 15-20 years of schooling (plus $$$) in order to become skilled at a job, only to suddenly have that job disappear due to accelerating technological change/improvement, and then some asshole one comes and tells them they should just “learn to code” spend another two to four years unemployed and paying for the privilege of learning another job and don’t see how fucking dispiriting this is to the already struggling.

The struggle for society is recognizing that even as standards of living may be generally rising, some people may absolutely be struggling with an economic system that offers much less certainty and stability than our ancestors enjoyed.

A final word from Auerswald:

… work divides or “bifurcates” as code advances in a predictable and repeatable way. The bifurcation of work in a critical mechanism by which the advance of code yields improvements in human well-being at the same time as it increases human reliance on code.

Which came first, the City or the Code? (book club Code Economy Ch 2)

The Code of Hammurabi

Writing, which is itself a form of code, enable humans to communicate code. Cities grow as code evolves. –Auerswald

Welcome to The Code Economy: A Forty-Thousand Year History, by Philip E. Auerswald. Chapter Two: Code looks at two epochal developments in human history: writing and cities.

One of the earliest pieces of writing we have uncovered is the Sumerian Hymn to Ninkasi, Goddess of Beer, which contains, yes, a recipe for making beer (translation by Miguel Civil):

Your father is Enki, Lord Nidimmud,
Your mother is Ninti, the queen of the sacred lake.
Ninkasi, your father is Enki, Lord Nidimmud,
Your mother is Ninti, the queen of the sacred lake.

You are the one who handles the dough [and] with a big shovel,
Mixing in a pit, the bappir with sweet aromatics,
Ninkasi, you are the one who handles the dough [and] with a big shovel,
Mixing in a pit, the bappir with [date] – honey,

You are the one who bakes the bappir in the big oven,
Puts in order the piles of hulled grains,
Ninkasi, you are the one who bakes the bappir in the big oven,
Puts in order the piles of hulled grains,

You are the one who waters the malt set on the ground,
The noble dogs keep away even the potentates,
Ninkasi, you are the one who waters the malt set on the ground,
The noble dogs keep away even the potentates,

You are the one who soaks the malt in a jar,
The waves rise, the waves fall.
Ninkasi, you are the one who soaks the malt in a jar,
The waves rise, the waves fall.

You are the one who spreads the cooked mash on large reed mats,
Coolness overcomes,
Ninkasi, you are the one who spreads the cooked mash on large reed mats,
Coolness overcomes,

You are the one who holds with both hands the great sweet wort,
Brewing [it] with honey [and] wine
(You the sweet wort to the vessel)
Ninkasi, (…)(You the sweet wort to the vessel)

The filtering vat, which makes a pleasant sound,
You place appropriately on a large collector vat.
Ninkasi, the filtering vat, which makes a pleasant sound,
You place appropriately on a large collector vat.

When you pour out the filtered beer of the collector vat,
It is [like] the onrush of Tigris and Euphrates.
Ninkasi, you are the one who pours out the filtered beer of the collector vat,
It is [like] the onrush of Tigris and Euphrates.

Sumerian tablet recording the allocation of beer

You guys requested beer or wine with your books, so here you go.

The hymn contains two layers of code–first, there is the code which allows each symbol or character to stand for a particular sound, which let the author write down the recipe and you, thousands of years later, decode and read the recipe; and second, there is the recipe itself, a code for producing beer.

The recipe’s code likely far predates the hymn itself, as humans had begun brewing beer at least a couple thousand years earlier.

Writing and cities go hand in hand; it is difficult to imagine managing the day-to-day need to import food (and water) for thousands of people without some ability to encode information. As cities grow larger, complexity grows: one man in the woods may relieve himself behind a tree; thousands of people packed into a square mile cannot.

Each solved problem, once routinized, becomes its own layer of code, building up as the city itself expands; a city of thousands or millions of people cannot solve each person’s problems anew each day.

Gobekli Tepe, Turkey

But which came first, the city or the alphabet? Did the growth of cities spur innovations that improved agricultural output, or did agricultural innovations spur the growth of cities?

For example, settlement and construction appear to have gotten underway at Jericho (one of the world’s oldest inhabited cities) around 9 or 10,000 BC and at the mysterious Gobekli Tepe site began around 7-9,000 BC, before agriculture emerged in the region.

Writing developed a fair bit later, developing from clay shapes to shapes impressed in clay between 8,000 and 4,000 BC.

Amphitheater, Norte Chico, Peru

Others of the world’s earliest civilizations had either no or very little writing. The Norte Chico civilization of Peru, for example; by the time the Spaniards arrived, the Inca had an accounting system based on the quipu, a kind of string abacus, but appear to have not yet developed a true writing system, despite their palaces, cities, roads, emperor, and tax collectors. (Here is my previous post on Norte Chico.)

The Great Bath of Mohenjo-daro

The extensive Indus Valley civilization had some form of symbolic encoding, but few of their inscriptions are longer than 4 or 5 characters–the longest inscription found so far is 26 symbols, spread over three different sides of an object. Not exactly an epic–but the Indus Valley Civilization was nevertheless quite large and impressive, supporting perhaps 5 million people. (Previous post on the Indus Valley.)

Auerswald documents some of the ways cities appear to drive innovation–and to “live”:

The Santa Fe team found that cities are like biological organisms when it comes to “metabolic” urban processes that are analogous to nutrient supply and waste removal–transportation, for example, ha a branching structure much like veins or bronchi–but that cities differ fundamentally from biological organisms when it comes to indicators reflecting the creation and transmission of code. measuring the size of cities based on population and on the urban “metabolism” using metrics such as wages, GDP, electric power and gasoline consumption, and total  road surface, the team found a systematic relationship between city size and indicators of the supply of “nutrients” and waste removal… However, while metabolic indicators do not keep pace with the size of cities as they grow, indicators relating to the creation and transmission of code increase at a greater rate than city size. … In short, the creation of ideas accelerates with city growth, whereas the cost of new infrastructure is minimized.

This intriguing macro-level departure from the inverse relationships that hold for organisms ends up risking more questions about the evolution of cities than it answers: What mechanism enables larger cities to produce disproportionately more innovation and wealth than smaller cities?

Data Economy has a fascinating article in a similar vein: Street Smarts: The Rise of the Learning City:

The city as a brain

An amalgam of terms that have been used for parallel conceptions of the Smart City among them cyberville, digital city, electronic communities, flexicity, information city, intelligent city, knowledge-based city, MESH city, telecity, teletopia, ubiquitous city, wired city.

However the one I would like to propose, with population movement in mind, is The Learning City.

The term is based on a combination of two theories The Ego City and The Flynn Effect.

In 2009 Neurobiologist Mark Changizi from the Rensselaer Polytechnic Institute released a paper entitled Ego City: Cities Are Organized Like Human Brain.

Changizi sees strikingly real similarities between the brain and a city.

The central idea being that they organise and evolve similarly due to the need for efficiency.

As brains grow more complex from one species to the next, they change in structure and organisation in order to achieve the right level of reciprocity.

This is analogous to the widening of streets in cities.

The research team found mutual “scaling laws” for brains and cities.

For example, as the surface area of a brain or city grows, the number of connectors (neurons or highways) increased at a similar rate for each.

Likewise, a bigger city needs more highway exits in the same proportion as a bigger brain needs more synapses connecting neurons.

“The brain is like a city.

Cities develop and grow bigger and may get problems with roads and infrastructure, which is similar to what happens to our brains when we get older”, notes Håkan Fischer, Professor of Biological Psychology at the Department of Psychology at Stockholm University.

 The learning city

This is curious when taken in the context of The Flynn Effect.

Intelligence Researcher James Flynn found that every decade without fail the human population scored higher on IQ tests.

An average increase of 3 points per decade.

His thesis suggests that the more information we as humans have to absorb and compute leads to an increase in IQ.

In this instance the increased information is data collected within the city.

As cities gain more data they adapt and in turn get smarter.

Human brains faced with a busier world filled with more information brings about an increase in IQ from generation to generation.

As people migrant to cities creating a more complex environment for the city it to must gather this data, learn and raise its Smart City IQ.

This is The Learning City.

On the other hand, the data Auerswald cites–from the “Santa Fe Team”–only looks at cities from the US, China, the EU, and Germany. How would this data look if it incorporated other megacities, like Manila, Philippines (the world’s densest city); Sao Paolo, Brazil; Bombay, India; Caracas, Venezuela; Karachi, Pakistan; or Jakarta, Indonesia? Of the world’s ten biggest cities, only two–Seoul, #1, and Tokyo, #10–are in the first world. (#9 Shanghai, is well on its way.)

#2 Sao Paolo might be more energy efficient than villages in the Brazilian hinterland (or it may not, as such towns may not even have electricity,) but does it produce more innovation than #11 New York City? (No American city made the top 10 by population.)

If cities are drivers of innovation, why are so many of the biggest in the third world? Perhaps third world countries offer their citizens so little that they experience a form of extreme brain drain, with everyone who can fleeing to the most productive regions. Or perhaps these cities are simply on their way–in a century, maybe Sao Paolo will be the world’s next Shanghai.

The city, by definition, is civilization–but does the city itself spur innovation? And are cities, themselves, living things?

Geoffrey West has some interesting things to say on this theme:

“How come it is very hard to kill a city? You can drop an atom bomb on a city, and 30 years later, it’s surviving.”

Here’s a transcript of the talk.

Hiroshima in 1945:

Hiroshima today:

Hiroshima montage

Detroit, 1905:

Belle Isle Park, Detroit, 1905–h/t Photos of Detroit’s Golden Age

Detroit today:

Detroit Book Depository

“Bombs don’t destroy cities; people destroy cities.”

I Dream of 3D: Makerbot, IP, and the advance of Technology

There is an oddly fascinating documentary on Netflix about 3D Printers, Print the Legend. The story follows two startups–MakerBot and Formlabs–and three established companies–Stratasys, PrintForm and 3D Systems.

I don’t think we’re heading toward a micro-industrial revolution, a 3D printer in every backyard, but they have many interesting possibilities:

3D printing seems perfect for reasonably small, individually customized items like prosthetics, dentures, hearing aids, and shoe inserts. I can easily imagine a vending machine at the shoe store that takes an impression of your feet and then prints custom inserts while you wait–like the photo booth that prints silly pictures of you and your friends.

But let’s discuss possibilities later–today we’re discussing MakerBot, IP, and learning curve. MakerBot was founded in 2009 by Adam Mayer, Zach Smith, and Bre Pettis. The original MakerBot Printers were quite cute, with a DIY, home-hobbiest feel. (They were, in fact, DIY-kits you assembled yourself.) Later MakerBots, by contrast, look like digital ovens and come pre-assembled–aimed at the “professional consumer” market.

In its early days, MakerBot was a creativity-driven startup cobbling everything together in a warehouse where, as they put it, new employees even had to build their own chair when they arrived.

In those days, MakerBot attracted the sorts of hacker nerds who wanted to work in a startup warehouse, and adhered to hacker ethics: the hardware was open-source.

Open-Source hardware meant you could copy their design and build your own, or you could modify your MakerBot and share your innovations with the broader MakerBot community. With an enthusiastic community working together, it wasn’t long before user-created innovations were incorporated back into the MakerBot’s products.

MakerBot also launched Thingiverse, essentially the MakerBot Open-Source community’s home and database on the web.

As MakerBot moved from startup dream to reality, the culture changed. By mid-2011, they had sold about 3,500 bots. In late 2011, The Foundry Group (venture capitalists) invested $10 million and joined the company’s board. In 2012, Bre Pettis pushed out co-founder Zach Smith, (who wanted to remain true to their founding principles.) A month later, the company moved from its startup garage to a New York apartment office headquarters in the sky.

Bre Pettis fired about 100 people (they only had 125 employees when they moved) and hired far more. These new employees weren’t hacker nerds; they were the kinds of people who wanted to wear suits and work in an office.

A few months later, in a massively controversial move, MakerBot went closed-source.

By June of 2013, they had sold 22,000 printers, and competitor Stratasys Incorporated decided to eliminate them by buying them for $604 million. Good deal for Bre Pettis; shitty for Zach Smith and all of the folks in the MakerBot community whose Open Source hardware ideas eventually made Pettis rich.

In 2016, MakerBot/Stratasys moved their manufacturing plant from New York to China.

Did MakerBot do wrong by transitioning from Open to Closed source? Did they cheat the people who helped them grow, or did they make a wise economic decision?

The growth curve for new startups is initially quite flat:

This is actually the growth curve for yeast, but it’s the same for companies. In their first few years, companies experience little–even negative–growth. Only once they reach a particular size and level of competence do corporations enter a period of rapid growth (until, at maturity, they have captured as much of the market as they reasonably can.)

Much of the difficulty for a new company–especially a company that is building a new product–is informational. Where do I buy parts? Where do I buy 10,000 parts? Where can I hire workers? How do I withhold income taxes from paycheques? Where did I put the receipts for those 10,000 widgets I ordered? What do you mean you threw out all of the steel because it wasn’t good enough?

Solving problems and then routinizing those solutions–as Auerswald would put it, developing code–is critical to early growth. More employees means more knowledge and ideas, but employees cost money, and new companies don’t have a lot of money.

Here’s where Open-Source comes in: by expanding the number of people effectively working on the problem (at least on the hardware end), the open-source community greatly increased MakerBot’s effective company size without increasing costs. Free expertise=faster growth. The community also fostered growth by increasing demand for the bots themselves, as each person who contributed quality printing ideas to the Thingiverse databases increased the realm of ideas other makers and potential makers had to be inspired by.

Once the hardware designs were basically perfected, Open-Source could no longer contribute to hardware innovation, and became a liability, as people could simply download blueprints and make their own bots without paying any money to MakerBot. At this point, as MakerBot entered its rapid growth phase, moved to bigger offices and hired a ton of new employees, it abandoned open-source.

There is a very similar phenomenon in the world of writing, but the ethics are regarded very differently. Many aspiring novelists are members of writer’s clubs, critique groups, or fandoms where they post, share, read, and give feedback on each other’s work. This creative foment and mixing of ideas spurs innovation–as when fan works take on a life of their own nearly independent of the original–and refinement, as when a novel is finally polished and sent out to publishers.

In some cases, very popular writers initially built up followings by publishing in fandoms based around established books or movies before transferring that audience to their own, original works. 50 Shades of Gray, for example, started as Twilight fan-fiction before morphing into its own book.

In other words, in their initial, creative phases, many novels are essentially “open;” this allows the writer to draw on the knowledge and expertise of dozens of other writers. When the novel is good enough to consider publication, it becomes “closed;” a published novel costs money. (It is considered good manners, though, to offer a free copy of the novel a a thank-you gift to anyone who gave significant help along the way.)

This is the same open and closed process as MakerBot pursued, but since it is considered normal and completely expected in writing communities for people to take suggestions, incorporate them into their stories, and then try to pitch the stories to agents, no one looks askance at it. I myself have edited many novels, one of which is now an Actually Published Book by a Real Author. I don’t resent that the book I once read for free and offered feedback for now costs money; I’m just happy on behalf of the author and glad I could help.

By contrast, people were surprised by MakerBot’s pivot, even though it made sound business sense. Surprising people tends to piss them off.

Traditional IP is structured so that copyright/patent protection starts at the time of innovation and eventually runs out; it doesn’t really include an open or semi-open period after which the work becomes closed. In writing this is handled by a convention that so long as the entire novel is not openly posted on the internet or elsewhere, the author can still sell the rights to it. I don’t know how things work over in patents, but given the number of patent infringement lawsuits filed every year, attempting to share designs that you would later like to make closed sounds like a potential nightmare.

Nevertheless, I think something like this Open-Closed process would be beneficial for many new companies, especially as they struggle to grow, learn, and optimize. If it were expected, as in writers’ communities, then the pivot to closed-source wouldn’t be seen as a betrayal, but as a sign of success–a company that had made it big.

Spurring innovation doesn’t just help companies and their owners. We all benefit from better products. Amputees benefit from better, cheaper prosthesis. Sick people benefit from better, cheaper medicines. Poor people benefit from better, cheaper houses.

Just imagine three of these, joined together, located anywhere you want to live…

 

Book Club: The Code Economy pt 1

I don’t think the publishers got their money’s worth on cover design

Welcome to EvX’s Book Club. Today we begin our exciting tour of Philip E. Auerswald’s The Code Eoconomy: A Forty-Thousand-Year History. with the introduction, Technology = Recipes, and Chapter one, Jobs: Divide and Coordinate if we get that far.

I’m not sure exactly how to run a book club, so just grab some coffee and let’s dive right in.

First, let’s note that Auerswald doesn’t mean code in the narrow sense of “commands fed into a computer” but in a much broader sense of all encoded processes humans have come up with. His go-to example is the cooking recipe.

The Code Economy describes the evolution of human productive activity from simplicity to complexity over the span of more than 40,000 years. I call this evolutionary process the advance of code.

I find the cooking example a bit cutesy, but otherwise it gets the job done.

How… have we humans managed to get where we are today despite our abundant failings, including wars, famine, and a demonstrably meager capacity for society-wide planning and coordination? … by developing productive activities that evolve into regular routines and standardized platforms–which is to say that we have survived, and thrived, by creating and advancing code.

There’s so much in this book that almost every sentence bears discussion. First, as I’ve noted before, social organization appears to be a spontaneous emergent feature of every human group. Without even really meaning to, humans just naturally seem compelled organize themselves. One day you’re hanging out with your friends, riding motorcycles, living like an outlaw, and the next thing you know you’re using the formal legal system to sue a toy store for infringement of your intellectual property.

Alexander Wienberger, Holodomor

At the same time, our ability to organize society at the national level is completely lacking. As one of my professors once put it, “God must hate communists, because every time a country goes communist, an “act of god” occurs and everyone dies.”

It’s a mystery why God hates communists so much, but hate ’em He does. Massive-scale social engineering is a total fail and we’ll still be suffering the results for a long time.

This creates a kind of conflict, because people can look at the small-scale organizing they do, and they look at large-scale disorganization, and struggle to understand why the small stuff can’t simply be scaled up.

And yet… society still kind of works. I can go to the grocery store and be reasonably certain that by some magical process, fresh produce has made its way from fields in California to the shelf in front of me. By some magical process, I can wave a piece of plastic around and use it to exchange enough other, unseen goods to pay for my groceries. I can climb into a car I didn’t build and cruise down a network of streets and intersections, reasonably confident that everyone else driving their own two-ton behemoth at 60 miles an hour a few feet away from me has internalized the same rules necessary for not crashing into me. Most of the time. And I can go to the gas station and pour a miracle liquid into my car and the whole system works, whether or not I have any clue how all of the parts manage to come together and do so.

The result is a miracle. Modern society is a miracle. If you don’t believe me, try using an outhouse for a few months. Try carrying all of your drinking water by hand from the local stream and chopping down all of the wood you need to boil it to make it potable. Try fighting off parasites, smallpox, or malaria without medicine or vaccinations. For all my complaints (and I know I complain a lot,) I love civilization. I love not worrying about cholera, crop failure, or dying from cavities. I love air conditioning, refrigerators, and flush toilets. I love books and the internet and domesticated strawberries. All of these are things I didn’t create and can’t take credit for, but get to enjoy nonetheless. I have been blessed.

But at the same time, “civilization” isn’t equally distributed. Millions (billions?) of the world’s peoples don’t have toilets, electricity, refrigerators, or even a decent road from their village to the next.

GDP per capita by country

Auerswald is a passionate champion of code. His answer to unemployment problems is probably “learn to code,” but in such a broad, metaphorical way that encompasses so many human activities that we can probably forgive him for it. One thing he doesn’t examine is why code takes off in some places but not others. Why is civilization more complex in Hong Kong than in Somalia? Why does France boast more Fields Medalists than the DRC?

In our next book (Niall Ferguson’s The Great Degeneration,) we’ll discuss whether specific structures like legal and tax codes can affect how well societies grow and thrive (spoiler alert: they do, just see communism,) and of course you are already familiar with the Jared Diamond environmentalist theory that folks in some parts of the world just had better natural resources to work than in other parts (also true, at least in some cases. I’m not expecting some great industry to get up and running on its own in the arctic.)

IQ by country

But laying these concerns aside, there are obviously other broad factors at work. A map of GDP per capita looks an awful lot like a map of average IQs, with obvious caveats about the accidentally oil-rich Saudis and economically depressed ex-communists.

Auerswald believes that the past 40,000 years of code have not been disasters for the human race, but rather a cascade of successes, as each new invention and expansion to our repertoir of “recipes” or “codes” has enabled a whole host of new developments. For example, the development of copper tools didn’t just put flint knappers out of business, it also opened up whole new industries because you can make more varieties of tools out of copper than flint. Now we had copper miners, copper smelters (a  new profession), copper workers. Copper tools could be sharpened and, unlike stone, resharpened, making copper tools more durable. Artists made jewelry; spools of copper wires became trade goods, traveling long distances and stimulating the prehistoric “economy.” New code bequeaths complexity and even more code, not mass flint-knapper unemployment.

Likewise, the increase in reliable food supply created by farming didn’t create mass hunter-gatherer unemployment, but stimulated the growth of cities and differentiation of humans into even more professions, like weavers, cobblers, haberdashers, writers, wheelwrights, and mathematicians.

It’s a hopeful view, and I appreciate it in these anxious times.

But it’s very easy to say that the advent of copper or bronze or agriculture was a success because we are descended from the people who succeeded. We’re not descended from the hunter-gatherers who got displaced or wiped out by agriculturalists. In recent cases where hunter-gatherer or herding societies were brought into the agriculturalist fold, the process has been rather painful.

Elizabeth Marshall Thomas’s The Harmless People, about the Bushmen of the Kalahari, might overplay the romance and downplay the violence, but the epilogue’s description of how the arrival of “civilization” resulted in the deaths and degradation of the Bushmen brought tears to my eyes. First they died of dehydration because new fences erected to protect “private property” cut them off from the only water. No longer free to pursue the lives they had lived for centuries, they were moved onto what are essentially reservations and taught to farm and herd. Alcoholism and violence became rampant.

Among the book’s many characters was a man who had lost most of his leg to snakebite. He suffered terribly as his leg rotted away, cared for by his wife and family who brought him food. Eventually, with help, he healed and obtained a pair of crutches, learned to walk again, and resumed hunting: providing for his family.

And then in “civilization” he was murdered by one of his fellow Bushmen.

It’s a sad story and there are no easy answers. Bushman life is hard. Most people, when given the choice, seem to pick civilization. But usually we aren’t given a choice. The Bushmen weren’t. Neither were factory workers who saw their jobs automated and outsourced. Some Bushmen will adapt and thrive. Nelson Mandela was part Bushman, and he did quite well for himself. But many will suffer.

What to do about the suffering of those left behind–those who cannot cope with change, who do not have the mental or physical capacity to “learn to code” or otherwise adapt remains an unanswered question. Humanity might move on without them, ignoring their suffering because we find them undeserving of compassion–or we might get bogged down trying to save them all. Perhaps we can find a third route: sympathy for the unfortunate without encouraging obsolete behavior?

In The Great Degeneration, Ferguson wonders why the systems (“code”) that supports our society appears to be degenerating. I have a crude but answer: people are getting stupider. It takes a certain amount of intelligence to run a piece of code. Even a simple task like transcribing numbers is better performed by a smarter person than a dumber person, who is more likely to accidentally write down the wrong number. Human systems are built and executed by humans, and if the humans in them are less intelligent than the ones who made them, then they will do a bad job of running the systems.

Unfortunately for those of us over in civilization, dysgenics is a real thing:

Source: Audacious Epigone

Whether you blame IQ itself or the number of years smart people spend in school, dumb people have more kids (especially the parents of the Baby Boomers.) Epigone here only looks at white data (I believe Jayman has the black data and it’s just as bad, if not worse.)

Of course we can debate about the Flynn effect and all that, but I suspect there two competing things going on: First, a rising 50’s economic tide lifted all boats, making everyone healthier and thus smarter and better at taking IQ tests and making babies, and second, declining infant mortality since the late 1800s and possibly the Welfare state made it easier for the children of the poorest and least capable parents to survive.

The effects of these two trends probably cancel out at first, but after a while you run out of Flynn effect (maybe) and then the other starts to show up. Eventually you get Greece: once the shining light of Civilization, now defaulting on its loans.

Well, we have made it a page in!

Termite City

What do you think of the book? Have you finished it yet? What do you think of the way Auersbach conceptualizes of “code” and its basis as the building block of pretty much all human activity? Do you think Auersbach is essentially correct to be hopeful about our increasingly code-driven future, or should we beware of the tradeoffs to individual autonomy and freedom inherent in becoming a glorified colony of ants?

Come read “The Code Economy: A 40,00 Year History” with us

I don’t think the publishers got their money’s worth on cover design

EvX’s Book Club is reading Philip Auerswald’s The Code Economy: A 40,000 Year History looks at how everything humans produce, from stone tools to cities to cryptocurrencies like bitcoin, requires the creation, transmission, and performance of “code,”  and explores the notion that human societies–and thus civilization–is built on a mountain of of encoded processes.

I loved this book and am re-reading it, so I would like to invite you to come read it, too.

Discussion of Chapter 1 Jobs: Divide and Coordinate, will begin on May 23 and last as long as we want it to.

Here’s Amazon’s blurb about the book:

What do Stone Age axes, Toll House cookies, and Burning Man have in common? They are all examples of code in action.

What is “code”? Code is the DNA of human civilization as it has evolved from Neolithic simplicity to modern complexity. It is the “how” of progress. It is how ideas become things, how ingredients become cookies. It is how cities are created and how industries develop.

In a sweeping narrative that takes readers from the invention of the alphabet to the advent of the Blockchain, Philip Auerswald argues that the advance of code is the key driver of human history. Over the span of centuries, each major stage in the advance of code has brought a shift in the structure of society that has challenged human beings to reinvent not only how we work but who we are.

We are in another of those stages now. The Code Economy explains how the advance of code is once again fundamentally altering the nature of work and the human experience. Auerswald provides a timely investigation of value creation in the contemporary economy-and an indispensable guide to our economic future.

Thoughts on the Loss of Social Capital

Spotted Toad posed a question on the loss of Social Capital, my response to which I have been encouraged to encapsulate in a post:

Do you tend to think of reduced social capital as more the result of overgrown education, government, etc “crowding out” other institutions or those institutions withering on the vine of themselves?

Using Toad’s definition of Social Capital as, “the networks of relationships that guide individuals’ behavior and identity (particularly outside of formal economic relationships),” here goes:

First, I’d like to note that Toad’s basic premise is correct. For example, in Social Isolation in America: Changes in Core Discussion Networks over Two Decades, researchers found that:

In 1985, the General Social Survey (GSS) collected the first nationally representative data on the confidants with whom Americans discuss important matters. In the 2004 GSS the authors replicated those questions to assess social change in core network structures. Discussion networks are smaller in 2004 than in 1985. The number of people saying there is no one with whom they discuss important matters nearly tripled. … Both kin and non-kin confidants were lost in the past two decades, but the greater decrease of non-kin ties leads to more confidant networks centered on spouses and parents, with fewer contacts through voluntary associations and neighborhoods.

Things have only gotten worse since 2004.

(Of course, Robert Putnam noticed this in Bowling Alone, which I’ll get to in a minute.)

We could look at a number of other metrics of loneliness/connection: number of kids people have; number of siblings; percent of people who are married; age of first married. Spoiler alert: all of the data is bad. We’re so atomized, we make actual “atoms” look positively social.

The causes of our decrease in social capital are obviously multi-factoral, but here are some important elements I see:

Clan House and Totem pole from Saxman, Alasaka (Haida People, I believe)

1. Few people live where they grew up, much less where their grandparents grew up. People used to live in communities (or houses!) with multiple generations of the same family–cousins, 2nd cousins, etc.

For example, the Northwest Coast Cultures, ie the Tlingit, Haida, Eyak, and Tsimshian peoples, built clan houses that held 20-50 people, most extended family members. Clan houses are found around the world, from Pakistan to China and even Melanesia.

A friend of mine grew up in an actual multi-generational household, including grandparents, parents, aunts, uncles, and cousins, (and liked it there.)

Another friend who moved back in with her parents after graduation once received a surprise phone call from an old friend she hadn’t seen since elementary school. That friend had tracked down her grandparents’ phone number from 25 years ago, and as her grandparents had only moved a block away in that time, it only took a few minutes for the house’s new residents to reconnect the old friends.

But today, most of us expect to move across the country for school and jobs. My grandparents live a thousand miles from where they grew up, so do my parents, and so do I. Calling my grandparents’ old house wouldn’t get you anywhere. Many of us go through decades where we move every year.

In a community where you grew up, and your parents grew up, and your friends grew up, and their parents grew up, you get the classic case of “everyone knows everyone.” Sure, that can be annoying–but it’s also useful when you’re looking for a skilled plumber and you can just hire the guy who did a great job on your grandma’s plumbing last year.

Communities have simultaneously become bigger and more transient. What’s the point of learning your neighbor’s name if they’re just going to move out in a few years?

2. On top of that, we have technology that makes staying inside more pleasant than going outside. We used to go on the porch to stay cool in the summer, giving us a chance to meet our neighbors; now we stay in with the AC on and watch TV/Twitter.

I like being outside and am often vaguely surprised when, on a particularly pleasant evening, suddenly neighbors I’ve never seen before are in their yards.

Even when we do go out, we’re often still immersed in our phones, ignoring the other humans around us.

3. Community Breakup

Of course Putnam wrote the book on declining social capital (linked at the top of the post.) Among the many causes he investigated, diversity has what appears to be the biggest negative effect:

Prof. PUTNAM: Well, I’ve been interested in the questions of our connections with one another for a long time. I sometimes use the jargon of social capital to refer to the connections – our ties with our friends and neighbors and community and institutions and so on.

And about seven or eight years ago, at the request of communities all across America – big communities and small communities – we did a very large national survey, trying to measure the level of civic engagement and the number of friends people have and how they got along with their local government and so on, in 40 very different communities, places you’ve heard of like Los Angeles or Boston or Atlanta or Detroit or Chicago, and places you haven’t heard, little rural counties in the South Dakota or up in the Appalachias in West Virginia, or villages in New Hampshire – places all over. …

But what we discovered in this research, somewhat to our surprise, was that in the short run the more ethnically diverse the neighborhood you live in, the more you – every – all of us tend to hunker down, to pull in. The more diverse – and when I say all of us, I mean all of us. I mean blacks and whites and Asians and Latinos, all of us. The more diverse the group around us, ethnically, in our neighborhood, the less we trust anybody, including people who look like us. Whites trust whites less. Blacks trust blacks less, in more diverse settings.

Why?

3 main factors: first, people from other cultures are literally not from yours; you don’t have the same cultural background and normative expectations as they do. Often people don’t even speak the same language. For a multi-cultural society to work entails creating a new, meta-culture that includes the norms and background knowledge of everyone involved–and that takes time.

Second, the presence of non-cultural members in your community means your community has been physically split apart. Consider an Irish Catholic neighborhood in which all of the locals can walk to the same church, restaurants, shops, and school, where they frequently meet and socialize. Now consider what happens when a new group moves in–let’s say Lutherans. The physical presence of the Lutherans means some of the Irish no longer live near the church or the shops. The old pub gets bought out and replaced with restaurant catering to Lutheran palates. Now you have to go two miles over to get proper mashed potatoes, and maybe you just don’t feel like going that far. The neighborhood has lots its “character.” It withers.

Third, crime. The end of Jim Crow and Great Migration of millions of African Americans to northern cities was marked by a sharp uptick in crime. There were riots–in 1967, the Detroit riot killed 43 people and burned 2,000 buildings. In 1910, Detroit was 98.7% white and one of the world’s richest cities; today it is <10% white, 82.7% black, and a festering wound that anyone who can escape, has.

Where integration happened, it typically didn’t happen in upper-class neighborhoods, but in working class burgs, notably Irish, Italian, and Jewish ones. For example, Harlem, NY, was mostly Jewish and Italian in 1900. In 1910, it was 10% black. By 1930, it was 70%, due to the efforts of enterprising black realtors who saw an opportunity to move blacks into Harlem. Today it is mostly black and Puerto Rican; the Jews and the Italians fled the violence.

When busing began in Boston, Southie’s Irish nearly rioted, hurling rocks at the buses and spit at the students.

Crime soared; inner-city schools became warzones; white students were withdrawn and sent to private schools across town. As neighborhoods cratered families moved, losing the investments they’d poured into their houses. Now moms, dads, and kids all commuted far from their homes every day. (Moms have to pitch in and work, too, to afford the increased housing, school, and transportation costs–so now kids don’t even get to see them after school.) If you were lucky enough to make a friend, you probably weren’t lucky enough to live near enough to hang out.

Few of us today have ever lived in anything resembling a healthy, organic community. Those of us in the suburbs live in HOA-ruled fiefdoms where neighbors report each other for parking in the street or letting their dogs defecate in the back yard, while those in the city are taught to always be alert and never make eye-contact with anyone they pass.

So there are no more organic communities; people commute to work because jobs and “good schools” aren’t in the same place; people stay inside and watch TV instead of go outside and meet their neighbors, etc.

4. Then there’s the big change in employment, from self-employed farmers to employees of larger conglomerates. People used to have individual skills, products, etc. that they could individually trade with each other. Bob might know how to raise a barn; Sally how to milk a goat. Together, Bob and Sally are a pretty good team. Even 50 years ago, even though barns and goats were less important, there were more small businesses, fewer Walmarts.

Today you trade your skills less directly with other humans and more often with corporations. Bob is “skilled with IT systems delivery” and Sally is an “HR representative.” Together they accomplish… not much.

So social capital itself is less important than “selling yourself to the corporation” capital. Maybe we’ll call that corporate capital.

5. There are probably lots of other factors, too, like increasing atheism (the local church is a good place to meet your neighbors if you all attend and a convenient place for community events.) Even an atheist can agree that churches are a great forum for running community events; they have spaces where dinners and weddings can be held; they host ritual gatherings and reinforce moral and social norms. They do charity and host social gatherings.

Further, religious institutions promote a sense of belonging and duty to the group (and maybe there is some inherent utility to believing in a deity.)

Local Optima, Diversity, and Patchwork

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.

Sequoyah’s syllabary, showing script and print forms

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.

When I walk around our cities, I often think about what their ruins will look like to explorers in a thousand years
We also pass a ruin of what once must have been a grand building. The walls are marked with logos from a Belgian University. This must have once been some scientific study centre of sorts.”

By contrast, there are many cases of people being exposed to or given a new technology but completely lacking the ability to functionally adopt, improve, or maintain it. The Democratic Republic of the Congo, for example, is full of ruined colonial-era buildings and roads built by outsiders that the locals haven’t maintained. Without the Belgians, the infrastructure has crumbled.

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.

Which gets us back to Patchwork.

Do Sufficiently Large Organizations Start Acting Like Malevolent AIs? (pt 2)

(Part 1 is here)

As we were discussing on Monday, as our networks have become more effective, our ability to incorporate new information may have actually gone down. Ironically, as we add more people to a group–beyond a certain limit–it becomes more difficult for individuals with particular expertise to convince everyone else in the group that the group’s majority consensus is wrong.

The difficulties large groups experience trying to coordinate and share information force them to become dominated by procedures–set rules of behavior and operation are necessary for large groups to operate. A group of three people can use ad-hoc consensus and rock-paper-scissors to make decisions; a nation of 320 million requires a complex body of laws and regulations. (I once tried to figure out just how many laws and regulations America has. The answer I found was that no one knows.)

An organization is initially founded to accomplish some purpose that benefits its founders–generally to make them well-off, but often also to produce some useful good or service. A small organization is lean, efficient, and generally exemplifies the ideals put forth in Adam Smith’s invisible hand:

It is not from the benevolence of the butcher, the brewer, or the baker, that we expect our dinner, but from their regard to their own interest. We address ourselves, not to their humanity but to their self-love, and never talk to them of our necessities but of their advantages. —The Wealth Of Nations, Book I

As an organization ages and grows, its founders retire or move on, it becomes more dependent on policies and regulations and each individual employee finds his own incentives further displaced from the company’s original intentions. Soon a company is no longer devoted to either the well-being of its founders or its customers, but to the company itself. (And that’s kind of a best-case scenario in which the company doesn’t just disintegrate into individual self-interest.)

I am reminded of a story about a computer that had been programmed to play Tetris–actually, it had been programmed not to lose at Tetris. So the computer paused the game. A paused game cannot lose.

What percentage of employees (especially management) have been incentivized to win? And what percentage are being incentivized to not lose?

And no, I don’t mean that in some 80s buzzword-esque way. Most employees have more to lose (ie, their jobs) if something goes wrong as a result of their actions than to gain if something goes right. The stockholders might hope that employees are doing everything they can to maximize profits, but really, most people are trying not to mess up and get fired.

Fear of messing up goes beyond the individual scale. Whole companies are goaded by concerns about risk–“Could we get sued?” Large corporation have entire legal teams devoted to telling them how they could get sued for whatever their doing and to filing lawsuits against their competitors for whatever they’re doing.

This fear of risk carries over, in turn, to government regulations. As John Sanphillipo writes in City Regulatory Hurdles Favor Big Developers, not the Little Guy:

A family in a town I visited bought an old fire station a few years ago with the intention of turning it into a Portuguese bakery and brewpub. They thought they’d have to retrofit the interior of the building to meet health and safety standards for such an establishment.

Turns out the cost of bringing the landscape around the outside of the building up to code was their primary impediment. Mandatory parking requirements, sidewalks, curb cuts, fire lanes, on-site stormwater management, handicapped accessibility, drought-tolerant native plantings…it’s a very long list that totaled $340,000 worth of work. … Guess what? They decided not to open the bakery or brewery. …

Individually it’s impossible to argue against each of the particulars. Do you really want to deprive people in wheelchairs of the basic civil right of public accommodation? Do you really want the place to catch fire and burn? Do you want a barren landscape that’s bereft of vegetation? …

I was in Hamtramck, Michigan a couple of years ago to participate in a seminar about reactivating neighborhoods through incremental small-scale development. …

While the event was underway the fire marshal happened to drive by and noticed there were people—a few dozen actual humans—occupying a commercial building in broad daylight. In a town that has seen decades of depopulation and disinvestment, this was an odd sight. And he was worried. Do people have permission for this kind of activity? Had there been an inspection? Was a permit issued? Is everything insured? He called one of his superiors to see if he should shut things down in the name of public safety.

It’s a good article. You should read the whole thing.

Back in Phillipe Bourgeois’s In Search of Respect: Selling Crack in el Barrio, Phillipe describes one drug dealer’s attempt to use the money he’d made to go into honest business by opening a convenience store. Unfortunately, he couldn’t get the store complaint with NYC disability-access regulations, and so the store never opened and the owner went back to dealing drugs. (What IQ, I wonder, is necessary to comply with all of these laws and regulations in the first place?)

Now, I’m definitely in favor of disabled people being able to buy groceries and use bathrooms. But what benefits a disabled person more: a convenience store that’s not fully wheel-chair accessible, or a crack house?

In My IRB Nightmare, Scott Alexander writes about trying to do a simple study to determine whether the screening test already being used to diagnose people with bipolar disorder is effective at diagnosing them:

When we got patients, I would give them the bipolar screening exam and record the results. Then Dr. W. would conduct a full clinical interview and formally assess them. We’d compare notes and see how often the screening test results matched Dr. W’s expert diagnosis.

Remember, they were already using the screening test on patients and then having them talk to the doctor for a formal assessment. The only thing the study added was that Scott would compare how well the screening results matched the formal assessment. No patients would be injected, subject to new procedures, or even asked different questions. They just wanted to compare two data sets.

After absurd quantities of paperwork and an approval process much too long to summarize here, the project got audited:

I kept the audit report as a souvenier. I have it in front of me now. Here’s an example infraction:

The data and safety monitoring plan consists of ‘the Principal Investigator will randomly check data integrity’. This is a prospective study with a vulnerable group (mental illness, likely to have diminished capacity, likely to be low income) and, as such, would warrant a more rigorous monitoring plan than what is stated above. In addition to the above, a more adequate plan for this study would also include review of the protocol at regular intervals, on-going checking of any participant complaints or difficulties with the study, monitoring that the approved data variables are the only ones being collected, regular study team meetings to discuss progress and any deviations or unexpected problems. Team meetings help to assure participant protections, adherence to the protocol. Having an adequate monitoring plan is a federal requirement for the approval of a study. See Regulation 45 CFR 46.111 Criteria For IRB Approval Of Research. IRB Policy: PI Qualifications And Responsibility In Conducting Research. Please revise the protocol via a protocol revision request form. Recommend that periodic meetings with the research team occur and be documented.

… Faced with submitting twenty-seven new pieces of paperwork to correct our twenty-seven infractions, Dr. W and I gave up. We shredded the patient data and the Secret Code Log. We told all the newbies they could give up and go home. … We told the IRB that they had won, fair and square; we surrendered unconditionally.

The point of all that paperwork and supervision is to make sure that no one replicates the Tuskegee Syphilis Experiment nor the Nazi anything. Noble sentiments–but as a result, a study comparing two data sets had to be canceled.

I’ve noticed recently that much of the interesting medical research is happening in the third world/China–places where the regulations aren’t as strong and experiments (of questionable ethics or not) can actually get done.

Like the computer taught not to lose at Tetris, all of these systems are more focused on minimizing risk–even non-existent risk–than on actually succeeding.

In his review of Yudkowsky’s Inadequate Equilibria, Scott writes:

…[Yudkowsky] continues to the case of infant parenteral nutrition. Some babies have malformed digestive systems and need to have nutrient fluid pumped directly into their veins. The nutrient fluid formula used in the US has the wrong kinds of lipids in it, and about a third of babies who get it die of brain or liver damage. We’ve known for decades that the nutrient fluid formula has the wrong kind of lipids. We know the right kind of lipids and they’re incredibly cheap and there is no reason at all that we couldn’t put them in the nutrient fluid formula. We’ve done a bunch of studies showing that when babies get the right nutrient fluid formula, the 33% death rate disappears. But the only FDA-approved nutrient fluid formula is the one with the wrong lipids, so we just keep giving it to babies, and they just keep dying. Grant that the FDA is terrible and ruins everything, but over several decades of knowing about this problem and watching the dead babies pile up, shouldn’t somebody have done something to make this system work better?

The doctors have to use the FDA-approved formula or they could get sued for malpractice. The insurance companies, of course, only cover the FDA-approved formula. The formula makers are already making money selling the current formula and would probably have to go through an expensive, multi-year review system (with experiments far more regulated than Scott’s) to get the new formula approved, and even then they might not actually get approval. In short, on one side are people in official positions of power whose lives could be made worse (or less convenient) if they tried to fix the problem, and on the other side are dead babies who can’t stand up for themselves.

The Chankiri Tree (Killing Tree) where infants were fatally smashed, Choeung Ek, Cambodia.

Communism strikes me as the ultimate expression of this beast: a society fully transformed into a malevolent AI. It’s impossible to determine exactly how many people were murdered by communism, but the Black Book of Communism estimates a death toll between 85 and 100 million people.

Capitalism, for all its faults, is at least somewhat decentralized. If you make a bad business decision, you suffer the consequences and can hopefully learn from your mistakes and make better decisions in the future. But in communist systems, one central planner’s bad decisions can cause suffering for millions of other people, resulting in mass death. Meanwhile, the central planner may suffer for correcting the bad decision. Centralized economies simply lack the feedback loops necessary to fix problems before they start killing people.

While FDA oversight of medicines is probably important, would it be such a bad thing if a slightly freer market in parenteral nutrition allowed parents to chose between competing brands of formula, each promising not to kill your baby?

Of course, capitalism isn’t perfect, either. SpottedToad recently had an interesting post, 2010s Identity Politics as Hostile AI:

There’s an interesting post mortem on the rise and fall of the clickbait liberalism site Mic.com, that attracted an alleged 65 million unique visitors on the strength of Woketastic personal stories like “5 Powerful Reasons I’m a (Male) Feminist,” …

Every time Mic had a hit, it would distill that success into a formula and then replicate it until it was dead. Successful “frameworks,” or headlines, that went through this process included “Science Proves TK,” “In One Perfect Tweet TK,” “TK Reveals the One Brutal Truth About TK,” and “TK Celebrity Just Said TK Thing About TK Issue. Here’s why that’s important.” At one point, according to an early staffer who has since left, news writers had to follow a formula with bolded sections, which ensured their stories didn’t leave readers with any questions: The intro. The problem. The context. The takeaway.

…But the success of Mic.com was due to algorithms built on top of algorithms. Facebook targets which links are visible to users based on complex and opaque rules, so it wasn’t just the character of the 2010s American population that was receptive to Mic.com’s specific brand of SJW outrage clickbait, but Facebook’s rules for which articles to share with which users and when. These rules, in turn, are calibrated to keep users engaged in Facebook as much as possible and provide the largest and most receptive audience for its advertisers, as befits a modern tech giant in a two-sided market.

Professor Bruce Charlton has a post about Head Girl Syndrome–the Opposite of Creative Genius that is good and short enough that I wish I could quote the whole thing. A piece must suffice:

The ideal Head Girl is an all-rounder: performs extremely well in all school subjects and has a very high Grade Point Average. She is excellent at sports, Captaining all the major teams. She is also pretty, popular, sociable and well-behaved.

The Head Girl will probably be a big success in life, in whatever terms being a big success happens to be framed …

But the Head Girl is not, cannot be, a creative genius. …

The more selective the social system, the more it will tend to privilege the Head Girl and eliminate the creative genius.

Committees, peer review processes, voting – anything which requires interpersonal agreement and consensus – will favour the Head Girl and exclude the creative genius.  …

*

We live in a Head Girl’s world – which is also a world where creative genius is marginalized and disempowered to the point of near-complete invisibility.

The quest for social status is, I suspect, one of the things driving the system. Status-oriented people refuse to accept information that comes from people lower status than themselves, which renders system feedback even more difficult. The internet as a medium of information sharing is beautiful; the internet as a medium of status signalling is horrible.

So what do you think? Do sufficiently large organization start acting like malevolent (or hostile) AIs?

(Back to Part 1)

Do Sufficiently Large Organizations Start Acting Like Malevolent AIs? (pt 1)

(and Society is an Extremely Large Organization)

What do I mean by malevolent AI?

AI typically refers to any kind of intelligence or ability to learn possessed by machines. Malevolent AI occurs when a machine pursues its programmed objectives in a way that humans find horrifying or immoral. For example, a machine programmed to make paperclips might decide that the easiest way to maximize paperclip production is to enslave humans to make paperclips for it. Superintelligent AI is AI that has figured out how to make itself smarter and thus keeps getting smarter and smarter. (Should we develop malevolent superintelligent AI, then we’ll really have something to worry about.)

Note: people who actually study AI probably have better definitions than I do.

While we like to think of ourselves (humans) as unique, thinking individuals, it’s clear that many of our ideas come from other people. Chances are good you didn’t think up washing your hands or brushing your teeth by yourself, but learned about them from your parents. Society puts quite a bit of effort, collectively speaking, into teaching children all of the things people have learned over the centuries–from heliocentrism to the fact that bleeding patients generally makes diseases worse, not better.

Just as we cannot understand the behavior of ants or bees simply by examining the anatomy of a single ant or single bee, but must look at the collective life of the entire colony/hive, so we cannot understand human behavior by merely examining a single human, but must look at the collective nature of human societies. “Man is a political animal,” whereby Aristotle did not mean that we are inherently inclined to fight over transgender bathrooms, but instinctively social:

Hence it is evident that the state is a creation of nature, and that man is by nature a political animal. And he who by nature and not by mere accident is without a state, is either above humanity, or below it; he is the ‘Tribeless, lawless, hearthless one,’ whom Homer denounces—the outcast who is a lover of war; he may be compared to a bird which flies alone.

Now the reason why man is more of a political animal than bees or any other gregarious animals is evident. Nature, as we often say, makes nothing in vain, and man is the only animal whom she has endowed with the gift of speech. And whereas mere sound is but an indication of pleasure or pain, and is therefore found in other animals (for their nature attains to the perception of pleasure and pain and the intimation of them to one another, and no further), the power of speech is intended to set forth the expedient and inexpedient, and likewise the just and the unjust. And it is a characteristic of man that he alone has any sense of good and evil, of just and unjust, and the association of living beings who have this sense makes a family and a state. –Aristotle, Politics

With very rare exceptions, humans–all humans, in all parts of the world–live in groups. Tribes. Families. Cities. Nations. Our nearest primate relatives, chimps and bonobos, also live in groups. Primates are social, and their behavior can only be understood in the context of their groups.

Groups of humans are able to operate in ways that individual humans cannot, drawing on the collective memories, skills, and knowledge of their members to create effects much greater than what could be achieved by each person acting alone. For example, one lone hunter might be able to kill a deer–or if he is extremely skilled, hardworking, and lucky, a dozen deer–but ten hunters working together can drive an entire herd of deer over a cliff, killing hundreds or even thousands. (You may balk at the idea, but many traditional hunting societies were dependent on only a few major hunts of migrating animals to provide the majority of their food for the entire year–meaning that those few hunts had to involve very high numbers of kills or else the entire tribe would starve while waiting for the animals to return.)

Chimps have never, to my knowledge, driven megafauna to extinction–but humans have a habit of doing so wherever they go. Humans are great at what we do, even if we aren’t always great at extrapolating long-term trends.

But the beneficial effects of human cooperation don’t necessarily continue to increase as groups grow larger–China’s 1.3 billion people don’t appear to have better lives than Iceland’s 332,000 people. Indeed, there probably is some optimal size–depending on activity and available communications technology–beyond which the group struggles to coordinate effectively and begins to degenerate.

CBS advises us to make groups of 7:

As it turns out, seven is a great number for not only forming an effective fictional fighting force, but also for task groups that use spreadsheets instead of swords to do their work.

That’s according to the new book Decide & Deliver: 5 Steps to Breakthrough Performance in Your Organization (Harvard Business Press).

Once you’ve got 7 people in a group, each additional member reduces decision effectiveness by 10%, say the authors, Marcia W. Blenko, Michael C. Mankins, and Paul Rogers.

Unsurprisingly, a group of 17 or more rarely makes a decision other than when to take a lunch break.

Princeton blog reports:

The trope that the likelihood of an accurate group decision increases with the abundance of brains involved might not hold up when a collective faces a variety of factors — as often happens in life and nature. Instead, Princeton University researchers report that smaller groups actually tend to make more accurate decisions, while larger assemblies may become excessively focused on only certain pieces of information. …

collective decision-making has rarely been tested under complex, “realistic” circumstances where information comes from multiple sources, the Princeton researchers report in the journal Proceedings of the Royal Society B. In these scenarios, crowd wisdom peaks early then becomes less accurate as more individuals become involved, explained senior author Iain Couzin, a professor of ecology and evolutionary biology. …

The researchers found that the communal ability to pool both pieces of information into a correct, or accurate, decision was highest in a band of five to 20. After that, the accurate decision increasingly eluded the expanding group.

Couzin found that in small groups, people with specialized knowledge could effectively communicate that to the rest of the group, whereas in larger groups, they simply couldn’t convey their knowledge to enough people and group decision-making became dominated by the things everyone knew.

If you could travel back in time and propose the idea of democracy to the inhabitants of 13th century England, they’d respond with incredulity: how could peasants in far-flung corners of the kingdom find out who was running for office? Who would count the votes? How many months would it take to tally up the results, determine who won, and get the news back to the outlying provinces? If you have a printing press, news–and speeches–can quickly and accurately spread across large distances and to large numbers of people, but prior to the press, large-scale democracy simply wasn’t practical.

Likewise, the communism of 1917 probably couldn’t have been enacted in 1776, simply because society at that time didn’t have the technology yet to gather all of the necessary data on crop production, factory output, etc. (As it was, neither did Russia of 1917, but they were closer.)

Today, the amount of information we can gather and share on a daily basis is astounding. I have at my fingertips the world’s greatest collection of human knowledge, an overwhelming torrent of data.

All of our these information networks have linked society together into an increasingly efficient meta-brain–unfortunately, it’s not a very smart meta-brain. Like the participants in Couzin’s experiments, we are limited to what “everyone knows,” stymied in our efforts to impart more specialized knowledge. (I don’t know about you, but I find being shouted down by a legion of angry people who know less about a subject than I do one of the particularly annoying features of the internet.)

For example, there’s been a lot of debate lately about immigration, but how much do any of us really know about immigrants or immigrant communities? How much of this debate is informed by actual knowledge of the people involved, and how much is just people trying to extend vague moral principles to cover novel situations? I recently had a conversation with a progressive acquaintance who justified mass-immigration on the grounds that she has friendly conversations with the cabbies in her city. Heavens protect us–I hope to get along with people as friends and neighbors, not just when I am paying them!

One gets the impression in conversation with Progressives that they regard Christian Conservatives as a real threat, because that group that can throw its weight around in elections or generally enforce cultural norms that liberals don’t like, but are completely oblivious to the immigrants’ beliefs. Most of our immigrants hail from countries that are rather more conservative than the US and definitely more conservative than our liberals.

Any sufficiently intelligent democracy ought to be able to think critically about the political opinions of the new voters it is awarding citizenship to, but we struggle with this. My Progressive acquaintance seems think that we can import an immense, conservative, third-world underclass and it will stay servile indefinitely, not vote its own interests or have any effects on social norms. (Or its interests will be, coincidentally, hers.)

This is largely an information problem–most Americans are familiar with our particular brand of Christian conservatives, but are unfamiliar with Mexican or Islamic ones.

How many Americans have intimate, detailed knowledge of any Islamic society? Very few of us who are not Muslim ourselves speak Arabic, and few Muslim countries are major tourist destinations. Aside from the immigrants themselves, soldiers, oil company employees, and a handful of others have spent time in Islamic countries, but that’s about it–and no one is making any particular effort to listen to their opinions. (It’s a bit sobering to realize that I know more about Islamic culture than 90% of Americans and I still don’t really know anything.)

So instead of making immigration policy based on actual knowledge of the groups involved, people try to extend the moral rules–heuristics–they already have. So people who believe that “religious tolerance is good,” because this rule has generally been useful in preventing conflict between American religious groups, think this rule should include Muslim immigrants. People who believe, “I like being around Christians,” also want to apply their rule. (And some people believe, “Groups are more oppressive when they’re the majority, so I want to re-structure society so we don’t have a majority,” and use that rule to welcome new immigrants.)

And we are really bad at testing whether or not our rules are continuing to be useful in these new situations.

 

Ironically, as our networks have become more effective, our ability to incorporate new information may have actually gone down.

The difficulties large groups experience trying to coordinate and share information force them to become dominated by procedures–set rules of behavior and operation are necessary for large groups to operate. A group of three people can use ad-hoc consensus and rock-paper-scissors to make decisions; a nation of 320 million requires a complex body of laws and regulations.

But it’s getting late, so let’s continue this discussion in the next post.