Book Club: The Code Economy, Chapter 11: Education and Death

Welcome back to EvX’s book club. Today we’re reading Chapter 11 of The Code Economy, Education.

…since the 1970s, the economically fortunate among us have been those who made the “go to college” choice. This group has seen its income row rapidly and its share of the aggregate wealth increase sharply. Those without a college education have watched their income stagnate and their share of the aggregate wealth decline. …

Middle-age white men without a college degree have been beset by sharply rising death rates–a phenomenon that contrasts starkly with middle-age Latino and African American men, and with trends in nearly every other country in the world.

It turns out that I have a lot of graphs on this subject. There’s a strong correlation between “white death” and “Trump support.”

White vs. non-white Americans

American whites vs. other first world nations

source

But “white men” doesn’t tell the complete story, as death rates for women have been increasing at about the same rate. The Great White Death seems to be as much a female phenomenon as a male one–men just started out with higher death rates in the first place.

Many of these are deaths of despair–suicide, directly or through simply giving up on living. Many involve drugs or alcohol. And many are due to diseases, like cancer and diabetes, that used to hit later in life.

We might at first think the change is just an artifact of more people going to college–perhaps there was always a sub-set of people who died young, but in the days before most people went to college, nothing distinguished them particularly from their peers. Today, with more people going to college, perhaps the destined-to-die are disproportionately concentrated among folks who didn’t make it to college. However, if this were true, we’d expect death rates to hold steady for whites overall–and they have not.

Whatever is affecting lower-class whites, it’s real.

Auerswald then discusses the “Permanent income hypothesis”, developed by Milton Friedman: Children and young adults devote their time to education, (even going into debt,) which allows us to get a better job in mid-life. When we get a job, we stop going to school and start saving for retirement. Then we retire.

The permanent income hypothesis is built into the very structure of our society, from Public Schools that serve students between the ages of 5 and 18, to Pell Grants for college students, to Social Security benefits that kick in at 65. The assumption, more or less, is that a one-time investment in education early in life will pay off for the rest of one’s life–a payout of such returns to scale that it is even sensible for students and parents to take out tremendous debt to pay for that education.

But this is dependent on that education actually paying off–and that is dependent on the skills people learn during their educations being in demand and sufficient for their jobs for the next 40 years.

The system falls apart if technology advances and thus job requirements change faster than once every 40 years. We are now looking at a world where people’s investments in education can be obsolete by the time they graduate, much less by the time they retire.

Right now, people are trying to make up for the decreasing returns to education (a highschool degree does not get you the same job today as it did in 1950) by investing more money and time into the single-use system–encouraging toddlers to go to school on the one end and poor students to take out more debt for college on the other.

This is probably a mistake, given the time-dependent nature of the problem.

The obvious solution is to change how we think of education and work. Instead of a single, one-time investment, education will have to continue after people begin working, probably in bursts. Companies will continually need to re-train workers in new technology and innovations. Education cannot be just a single investment, but a life-long process.

But that is hard to do if people are already in debt from all of the college they just paid for.

Auerswald then discusses some fascinating work by Bessen on how the industrial revolution affected incomes and production among textile workers:

… while a handloom weaver in 1800 required nearly forty minutes to weave a yard of coarse cloth using a single loom, a weaver in 1902 could do the same work operating eighteen Nothrop looms in less than a minute, on average. This striking point relates to the relative importance of the accumulation of capital to the advance of code: “Of the roughly thirty-nine-minute reduction in labor time per yard, capital accumulation due to the changing cost of capital relative to wages accounted for just 2 percent of the reduction; invention accounted for 73 percent of the reduction; and 25 percent of the time saving came from greater skill and effort of the weavers.” … “the role of capital accumulation was minimal, counter to the conventional wisdom.”

Then Auerswald proclaims:

What was the role of formal education in this process? Essentially nonexistent.

Boom.

New technologies are simply too new for anyone to learn about them in school. Flexible thinkers who learn fast (generalists) thus benefit from new technologies and are crucial for their early development. Once a technology matures, however, it becomes codified into platforms and standards that can be taught, at which point demand for generalists declines and demand for workers with educational training in the specific field rises.

For Bessen, formal education and basic research are not the keys to the development of economies that they are often represented a being. What drives the development of economies is learning by doing and the advance of code–processes that are driven at least as much by non-expert tinkering as by formal research and instruction.

Make sure to read the endnotes to this chapter; several of them are very interesting. For example, #3 begins:

“Typically, new technologies demand that a large number of variables be properly controlled. Henry Bessemer’s simple principle of refining molten iron with a blast of oxygen work properly only at the right temperatures, in the right size vessel, with the right sort of vessel refractory lining, the right volume and temperature of air, and the right ores…” Furthermore, the products of these factories were really one that, in the United States, previously had been created at home, not by craftsmen…

#8 states:

“Early-stage technologies–those with relatively little standardized knowledge–tend to be used at a smaller scale; activity is localized; personal training and direct knowledge sharing are important, and labor markets do not compensate workers for their new skills. Mature technologies–with greater standardized knowledge–operate at large scale and globally, market permitting; formalized training and knowledge are more common; and robust labor markets encourage workers to develop their own skills.” … The intensity of of interactions that occur in cities is also important in this phase: “During the early stages, when formalized instruction is limited, person-to-person exchange is especially important for spreading knowledge.”

This reminds me of a post on Bruce Charlton’s blog about “Head Girl Syndrome“:

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…

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

*

Modern society is run by Head Girls, of both sexes, hence there is no place for the creative genius.

Modern Colleges aim at recruiting Head Girls, so do universities, so does science, so do the arts, so does the mass media, so does the legal profession, so does medicine, so does the military…

And in doing so, they filter-out and exclude creative genius.

Creative geniuses invent new technologies; head girls oversee the implementation and running of code. Systems that run on code can run very smoothly and do many things well, but they are bad at handling creative geniuses, as many a genius will inform you of their public school experience.

How different stages in the adoption of new technology and its codification into platforms translates into wages over time is a subject I’d like to see more of.

Auerswald then turns to the perennial problem of what happens when not only do the jobs change, they entirely disappear due to increasing robotification:

Indeed, many of the frontier business models shaping the economy today are based on enabling a sharp reduction in the number of people required to perform existing tasks.

One possibility Auerswald envisions is a kind of return to the personalized markets of yesteryear, when before massive industrial giants like Walmart sprang up. Via internet-based platforms like Uber or AirBNB, individuals can connect directly with people who’d like to buy their goods or services.

Since services make up more than 84% of the US economy and an increasingly comparable percentage in coutnries elsewhere, this is a big deal.

It’s easy to imagine this future in which we are all like some sort of digital Amish, continually networked via our phones to engage in small transactions like sewing a pair of trousers for a neighbor, mowing a lawn, selling a few dozen tacos, or driving people to the airport during a few spare hours on a Friday afternoon. It’s also easy to imagine how Walmart might still have massive economies of scale over individuals and the whole system might fail miserably.

However, if we take the entrepreneurial perspective, such enterprises are intriguing. Uber and Airbnb work by essentially “unlocking” latent assets–time when people’s cars or homes were sitting around unused. Anyone who can find other, similar latent assets and figure out how to unlock them could become similarly successful.

I’ve got an underutilized asset: rural poor. People in cities are easy to hire and easy to direct toward educational opportunities. Kids growing up in rural areas are often out of the communications loop (the internet doesn’t work terribly well in many rural areas) and have to drive a long way to job interviews.

In general, it’s tough to network large rural areas in the same ways that cities get networked.

On the matter of why peer-to-peer networks have emerged in certain industries, Auerswald makes a claim that I feel compelled to contradict:

The peer-to-peer business models in local transportation, hospitality, food service, and the rental of consumer goods were the first to emerge, not because they are the most important for the economy but because these are industries with relatively low regulatory complexity.

No no no!

Food trucks emerged because heavy regulations on restaurants (eg, fire code, disability access, landscaping,) have cut significantly into profits for restaurants housed in actual buildings.

Uber emerged because the cost of a cab medallion–that is, a license to drive a cab–hit 1.3 MILLION DOLLARS in NYC. It’s a lucrative industry that people were being kept out of.

In contrast, there has been little peer-to-peer business innovation in healthcare, energy, and education–three industries that comprise more than a quarter of the US GDP–where regulatory complexity is relatively high.

Again, no.

There is a ton of competition in healthcare; just look up naturopaths and chiropractors. Sure, most of them are quacks, but they’re definitely out there, competing with regular doctors for patients. (Midwives appear to be actually pretty effective at what they do and significantly cheaper than standard ob-gyns.)

The difficulty with peer-to-peer healthcare isn’t regulation but knowledge and equipment. Most Americans own a car and know how to drive, and therefore can join Uber. Most Americans do not know how to do heart surgery and do not have the proper equipment to do it with. With training I might be able to set a bone, but I don’t own an x-ray machine. And you definitely don’t want me manufacturing my own medications. I’m not even good at making soup.

Education has tons of peer-to-peer innovation. I homeschool my children. Sometimes grandma and grandpa teach the children. Many homeschoolers join consortia that offer group classes, often taught by a knowledgeable parent or hired tutor. Even people who aren’t homeschooling their kids often hire tutors, through organizations like Wyzant or afterschool test-prep centers like Kumon. One of my acquaintances makes her living primarily by skype-tutoring Koreans in English.

And that’s not even counting private schools.

Yes, if you want to set up a formal “school,” you will encounter a lot of regulation. But if you just want to teach stuff, there’s nothing stopping you except your ability to find students who’ll pay you to learn it.

Now, energy is interesting. Here Auerswsald might be correct. I have trouble imagining people setting up their own hydroelectric dams without getting into trouble with the EPA (not to mention everyone downstream.)

But what if I set up my own windmill in my backyard? Can I connect it to the electric grid and sell energy to my neighbors on a windy day? A quick search brings up WindExchange, which says, very directly:

Owners of wind turbines interconnected directly to the transmission or distribution grid, or that produce more power than the host consumes, can sell wind power as well as other generation attributes.

So, maybe you can’t set up your own nuclear reactor, and maybe the EPA has a thing about not disturbing fish, but it looks like you can sell wind and solar energy back to the grid.

I find this a rather exciting thought.

Ultimately, while Auerswald does return to and address the need to radically change how we think about education and the education-job-retirement lifepath, he doesn’t return to the increasing white death rate. Why are white death rates increasing faster than other death rates, and will transition to the “gig economy” further accelerate this trend? Or was the past simply anomalous for having low white death rates, or could these death rates be driven by something independent of the economy itself?

Now, it’s getting late, so that’s enough for tonight, but what are your thoughts? How do you think this new economy–and educational landscape–will play out?

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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)