Whither HBD: Happy 1,000 posts

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Gratuitous pic of Niels Bohr and Einstein, 1925, because this is my party.

This blog is now 1,000 posts long, which I think calls for a bit of celebration.

I started this blog because I found the idea that evolution–a process normally thought of as turning fins to feet and gills to lungs–could also code for emergent, group-level behavior like the building of termite mounds or nation states fascinating. Could evolution code for other things? Could it give us male and female behavior? Emotions? Political preferences?

I started reading JayMan’s work, then Peter Frost and HBD Chick, and of course Cochran and Harpending. Each of these blogs had new (at least to me) and fascinating ideas about why humans behave the many ways they do. Then came Slate Star Codex and Unqualified Reservations. There were others, of course; a complete listing of one’s intellectual predecessors is always impossible.

Evolution is ultimately a numbers game: if more people who do X have children than people who do Y, then X is likely to become more common than Y–even if we all believe that Y is better than X.

This gets interesting when X is not obviously mediated by genetics–your eye color, sans contacts, is clearly genetic, but the number of years you spend in school is influenced by external factors like whether schools exist in your society. This is where some people get hung up on causation. We don’t need to posit a gene that causes people to get more or less school. Maybe your village has a school because a mountain climber got lost nearby, your village rescued him, and in gratitude, he built you a school, while the village on the other side of the mountain doesn’t have a school because no mountain climber got lost there. Once a school exists, though, it can start having effects, and if those effects are not random, we’ll see genetic correlations.

If people who have more education make more money and end up buying more food and raising more children, then school is exerting a selective effect on society by causing the kids who happened to live near the school to have more children. From an ecological standpoint, the school is operating like a spring in a desert–we get more growth near the spring than far away from it, and whatever traits were common in the village–even ones that have nothing to do with education–will become more numerous in the overall population. If this trend continues, then the cultural habit of “going to school” will continue to proliferate.

We can also posit the opposite case: in the village with the school, kids spend many years at school and end up marrying later and are more educated about things like “birth control” than their neighbors on the other side of the mountain. The kids on the other side of the mountain marry younger and have a bunch of unintended children. In this case, education is suppressing fertility; in this niche, education is like a drought. The educated kids have fewer children of their own, and whatever traits the uneducated kids happen to have spread through society because there are now much more of them (at least as a percent of the total). If this trend continues, then the cultural habit of “going to school” may well die out.

In both of these cases, education caused a change in the distribution of genetic traits in the overall population without requiring any genetic predispositions from the students involved. We are looking at the evolution of the whole society.

But this is a highly constrained example; it is rare in places like the modern US to find areas where one village has a school and the next does not. Once schools are everywhere, they’re not going to select for (or against) “living near a school.” The traits that cause a person to attend more years of schooling or do better in school will be less random–traits like conscientiousness, ability to recognize letters, or family income. In an agricultural society with no schools, raw, physical strength may be at a premium as people must wrest their living from the soil, rocks, trees, and beasts. This selects for physical strength. Once we introduce schools, if the better educated have more children, then physical strength becomes less important, and its prominence in the next generation diminishes. The ability to sit in a chair for long hours may be positively selected, leading to a proliferation of this trait.

This is gene-culture co-evolution–a cultural change can shift the balance of genes in a society, and that in turn can cause further cultural changes, which cause more genetic changes.

I would like to pause and note just how annoying the “but you haven’t proven causation!” crowd is:

Imagine if I said that I thought the blood circulates through the body in a loop instead of being generated anew by the heart with every pump, and someone protested that blood couldn’t possibly circulate because I hadn’t shown any way for blood to get from the arteries to the veins and back to the heart.

This was a real debate in physiology. That the heart pumps is obvious. That veins and arteries carry blood is also obvious. That people die if you cut them open and let the blood drain out, though, mystified doctors for centuries.

Capillaries, unfortunately for many patients, are too small to see with the naked eye. Without any mechanism to return blood from the arteries to the heart, doctors refused to believe that it did. They instead believed that blood was produced anew with every heartbeat and was consumed at our extremities. Bleeding patients, therefore, shouldn’t cause any great difficulties.

The fact that we could not see capillaries before the invention of the microscope should not have caused doctors to reject the theory of circulation, only to say that a mechanism had not yet been found to make it work. The circulation hypothesis did a better job of explaining various facts of human anatomy–like the existence of veins carrying blood to the heart and the habit of patients to die after bleeding–than the heart-generation hypothesis.

The insistence on clinging to the older theory due to the lack of a capillary mechanism lead, of course, to the deaths of thousands of patients. (For more on the history of medicine, anatomy, and circulation, I recommend William Bynum’s A Little History of Science.)

How something works is vastly secondary to the question of whether it works at all in the first place. If it works, it works. If you can’t figure out how, you call it magic admit that you don’t know and hope that someday it’ll be clear. What you don’t do is claim that a thing cannot be true or cannot actually work simply because you don’t understand how it happens.

I don’t understand how airplanes stay in the sky, but that doesn’t make them fall down. Reality doesn’t stop just because we don’t understand it; to think that it does is pure, asinine hubris.

The next objection I commonly hear to the idea that cultural changes (like the proliferation of schools) could trigger changes in the genetic makeup of society is that “evolution doesn’t work that fast.”

This is a funny objection. The speed of evolution depends on the nature of the trait we are discussing. Developing a radically new trait, or greatly modifying an existing one, such as developing the ability to breath air instead of water, does indeed take a long time–sometimes millions or even billions of years. But simply modifying the distribution of existing traits in a population can be done nearly instantly–if an invading army lops the heads off of anyone over 5’9″, the average height of the population will fall immediately. From a genetic perspective, this is “negative selection” against height, and the population has “evolved” to be shorter.

(You might object that this is too artificial an example, so consider the inverse: a situation where everyone over a certain size used to die, but due to environmental changes they now survive. Modern obstetrics and the cesarean section have rescued mothers of large babies from the once-common fate of death in childbirth. This was of course often fatal to the infants, as well, and prevented their parents from producing any further children. Large babies were a serious evolutionary problem for our ancestors, but much less so for us, which has probably contributed to the rise in average heights over the past century.)

Usually selection is less extreme, but the point remains: traits that already exist (and vary) in a population, like height, weight, blood type, or temperament, can be selected for (or against) on very short timescales.

In fact, human societies are always selecting for some traits; this means that we are always evolving. The distribution of traits in humans today is not the same as the distribution of traits in humans 20 years ago, much less 100 years ago.

And we can look at all of the things humans are being selected for (or selecting themselves for) and speculate how this will change society. Religious people have more children than atheists, and some religions produce far more children than other religions. This trend is juxtaposed against the massive rise in atheism over the past few decades. Will atheism continue to spread to the children of the religious, or will the religious “core” be effectively immune and overwhelm the remaining agnostics with numbers?

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Source: Do Schooling and City Living lead to Fewer Babies?

Education (or perhaps it is just a proxy for intelligence) seems to have different effects on different folks and different levels of society. Highschool dropouts have a lot of kids. People with PhDs have a fair number of kids. People who have merely graduated from college, by contrast, have the fewest kids.

Fertility is also different for men and women, with more educated women taking a bigger fertility hit than educated men.

Any discussion of “what’s up with the American middle/working class” has to address facts like these–our country is effectively bifurcating into two “success” models: one very high achieving and one very low achieving. The middle, it seems, is getting cut out.

But we can apply evolutionary theory to much more than humans and their societies. We can analyze ideas, transportation networks, technology, etc.

My first–and probably best–idea in this area was that the idea that the way we transmit ideas influences the nature of our ideas. One of the biggest changes of the past century has been a massive change in the way we communicate, from the rise of mass media to the explosion of social media. Before radio and TV, most people got most of their information from people they knew personally, mostly their families. Today, we get most of our information from total strangers.

Ideas we get from strangers I refer to as meme viruses, (meme as in “unit of idea,” not “funny picture on the internet”) because horizontal transmission resembles the transmission of viruses. Ideas we get from our families I refer to as mitochondrial memes, because vertical transmission resembles the transmission of mitochondrial DNA.

Since the interests of strangers are different from the interests of your close family (your parents are much more interested in you making lots of money, getting married, and making grandbabies than strangers are), they will tend to promote different sorts of ideas. Your parents generally want you to succeed, while strangers would prefer that you do things that help them succeed.

It is this change in the way we communicate, rather than the actions or intentions of any particular group, that I think explains the rise of many modern political trends. (This is the condensed version; I recommend reading one of my posts on memes if you want more.)

I am obviously interested in politics, but not in the conventional sense. I have very little interest in anything associated with particular people in politics, outside of a few historical figures. I have no interest in the latest thing Nancy Pelosi or Emmanuel Macron has been up to. I think people place too much importance on individuals; I am more interested in broad trends (like the spread of technology) that are much bigger and further-reaching than any individual politicians (often their bigger than individual countries).

I’ve come over the years to the conclusion that conventional politics drive people to do (and say) very stupid things. People develop a tribal identity attached to one side or another, and suddenly everything their side does is good and sensible, and everything the other side does is nefarious and dumb. This is not a bad instinct when your enemies have pointy spears and want to turn you into lunch, but it’s terrible when your enemy disagrees with you on optimal interest rates.

My second purpose in founding this blog was to reach out to people who were, as I see it, harmed by the cult-like behavior of modern leftism. When I say “cult-like,” I mean it. Atheism is on the rise, but religious thinking and behavior remains strong. When peoples’ self-identities as “good people” become linked to their membership in political tribes, the threat of excommunication becomes particularly powerful.

Here’s a public example:

… far more unsettling was what happened two weeks later, when knitters who claim to be champions of social justice went after a gay man within the community because he’d written a satirical poem suggesting (correctly) that all the recent anti-racism mobbings might be having a toxic effect on the community. …

The next day, Taylor’s husband Benjamin Till, a composer (who also happens to be Jewish) posted on Sockmatician’s account: “This is Nathan’s husband, Benjamin. At 3 pm today, Nathan was admitted to [the emergency room at] Barnet Hospital. …

Till also wrote on his blog about what had happened:

… Nathan disabled comments when the sheer weight of them became too much, but the following morning, his other Instagram posts, and then his Twitter feed had been hijacked by the haters. The taunts continued. He was a white supremacist, a Nazi apologist…He started obsessively reading the posts but became increasingly worked up, then more and more erratic and then suddenly he snapped, screaming like a terrified animal, smashing boxes and thumping himself. I was forced to wrestle him to the ground and hold onto him for dear life as the waves of pain surged through his body. He made a run for the car keys. He said he wanted to drive at 100 miles per hour until he crashed. I called our doctor and they could hear him screaming in the background and said I was to immediately take him to [the hospital], where he was instantly assessed and put on suicide watch …

This was not the end of Nathan’s ordeal at the hands of people who supposedly believe in “social justice” and helping the powerless, as people continued piling on (yelling at him in public) because of the “harm” he had caused.

I wish I could reach out to everyone like Nathan and tell them that they’re not bad, cults are bad.

The right has its own issues, but I come from a leftist background and so am responding to what I know personally, not abstractly. 

From time to time I get a question about the future of HBD (human bio-diversity). The online HBD community was quite vibrant about a decade ago, but many of the brightest lights have faded. Henry Harpending of Westhunter and co-author of The 10,000 Year Explosion has sadly passed away. HBD Chick and Jayman are both occupied with their own lives.

The future of HBD isn’t in blogs or the internet generally (though we can read about it here). It’s over in real genetics research. Yes, there are some subjects that academics don’t want to touch for fear of losing their jobs, but there are many researchers forging paths into fascinating new territory. The field of ancient DNA is unlocking the story of human migration and dispersal, from Neanderthals to Anglo Saxons. Thanks to aDNA, we’ve discovered a whole new Human species, the Denisovans, that interbred with the ancestors of modern Homo sapiens (as did the Neanderthals). We have also discovered “ghost” species in our DNA that we have no name for.

The field of modern DNA is also advancing; we’re learning new things all the time. CRISPRing humans is just one fascinating possibility.

Imagine the ability to remove simple genetic flaws that cause painful and fatal diseases, make ourselves beautiful or smarter. How much are 20 IQ points worth? One study found that people with IQs of 100 average $58,000 a year, while 120s made $128,000. $70,000 a year, averaged over a few decades of working life, (less intelligent people tend to enter the workforce and start earning younger, so it’s not a simple multiplication problem), adds up quickly.

Let’s imagine a scenario in which CRISPR actually works. Only the wealthy–and perhaps those with genetic diseases willing to shell out thousands or covered by insurance–will be able to afford it. The current bifurcation trend will become even more extreme as the poor continue reproducing normally, while the wealthy make themselves smarter, healthier, and prettier.

But if CRISPR confers advantages to society as a whole–for example, if smarter people make fabulous new inventions that everyone benefits from–then we could see foundations, charities, and even welfare programs aimed at making sure everyone has the CRISPR advantage.

After all, if an extra year in school boosts IQ by 3.4 points (I’m not saying it does, but let’s assume), then 6 extra years in school will give you 20.4 points. We pay about $10,600 per pupil per year for public schools, so those six years are worth $63,600. If you can CRISPR 20 IQ points for less, then it’s a better deal.

Of course, CRISPR might just be a pipe dream that gives people cancer.

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Isaac Newton

Whatever happens, the real future of HBD lies in real labs with real budgets, not online blogs. I’m just here to share, discuss, and think–and hopefully there will be enough interesting ideas to discuss for another thousand posts.

Thanks for being part of all these discussions. Blogs are nothing without readers, after all.

Capitalism of Place

One of the interesting themes in Arnade’s Dignity: Seeking Respect in Back Row America is the role of capitalism in creating community spaces.

Arnade spends most of his time in the book in three places: McDonald’s, drug dens, and churches. Two of these–McD’s and the drug Ds–are capitalist enterprises: they exist to sell you things, legal or not. Churches are not explicitly capitalist, but can be understood using the same model. They are interested in attracting enough members to cover their operating costs, so a church that does a better job of “selling” religion or provides a more enjoyable religious experience will probably attract more parishioners and will do better financially. (A church that can attract no members is, ultimately, dead.)

The lack of good common spaces that do not require spending money is one of the minor annoyances of my life. I like being outdoors, but it rains out there. National parks are lovely, but not near the house. It’s especially difficult to find locations that are attractive to multiple generations, or both children and childless adults (if I want to socialize with friends who do not have kids of their own).

As Arnade notes, for poor neighborhoods, McDonald’s fills that niche. It has a playground and happy meals for kids; it has booths and hamburgers for adults. It is warm and dry in the winter, cool in the summer, and even has a bathroom. The price of admission is low–a cup of coffee.

In Arnade’s telling, the organizations that ought to be providing community spaces, like the local government, really don’t. From a libertarian perspective, if attracting more people to these places doesn’t directly benefit the people running them, then they won’t put effort into making these spaces comfortable and attractive. Since McDonald’s (or the other locations Arnade visits) do make money off customers, even homeless ones who just order a cup of coffee, McD’s has an incentive to make its environs comfortable and welcoming to as many people as possible.

We can find other examples of capitalist enterprises providing communal spaces, like salons, barber shops, shopping malls, bars, and sports bars.

Of course, this inevitably runs up against class issues. McD makes plenty of money selling food to the poor, and Whole Foods makes plenty selling food to the rich, but it is difficult to sell to both markets. Back in our review of Auerswald’s The Code Economy, we discussed his observation that capitalistic markets tends to bifurcate into supplying low and high class versions of products, with a dearth in between. Auerswald discusses the evolution of watch making, from expensive luxuries to common watches to the clock included on your phone. He writes that both the clock-in-your phone and the luxury Rolex markets are doing fine, while sales of mid-price watches have withered.

Community seems to have undergone a similar process. McDonald’s is doing fine, financially, and I’m sure ski clubs in Alta are doing fine, too. It’s in between that we find people who are watching their money and can’t afford to spend $80-$120 a day on trips to the museum/zoo/movies, etc, but don’t want to hang out at McDonald’s, either. In general I think of “let’s avoid the poors” social signaling as a scam–products/services that signal your social class will happily increase in cost until they’ve sucked up all of your money–but sometimes avoiding other people legitimate. Personally, I would go to McDonald’s more often if my children weren’t prone to getting horribly ill when we visit–social class may be socially constructed, but diarrhea is real. Avoiding criminals, drug addicts, diseases, and folks who haven’t bathed recently is perfectly reasonable.

There aren’t a lot of spaces that do this for the middle class. Chick-fil-A comes close, but their playgrounds are designed for kids under 5. The best place I can think of for middle class families to hang out and socialize (which is also a good place for the poor and upper class) is church. And indeed, Arnade meets lots of people at churches across the country. Churches (or other religions’ houses of worship) are generally warm (or cool), hold community events, mark lifecycle events, and generally even have dedicated areas for children. The only difficulty is that churches are structured around belief in a particular religion, which is awkward for the nation’s increasing numbers of atheists, and occasionally use their parishioners’ beliefs in the morality of the church for self-gratification/manipulation. (EG, every cult ever.)

Arnade also visits one other variety of social club in the book, the “Snowshoe Club” IIRC, dedicated not to snowshoeing, but to French Canadians in the US. Like many social clubs, the Snowshoes get together for dinner and social events, costs five dollars to join, and officially you don’t have to be French Canadian to be a member. These sorts of social clubs used to be much more common in the US (See: Bowling Alone), but have been on the wane for decades.

How do you feel about community in your own town? Are there good places to meet people and socialize, or do you feel a dearth? Does capitalism do a good job of filling this role, or would some other structure or institution perform better? Is the bifurcation I have described a real thing, or just an illusion of some sort? In short, what do you think?

Book Club: Code Economy, Ch. 10: In which I am Confused

Welcome back to EvX’s Book Club. Today we start the third (and final) part of Auerswald’s The Code Economy: The Human Advantage.

Chapter 10: Complementarity discuses bifurcation, a concept Auerswald mentions frequently throughout the book. He has a graph of the process of bifurcation, whereby the development of new code (ie, technology), leads to the creation of a new “platform” on the one hand, and new human work on the other. With each bifurcation, we move away from the corner of the graph marked “simplicity” and “autonomy,” and toward the corner marked “complexity” and “interdependence.” It looks remarkably like a graph I made about energy inputs vs outputs at different complexity levels, based on a memory of a graph I saw in a textbook some years ago.

There are some crucial differences between our two graphs, but I think they nonetheless related–and possibly trying to express the same thing.

Auerswald argues that as code becomes platform, it doesn’t steal jobs, but becomes the new base upon which people work. The Industrial Revolution eliminated the majority of farm laborers via automation, but simultaneously provided new jobs for them, in factories. Today, the internet is the “platform” where jobs are being created, not in building the internet, but via businesses like Uber that couldn’t exist without the internet.

Auerswald’s graph (not mine) is one of the few places in the book where he comes close to examining the problem of intelligence. It is difficult to see what unintelligent people are going to do in a world that is rapidly becoming more complicated.

On the other hand people who didn’t have access to all sorts of resources now do, due to internet-based platforms–people in the third world, for example, who never bought land-line telephones because their country couldn’t afford to build the infrastructure to support them, are snapping up mobile and smartphones at an extraordinary rate:

And overwhelming majorities in almost every nation surveyed report owning some form of mobile device, even if they are not considered “smartphones.”

And just like Auerswald’s learning curves from the last chapter, technological spread is speeding up. It took the landline telephone 64 years to go from 0% to 40% of the US market. Mobile phones took only 20 years to accomplish the same feat, and smartphones did it in about 10. (source.)

There are now more mobile phones in the developing world than the first world, and people aren’t just buying just buying these phones to chat. People who can’t afford to open bank accounts now use their smarphones as “mobile wallets”:

According to the GSMA, an industry group for the mobile communications business, there are now 79 mobile money systems globally, mostly in Africa and Asia. Two-thirds of them have been launched since 2009.

To date, the most successful example is M-Pesa, which Vodafone launched in Kenya in 2007. A little over three years later, the service has 13.5 million users, who are expected to send 20 percent of the country’s GDP through the system this year. “We proved at Vodafone that if you get the proposition right, the scale-up is massive,” says Nick Hughes, M-Pesa’s inventor.

But let’s get back to Auerswald. Chapter 10 contains a very interesting description of the development of the development of the Swiss Watch industry. Of course, today, most people don’t go out of their way to buy watches, since their smartphones have clocks built into them. Have smartphones put the Swiss out of business? Not quite, says Auerswald:

Switzerland… today produces fewer than 5 percent of the timepieces manufactured for export globally. In 2014, Switzerland exported 29 million watches, as compaed to China’ 669 million… But what of value? … Swiss watch exports were worth 24.3 billion in 2014, nearly five times as much as all Chinese watches combined.

Aside from the previously mentioned bifurcation of human and machine labor, Auerswald suggests that automation bifurcates products into cheap and expensive ones. He claims that movies, visual art services (ie, copying and digitization of art vs. fine art,) and music have also undergone bifurcation, not extinction, due to new technology.

In each instance, disruptive advances in code followed a consistent and predictable pattern: the creation of a new high-volume, low-price option creates a new market for the low-volume, high-price option. Every time this happens, the new value created through improved code forces a bifurcation of markets, and of work.

Detroit

He then discusses a watch-making startup located in Detroit, which I feel completely and totally misses the point of whatever economic lessons we can draw from Detroit.

Detroit is, at least currently, a lesson in how people fail to deal with increasing complexity, much less bifurcation.

Even that word–bifurcation–contains a problem: what happens to the middle? A huge mass of people at the bottom, making and consuming cheap products, and a small class at the top, making and consuming expensive products–well I will honor the demonstrated preferences of everyone involved for stuff, of whatever price, but what about the middle?

Is this how the middle class dies?

But if the poor become rich enough… does it matter?

Because work is fundamentally algorithmic, it is capable of almost limitless diversification though both combinatorial and incremental change. The algorithms of work become, fairly literally, the DNA of the economy. …

As Geoff Moore puts it, “Digital innovation is reengineering our manufacturing-based product-centric economy to improve quality, reduce cost, expand markets, … It is doing so, however, largely at the expense of traditional middle class jobs. This class of work is bifurcating into elite professions that are highly compensated but outside the skillset of the target population and commoditizing workloads for which the wages fall well below the target level.”

It is easy to take the long view and say, “Hey, the agricultural revolution didn’t result in massive unemployment among hunter-gatherers; the bronze and iron ages didn’t result in unemployed flint-knappers starving in the streets, so we’ll probably survive the singularity, too,” and equally easy to take the short view and say, “screw the singularity, I need a job that pays the bills now.”

Auerswald then discusses the possibilities for using big data and mobile/wearable computers to bring down healthcare costs. I am also in the middle of a Big Data reading binge, and my general impression of health care is that there is a ton of data out there (and more being collected every day,) but it is unwieldy and disorganized and doctors are too busy to use most of it and patients don’t have access to it. and if someone can amass, organize, and sort that data in useful ways, some very useful discoveries could be made.

Then we get to the graph that I didn’t understand,”Trends in Nonroutine Task Input, 1960 to 1998,” which is a bad sign for my future employment options in this new economy.

My main question is what is meant by “nonroutine manual” tasks, and since these were the occupations with the biggest effect shown on the graph, why aren’t they mentioned in the abstract?:

We contend that computer capital (1) substitutes for a limited and well-defined set of human activities, those involving routine (repetitive) cognitive and manual tasks; and (2) complements activities involving non-routine problem solving and interactive tasks. …Computerization is associated with declining relative industry demand for routine manual and cognitive tasks and increased relative demand for non-routine cognitive tasks.

Yes, but what about the non-routine manual? What is that, and why did it disappear first? And does this graph account for increased offshoring of manufacturing jobs to China?

If you ask me, it looks like there are three different events recorded in the graph, not just one. First, from 1960 onward, “non-routine manual” jobs plummet. Second, from 1960 through 1970, “routine cognitive” and “routine manual” jobs increase faster than “non-routine analytic” and “non-routine interactive.” Third, from 1980 onward, the routine jobs head downward while the analytic and interactive jobs become more common.

*Downloads the PDF and begins to read* Here’s the explanation of non-routine manual:

Both optical recognition of objects in a visual field and bipedal locomotion across an uneven surface appear to require enormously sophisticated algorithms, the one in optics and the other in mechanics, which are currently poorly understood by cognitive science (Pinker, 1997). These same problems explain the earlier mentioned inability of computers to perform the tasks of long haul truckers.

In this paper we refer to such tasks requiring visual and manual skills as ‘non-routine manual activities.’

This does not resolve the question.

Discussion from the paper:

Trends in routine task input, both cognitive and manual, also follow a striking pattern. During the  1960s, both forms of input increased due to a combination of between- and within-industry shifts. In the 1970s, however, within-industry input of both tasks declined, with the rate of decline accelerating.

As distinct from the other four task measures, we observe steady within- and between-industry shifts against non-routine manual tasks for the entire four decades of our sample. Since our conceptual framework indicates that non-routine manual tasks are largely orthogonal to computerization, we view
this pattern as neither supportive nor at odds with our model.

Now, it’s 4 am and the world is swimming a bit, but I think “we aren’t predicting any particular effect on non-routine manual tasks” should have been stated up front in the thesis portion. Sticking it in here feels like ad-hoc explaining away of a discrepancy. “Well, all of the other non-routine tasks went up, but this one didn’t, so, well, it doesn’t count because they’re hard to computerize.”

Anyway, the paper is 62 pages long, including the tables and charts, and I’m not reading it all or second-guessing their math at this hour, but I feel like there is something circular in all of this–“We already know that jobs involving routine labor like manufacturing are down, so we made a models saying they decreased as a percent of jobs because of computers and automation, looked through jobs data, and low and behold, found that they had decreased. Confusingly, though, we also found that non-routine manual jobs decreased during this time period, even though they don’t lend themselves to automation and computerization.”

I also searched in the document and could find no instance of the words “offshor-” “China” “export” or “outsource.”

Also, the graph Auerswald uses and the corresponding graph in the paper have some significant differences, especially the “routine cognitive” line. Maybe the authors updated their graph with more data, or Auerswald was trying to make the graph clearer. I don’t know.

Whatever is up with this paper, I think we may provisionally accept its data–fewer factory workers, more lawyers–without necessarily accepting its model.

The day after I wrote this, I happened to be reading Davidowitz’s Everybody Lies: Big Data, New Data, and What the Internet Can Tell us about who we Really Are, which has a discussion of the best places to raise children.

Talking about Chetty’s data, Davidowitz writes:

The question asked: what is the chance that a person with parents in the bottom 20 percent of the income distribution reaches the top 20 percent of the income distribution? …

So what is it about part of the United States where there is high income mobility? What makes some places better at equaling the playing field, of allowing a poor kid to have a pretty good life? Areas that spend more on education provide a better chance to poor kids. Places with more religious people and lower crime do better. Places with more black people do worse. Interestingly, this has an effect on not just the black kids but on the white kids living there as well.

Here is Chetty’s map of upward mobility (or the lack thereof) by county. Given how closely it matches a map of “African Americans” + “Native Americans” I have my reservations about the value of Chetty’s research on the bottom end (is anyone really shocked to discover that black kids enjoy little upward mobility?) but it still has some comparative value.

Davidowitz then discusses Chetty’s analysis of where people live the longest:

Interestingly, for the wealthiest Americans, life expectancy is hardly affected by where you live. …

For the poorest Americans, life expectancy varies tremendously…. living in the right place can add five years to a poor person’s life expectancy. …

religion, environment, and health insurance–do not correlate with longer life spans for the poor. The variable that does matter, according to Chetty and the others who worked on this study? How many rich people live in a city. More rich people in a city means the poor there live longer. Poor people in New York City, for example, live longer than poor people in Detroit.

Davidowitz suggests that maybe this happens because the poor learn better habits from the rich. I suspect the answer is simpler–here are a few possibilities:

1. The rich are effectively stopping the poor from doing self-destructive things, whether positively, eg, funding cultural that poor people go to rather than turn to drugs or crime out of boredom, or negatively, eg, funding police forces that discourage life-shortening crime.

2. The rich fund/support projects that improve general health, like cleaner water systems or better hospitals.

3. The effect is basically just a measurement error that doesn’t account for rich people driving up land prices. The “poor” of New York would be wealthier if they had Detroit rents.

(In general, I think Davidowitz is stronger when looking for correlations in the data than when suggesting explanations for it.)

Now contrast this with Davidowitz’s own study on where top achievers grow up:

I was curious where the most successful Americans come from, so one day I decided to download Wikipedia. …

[After some narrowing for practical reasons] Roughly 2,058 American-born baby boomers were deemed notable enough to warrant a Wikipedia entry. About 30 percent made it through achievements in art or entertainment, 29 percent through sports, 9 percent via politics, and 3 percent in academia or science.

And this is why we are doomed.

The first striking fact I noticed in the data was the enormous geographic variation in the likelihood of becoming a big success …

Roughly one in 1,209 baby boomers born in California reached Wikipedia. Only one in 4,496 baby boomers born in West Virginia did. … Roughly one in 748 baby boomers born in Suffolk County, MA, here Boston is located, made it to Wikipedia. In some counties, the success rate was twenty times lower. …

I closely examined the top counties. It turns out that nearly all of them fit into one of two categories.

First, and this surprised me, many of these counties contained a sizable college town. …

I don’t know why that would surprise anyone. But this was interesting:

Of fewer than 13,000 boomers born in Macon County, Alabama, fifteen made it to Wikipedia–or one in 852. Every single one of them is black. Fourteen of them were from the town of Tuskegee, home of Tuskegee University, a historically black college founded by Booker . Washington. The list included judges, writers, and scientists. In fact, a black child born in Tuskegee had the same probability of becoming a notable in a field outside of ports as a white child born in some of the highest-scoring, majority-white college towns.

The other factor that correlates with the production of notables?

A big city.

Being born in born in San Francisco County, Los Angeles County, or New York City all offered among the highest probabilities of making it to Wikipedia. …

Suburban counties, unless they contained major college towns, performed far worse than their urban counterparts.

A third factor that correlates with success is the proportion of immigrants in a county, though I am skeptical of this finding because I’ve never gotten the impression that the southern border of Texas produces a lot of famous people.

Migrant farm laborers aside, though, America’s immigrant population tends to be pretty well selected overall and thus produces lots of high-achievers. (Steve Jobs, for example, was the son of a Syrian immigrant; Thomas Edison was the son of a Canadian refugee.)

The variable that didn’t predict notability:

One I found more than a little surprising was how much money a state spends on education. In states with similar percentages of its residents living in urban areas, education spending did not correlate with rates of producing notable writers, artists, or business leaders.

Of course, this is probably because 1. districts increase spending when students do poorly in school, and 2. because rich people in urban send their kids to private schools.

BUT:

It is interesting to compare my Wikipedia study to one of Chetty’s team’s studies discussed earlier. Recall that Chetty’s team was trying to figure out what areas are good at allowing people to reach the upper middle class. My study was trying to figure out what areas are good at allowing people to reach fame. The results are strikingly different.

Spending a lot on education help kids reach the upper middle class. It does little to help them become a notable writer, artist, or business leader. Many of these huge successes hated school. Some dropped out.

Some, like Mark Zuckerberg, went to private school.

New York City, Chetty’s team found, is not a particularly good place to raise a child if you want to ensure he reaches the upper middle class. it is a great place, my study found, if you want to give him a chance at fame.

A couple of methodological notes:

Note that Chetty’s data not only looked at where people were born, but also at mobility–poor people who moved from the Deep South to the Midwest were also more likely to become upper middle class, and poor people who moved from the Midwest to NYC were also more likely to stay poor.

Davidowitz’s data only looks at where people were born; he does not answer whether moving to NYC makes you more likely to become famous. He also doesn’t discuss who is becoming notable–are cities engines to make the children of already successful people becoming even more successful, or are they places where even the poor have a shot at being famous?

I reject Davidowitz’s conclusions (which impute causation where there is only correlation) and substitute my own:

Cities are acceleration platforms for code. Code creates bifurcation. Bifurcation creates winners and losers while obliterating the middle.

This is not necessarily a problem if your alternatives are worse–if your choice is between poverty in NYC or poverty in Detroit, you may be better off in NYC. If your choice is between poverty in Mexico and poverty in California, you may choose California.

But if your choice is between a good chance of being middle class in Salt Lake City verses a high chance of being poor and an extremely small chance of being rich in NYC, you are probably a lot better off packing your bags and heading to Utah.

But if cities are important drivers of innovation (especially in science, to which we owe thanks for things like electricity and refrigerated food shipping,) then Auerswald has already provided us with a potential solution to their runaway effects on the poor: Henry George’s land value tax. As George accounts, one day, while overlooking San Francisco:

I asked a passing teamster, for want of something better to say, what land was worth there. He pointed to some cows grazing so far off that they looked like mice, and said, “I don’t know exactly, but there is a man over there who will sell some land for a thousand dollars an acre.” 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.[28]

Alternatively, higher taxes on fortunes like Zuckerberg’s and Bezos’s might accomplish the same thing.