Does the DSM need to be re-written?

I recently came across an interesting paper that looked at the likelihood that a person, once diagnosed with one mental disorder, would be diagnosed with another. (Exploring Comorbidity Within Mental Disorders Among a Danish National Population, by Oleguer Plana-Ripoll.)

This was a remarkable study in two ways. First, it had a sample size of 5,940,778, followed up for 83.9 million person-years–basically, the entire population of Denmark over 15 years. (Big Data indeed.)

Second, it found that for virtually every disorder, one diagnoses increased your chances of being diagnosed with a second disorder. (“Comorbid” is a fancy word for “two diseases or conditions occurring together,” not “dying at the same time.”) Some diseases were particularly likely to co-occur–in particular, people diagnosed with “mood disorders” had a 30% chance of also being diagnosed with “neurotic disorders” during the 15 years covered by the study.

Mood disorders includes bipolar, depression, and SAD;

Neurotic disorders include anxieties, phobias, and OCD.

Those chances were considerably higher for people diagnosed at younger ages, and decreased significantly for the elderly–those diagnosed with mood disorders before the age of 20 had a +40% chance of also being diagnosed with a neurotic disorder, while those diagnosed after 80 had only a 5% chance.

I don’t find this terribly surprising, since I know someone with at least five different psychological diagnoses, (nor is it surprising that many people with “intellectual disabilities” also have “developmental disorders”) but it’s interesting just how pervasive comorbidity is across conditions that are ostensibly separate diseases.

This suggests to me that either many people are being mis-diagnosed (perhaps diagnosis itself is very difficult,) or what look like separate disorders are often actually one, single disorder. While it is certainly possible, of course, for someone to have both a phobia of snakes and seasonal affective disorder, the person I know with five diagnoses most likely has only one “true” disorder that has just been diagnosed and treated differently by different clinicians. It seems likely that some people’s depression also manifests itself as deep-rooted anxiety or phobias, for example.

While this is a bit of a blow for many psychiatric diagnoses, (and I am quite certain that many diagnostic categories will need a fair amount of revision before all is said and done,) autism recently got a validity boost–How brain scans can diagnose Autism with 97% accuracy.

The title is overselling it, but it’s interesting anyway:



N=34 is not quite as impressive as N=Denmark, but it’s a good start.

A Little Review of Big Data Books







































(Or these companies are massively over-valued.)





Please discuss the implications for

1. Third world mega-cities like Karachi or Lagos.

2. Immigration from third world to first world.

3. Digital real estate, like Twitter.

About the digital economy Second Life, Auerswald writes:










Auerswald then makes a very interesting observation:








Remember: everything else is downstream from territory.






















Is this how the middle class dies?

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













This does not resolve the question.

Discussion from the paper:


this pattern as neither supportive nor at odds with our model.







Talking about Chetty’s data, Davidowitz writes:




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












And this is why we are doomed.







The other factor that correlates with the production of notables?

A big city.





The variable that didn’t predict notability:






Some, like Mark Zuckerberg, went to private school.


A couple of methodological notes:










Book Club: Code Economy: Economics as Information Theory

If the suggestion… that the economy is “alive” seems fanciful or far-fetched, it is much less so if we consider the alternative: that it is dead.

Welcome back to your regularly scheduled discussion of Auerswald’s The Code Economy: a Forty-Thousand-Year History. Today we are discussing Chapter 9: Platforms, but feel free to jump into the discussion even if you haven’t read the book.

I loved this chapter.

We can safely answer that the economy–or the sum total of human provisioning, consumptive, productive and social activities–is neither “alive” nor, exactly, “non-living.”

The economy has a structure, yes. (So does a crystal.) It requires energy, like a plant, sponge, or macaque. It creates waste. But like a beehive, it is not “conscious;” voters struggle to make any kind of coherent policies.

Can economies reproduce themselves, like a beehive sending out swarms to found new hives? Yes, though it is difficult in a world where most of the sensible human niches have already been filled.

Auerswald notes that his use of the word “code” throughout the book is not (just) because of its modern sense in the coding of computer programs, but because of its use in the structure of DNA–we are literally built from the instructions in our genetic “code,” and society is, on top of that, layers and layers of more code, for everything from “how to raise vegetables” to “how to build an iPhone” to, yes, Angry Birds.

Indeed, as I have insisted throughout, this is more than an analogy: the introduction of production recipes into economics is… exactly what the introduction of DNA i to molecular biology. it is the essential first step toward a transformation of economics into a branch of information theory.

I don’t have much to say about information theory because I haven’t studied information theory, beyond once reading a problem about a couple of people named Alice and Bob who were trying to send messages to each other, but I did read Viktor Mayer-Schönberger and, Kenneth Cukier‘s Big Data: A revolution that will transform how we live, work, and think a couple of weeks ago. It doesn’t rise to the level of “OMG this was great you must read it,” but if you’re interested in the subject, it’s a good introduction and pairs nicely with The Code Economy, as many of the developments in “big data” are relevant to recent developments in code. It’s also helpful in understanding why on earth anyone sees anything of value in companies like Facebook and LinkedIn, which will be coming up soon.

You know, we know that bees live in a hive, but do bees know? (No, not for any meaningful definition of “knowing.”) But imagine being a bee, and slowly working out that you live in a hive, and that the hive “behaves” in certain ways that you can model, just like you can model the behavior of an individual bee…


Economics has a lot to say about how to optimize the level of inputs to get output, but what about the actual process of tuning inputs into outputs? … In the Wonderful World of Widgets that i standard economic, ingredients combine to make a final product, but the recipe by which the ingredients actually become the product is nowhere explicitly represented.

After some papers on the NK model and th shift in organizational demands from pre-industrial economic production to post-industrial large-scale production by mega firms, (or in the case of communism, by whole states,) Auerswald concludes that

…the economy manages increasing complexity by “hard-wiring” solution into standards, which in turn define platforms.

Original Morse Telegraph machine, circa 1835

This is an important insight. Electricity was once a new technology, whose mathematical rules were explored by cutting-edge scientists. Electrical appliances and the grid to deliver the electricity they run on were developed by folks like Edison and Tesla.

But today, the electrical grid reaches nearly every house in America. You don’t have to understand electricity at all to plug in your toaster. You don’t have to be Thomas Edison to lay electrical lines. You just have to follow instructions.

Electricity + electrical appliances replaced many jobs people used to do, like candle making or pony express delivery man, but electricity has not resulted in an overall loss of jobs. Rather, far more jobs now exist that depend on the electrical grid (or “platform”) than were eliminated.

(However, one of the difficulties or problems with codifying things into platforms is then, systems have difficulty handling other, perfectly valid methods of doing things. Early codification may lock-in certain ways of doing things that are actually suboptimal, like how our computer keyboard layout is intentionally difficult to use not because of anything to do with computers, but because typewriters in the 1800s jammed if people typed on them too quickly. Today, we would be better off with a more sensible keyboard layout, but the old one persists because too many systems use it.)

The Industrial Revolution was a time of first technological development, and then encoding into platforms of many varieties–transportation networks of water and rail; electrical, sewer, and fresh water grids; the large-scale production of antibiotics and vaccines; and even the codification of governments.

The English, a nation of a couple thousand years or so, are governed under a system known as “Common Law,” which is just all of the legal precedents and traditions built up over that time that have come into customary use.

When America was founded, it didn’t have a thousand years of experience to draw on because, well, it had just been founded, but it did have a thousand years of cultural memory of England’s government. English Common Law was codified as the base of the American legal system.

The Articles of Confederation, famous only for not working very well, were the fledgling country’s first attempt at codifying how the government should operate. They are typically described as failing because they allocated insufficient power to the federal government, but I propose a more nuanced take: the Articles laid out insufficient code for dealing with nation-level problems. The Constitution solved these problems and instituted the basic “platform” on which the rest of the government is built. Today, whether we want to ratify a treaty or change the speed limit on i-405, we don’t have to re-derive the entire decisions-making structure from scratch; legitimacy (for better or for worse) is already built into the system.

Since the days of the American and French revolutions, new countries have typically had “constitutions,” not because Common Law is bad, but because there is no need to re-derive from scratch successful governing platforms–they can just be copied from other countries, just as one firm can copy another firms organizational structure.

Continuing with Auerswald and the march of time:

Ask yourself what the greatest inventions were over the past 150 years: Penicillin? The transistor? Electrical power? Each of these has been transformative, but equally compelling candidates include universal time, container shipping, the TCP/IP protocols underlying the Internet, and the GSM and CDMA standards that underlie mobile telephony. These are the technologies that make global trade possible by making code developed in one place interoperable with code developed in another. Standards reduce barriers among people…

Auerswald, as a code enthusiast, doesn’t devote much space to the downsides of code. Clearly, code can make life easier, by reducing the number of cognitive tasks required to get a job done. Let’s take the matter of household management. If a husband and wife both adhere to “traditional gender norms,” such as an expectation that the wife will take care of internal household chores like cooking and vacuuming, and the husband will take care of external chores, like mowing the lawn, taking out the trash, and pumping gas, neither spouse has to ever discuss “who is going to do this job” or wonder “hey, did that job get done?”

Following an established code thus aids efficiency and appears to decrease marital stress (there are studies on this,) but this does not mean that the code itself is optimal. Perhaps men make better dish-washers than women. Or for a couple with a disabled partner, perhaps all of the jobs would be better performed by reversing the roles.

Technological change also encourages code change:

The replacement of manual push-mowers with gas-powered mowers makes mowing the lawn easier for women, so perhaps this task would be better performed by housewives. (Even the Amish have adopted milking machines on the grounds that by pumping the milk away from the cow for you, the machines enable women to participate equally in the milking–a task that previously involved picking up and carrying around 90 lb milkjugs.)

But re-writing the entire code is work and involves a learning curve as both parties sort out and get used to new expectations. (See my previous thread on “emotional labor” and its relation to gender norms.) So even if you think the old code isn’t fair or optimal, it still might be easier than trying to make a new code–and this extends to far more human relations than just marriage.

And then you get cases where the new technology is incompatible with the old code. Take, for example, the relationship between transportation, weights and measures, and the French Revolution.

A country in which there is no efficient way to get from Point A to Point B has no need for a standardized set of weights and measures, as people in Community A will never encounter or contend with whatever system they are using over in Community B. Even if a king wanted to create a standard system, he would have difficulty enforcing it. Instead, each community tends to evolve a system that works well for its own needs. A community that grows bananas, for example, will come up with measures suitable to bananas, like the “bunch,” a community that deals in grain will invent the “bushel,” and a community that enumerates no goods, like the Piraha, will not bother with large quantities quantities.

(Diamonds are measured in “carats,” which have nothing to do with the orange vegetable, but instead are derived from the seeds of the carob tree, which apparently are small enough to be weighed against small stones.)

Since the French paid taxes, there was some demand for standardized weights and measures within each province–if your taxes are “one bushel of grain,” you want to make sure “bushel” is well defined so the local lord doesn’t suddenly define this year’s bushel as twice as big as last year’s bushel–and likewise, the lord doesn’t want this year’s bushel to be defined as half the size as last year’s.

But as roads improved and trade increased, people became concerned with making sure that a bushel of grain sold in Paris was the same as a bushel purchased in Nice, or that 5 carats of diamonds in Bordeaux was still 5 carats when you reached Cognac.

But the established local power of the local nobility made it very hard to change whatever measures people were using in each individual place. That is, the existing code made it hard to change to a more efficient code, probably because local lords were concerned the new measures would result in fewer taxes, and the local peasants concerned it would result in higher taxes.

Thus it was only with the decapitation of the Ancien Regime and wiping away of the privileges and prerogatives of the nobility that Revolutionary France established, as one of its few lasting reforms, a universal system of weights and measures that has come down to us today as the metric or SI system.

Now, speaking as an American who has been trained in both Metric and Imperial units, using multiple systems can be annoying, but is rarely deadly. On the scale of sub-optimal ideas, humans have invented far worse.

Quoting Richard Rhodes, The Making of the Atomic Bomb:





Russian Troops waiting for death

On the Eastern Front, the Death Machine was defeated by the Russian Revolution, as the canon fodder decided it didn’t want to be turned into corpses anymore.

I find World War I more interesting than WWII because it makes far less sense. The combatants in WWII had something resembling sensible goals, some chance of achieving their goals, and attempted to protect the lives of their own people. WWI, by contrast, has no such underlying logic, yet it happened anyway–proof that seemingly logical people can engage in the ultimate illogic, even as it reduces whole countries to nothing but death machines.

Why did some countries revolt against the cruel code of war, and others not? Perhaps an important factor is the perceived legitimacy of the government itself (though regular food shipments are probably just as critical.) Getting back to information theory, democracy itself is a kind of blockchain for establishing political legitimacy, (more on this in a couple of chapters) which may account for why some countries perceived their leadership as more legitimate, and other countries suddenly discovered, as information about other people’s opinions became easier to obtain, that the government enjoyed very little legitimacy.

But I am speculating, and have gotten totally off-topic (Auerswald was just discussing the establishment of TCP/IP protocols and other similar standards that aid international trade, not WWI!)

Returning to Auerswald, he cites a brilliant quote from Alfred North Whitehead


As we were saying, while sub-optimal (or suicidal) code can and does destroy human societies, good code can substantially increase human well-being.

The discovery and refinement of new inventions, technologies, production recipes, etc., involves a steep learning curve as people first figure out how to make the thing work and to source and put together all of the parts necessary to build it, (eg, the invention of the automobile in the late 1800s and early 1900s,) but once the technology spreads, it simply becomes part of the expected infrastructure of everyday life (eg, the building of interstate highways and gas stations, allowing people to drive cars all around the US,) a “platform” on which other, future innovations build. Post-1950, most automobile-driven innovation was located not in refinements to the engines or brakes, but in things you can do with vehicles, like long-distance shipping.

Interesting things happen to income as code becomes platforms, but I haven’t worked out all of the details.

Continuing with Auerswald:

Note that, in code economics, a given country’s level of “development” is not sensibly measured by the total monetary value of all goods and services it produces…. Rather, the development of a country consists of … it capacity to execute more complex code. …

Less-developed countries that lack the code to produce complex products will import them, and they will export simpler intermediate products and raw materials in order to pay for the required imports.

By creating and adhering to widely-observed “standards,” increasing numbers of countries (and people) are able to share inventions, code, and development.

Of the drivers of beneficial trade, international standards are at once among the most important and the least appreciated. … From the invention of bills of exchange in the Middle Ages … to the creation of twenty-first-century communications protocols, innovations in standards have lowered the cost and enhanced the value of exchange across distance. …

For entrepreneurs in developing countries, demonstrated conformity with international standards… is a universally recognized mark of organizational capacity that substantially eases entry into global production and distribution networks.

In other words, you are more likely to order steel from a foreign factory if you have some confidence that you will actually receive the variety you ordered, and the factory can signal that it knows what it is doing and will actually deliver the specified steel by adhering to international standards.

On the other hand, I think this can degenerate into a reliance on the appearance of doing things properly, which partially explains the Elizabeth Holmes affair. Holmes sounded like she knew what she was doing–she knew how to sound like she was running a successful startup because she’d been raised in the Silicon Valley startup culture. Meanwhile, the people investing in Holmes’s business didn’t know anything about blood testing (Holmes’s supposed invention tested blood)–they could only judge whether the company sounded like it was a real business.

Auerswald then has a fascinating section comparing each subsequent “platform” that builds on the previous “platform” to trophic levels in the environment. The development of each level allows for the development of another, more complex level above it–the top platform becomes the space where newest code is developed.

If goods and services are built on platforms, one atop the other, then it follows that learning at higher levels of the system should be faster than learning at lower levels, for the simple reason that leaning at higher levels benefits from incremental learning all the way down.

There are two “layers” of learning. Raw material extraction shows high volatility around a a gradually increasing trend, aka slow learning. By contrast, the delivery of services over existing infrastructure, like roads or wireless networks, show exponential growth, aka fast learning.

In other words, the more levels of code you already have established and standardized into platforms, the faster learning goes–the basic idea behind the singularity.


That’s all for today. See you next week!

War is Code for the Production of Corpses

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





Big Data describes another war of attrition:







Like human sacrifice and cannibalism:



