Monthly Archives: May 2011

Industry At Home

Reading The Hunger Games (2008) and watching Visioneers (2008) recently reminded me that last year I read We (1921) and Pictures of the Socialistic Future [POTSF] (1891). Recent social commentary (i.e., utopian and dystopian) fiction seems to me much less interesting than these older treatments. The reason: 1891 and 1921 were still relatively early in the industrial revolution, when folks were far more uncertain about where this revolution would ultimately lead.

Today the developed world has relatively stable politics, gender and employee relations, leisure activities, etc. So dystopian commentary must get people to see their familiar world from an alien perspective, where they might like it less. Such commentary may try to get people to see themselves as being illicitly dominated, or as pitifully weak and unimpressive, or as insensitive jerks. But this mostly fails, as people are already pretty comfortable with seeing their world in their usual way.

Early treatments like We and POTSF, however, could far more plausibly suggest that quite visible then-current trends would lead to alien worlds that would actually be their grandkids’ future. Some of these fears were of course centered on politics – imagining illicit dominators telling people what to do, be they capitalist oligarchs or socialist bureaucrats. But far more important, I think, were fears that industrial style regimentation and conformity might spread out of workplaces into homes, food, love lives, leisure activities etc. For example:

We is set in the future. D-503 lives in the One State, an urban nation constructed almost entirely of glass, which allows the secret police/spies to inform on and supervise the public more easily. … Life is organized to promote maximum productive efficiency … People march in step with each other and wear identical clothing. There is no way of referring to people save by their given numbers. … D-503′s … friend R-13, a State poet, is employed to write songs in praise of the State.D-503 meets I-330, a woman who dresses erotically and teases and entices him instead of sleeping with him in an impersonal fashion. … He begins to have dreams at night, which disturbs him, as dreams are irrational. … At the novel’s end, D-503 is subjected to the “Great Operation” that has recently been mandated for the whole population of the One State. This operation removes the imagination by striking a certain region of the brain with x-rays. After this operation, D-503 watches the torture and execution of I-330 with equanimity.

I’d love to know what 1800 era folks really think about our lives, relative to these fears. I suspect they’d be somewhat horrified by just how far we have taken workplace regimentation, but they’d be relieved to see us mostly rejecting it in our homes, food, love lives, and leisure activities. Relative to our farmer ancestors, we have become hyper-farmers at work, but have used the resulting wealth to return to forager styles the rest of the time.

Our robot/em descendants, however, may well not have the wealth to afford forager styles outside work. So they may change to more efficient non-work lives, and become workaholics with far less such lives. Such descendants may better realize some of the fears of these early visions of an industrial future. That makes this scenario as interesting to me as those early industrial social commentaries.

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Beware Men With Sticks

Credit: Tom Munnecke

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Letting Leaders Off

Bryan Caplan:

The gold standard of modern social science is … a “random controlled trial.” … And yet… real-world policy-makers continue to neglect, evade, and actively oppose experimental tests of efficacy. … Tim Harford explains why:

Politicians resist pilot schemes with objective measures of success. … politically inconvenient is the fact that half of the pilot schemes will fail… so the pilot will simply produce stark evidence of that failure. …

This is all a nice example of a theme I’ve been pushing for a while ….

Political agency problems are often a byproduct of voter irrationality. The principals give their agents grossly suboptimal incentives, then complain that the agents fail to carry out their assignments. … Pay-for-performance is a good idea, but the public is too irrational to accept it.

Note that private CEOs are also quite reluctant to run randomized trials of their business ideas. Yes some trials happens in marketing, but firms overall still display a puzzling neglect of randomized trials, and of prediction markets. Both mechanisms offer more accurate info, but at the cost of a high rate of clear public embarrassments – clear evidence showing that you endorsed crap.

Yes firms do implement incentive pay more often, but firms still remain puzzlingly reluctant to correct such incentives for overall trends in the economy or the local industry. Maybe voters are more reluctant than stockholders to discipline their agents, making the private sector more efficient at managing many forms of activity. But in both cases there remains a puzzling reluctance to force leaders to prove their value.

My hypothesis: leaders have status, with which voters and stockholders want to affiliate. While people talk about being offended by leader dominance, they are actually quite eager to submit, and reluctant to risk leader wrath by questioning leader quality. The people’s romance with the state makes them even more reluctant to hold political leaders accountable, so this effect is even worse in politics.

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Blocked State Innovation

I’ve complained that regulation usually slows innovation. For example, huge driverless cars gains seem needlessly delayed by excess regulation (Tyler agrees). The problem, however, is not government per se, but the citizens to whom government defers. Politics is not about policy; voters are far more interested in showing off symbolic stances than in giving citizens more of what they want.

But to be fair, citizens hinder not only private innovation, but also government innovation. Long ago when people were imagining a future of cheap computing and communication, they imagined dramatic gains from government databases and citizen monitoring. But then some warned of how such data and monitoring could support tyranny, and ever since most voters have been so eager to signal their disapproval of such Big Brother domination that they are unwilling to consider the most promising government innovations in data and monitoring.

For example, me a year ago:

Overall my students oppose change, moderately favoring whatever is the status quo. So I was quite surprised to see … 85% of my students said yes to: Should all medical practice data be published, aside from data identifying patients?

I assigned this paper topic again this year and, combining the two years, 76% of 76 students favored the change, which correlated 0.29 with student ability to identify relevant pro/con arguments. Again, I don’t grade students on their position, I don’t say what I support, and students usually oppose change. (For example, they overwhelmingly opposed stricter public-place policies on hand washing after sneezing or using restrooms.)

Last year, commenters’ main complaint was that it is impossible guarantee privacy. And this is true. In principle, any piece of info you publish about someone could be the last little clue someone else needs to uncover a great secret about them. It all depends on what other info people reveal, and to whom. The only safe policy is to never publish anything about anyone. And since info supposedly only visible to government employees are often leaked via bribes, the only really safe policy is to never collect any info.

But note that this same argument applies to every piece of info the government reveals about anyone, including date of birth, addresses, who/when they marry or divorce, professional licenses, lawsuits, bankruptcies, tax liens, criminal records, etc. The reason few complain about privacy leaks due to such revelations is that most folks have adapted their other info behavior to expecting this info to be made public.

Similarly, if we gave sufficient advanced warning on a new regime of revealing all med info (minus directly identifying info), most people could adapt their other info behavior to preserve the privacy they want. Don’t let friends drive you to the doc if you don’t want them to know who is your doc. Of course some would mistakenly reveal themselves, and illegal bribery would reveal more. But that can be a price worth paying if there is much to be gained.

Alas, while even my undergrads can see that revealing all med info could easily meet a cost benefit test, voter distaste for anything smacking of Big Brother will probably long block this innovation. This even though recent legal changes go a long way to actually enabling future dictators:

Our Presidents can now, on their own: order assassinations, including American citizens; operate secret military tribunals; engage in torture; enforce indefinite imprisonment without due process; order searches and seizures without proper warrants. (more)

Citizens don’t make a careful tradeoff between social value and preventing future dictators. Instead, thoughtless voters enable Big Brother while symbolically opposing him, and block useful government innovation in the process.

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Status And Glory

Once upon a time it was elites who went to war, who took the risks but could gain the glory. Once upon a time gambling was banned for ordinary folks but elites could take such risks and gain glory if they won. Today, consider this NYT article (in which I’m quoted):

John Delaney, an Irish businessman who founded Intrade, an online prediction market that allows customers to bet on world political, entertainment and financial events, died on Saturday after coming within 50 yards of the summit of Mount Everest. He was 42.

This article said nothing on banning Everest climbs; few articles on Everest climbs do. Yet:

The overall mortality rate for Everest mountaineers during the entire 86-year period was 1.3 percent; the rate among climbers was 1.6 percent and the rate among sherpas was 1.1 percent. During the past 25 years, a period during which a greater percentage of moutaineers climbed above 8,000 meters, the death rate for non-Himalayan climbers descending via the longer Tibetan northeast ridge was 3.4 percent, while on the shorter Nepal route it was 2.5 percent.

Contrast this to strong widespread feelings that bike helmets should be required, even though cyclists suffer only about 7 injuries per million miles of biking, and despite serious doubts if helmets help. Even the proverbial banned lawn darts caused ~30 deaths a year with 10-15 million of them in use, far far less than a 2% user death rate.

Why do ban activities with very low risks yet celebrate very high risk mountain climbing? Status seems the obvious explanation. It takes a lot of money to even attempt to climb Everest. We celebrate high status risk-takers, and ban low status ones.

Need more data? Consider the widespread bans on “noodling”, i.e., catching fish with your bare hands:

Brady Knowlton believes it’s his inalienable right as a Texan to shove his bare hand into the mouth of a 60-pound catfish and yank it out of a river. But wrestling a flapping, whiskered giant as it latches onto your arm with its jaws isn’t among Texas’s accepted methods of capturing fish. It is, rather, a class C misdemeanor, with fines of up to $500. … Rod-and-reel anglers … say noodling is unfair to the fish, since they’re grabbed in their burrows without a chance to swim away. … Missouri … prohibits fish-grabbing on grounds that it would deplete the fish population. (more)

When you picture a fish-noodler do you picture someone high status? Didn’t think so.

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The Poor Don’t Revolt

A standard myth:

Once upon a time, poor masses suffered under rich elites. Then one day the poor realized they could revolt, and since then, the rich help the poor, fearing the poor will revolt if they ever feel they suffer too much.

Revolution experts mostly reject this myth; famous revolutions happened after things had gotten better, not worse, for the poor. Yet Matt Yglesias (responding to Bryan Caplan responding to me) seems to echo this myth:

Another way of putting it would be Simon (i.e., plenty) for capital and Malthus (i.e., subsistence) for labor. That, of course, is Karl Marx’s vision of long-term economic development. And while I don’t have a strong opinion as to whether or not this is accurate over the long term, it’s certainly a plausible story about the future, and Marx’s solution—socialism—unquestionably seems to me to be the correct one. Marx’s forecast of the immiseration of labor and all the returns going to the owners of capital clearly hasn’t been true in the 150 years or so since his time, but it certainly could happen. … If the robots are sentient beings, then we’d presumably be looking at an eventual slave revolt and Communist revolution.

Matt claims that if sentient robots are poor, they must eventually revolt. Karl Smith responds:

The robots will be EMs. But, … they will likely remember having been stems [= flesh and blood people]. … This means the robots get the ability to feel jealousy right along with the ability to engineer new products. … However, the analogy isn’t as Matt suggests a return to the late 1800s. It’s a return to the 1600s. The Stems won’t be capitalists. … The Stems will be landed gentry. …

The EMs will likely not be slaves because there will be no reason to enslave them. The rent on land will exceed the profits from running a slave operation. Lastly the EMs will not revolt because there will be little to gain. … Stems are extremely wealthy because you are taking a tiny slice of a huge amount of economic output and then giving it to an incredibly tiny fraction of the population.

I doubt it matters whether a tiny elite, presumably including most humans, owns capital or land. But Karl is quite right about the key point: poverty does not by itself lead to revolt. While a transition could be rough, once the world is in a Malthusian equilibrium there’s no particular reason to expect trillions of ems to revolt, any more than ancient farmer masses did, or most of the world’s poor today.  (Current “Arab Spring” revolts are driven more by under-employed well-educated.)

Keep in mind that in a Malthusian world, even if future robots could grab all the capital or land, it would be worth only a modest fraction of total wealth, and a revolution could threaten the productive system on which they all depend.

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No Generic City Effect

This is my last post on results from Ken Lee’s excellent thesis.

People who in rural areas die consistently less than others, even after controlling for other death predictors. To study this effect, Lee tried interacting urbanity with many other predictors, including geography. That is, Lee looked at all combinations of whether someone lived in a city, suburb, or rural area, and in which of nine regions of the US they lived.

After controlling for his other usual predictors (age, race, gender, married, education, income), Lee found that eleven of the 26 interaction ratios were 5% significant, and six were 1% significant. It seems that there is just no such thing as a generic effect of living in a city, suburb or rural area, nor a generic effect of living in each region. Instead, each of the 27 different place combinations has its own distinct influence on health. Put another way, each of the nine US region has a different city, suburb, or rural effect. Here are the estimated death ratios of each place (relative to Middle Atlantic cities):


It is West North Central, New England, and Mountain rural areas that are good for health (adding a year or so of life), and it is South Atlantic cities that are the worst for health (cutting ~1.5 years of life).

FYI, these are the ratios and significance from Lee’s table 17: Continue reading "No Generic City Effect" »

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School Death Puzzle

When Ken Lee looked at 367,101 folks followed over 11 years, he found (in Table 12) that richer folks consistently died less. But for education, the trend wasn’t as consistent:


Folks who graduate from high school die less than those who only start high school, those who graduate from college die even less, and those who have some grad school live even more. But, folks with no school at all do as well as college graduates! And compared with those who stop at three years of high school, those who get less school than three years of high school seem to suffer no health penalty – if anything they die less!  This fits with seeing higher mortality in states with more high school graduates, after controlling for college grads, but is odd. What gives?

Could this be a status effect, where those who didn’t buy into school as an ideal don’t mind that they didn’t get so much school?

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Jobs Kill, BIG Time

I’ve saved the most interesting result in Ken Lee’s thesis till today. The subject is how death rates vary with jobs. The big result: death rates depend on job details more than on race, gender, marriage status, rural vs. urban, education, and income combined! Now for the details.

The US Department of Labor has described each of 807 occupations with over 200 detailed features on how jobs are done, skills required, etc.. Lee looked at seven domains of such features, each containing 16 to 57 features, and for each domain Lee did a factor analysis of those features to find the top 2-4 factors. This gave Lee a total of 22 domain factors. Lee also found four overall factors to describe his total set of 225 job and 9 demographic features. (These four factors explain 32%, 15%, 7%, and 4% of total variance.)

Lee then tried to use these 26 job factors, along with his other standard predictors (age, race, gender, married, rural, education, income) to predict deaths in the 302,890 people for whom he had job data. Lee found that his standard predictors didn’t change much, and found these job factor risk ratios (Table 34, column 2):


Ten of the 26 estimates are 5% significant, and five are 1% significant – this isn’t random noise (*** p<0.01, ** p<0.05, * p<0.1). Each factor is scaled to range in value from 0 to 1 across the 806 occupations; its risk ratio is an estimated ratio of death rates when that factor has its max value of one, relative to death rates when that factor has its min value of zero. And these are huge risk ratios!

If you take all of Lee’s standard non-age predictors (race, gender, married, rural, education, income), and multiply together their risk ratios, you’ll find that a poor badly-schooled unmarried urban black male dies 17.7 times as often as a rich well-educated married rural asian woman (of the same age), with a lifespan roughly thirty years shorter on average. (A risk ratio of 1.57 costs roughly five years of life.)

Yet big as this effect is, the top five job factor risk ratios give a total ratio of 19.7, bigger that all the other non-age effects put together! And the top ten job factor ratios give a total risk ratio of over 100!  (All twenty six factors together give a total risk ratio of 563.) Jobs are clearly a huge and neglected influence on who lives and who dies.

If you cared about preventing death, rather than just signaling your concern, these results suggest you stop wasting your efforts on tiny effects like medical insurance, auto accidents, crime, recreational drugs, radiation, or food safety, and focus on: jobs. Yes a lot of job-death variation must come from different types of people doing different types of jobs, but a great deal of this variation is also likely causal – some jobs kill folks much more than others.

At the very least we should try to tell people about the huge life and death consequences of their job choices. Then workers could demand higher wages for more deadly jobs, which should induce employers to seek ways to substitute less deadly for more deadly jobs. Alas I suspect most folks will just shrug their shoulders – these sort of effects seem too abstract to elicit much concern. If you look at a person doing a job they don’t look like they are dying. Not like if snakes were killing people on planes …

FYI, here are some sample jobs rated high and low on the four overall job factors (from Table 49): Continue reading "Jobs Kill, BIG Time" »

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5 Million Visits

Today we had our five millionth visit to Overcoming Bias, at least as measured by sitemeter. Woo and hoo … :)

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