Monthly Archives: March 2010

Not Paleolithic Mating

In February I quoted Charlotte Allen quoting Geoffrey Miller on New Paleolithic Mating:

Some relationships might have lasted no more than a few days. … Many Pleistocene mothers probably had boyfriends. But each woman’s boyfriend may not have been the father of any of her offspring. … Males may have given some food to females and their offspring, and may have defended them from other men, but … more as courtship effort than paternal investment.

That’s a pretty fair description of mating life today in the urban underclass and the meth-lab culture of rural America. Take away the offspring, blocked by the Pill and ready abortion, and it’s also a pretty fair description of today’s prolonged singles scene.

Lately I’ve been filling a big hole in my social science education, by reading lots of anthropology of nomadic forager bands, our main fossil evidence on our distant ancestors’ lives.  I’ve learned modern mating is far from Paleolithic!  Consider:

It is unusual, but not exceptional, for a lone woman to spend the day gathering. In the times I observed at the Duda camps, the solitary foragers were either postmenopausal women or young, unmarried women who were still without children. Women with children or adolescent, unmarried girls usually gather bush food in the company of two or more other women. The !Kung themselves claim that lovers (as well as married couples) sometimes arrange to meet privately in the bush. !Kung sleeping arrangements may promote these tactics, for at night whole families sleep outdoors together gathered around individual campfires and within a few feet of other families sleeping at their own fires. …

In the bush [in contrast to villages,] concerned relatives will work to keep a young couple together up to a certain  point, but if the individuals themselves feel mis-matched, there are few, if any, arguments that will persuade them to stay together.  When (as often happens) the young couple divorces, no one loses a great deal – no property of any economic weight has changed hands, etc. … Such a marriage in the bush setting would have had a different history.  !Uku would have left her husband long before, in all likelihood to spend another year or two in casual flirtations before marrying again.

In one evening, a modern city woman can see and choose among more men her age than a forager woman would meet people in her lifetime.  If a modern woman prefers, all those men can be strangers, so that if she goes home with one there is little risk of word getting back to anyone she knows.  The next night she can choose among an entirely different group just as big.

In contrast, a typical forager woman only has frequent contact with the 30-50 people in her band, with a handful of men near her age.  Most of the men she might find attractive already have a woman.  Foragers bands meet periodically with a few known associate bands, and a young woman typically switches from her parent’s band, usually to be with a particular man.

The band lives in very close quarters, with everyone watching everyone’s faces closely.  Illicit flirtation must be very subtle.  People know who goes off alone, and quickly draw conclusions about who might meet whom out there; happily mated folks are expected not to go off alone.

Yes foragers switch mates during their lives, but men often react to betrayal with violence, and women aren’t above spreading malicious gossip about rivals.  Babies of single forager moms face a greater risk of harm.  For our distant ancestors, switching and cheating were far harder, and the options far more limited.  Modern dating is really quite unlike that of our ancestors.

Added: Thursday adds “three most important factors driving modern mating:  1. Urban anonymity  2. Reliable birth control 3. A woman’s ability to support herself.”

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Homo Hypocritus

The standard social brain theory seems in conflict with standard anthropologist accounts of ancestral forager lifestyles.  Might “man the sly rule bender” resolve this conflict?

Why do we have ginormous brains?  Animals tend to have big brains when they have big bodies, but beyond that the main brain pattern is social: bigger brains are found in birds and mammals that compete with predators or prey, and who manage pair-bonding mate relations.  The extra costs of big brains is outweighed by benefits of not being out-witted by others.

Primates (and hyenas) hit on the trick of reusing pair-bonding skills to manage friendships in large social groups.  Primates have huge expensive brains, which are bigger in species with larger social groups, and these groups spend more of their time managing social relations.  Bigger groups better protect against predators, though the coalition politics of dominance gets more complex in bigger groups.

Primates not only manage relations and coalitions, but they also track the relations and coalitions of others.  They are adept at judging how to help their coalitions, and when to switch sides.  The top chimp is often not the strongest, but instead the one with the strongest coalition, which gets to dominate food and mating, and stay best protected from predators; chimp investments in big brains often pay off handsomely.

Humans have the biggest primate brains of all. Over the last two million years hominid brains grew more where climates were variable, but they grew most where population densities were high.  This suggests that human brains were also big mainly due to social pressures.  The “mating mind” sexual selection hypothesis seems at odds with this density effect, and with the more general fact that polygamous species tend to have smaller brains.  “Man the tool user” stories seem to confuse broad group gains with individual benefits – smaller brains seem sufficient for copying others’ tool skills.  But even if social pressures were key, which pressures exactly?

Isolated nomadic forager bands today are “fossils” with crucial clues about our distant ancestors.  Anthropologists who study them report that overt dominance is rare, and long distances make war rare (as 4 million year old fossils suggest). Foragers live in tight quarters and use language to express and enforce social norms on food sharing, non-violence, mating freedom, communal decision making, and norm enforcement.  Anger, bragging, giving orders, and anything remotely resembling dominance among men is punished by avoidance, exile, and death as required.  Human’s unusual hidden female fertility also limits male dominance temptations.

The puzzle here is that consistent enforcement of such norms seems to drastically reduce the payoff to expensive coalition-politics-savvy brains.  If you can’t collude to grab the food or the women, and everyone is treated fairly based on their contributions, why bother to be so clever?  Yes, some brain innovations were required to support language, and maybe they wouldn’t have occurred in a small brain, but after that innovation human brains could have shrunk (as perhaps with hobbits).  Why did humans keep huge expensive brains?

In a messy real world, social norms expressed in language typically have many iffy boundary cases and ambiguities.  How much of what sort of food of what quality offered how conveniently counts as food sharing?  How big a frown is a grimace?  Sex with how close a relative counts as incest?  And so on.  This wouldn’t matter if boundary cases were decided randomly, but that seems unlikely.  Instead big brain gains come five ways:

Unnormed – coalition politics on acts uncovered by norms.
Skirt – keep actions near but not over edge of violating norms.
Cover – politics of observers on if to report an act to others.
Frame – lawyer-like arguing on if acts violate social norms.
Conspire – form coalitions on how to publicly interpet iffy acts.

Most norms have meta-norms against consciously trying to evade them.  Self-deception should help here; foragers might sincerely believe they usually just do their job and “tell it like it is”, and then unconsciously try to act, selectively report and frame acts, and support interpretation coalitions, to their advantage.  Instead of “man the tool user”, we might be better understood as “man the sly rule bender.”

Gains to rule bending could be greatly reduced via social norms with very clear simple rules.  But humans seems to usually prefer complex and ambiguous rules that require “judgment” to apply.  For example, foragers often have complex incest rules, forbidding a much wider range of sex partners than is needed to prevent genetic problems.  And acts of sorcery are allowed to count as acts of aggression that violate social norms and must be punished, even without concrete evidence showing such acts.  Both complex broad incest rules and allowing sorcery complaints greatly increase the scope for gains to large rule-bending brains, and suggest that we tend to prefer to allow such scope.

The idea that the main reason we have huge brains is to hypocritically bend rules seems to me a dramatic change in how we think about human nature.  If true, it should change how we understand a great many things in psychology and social science.  I’ve been obsessing about his topic for weeks, and last Thursday I ran it past Robin Dunbar, famed for his contributions to the social brain account, and he said it was pretty close to his view on the subject, and he suggested the incest example.

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Very Bad News

Back in ’98 I considered the “doomsday argument”:

A creative argument [suggests] “doom” is more likely than we otherwise imagine. … [Consider] the case of finding yourself in an exponentially growing population that will suddenly end someday. Since most of the members will appear just before the end, you should infer that that end probably isn’t more than a few doubling times away from now.

I didn’t buy it (nor did Tyler):

Knowing that you are alive with amnesia tells you that you are in an unusual and informative situation. … The mere fact that you exist would seem to tell you a lot.

I instead embraced “self-indication analysis”, which blocks the usual doomsday argument.  In ’08 I even suggested self-indication helps explain time-asymmetry:

Even if we knew everything about what will happen where and when in the universe, we could still be uncertain about where/when we are in that universe. … [So] we need … a prior which says where/when we should expect to find ourselves, if we knew the least possible about that topic. …  Self-indication … says … you should … expect more to find yourself in universes that have many slots for creatures like you. …

Given self-indication we should expect to be in a finite-probability universe with nearly the max possible number of observer-moment slots.  … [which] seem large enough to have at least one inflation origin, which then implies … large regions of time-asymmetry.

Alas, Katja Grace had just shown that, given a great filter, self-indication implies doom!  This is the great filter:

Humanity seems to have a bright future, i.e., a non-trivial chance of expanding to fill the universe with lasting life. But the fact that space near us seems dead now tells us that any given piece of dead matter faces an astronomically low chance of begating such a future. There thus exists a great filter between death and expanding lasting life, and humanity faces the ominous question: how far along this filter are we?

And here is Katja’s simple argument, in one elegant diagram:

doom

Here are three possible worlds, and within each possible world three different planets are shown on the X axis, while three different times are shown on the Y axis.  The three worlds correspond to three different times when the great filter might occur:  1) before any life, 2) before intelligent life, or 3) before space colonization.

After at first thinking you are in a random box, you update on the fact that your planet recently acquired intelligence, and conclude you are somewhere in the middle row.  Then you update on self-indication, i.e., that you exist, and so are in an orange box.  You conclude you likely live in world 3.  (It has 3/5 of the orange boxes.)  Doom awaits!

The diagram just illustrates the general principle.  As Katja disclaims:

The small number of planets and stages and the concentration of the filter is for simplicity; in reality the filter needn’t be only one unlikely step, and there are many planets and many phases of existence between dead matter and galaxy colonizing civilization.

Alas I now drastically increase my estimate of our existential risk; I am, for example, now far more eager to improve our refuges.  And let’s avoid the common bias to punish the bearers of bad news; Katja deserves our deepest gratitude; fore-warned is fore-armed.

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How To Survey Confidence

In a 3-point elicitation procedure, an expert is asked for a lower limit, upper limit, and best guess, the two limits creating an interval of some assigned confidence level (e.g., 80%). In our 4-step interval elicitation procedure, experts were also asked for a realistic lower limit, upper limit, and best guess, but no confidence level was assigned; the fourth step was to rate their anticipated confidence in the interval produced. … We … found average overconfidence of 11.9%, 95% CI [3.5, 20.3] (a hit rate of 68.1% for 80% intervals)—a substantial decrease in overconfidence compared with previous studies.

More here.

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Is God Here To Stay?

According to a new cross-cultural study, … people living in communities most like those of Stone Age hunter-gatherers — small in numbers and lacking a “moralizing god” — made the most unfair offers to strangers and were least likely to punish stingy partners.

More here.  This confirms that moralizing Gods function to encourage cooperation in large societies, and adds moralizing gods, and fairness to strangers, to the many innovations that came with farming, such as war, slavery, marriage as property, class hierarchies and large wealth inequalities.

The strength of modern attachment to moralizing gods was emphasized to me twice recently.  First, I was reminded the [US] public hates atheists:

Mosaic Project researchers asked survey questions to determine Americans’ reactions to situations involving members of various out-groups (e.g. a person’s feeling about one their children marrying a Jewish or Muslim or Catholic or atheist person). … ‘Atheist’ was by far the ‘lightning rod’ category on multiple queries and atheists were even described as “evil and immoral”.

Second, I attended a lecture by famed philosopher of science Philip Kitcher, on “Militant Modern Atheism”:

Religious scholars who criticize the militant atheists often view religion as centered in social practices that inform and enrich human lives. … Doctrines that atheists might subject to epistemic evaluation … are … pieces of scaffolding, that are, in principle, dispensable. … Militant modern atheism is incomplete (and likely counter-productive) so long as it fails to attend systematically to the roles religion fulfills in human lives. … The challenge is to develop a well-articulated and convincing version of secular humanism.

Kitcher was vague on how religion “enriches,” mentioning identity, community, and “giving meaning.”  He likes folks to start from core values and pick a religion to match, and not take anything transcendent beings say too literally.  I asked the last question of the evening: what if we can’t reform religion much; which would he choose between atheism and the today’s distribution of religious styles?  He refused to answer that question, insisting we can reform religion.  Apparently some choices are morally repugnant to consider, and even to a famed analytic philosopher, “what if we can’t take crazy beliefs out of religion?” is one of them.

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Forensic Delusions

A groundbreaking report by the National Academy of Sciences (NAS) last year recognized that much of forensic science is not rooted in solid science. Many forensic disciplines — such as hair microscopy, bite-mark comparisons, fingerprint analysis, firearm testing and tool-mark analysis — were developed solely to solve crimes.  They evolved mainly in the context of individual cases, which often had significant variation in resources and expertise. They have not been subjected to rigorous experimental scrutiny, and there are no standards or oversight in the United States or elsewhere to ensure that validated, reliable forensic methods are used consistently. With the exception of DNA analysis, no forensic method has been proved to reliably and accurately demonstrate a connection between evidence and a specific source. …

We advocate the creation of an office of forensic science improvement and support (OFSIS) within the US Department of Commerce to spur independent research, develop standards and ensure compliance. … [Some] within the forensic-science and law-enforcement fields … argue that an OFSIS is not necessary and that laboratory accreditation is sufficient. … They argue that an OFSIS would cost too much … and that it could create chaos in the US justice system by reopening countless old cases. … Political and criminal-justice ends — rather than research imperatives — have taken forensic science off course. … See www.just-science.org.

More here.  The primary social pressure on law court practices is for courts to give the appearance of punishing guilty folks.  Observers have much less info on who is actually guilty.  So the main pressure on legal standards is that officially-accepted evidence seem to the public, juries, and judges to indicate guilt, not that it actually indicate guilt.  We expect the law to be overconfident about its evidence.

Requiring that legal evidence standards stand up to independent experimental scrutiny would create a more accurate legal system, but at the expense of reducing the apparent rate at which the guilty are punished.  So I expect, sadly, this proposal to be rejected.

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Future Discounts

In few billion years our descendants may spread across billions of galaxies. Even so, if they do not drastically change the structure of space-time, then within a trillion years they will fragment into billions of isolated galaxy-sized “universes”.  Standard physics, you see, says that in a trillion or two years all the galaxies near the Milky Way will merge into one big galaxy, and other galaxies will be too distant to see in any way.  For all practical purposes, that merged galaxy will be a separate universe.

If we do nothing to change the situation, then within ten or so trillion years, all current stars will be dead (degenerate), and no more stars will form.  Over the next billion trillion years, stars will occasionally smash in a flash, or pass close enough to each other to throw one out of the galaxy; in the end 1-10% remain in a central black hole.

What if we change the situation?  Most useful resources, such as hydrogen to turn into lead, or mass not yet dropped into the central black hole, will likely be identified and claimed within a few million years.  How fast will folks use up these resources?

In principle, most everything might be burned quickly in a few million years of party-hardy gluttony, or most might be saved to use steadily over the billion trillion trillion years or more before protons decay.  How fast resources are actually used would be determined by the discount factors of the creatures who control resources.  But what would those be?

If unused resources were completely stable and if property rights in resources were completely secure, then we’d mainly have a selection effect in discount rates.  Agents who discount fast would dominate early activity, while those who discount slowly would dominate late activity.  Even if initially only a tiny fraction of agents cared about activity in a billion trillion trillion years, those agents would dominate such late activity.

Any natural rate at which resources decay would set an upper limit on discounting.  There is no point in planning to use resources long after you expect them to decay.  Similarly, insecure property rights would increase discount rates. If you expect a 1% chance that your property will be stolen every million years, you won’t expect to still have much after a billion years, so you might as well plan to use most of it before then.   The same holds if your property is never stolen, but you have to spend 1% of your resources every million years to ensure that fact.

“Switzerlands,” from which theft is naturally harder, might be the last locations of activity in each galaxy.  These might be matter sent on very long secret orbits, to return back to galaxy central after a very long time.  Similarly, resources which simply could not be physically used until a long delay might ensure some late universe activity.

The inhabitants of a galaxy-universe could have different degrees of central coordination; some might have a strong central government, while others lived in anarchy.  With a strong central government, long term activity seems strongly influenced by the discount rate of that government. If this government taxed 1% of resources every million years, and didn’t invest those resources for the long run, then there would be little point in planning to use your resources after a billion years.  No obvious selection effect ensures that galaxy governments take a long view.

Physics may set the ultimate limits on how long resources, and life, can last, but governments and property rights will determine when they are actually used. Resources, and life, will likely die long before their physical expiration dates.

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Twin Conspiracies

In a twin conspiracy, a pair of identical twins would pretend to be only one person. For example, in college each twin could specialize in, and then ace, half of the classes; their GPA would soar.  They might together make partner in a law firm by handling a lot more work than other lawyers.  They could cheat on their spouse while offering that spouse a near-constant video of “their” activities.  In fact, they could always have an alibi for anything they did.

This strategy seems tempting in “winner take all” areas of life where small productive gains are given huge rewards, or where secretly having more time can make you seem a lot more productive.  For example, high level managers attend a great many meetings to connect different parts of their organization.  A secretly-twin-CEO could attend twice as many meetings, and make twice the connections.

Of course if this actually happened often our institutions could easily adapt to check for secret twin conspiracies.  They don’t now look because they don’t expect them.  It would be interesting to search for such secret twins.  For example, one might take a list of top CEOs and compare the ratio of non-identical to identical twins in this group. If that ratio was substantially larger than in the larger population, that might suggests many secret twins hiding among CEOs.

One twin told me the loss of autonomy in this secret twin scenario would make it unacceptable to her, no matter what worldly success it produced.   Do people really care that much more about autonomy than success?

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Stop Stale Eggs, Jobs?

Some men see things as they are and ask why. Others dream things that never were and ask why not. Shaw

The average woman is born with around 300,000 eggs … 12 percent of those eggs remaining at the age of 30, and only 3 percent left by 40. … From the mid-30s on, the decline in fertility is much steeper with each passing year. … Female undergraduates significantly overestimated their fertility prospects at all ages. … The biological reality that female fertility peaks in the teens and early 20s can be difficult for many American women to swallow, as they delay childbirth further every year. … The older you get, the more difficult it is to get pregnant and the higher the chance of miscarriage, pregnancy problems such as gestational diabetes and hypertension, and chromosomal abnormalities such as Down syndrome. … The risk of autism increases with a mother’s age.

More here.  Also, Andrew Leigh:

We estimate the relationship between maternal age and child … learning outcomes and social outcomes. … Children of older mothers have better outcomes. … When we control for other socioeconomic characteristics, such as family income, parental education and single parenthood, the coefficients on maternal age become small and statistically insignificant.

Today high status women stay long in school, start careers, and take long to match up with a man before having kids.  They are often too late, their kids have more defects, and the interruption hurts their career.  Low status women more often have an accidental early kid out of wedlock.

Imagine a different equilibrium, where females pick a male at 15, then school more slowly to have kids till some standard age (20? 25? 30?), when females return to full-time school and uninterrupted careers.

While it is not entirely clear if this new equilibrium would be better or worse, it certainly has some positive features.  Kids and moms would be healthier, kids more numerous and less accidental, moms more energetic, older folk would enjoy more grand kids etc., and career interruptions wouldn’t make female employees suspect.

Early parenting would have to be paid for by grandparents or via loans (or perhaps income shares), presumably in trade for some loss of autonomy.  While childhood does seem to be lengthening, it is not clear if this autonomy loss could be accepted.

For the male pattern, there are two obvious variations: males switch life-plans along with females, or males stay on the current plan.  Having males also switch would keep mates at similar ages, promote healthier kids and more energetic dads, and reduce opportunities for gender discrimination.

Randomness in kid timing and number would make it a bit harder to estimate student quality based on student performance – could we find ways to correct for this?  And the fact that low status moms now have kids early makes it harder to coordinate a switch to this new equilibrium.  But still, it seems an interesting thing that never was, about which to ask: why not?

From a conversation with Rob Wiblin, Katja Grace.

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Efficiency Disclaimers

Though I generally avoid disclaimers, since Bryan Caplan calls my latest claim that econ efficiency is a good tool for finding win-win deals “complete nonsense,” let me try to clarify:

  • We have many purposes when we talk about “what to do”, and making deals is only one of our purposes.
  • Getting what we want is only one of many reasons we try to achieve deals; we also want to signal our features, for example.
  • Analysis aids are only one of many sorts of aids that can help us to make deals; aids can also to organize negotiations, enforce deals, etc.
  • Most useful deal aids are relatively specific to a particular context, such as real estate sales, or marriages; when available, more specific tools tend to be more useful.
  • Deal aids can specialize in what groups that they best assist.  A particular aid might be best suited for couples, club, firms, or nations.  Wider aids specialize in assisting larger groups.

Economic efficiency is our best wide general analysis tool for finding win-win deals that get people what they want.  That isn’t everything, but it is a lot.  I’m glad I mastered this tool and am eager to apply it.  Efficiency can:

  • Suggest Deals – Efficiency analysis suggests policies to make “the biggest pie.” A deal also needs folks to agree on a way to divide the pie, such as via cash transfers between the parties.  Even so, knowing better ways to make bigger pies should make parties more eager to agree to deals to lock in such gains.
  • Be Part Of A Deal –  Groups can make explicit deals to adopt the results of efficiency analysis.  For example, legal systems can adopt a general accident rule that puts responsibility on the least cost accident avoider, and government agencies can be instructed to make policy decisions on a cost-benefit basis.  Most can reasonably expect to gain from such policies, even if they do not expect to gain from each particular application.

Admittedly:

  • Efficiency analysis is a rough guide, and does not determine exact implications with certainty for each possible situation.
  • The policies efficiency recommends depend on particular modeling assumptions and parameter estimates, for example, and those depend on particular analysts and sources used.
  • Even when negotiators have access to solid analyses, deals can fail for many other reasons; good analysis doesn’t ensure good deals.
  • Most deals are not between all possible parties, and each deal may well disadvantage those not included in the deal.
  • People may expect to gain from a deal, but end up not actually benefiting.
  • As a wide general tool, efficiency is less useful for small deals or for contexts where specialized tools are available.
  • Efficient deals may well be immoral, or unattractive for other purposes of deal-making, or of “what to do” talking.

Few deals can guarantee to get everyone more of what they want, but by encouraging and enabling more better wider deals, the use of efficiency analysis sure seems to me to tend to get most everyone more of what they want.  Isn’t that good enough?

OK, now that I’ve tried this exercise of explicitly listing many possible disclaimers, when is this sort of exercise actually worth the effort?

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