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Slide 1: Psychology and Neuroscience Magazine Issue No. 1 February 2009 One is only micrometers wide. The other is billions of light years across. One shows neurons in a mouse brain. The other is a simulated image of the universe. Together they suggest the unsurprisingly similar patterns found in vastly different natural phenomena. Contents Page No Neuroscience: Socioeconomic status and brain differences between poor and rich kids ………. 2 Darwinism: Why we are, as we are ………………………………………………………………………………………….. 6 Neuroscience: Hijacking the brain circuits with a nickel slot machine …………………………………….15 Animal Behaviour: Swarm theory …………………………………………………………………………………………….18 Humour: They’re made out of meat …………………………………………………………………………………………..26 Book Review: Born to rebel ……………………………………………………………………………………………………….28 Economics: Paul Krugman and his four rules of research ………………………………………………………..34 0
Slide 2: Editor’s Note Welcome to the first issue of Brain Maya. This magazine consists of a collection of various articles from various sources and has been published with the intention of increasing public awareness and education about developments in psychology, neuroscience and related fields. If you would like to contribute articles or have something to say you can contact the editor at brainmaya@gmail.com Cover Image (Left Image) Mark Miller, a doctoral student at Brandeis University, is researching how particular types of neurons in the brain are connected to one another. By staining thin slices of a mouse's brain, he can identify the connections visually. The image above shows three neuron cells on the left (two red and one yellow) and their connections. (Right Image) An international group of astrophysicists used a computer simulation last year to recreate how the universe grew and evolved. The simulation image above is a snapshot of the present universe that features a large cluster of galaxies (bright yellow) surrounded by thousands of stars, galaxies and dark matter (web). (Source by Mark Miller, Brandeis University; Virgo Consortium for Cosmological Supercomputer Simulations; www.visualcomplexity.com) 1
Slide 3: Neuroscience Socioeconomic status and brain differences between poor and rich kids BERKELEY — University of California, Berkeley, researchers have shown for the first time that the brains of low-income children function differently from the brains of high-income kids. In a study recently accepted for publication by the Journal of Cognitive Neuroscience, scientists at UC Berkeley's Helen Wills Neuroscience Institute and the School of Public Health report that normal 9- and 10year-olds differing only in socioeconomic status have detectable differences in the response of their prefrontal cortex, the part of the brain that is critical for problem solving and creativity. "Kids from lower socioeconomic levels show brain physiology patterns similar to someone who actually had damage in the frontal lobe as an adult," said Robert Knight, director of the institute and a UC Berkeley professor of psychology. "We found that kids are more likely to have a low response if they have low socioeconomic status, though not everyone who is poor has low frontal lobe response." Previous studies have shown a possible link between frontal lobe function and behavioral differences in children from low and high socioeconomic levels, but according to cognitive psychologist Mark Kishiyama, first author of the new paper, "those studies were only indirect measures of brain function and could not disentangle the effects of intelligence, language proficiency and other factors that tend to be associated with low socioeconomic status. Our study is the first with direct measure of brain activity where there is no issue of task complexity." Co-author W. Thomas Boyce, UC Berkeley professor emeritus of public health who currently is the British Columbia Leadership Chair of Child Development at the University of British Columbia (UBC), is not surprised by the results. "We know kids growing up in resource-poor environments have more trouble with the kinds of behavioral control that the prefrontal cortex is involved in regulating. But the fact that we see functional differences in prefrontal cortex response in lower socioeconomic status kids is definitive." Electroencephalography, or EEG, uses electrodes on the scalp and held in place by a cap to measure underlying brain activity. (Lee Michael Perry/UC Berkeley) Brain function was measured by means of an electroencephalograph (EEG) - basically, a cap fitted with electrodes to measure electrical activity in the brain - like that used to assess epilepsy, sleep disorders and brain tumors. Boyce, a pediatrician and developmental psychobiologist, heads a joint UC Berkeley/UBC research program called WINKS - Wellness in Kids - that looks at how the disadvantages of growing up in low socioeconomic circumstances change children's basic neural development over the first several years of life. "This is a wake-up call," Knight said. "It's not just that these kids are poor and more likely to have health problems, but they might actually not be getting full 2
Slide 4: brain development from the stressful and relatively impoverished environment associated with low socioeconomic status: fewer books, less reading, fewer games, fewer visits to museums." Kishiyama, Knight and Boyce suspect that the brain differences can be eliminated by proper training. They are collaborating with UC Berkeley neuroscientists who use games to improve the prefrontal cortex function, and thus the reasoning ability, of school-age children. "It's not a life sentence," Knight emphasized. "We think that with proper intervention and training, you could get improvement in both behavioral and physiological indices." The subjects were instructed to click a button when a slightly skewed triangle flashed on the screen. The researchers were interested in the brain's very early response - within as little as 200 milliseconds, or a fifth of a second after a novel picture was flashed on the screen, such as a photo of a puppy or of Mickey and Minnie Mouse. "An EEG allows us to measure very fast brain responses with millisecond accuracy," Kishiyama said. The researchers discovered a dramatic difference in the response of the prefrontal cortex not only when an unexpected image flashed on the screen, but also when children were merely watching the upright triangles waiting for a skewed triangle to appear. Those from low socioeconomic environments showed a lower response to the unexpected novel stimuli in the prefrontal cortex that was similar, Kishiyama said, to the response of people who have had a portion of their frontal lobe destroyed by a stroke. "When paying attention to the triangles, the prefrontal cortex helps you process the visual stimuli better. And the prefrontal cortex is even more involved in detecting novelty, like the unexpected photographs," he said. But in both cases, "the low socioeconomic kids were not detecting or processing the visual stimuli as well. They were not getting that extra boost from the prefrontal cortex." "These kids have no neural damage, no prenatal exposure to drugs and alcohol, no neurological damage," Kishiyama said. "Yet, the prefrontal cortex is not functioning as efficiently as it should be. This difference may manifest itself in problem solving and school performance." The researchers suspect that stressful environments and cognitive impoverishment are to blame, since in animals, stress and environmental deprivation have been shown 3 Children of high socioeconomic status (SES) show more activity (dark green) in the prefrontal cortex (top) than do kids of low SES when confronted with a novel or unexpected stimulus. (Mark Kishiyama/UC Berkeley) Kishiyama, Knight, Boyce and their colleagues selected 26 children ages 9 and 10 from a group of children in the WINKS study. Half were from families with low incomes and half from families with high incomes. For each child, the researchers measured brain activity while he or she was engaged in a simple task: watching a sequence of triangles projected on a screen.
Slide 5: to affect the prefrontal cortex. UC Berkeley's Marian Diamond, professor of integrative biology, showed nearly 20 years ago in rats that enrichment thickens the cerebral cortex as it improves test performance. And as Boyce noted, previous studies have shown that children from poor families hear 30 million fewer words by the time they are four than do kids from middle-class families. "In work that we and others have done, it really looks like something as simple and easily done as talking to your kids" can boost prefrontal cortex performance, Boyce said. "We are certainly not blaming lower socioeconomic families for not talking to their kids - there are probably a zillion reasons why that happens," he said. "But changing developmental outcomes might involve something as accessible as helping parents to understand that it is important that kids sit down to dinner with their parents, and that over the course of that dinner it would be good for there to be a conversation and people saying things to each other." "The study is suggestive and a little bit frightening that environmental conditions have such a strong impact on brain development," said Silvia Bunge, UC Berkeley assistant professor of psychology who is leading the intervention studies on prefrontal cortex development in teenagers by using functional magnetic resonance imaging (fMRI). Boyce's UBC colleague, Adele Diamond, showed last year that 5- and 6-year-olds with impaired executive functioning, that is, poor problem solving and reasoning abilities, can improve their academic performance with the help of special activities, including dramatic play. Bunge hopes that, with fMRI, she can show improvements in academic performance as a result of these games, actually boosting the activity of the prefrontal cortex. "People have tried for a long time to train reasoning, largely unsuccessfully," Bunge said. "Our question is, 'Can we replicate these initial findings and at the same time give kids the tools to succeed?'" Berkerly http://www.berkeley.edu/news/media/releas es/2008/12/02_cortex.shtml Poor Kids Hear 30 Million Fewer Words by Time they Reach 4 Years UC Berkeley's Marian Diamond professor emeritus of integrative biology, showed nearly 20 years ago in rats that enrichment thickens the cerebral cortex as it improves test performance. And as Boyce noted, previous studies have shown that children from poor families hear 30 million fewer words by the time they are four than do kids from middle-class families. "In work that we and others have done, it really looks like something as simple and easily done as talking to your kids" can boost prefrontal cortex performance, Boyce said. The outer layer of grey matter, approximately 2 mm thick, covering the entire surface of the cerebral hemispheres. The cerebral cortex is made up of neuron and supporting cells (glial cells) and functions to correlate information from many sources to maintain cognitive function (all aspects of perceiving, thinking and remembering). 4
Slide 6: "We are certainly not blaming lower socioeconomic families for not talking to their kids - there are probably a zillion reasons why that happens," he said. "But changing developmental outcomes might involve something as accessible as helping parents to understand that it is important that kids sit down to dinner with their parents, and that over the course of that dinner it would be good for there to be a conversation and people saying things to each other.". Boyce's Cal colleague, Adele Diamond, showed last year that 5- and 6-year-olds with impaired executive functioning, that is, poor problem solving and reasoning abilities, can improve their academic performance with the help of special activities, including dramatic play. Bunge hopes that she can show improvements in academic performance as a result of these games, actually boosting the activity of the prefrontal cortex. 5
Slide 7: Darwinism Why we are, as we are As the 150th anniversary of the publication of “On The Origin of Species” approaches, the moment has come to ask how Darwin’s insights can be used profitably by policymakers Charles Darwin(12 February 1809 – 19 April 1882) get to the nitty-gritty of what it truly is to be human. Policy based on them does not work. This is because they ignore the forces that made people what they are: the forces of evolution. The reasons for that ignorance are complex. Philosophers have preached that there exists between man and beast an unbridgeable distinction. Sociologists have been seduced by Marxist ideas about the perfectibility of mankind. Theologians have feared that the very thought of evolution threatens divine explanations of the world. Even fully paid-up members of the Enlightenment, people who would not for a moment deny humanity’s simian ancestry, are often sceptical. They seem to believe, as Anne Campbell, a psychologist at Durham University, in England, elegantly puts it, that evolution stops at the neck: that human anatomy evolved, but human behaviour is culturally determined. The corollary to this is the idea that with appropriate education, indoctrination, social conditioning or what have you, people can be made to behave in almost any way imaginable. The evidence, however, is that they cannot. The room for shaping their behaviour is actually quite limited. Unless that is realised, and the underlying biology of the behaviour to be shaped is properly understood, attempts to manipulate it are likely to fail. Unfortunately, even as the 150th anniversary of Darwin’s masterwork, “On The Origin of Species”, approaches (it was published in 1859) that fact has not been properly accepted. Time, then, to see what a Darwinian analysis has to offer the hardpressed policymaker, and whether it can make a practical difference to outcomes. Mencken’s observation neatly explains two aspects of modern life. One is the openendedness of economic growth. The other is that no matter how rich your country becomes, the poor you will always have with you. But what explains Mencken’s observation? WEALTH, according to H.L. Mencken, an American satirist of the last century, “is any income that is at least $100 more a year than the income of one’s wife’s sister’s husband.” Adjusted for inflation since 1949, that is not a bad definition. But why do those who are already well-off feel the need to out-earn other people? And why, contrariwise, is it so hard to abolish poverty? America, Mencken’s homeland, executes around 40 people a year for murder. Yet it still has a high murder rate. Why do people murder each other when they are almost always caught and may, in America at least, be killed themselves as a result? Why, after 80 years of votes for women, and 40 years of the feminist revolution, do men still earn larger incomes? And why do so many people hate others merely for having different coloured skin? Traditionally, the answers to such questions, and many others about modern life, have been sought in philosophy, sociology, even religion. But the answers that have come back are generally unsatisfying. They describe, rather than explain. They do not 6
Slide 8: For a Darwinian, life is about two things: survival and reproduction. Of the two, the second is the more significant. To put it crudely, the only Darwinian point of survival is reproduction. As a consequence, much of daily existence is about showing off, subtly or starkly, in ways that attract members of the opposite sex and intimidate those of the same sex. In humans—unlike, say, peafowl, where only the cocks have the flashy tails, or deer, where only the stags have the chunky antlers—both sexes engage in this. Men do it more than women, but you need look no further than Ascot race course on Gold Cup day to see that women do it too. Status and hierarchy matter. And in modern society, status is mediated by money. Girls have always liked a rich man, of course. Darwinians used to think this was due to his ability to provide materially for their children. No doubt that is part of it. But the thinking among evolutionary biologists these days is that what is mainly going on is a competition for genes, not goods. Highstatus individuals are more likely to have genes that promote health and intelligence, and members of the opposite sex have been honed by evolution to respond accordingly. A high-status man will get more opportunities to mate. A high-status woman can be more choosy about whom she mates with. Life is about survival and reproduction For men, at least, this is demonstrably true. Evolutionary biologists are fond of quoting extreme examples to make the point, the most famous being Moulay Ismail the Bloodthirsty, a Moroccan ruler who fathered over 1,000 children. But kings have powers of coercion. Some better examples are provided by Joe Studwell, in his book “Asian Godfathers”, which dissects the lives of businessmen. Stanley Ho, a veteran operator in Hong Kong and Macau, has 17 children by several women. Oei Tiong Ham, a tycoon who died in 1924, had 18 concubines and 42 children. The relationship holds good further down the social ladder. Danile Nettle and Thomas Pollet, of Newcastle University, recently showed that in Britain the number of children a man has fathered is, on average, related to his income, the spread of modern contraception notwithstanding. Status, though, is always relative: it is linked to money because it drives the desire to make more of the stuff in order to outdo the competition. This is the ultimate engine of economic growth. Since status is a moving target, there is no such thing as enough money. The relative nature of status explains the paradox observed in 1974 by an economist called Richard Easterlin that, while rich people are happier than poor people within a country, average happiness does not increase as that country gets richer. This has been disputed recently. But if it withstands scrutiny it means the free-market argument—that because economic growth makes everybody better off, it does not matter that some are more better off than others—does not stand up, at least if “better off” is measured in terms of happiness. What actually matters, Darwinism suggests, is that a free society allows people to rise through the hierarchy by their own efforts: the American dream, if you like. Conversely, the Darwinian explanation of continued support for socialism—in the teeth of evidence that it results in low economic 7 The book that turns 150 this year.
Slide 9: growth—is that even though making the rich poorer would not make the poor richer in financial terms, it would change the hierarchy in ways that people at the bottom would like. When researchers ask people whether they would rather be relatively richer than their peers even if that means they are absolutely worse off, the answer is yes. (Would you rather earn $100,000 when all your friends earn $50,000, or $150,000 when everybody else earns $300,000?) The reason socialism does not work in practice is that this is not a question that most people ask themselves. What they ask is how to earn $300,000 when all around them people are earning $50,000. A Darwinian analysis does, however, support one argument frequently made by the left and pooh-poohed by the right. This is that poverty is relative. The starkest demonstration of this, discovered by Richard Wilkinson of Nottingham University, in England, is that once economic growth has lifted a country out of penury, its inhabitants are likely to live longer, healthier lives if there are not huge differences between their incomes. This means that poorer countries with low income-variation can outscore richer ones with high variation. It is also true, as was first demonstrated by Michael Marmot, of University College, London, that those at the bottom of social hierarchies have worse health than those at the top— even when all other variables are statistically eliminated, including the fact that those who are healthier are more likely to rise to the top in the first place. In the 1970s, when Dr Marmot made this observation, expert opinion predicted the opposite. Executives were expected to suffer worse stress than groundlings, and this was expected to show up as heart attacks, strokes and so forth. In fact, the opposite is true. It is the Darwinian failure of being at the bottom of the heap that is truly stressful and bad for the health. That, writ large, probably explains the mortality patterns of entire countries. In this case, therefore, the Darwinian conclusion is that there is no right answer— or at least no Utopian one. Of course, it does not take a Darwinist to work out that any competition has losers. The illuminating point is that losing has a real cost, not just the absence of gain. With the stakes this high—early death for the failures and genetic continuity for the successes—it is hardly surprising that those at the bottom of the heap sometimes seek status, or at least “respect”, in other ways. This is a point that should be taken seriously by policymakers. For those “other ways” are also explicable by Darwinism. That crime is selfish is hardly news. But the idea that criminal behaviour is an evolved response to circumstances sounds shocking. It calls into question the moral explanation that crime is done by “bad people”. Yet that explanation is itself susceptible to Darwinian analysis: evolution probably explains why certain behaviours are deemed worthy of punishment. The study of the evolutionary roots of crime began with the work of Martin Daly and Margo Wilson, a married couple who work at McMaster University in Canada. They looked at what is usually regarded as the most serious crime of all, murder. That murderers are usually young men is well known, but Dr Daly and Dr Wilson dug a bit deeper. They discovered that although the murder rate varies from place to place, the pattern does not. Plot the rate against the age of the perpetrator and the peak is the same (see chart next page). 8
Slide 10: low status. A woman will rarely have difficulty finding a mate, even if he does not measure up to all her lofty ideals. In the world of Moulay Ismail the Bloodthirsty, however, a low-status man may be cast on the reproductive scrap heap because there are no women available to him at all. Though the world in which humanity evolved was nowhere near as polygamous as Moulay Ismail’s, neither did it resemble the modern one of monogamous marriage, which distributes women widely. In those circumstances, if the alternative was reproductive failure, risking the consequences of violence may have been are worth the gamble—and instincts will have evolved accordingly. Moreover, the pattern of the victims is similar. They, too, are mostly young men. In the original study, 86% of the victims of male killers aged between 15 and 19 were also male. This is the clue as to what is going on. Most violence (and thus most murder, which is simply violence’s most extreme expression) is a consequence of competition between young, unemployed, unmarried men. In the view of Darwinists, these men are either competing for women directly (“You looking at my girl, Jimmy?”) or competing for status (“You dissing me, man?”). This is not to deny that crimes of violence are often crimes of poverty (for which read low status). But that is precisely what Darwinism would predict. There is no need to invoke the idea that people are “born criminal”. All that is required is the evolution of enough behavioural flexibility to respond appropriately when violence is (or would have been, in the evolutionary past) an appropriate response. For similar reasons, it is no surprise to Darwinists that those who rape strangers are also men of low status. Oddly, considering it is an act that might result in a child, the idea that rape is an evolved behaviour is even more controversial than the Darwinian explanation of murder. Randy Thornhill of the University of New Mexico, who proposed it on the basis of criminal data and by comparing people with other species, was excoriated by feminists who felt he was somehow excusing the crime. On the other hand, it has become a mantra among some feminists that all men are rapists, which sounds a lot like the opposite point of view: biological determinism. Insert the word “potential”, however, and this claim is probably true. To a Darwinist, the most common form of forced mating, so-called date rape, which occurs in an already charged sexual environment, looks a lot like an adaptive response. Men who engage in it are likely to have more offspring than those who do not. If a genetic disposition for men to force their attentions on women in this way does exist, it would inevitably spread. Sexual success, by contrast, tends to dampen criminal behaviour down. Getting married and having children—in other words, achieving at least part of his Darwinian ambition—often 9 Crime… An evolutionary analysis explains many things about crime (and not just murder)— particularly why most criminals are males of
Slide 11: terminates a criminal’s career. Again, that is a commonplace observation. However, it tends to be explained as “the calming influence of marriage”, which is not really an explanation at all. “Ambition fulfilled” is a better one. The murder of children, too, can be explained evolutionarily. On the face of things it makes no sense to kill the vessels carrying your genes into the next generation. And, indeed, that is not what usually happens. But sociologists failed to notice this. It was not until Dr Daly and Dr Wilson began researching the field that it was discovered that a child under five is many times more likely to die an unnatural death in a household with a stepfather present (whether or not that relationship has been formalised by law) than if only biological parents are there. In this, humans follow a pattern that is widespread in mammals: male hostility to a female’s offspring from previous matings. In some species, such as lions and langurs, this results in deliberate infanticide. In humans things not are always as brutal and explicit. But neglect and a low threshold of irritation at the demands of a dependent non-relative can have the same effect. Intriguingly, though, if a genetic parent is the killer it is often the mother. Infanticidal mothers are usually young. A young mother has many years of potential reproduction ahead of her. If circumstances do not favour her at the time (perhaps the father has deserted her) the cost to her total reproductive output of bringing up a child may exceed the risk of killing it. Not surprisingly, maternal infanticide is mainly a crime of poor, single women. Many people might sympathise with those driven to commit this particular form of homicide. But in general crimes such as murder and rape provoke a desire to punish the perpetrators, not to forgive them. That, too, is probably an evolved response—and it may well be a uniquely human one. No court sits in judgment over a drake who has raped 10 a duck. A lioness may try to defend her cubs against infanticide, but if she fails she does not plan vengeance against the male who did it. Instead, she usually has sex with him. Yet ideas of revenge and punishment lie deep in the human psyche. …and punishment Economists were long puzzled, for example, by the routine outcome of a game in which one player divides a sum of money between himself and a competitor, who then decides whether the shares are fair. If the second player decides the shares are not fair, neither player gets anything. What is curious about this game is that, in order to punish the first player for his selfishness, the second player has deliberately made himself worse off by not accepting the offer. Many evolutionary biologists feel that the sense of justice this illustrates, and the willingness of one player to punish the other, even at a cost to himself, are among the things that have allowed humans to become such a successful, collaborative species. In the small social world in which humans evolved, people dealt with the same neighbours over and over again. Punishing a cheat has desirable long-term consequences for the person doing the punishing, as well as for the wider group. In future, the cheat will either not deal with him or will do so more honestly. Evolution will favour the development of emotions that make such reactions automatic. What goes for cheating goes for other bad behaviour, up to and including the murder of relatives and friends. Moreover, if publicly observed, punishment sends the same message to those who might be considering a similar course of action. It is therefore one of the marvels of civilisation that punishment and revenge have, for the most part, been institutionalised. But to be successful, the institutionalised punishment has to be seen as a proper outcome by the individuals who
Slide 12: were harmed. Otherwise, they might mete out their own revenge. That may worry those who believe that reforming the criminal should be the main goal of sentencing policy. If people no longer believe that the punishment fits the crime, a Darwinian would predict that they will stop supporting the criminal-justice system. Even deterrence, however, does not always work. On the face of things, capital punishment ought to be the ultimate deterrent. But it does not seem to be. Satoshi Kanazawa, an evolutionary psychologist at the London School of Economics, suggests that this is further evidence of the reproduction-related nature of murder. Since failure to reproduce is a Darwinian dead-end anyway, risking death to avoid that fate—or, rather, being impelled to do so in the heat of the moment by an evolved instinct—is not as stupid as it looks. Some sorts of murder might be discouraged by the threat of the noose or the needle. But not the most common sort: young man on young man over status and sex. A woman’s place Crime, then, is one field in which women are unequal with men. That does not bother feminists, but perhaps it should. For it might reflect a wider truth which those who believe that the sexes should not merely have equal rights but enjoy equal outcomes will find uncomfortable. When outcomes are unequal in socially acceptable areas of behaviour, such as employment, it is often interpreted as a sign of discrimination. But people who draw this conclusion rarely consider that the discrimination in question might actually be being exercised by the supposedly disadvantaged women themselves. A classic example is income. Women earn less than men. Or do they? In fact, younger women do not, or not much. A recent report by the Institute of Economic Affairs (IEA), a British think-tank, found that British women aged between 22 and 29 who were in full11 time employment earned only 1% less than their male counterparts. This age group corresponds for many women to the period when they are single. Once they have found the best available mate, the calculation changes: a woman no longer needs to show off. In that context, it is less of a surprise that older women are out-earned by their male contemporaries. One reason is that they now care less about the size of their earnings. Of the top 25 ideal employers, as chosen by women, the IEA found that 12 were in the public or voluntary sectors—areas where salaries for equivalent work tend to be lower than in the private sector, though job security is higher and job satisfaction is often believed to be greater. For men, only four employers were in this category. The other reason, of course, is that women usually look after the children. Indeed, the study by Dr Nettle and Dr Pollet which found that reproductive success correlates with men’s income, also points out that with women the correlation is inverted. But the IEA study also found that it is women themselves who are taking the decisions about child care. It reports that two-thirds of the women who had not already had a “career break”, as it is euphemistically known, planned to take one at some point in the future. Less than an eighth of men had similar aspirations. That, too, would be predicted by a Darwinist. Although there is a strong argument for making working conditions more sympathetic to the needs of parents of both sexes, the underlying point is that many women—and
Slide 13: certainly many women with children—do not care as much about striving ahead in their careers as men do. Men, the report found, are more motivated by pay and less by job satisfaction than women are. If managers, they are more likely to work long hours. They also take more risks—or, at least, are more frequently injured at work. The consequence, as Len Shackleton, the IEA report’s main author, puts it, is that: “The widespread belief that the gender pay gap is a reflection of deep-rooted discrimination by employers is ill-informed and an unhelpful contribution to the debate. The pay gap is falling but is also a reflection of individuals’ lifestyle preferences. Government can’t regulate or legislate these away, and shouldn’t try to.” He failed to add, however, that these preferences are often the result of biological differences between the sexes. What goes for pay probably goes for career choice as well. At one extreme, it is foolish, as Kingsley Browne of Wayne State University, in Michigan, suggests, to expect equal outcomes in organisations like the armed forces. Not only are men stronger and more aggressive but, Mr Browne suggests, the psychology of both sexes has evolved to trust men (and not trust women) in combat, precisely because of this aggression and strength. At the other end of the scale, it is probably an opposite mixture of evolved aptitudes and attitudes that causes the domination by females of professions such as nursing. This is not to say there can be no good female soldiers or male nurses. Patently, there can. But it is not clear evidence of discrimination that they are rarer than their counterparts of the opposite sex. A Darwinian analysis of the matter cannot say where the equilibrium would lie in a world free from discrimination. But it can say with reasonable confidence that this equilibrium will often not be 50/50. Many may harrumph at such a Darwinian interpretation of feminism, and say that it is 12 a circuitous route to a traditional destination. It isn’t: not expecting an equal distribution of the sexes within every profession is not the same as saying that a woman’s place is in the home. And having dared to question the assumptions of both feminists and their opponents, some evolutionary biologists are now hoping to turn conventional wisdom upside down in another area where civil rights meet long-standing prejudice. This is the vexed question of race. Race to the finish Racial difference is an area where modern Darwinists have feared, until recently, to tread. This is hardly surprising, given the topic’s history. Many early evolutionary biologists (though not Darwin himself) thought that just as man was a risen ape, so white, European man was the zenith of humanity, and that people from other parts of the world were necessarily inferior. The consequences of that have been terrible. It gave a veneer of intellectual respectability to the eugenic horrors which culminated in the Nazi death camps. Indeed, it is probably one of the roots of the “evolution stops at the neck” point of view. But evolutionary biology is now making amends. By overturning understanding of what race actually is, it may yet provide the tools that allow people of different backgrounds to live in reasonable harmony. Revenge and punishment lie deep in the human psyche Its first observation is a bleak one. This is that racism, or at least xenophobia, is a deeply ingrained human characteristic. But its second observation is that, so far as can be determined, the traditional definition of race—the tendency of people living in different parts of the world to have different skin colour, hair colour and physiognomy— has no wider ramifications in areas such as intelligence. Racial prejudice, then, is just
Slide 14: that: prejudice. Though an individual might reasonably be expected to know many members of his tribe personally, he would probably not know them all. There would thus be a biological advantage in tribal branding, as it were. Potential allies would quickly identify what marked them out from others, and what marked others out from them—and, because those differences would probably be small, the detector would need to be very sensitive. In the past, such markers would often have been cultural, since local physical differences would have been minimal. A telling instance is recorded in the Bible: Then said they unto him, Say now Shibboleth: and he said Sibboleth: for he could not frame to pronounce it right. Then they took him and slew him. The questioners were the Gileadites. The slain, an Ephraimite. But no physical difference could distinguish the tribes, so the Gileadite ethnic-cleansers had to rely on linguistic tics. In a world where a syllable can get you killed, having differently coloured skin is a pretty strong brand of identity. However, it is not a unique signal. Experiments that Dr Cosmides, Dr Tooby and their students have conducted in both America and Brazil (another racially mixed country) suggest it is surprisingly easy to rebrand even people of different skin colour by making other badges of allegiance more significant—as happens when sportsmen clothe themselves in coloured team shirts. Moreover, Andrew Penner of the University of California, Irvine, and Aliya Saperstein of the University of Oregon have shown that perception of a person’s race can actually change in the real world. Many people shift from being “white” to “black”, in both their own eyes and the eyes of others, in response to unemployment, impoverishment or imprisonment. That is an uncomfortable reminder of the way group solidarity works in America. The hope this analysis brings, though, is that 13 What is being proposed instead, by another husband and wife team of Darwinists, Leda Cosmides and John Tooby of the University of California, Santa Barbara, is a theory of ethnicity that explains the mishmash of categories anthropologists have tried to shoehorn into the general class of “race”. Are Jews and Sikhs, who are defined by religious exclusivity, races? Are Serbs and Croats, who share their religions with others, but not with each other, and whom no geneticist could tell apart? These examples, and similar ones, argue that race has no biological meaning. But it does. It is just not the traditional meaning. Social psychologists have long observed that, on first meeting, people automatically classify each other in three ways: by sex, by age and by race. But Dr Cosmides and Dr Tooby pointed out that before long-distance transport existed, only two of those would have been relevant. People of different ages and sexes would meet; people of different races would not. The two researchers argue that modern racial discrimination is an overstimulated response to what might be called an “alliance” detector in the human brain. In a world where the largest social unit is the tribe, clan or what-you-will of a few hundred people, your neighbours and your other allies will normally look a lot like you, and act similarly. However, it is known from the study of modern hunter-gatherers, and inferred from archaeological evidence about ancient ones, that neighbouring tribes are often hostile.
Slide 15: there is nothing particularly special about biologically based brands such as skin colour. If other brands of group membership can be strengthened, the traditional ones may diminish, even if they do not disappear completely. If this theory of race is correct (and more research is certainly needed), it indicates a strong prescription: policies that encourage groups to retain their identity within a society will cause trouble, but those that encourage cultural integration will smooth things over. In practice, the history of that most racially mixed country of all, the United States, supports this idea. When integration has been encouraged, as with the descendants of the great flood of European immigrants in the late 19th and early 20th centuries, ethnic distinctions have vanished. When integration has been discouraged, as with the descendants of slaves liberated shortly before those European immigrants arrived, differences have been sharpened. Even in Britain, official policy seems to be shifting from “multiculturalism”, which celebrated diversity and thus encouraged distinction, to a deliberate attempt to forge a cultural consensus. What the brand theory of ethnicity does not require, however, is that minorities submit to the majority’s definition of what the brands should be. All that is needed is for each generation to be encouraged to form its own identity from the widest range of materials possible. (obesity plus high blood-pressure equals diabetes plus heart disease) seems to Darwinists the consequence of people trying to sate appetites for sugar and fat that evolution put no brakes on because they were so rare in the natural world. Pretending young adults are children so that they can be educated en masse in schools is another area ripe for investigation. And the refusal of people to adhere to the patterns of behaviour prescribed for them by classical economics has already spun off a field called behavioural economics that often has Darwinian thinking at its roots. No one is suggesting Darwinism has all the answers to social questions. Indeed, with some, such as the role of hierarchies, it suggests there is no definitive answer at all—itself an important conclusion. What is extraordinary, though, is how rarely an evolutionary analysis is part of the process of policymaking. To draw an analogy, it is like trying to fix a car without properly understanding how it works: not impossible, but as likely as not to result in a breakdown or a crash. Perhaps, after a century and a half, it is time not just to recognise but also to understand that human beings are evolved creatures. To know thyself is, after all, the beginning of wisdom. The Economist http://www.economist.com/science/displayst ory.cfm?story_id=12795581 A Darwinian analysis thus sheds light on a number of pressing questions. There are others. The rise of metabolic syndrome 14
Slide 16: Neuroscience Hijacking the Brain Circuits With a Nickel Slot Machine Compulsive gambling, attendance at sporting events, vulnerability to telephone scams and exuberant investing in the stock market may not seem to have much in common. But neuroscientists have uncovered a common thread. The idea has been around since Freud, said Dr. Gregory Berns, a psychiatrist at Emory University School of Medicine in Atlanta. Psychologists have studied unconscious processing of information in terms of subliminal effects, memory and learning, he said, and they have started to map out what parts of the brain are involved in such processing. But only now are they learning how these different circuits interact, he said. ''My hunch is that most decisions are made subconsciously with many gradations of awareness,'' Dr. Berns said. ''For example, I'm vaguely aware of how I got to work this morning. But consciousness seems reserved for more important things.'' Dr. P. Read Montague, a neuroscientist at Baylor College of Medicine in Houston, says the idea that people can get themselves to work on automatic pilot raises two questions: how does the brain know what it must pay conscious attention to? And how did evolution create a brain that could make such distinctions? The answer emerging from experiments on animals and people is that the brain has evolved to shape itself, starting in infancy, according to what it encounters in the external world. As Dr. Montague explained it, much of the world is predictable: buildings usually stay in one place, gravity makes objects fall, light falling at an oblique angle makes long shadows and so forth. As children grow, their brains build internal models of everything they encounter, gradually learning to identify objects and to predict how they move through space and time. As new information flows into it from the outside world, the brain automatically compares it to what it already knows. If things match up -- as when people drive to work every day along the same route -events, objects and the passage of time may not reach conscious awareness. Such behaviors, they say, rely on brain circuits that evolved to help animals assess rewards important to their survival, like food and sex. Researchers have found that those same circuits are used by the human brain to assess social rewards as diverse as investment income and surprise home runs at the bottom of the ninth. And, in a finding that astonishes many people, they found that the brain systems that detect and evaluate such rewards generally operate outside of conscious awareness. In navigating the world and deciding what is rewarding, humans are closer to zombies than sentient beings much of the time. The findings, which are gaining wide adherence among neuroscientists, challenge the notion that people always make conscious choices about what they want and how to obtain it. In fact, the neuroscientists say, much of what happens in the brain goes on outside of conscious awareness. 15
Slide 17: But if there is a surprise -- a car suddenly runs a red light -- the mismatch between what is expected and what is happening instantly shifts the brain into a new state. A brain circuit involved in decision making is activated, again out of conscious awareness. Drawing on past experience held in memory banks, a decision is made: hit the brake, swerve the wheel or keep going. Only a second or so later, after hands and feet have initiated the chosen action, does the sense of having made a conscious decision arise. Dr. Montague estimates that 90 percent of what people do every day is carried out by this kind of automatic, unconscious system that evolved to help creatures survive. Animals use these circuits to know what to attend to, what to ignore and what is worth learning about. People use them for the same purposes which, as a result of their bigger brains and culture, include listening to music, eating chocolate, assessing beauty, gambling, investing in stocks and experimenting with drugs -- all topics that have been studied this past year with brain imaging machines that directly measure the activity of human brain circuits. The two circuits that have been studied most extensively involve how animals and people assess rewards. Both involve a chemical called dopamine. The first circuit, which is in a middle region of the brain, helps animals and people instantly assess rewards or lack of rewards. with various types of rewards, usually squirts of apple juice that the animal liked. Dr. Schultz found that when the monkey got more juice than it expected, dopamine neurons fired vigorously. When the monkey got an amount of juice that it expected to get, based on previous squirts, dopamine neurons did nothing. And when the monkey expected to get juice but got none, the dopamine neurons decreased their firing rate, as if to signal a lack of reward. Scientists believe that this midbrain dopamine system is constantly making predictions about what to expect in terms of rewards. Learning takes place only when something unexpected happens and dopamine firing rates increase or decrease. When nothing unexpected happens, as when the same amount of delicious apple juice keeps coming, the dopamine system is quiet. In animals, Dr. Montague said, these midbrain dopamine signals are sent directly to brain areas that initiate movements and behavior. These brain areas figure out how to get more apple juice or sit back and do nothing. In humans, though, the dopamine signal is also sent to a higher brain region called the frontal cortex for more elaborate processing. Dr. Jonathan Cohen, a neuroscientist at Princeton, studies a part of the frontal cortex called the anterior cingulate, located in back of the forehead. This part of the brain has several functions, Dr. Cohen said, including the task of detecting errors and conflict in the flow of information being processed automatically. Brain imaging experiments are beginning to show that when a person gets an unexpected reward -- the equivalent of a huge shot of delicious apple juice -- more dopamine reaches the anterior cingulate. When a person expects a reward and does not get it, less dopamine reaches the region. And when a person expects a reward and gets it, the anterior cingulate is silent. 16 The circuit was described in greater detail several years ago by Dr. Wolfram Schultz, a neuroscientist at Cambridge University in England, who tracked dopamine production in a monkey's midbrain and experimented
Slide 18: When people expect a reward and do not receive it, their brains need a way to register the fact that something is amiss so it can recalibrate expectations for future events, Dr. Cohen said. As in monkeys, human dopamine neurons project to areas that plan and control movements, he said. Fluctuating levels of dopamine make people get up and do things, outside their conscious awareness. The number of things people do to increase their dopamine firing rates is unlimited, neuroscientists are discovering. Several studies were published last year looking at monetary rewards and dopamine. Money is abstract but to the brain it looks like cocaine, food, sex or anything a person expects is rewarding, said Dr. Hans Breiter, a neuroscientist at Harvard. People crave it. Some people seem to be born with vulnerable dopamine systems that get hijacked by social rewards. The same neural circuitry involved in the highs and lows of abusing drugs is activated by winning or losing money, anticipating a good meal or seeking beautiful faces to look at, Dr. Breiter said. For example, dopamine circuits are activated by cocaine; people become addicted when their reward circuits have been hijacked by the drug, Dr. Montague said. Winning in gambling can also hijack the dopamine system, Dr. Berns said. Many people visit a casino, lose money and are not tempted to go back. But compulsive gamblers seem to have vulnerable dopamine systems, he said. The first time they win, they get a huge dopamine rush that gets embedded in their memory. They keep gambling and the occasional dopamine rush of winning overrides their conscious knowledge that they will lose in the long run. Other experiments show that reward circuits are activated when young men look at photos of beautiful women and that these circuits are defective in women with eating disorders like bulimia. Bulimics say they are addicted to vomiting because it gives them a warm, positive feeling. 17 Music activates neural systems of reward and emotion. Older people with age-related impairments to the frontal cortex do poorly on gambling tasks and, experiments show, are prone to believe misleading advertising. Neuroscientists say that part of the appeal of live sporting events is their inherent unpredictability. When a baseball player with two outs at the bottom of the ninth inning hits a home run to win the game, thousands of spectators simultaneously experience a huge surge of dopamine. People keep coming back, as if addicted to the euphoria of experiencing unexpected rewards. One of the most promising areas for looking at unconscious reward circuits in human behavior concerns the stock market, Dr. Montague said. Economists do not study people, they study collective neural systems in people who form mass expectations. For example, when the Federal Reserve unexpectedly lowered interest rates twice last year, the market went up, he said. When it lowered interest rates on other occasions and investors knew the move was coming, markets did not respond. Economists and neuroscientists use the same mathematical equations for modeling market behavior and dopamine behavior, Dr. Montague said. Neuroscience may provide an entirely new set of constructs for understanding economic decision making. New York Times http://query.nytimes.com/gst/fullpage.html? res=9800E5D61E3FF93AA25751C0A9649C8 B63
Slide 19: Animal Behaviour Swarm Theory :The Genius of Swarms A single ant or bee isn't smart, but their colonies are. The study of swarm intelligence is providing insights that can help humans manage complex systems, from truck routing to robots. I used to think ants knew what they were doing. The ones marching across my kitchen counter looked so confident, I just figured they had a plan, knew where they were going and what needed to be done. How else could ants organize highways, build elaborate nests, stage epic raids, and do all the other things ants do? Turns out I was wrong. Ants aren't clever little engineers, architects, or warriors after all—at least not as individuals. When it comes to deciding what to do next, most ants don't have a clue. "If you watch an ant try to accomplish something, you'll be impressed by how inept it is," says Deborah M. Gordon, a biologist at Stanford University. How do we explain, then, the success of Earth's 12,000 or so known ant species? They must have learned something in 140 million years. "Ants aren't smart," Gordon says. "Ant colonies are." A colony can solve problems unthinkable for individual ants, such as finding the shortest path to the best food source, allocating workers to different tasks, or defending a territory from neighbors. As individuals, ants might be tiny dummies, but as colonies they respond quickly and effectively to their environment. They do it with something called swarm intelligence. Where this intelligence comes from raises a fundamental question in nature: How do the simple actions of individuals add up to the complex behavior of a group? How do hundreds of honeybees 18 make a critical decision about their hive if many of them disagree? What enables a school of herring to coordinate its movements so precisely it can change direction in a flash, like a single, silvery organism? The collective abilities of such animals—none of which grasps the big picture, but each of which contributes to the group's success—seem miraculous even to the biologists who know them best. Yet during the past few decades, researchers have come up with intriguing insights. One key to an ant colony, for example, is that no one's in charge. No generals command ant warriors. No managers boss ant workers. The queen plays no role except to lay eggs. Even with half a million ants, a colony functions just fine with no management at all—at least none that we would recognize. It relies instead upon countless interactions between individual ants, each of which is following simple rules of thumb. Scientists describe such a system as self-organizing. Consider the problem of job allocation. In the Arizona desert where Deborah Gordon studies red harvester ants (Pogonomyrmex barbatus), a colony calculates each morning how many workers to send out foraging for food. The number can change, depending on conditions. Have foragers recently discovered a bonanza of tasty seeds? More ants may be needed to haul the bounty home. Was the nest damaged by a storm last night? Additional maintenance workers may be held back to make repairs. An ant might be a nest worker one day, a trash collector the next. But how does a colony
Slide 20: make such adjustments if no one's in charge? Gordon has a theory. Ants communicate by touch and smell. When one ant bumps into another, it sniffs with its antennae to find out if the other belongs to the same nest and where it has been working. (Ants that work outside the nest smell different from those that stay inside.) Before they leave the nest each day, foragers normally wait for early morning patrollers to return. As patrollers enter the nest, they touch antennae briefly with foragers. "When a forager has contact with a patroller, it's a stimulus for the forager to go out," Gordon says. "But the forager needs several contacts no more than ten seconds apart before it will go out." To see how this works, Gordon and her collaborator Michael Greene of the University of Colorado at Denver captured patroller ants as they left a nest one morning. After waiting half an hour, they simulated the ants' return by dropping glass beads into the nest entrance at regular intervals—some coated with patroller scent, some with maintenance worker scent, some with no scent. Only the beads coated with patroller scent stimulated foragers to leave the nest. Their conclusion: Foragers use the rate of their encounters with patrollers to tell if it's safe to go out. (If you bump into patrollers at the right rate, it's time to go foraging. If not, better wait. It might be too windy, or there might be a hungry lizard waiting out there.) Once the ants start foraging and bringing back food, other ants join the effort, depending on the rate at which they encounter returning foragers. "A forager won't come back until it finds something," Gordon says. "The less food there is, the longer it takes the forager to find it and get back. The more food there is, the faster it comes back. So nobody's deciding whether it's a good day to forage. The collective is, but no particular ant is." That's how swarm intelligence works: simple creatures following simple rules, each one acting on local information. No ant sees the big picture. No ant tells any other ant what to do. Some ant species may go about this with more sophistication than others. (Temnothorax albipennis, for example, can rate the quality of a potential nest site using multiple criteria.) But the bottom line, says Iain Couzin, a biologist at Oxford and Princeton Universities, is that no leadership is required. "Even complex behavior may be coordinated by relatively simple interactions," he says. Inspired by the elegance of this idea, Marco Dorigo, a computer scientist at the Université Libre in Brussels, used his knowledge of ant behavior in 1991 to create mathematical procedures for solving particularly complex human problems, such as routing trucks, scheduling airlines, or guiding military robots. In Houston, for example, a company named American Air Liquide has been using an antbased strategy to manage a complex business problem. The company produces industrial and medical gases, mostly nitrogen, oxygen, and hydrogen, at about a hundred locations in the United States and delivers them to 6,000 sites, using pipelines, railcars, and 400 trucks. Deregulated power markets in some regions (the price of electricity changes every 15 minutes in parts of Texas) add yet another layer of complexity. "Right now in Houston, the price is $44 a megawatt for an industrial customer," says Charles N. Harper, who oversees the supply system at Air Liquide. "Last night the price went up to $64, and Monday when the cold front came through, it went up to $210." The company needed a way to pull it all together. Working with the Bios Group (now NuTech Solutions), a firm that specialized in artificial intelligence, Air Liquide developed a computer model based on algorithms inspired by the foraging behavior of Argentine ants (Linepithema humile), a 19
Slide 21: species that deposits chemical substances called pheromones. "When these ants bring food back to the nest, they lay a pheromone trail that tells other ants to go get more food," Harper explains. "The pheromone trail gets reinforced every time an ant goes out and comes back, kind of like when you wear a trail in the forest to collect wood. So we developed a program that sends out billions of software ants to find out where the pheromone trails are strongest for our truck routes." Ants had evolved an efficient method to find the best routes in their neighborhoods. Why not follow their example? So Air Liquide combined the ant approach with other artificial intelligence techniques to consider every permutation of plant scheduling, weather, and truck routing—millions of possible decisions and outcomes a day. Every night, forecasts of customer demand and manufacturing costs are fed into the model. "It takes four hours to run, even with the biggest computers we have," Harper says. "But at six o'clock every morning we get a solution that says how we're going to manage our day." For truck drivers, the new system took some getting used to. Instead of delivering gas from the plant closest to a customer, as they used to do, drivers were now asked to pick up shipments from whichever plant was making gas at the lowest delivered price, even if it was farther away. "You want me to drive a hundred miles? To the drivers, it wasn't intuitive," Harper says. But for the company, the savings have been impressive. "It's huge. It's actually huge." Other companies also have profited by imitating ants. In Italy and Switzerland, fleets of trucks carrying milk and dairy products, heating oil, and groceries all use ant-foraging rules to find the best routes for deliveries. In England and France, telephone 20 companies have made calls go through faster on their networks by programming messages to deposit virtual pheromones at switching stations, just as ants leave signals for other ants to show them the best trails. In the U.S., Southwest Airlines has tested an ant-based model to improve service at Sky Harbor International Airport in Phoenix. With about 200 aircraft a day taking off and landing on two runways and using gates at three concourses, the company wanted to make sure that each plane got in and out as quickly as possible, even if it arrived early or late. "People don't like being only 500 yards away from a gate and having to sit out there until another aircraft leaves," says Doug Lawson of Southwest. So Lawson created a computer model of the airport, giving each aircraft the ability to remember how long it took to get into and away from each gate. Then he set the model in motion to simulate a day's activity. "The planes are like ants searching for the best gate," he says. But rather than leaving virtual pheromones along the way, each aircraft remembers the faster gates and forgets the slower ones. After many simulations, using real data to vary arrival and departure times, each plane learned how to avoid an intolerable wait on the tarmac. Southwest was so pleased with the outcome, it may use a similar model to study the ticket counter area. When it comes to swarm intelligence, ants aren't the only insects with something useful to teach us. On a small, breezy island off the southern coast of Maine, Thomas Seeley, a biologist at Cornell University, has been looking into the uncanny ability of honeybees to make good decisions. With as many as 50,000 workers in a single hive, honeybees have evolved ways to work through individual differences of opinion to do what's best for the colony. If only people could be as effective in boardrooms, church committees, and town
Slide 22: meetings, Seeley says, we could avoid problems making decisions in our own lives. During the past decade, Seeley, Kirk Visscher of the University of California, Riverside, and others have been studying colonies of honeybees (Apis mellifera) to see how they choose a new home. In late spring, when a hive gets too crowded, a colony normally splits, and the queen, some drones, and about half the workers fly a short distance to cluster on a tree branch. There the bees bivouac while a small percentage of them go searching for new real estate. Ideally, the site will be a cavity in a tree, well off the ground, with a small entrance hole facing south, and lots of room inside for brood and honey. Once a colony selects a site, it usually won't move again, so it has to make the right choice. To find out how, Seeley's team applied paint dots and tiny plastic tags to identify all 4,000 bees in each of several small swarms that they ferried to Appledore Island, home of the Shoals Marine Laboratory. There, in a series of experiments, they released each swarm to locate nest boxes they'd placed on one side of the half-mile-long (one kilometer) island, which has plenty of shrubs but almost no trees or other places for nests. In one test they put out five nest boxes, four that weren't quite big enough and one that was just about perfect. Scout bees soon appeared at all five. When they returned to the swarm, each performed a waggle dance urging other scouts to go have a look. (These dances include a code giving directions to a box's location.) The strength of each dance reflected the scout's enthusiasm for the site. After a while, dozens of scouts were dancing their little feet off, some for one site, some for another, and a small cloud of bees was buzzing around each box. The decisive moment didn't take place in the main cluster of bees, but out at the boxes, where scouts were building up. As soon as the number of scouts visible near the entrance to a box reached about 15—a 21 threshold confirmed by other experiments— the bees at that box sensed that a quorum had been reached, and they returned to the swarm with the news. "It was a race," Seeley says. "Which site was going to build up 15 bees first?" Scouts from the chosen box then spread through the swarm, signaling that it was time to move. Once all the bees had warmed up, they lifted off for their new home, which, to no one's surprise, turned out to be the best of the five boxes. The bees' rules for decision-making— seek a diversity of options, encourage a free competition among ideas, and use an effective mechanism to narrow choices—so impressed Seeley that he now uses them at Cornell as chairman of his department. "I've applied what I've learned from the bees to run faculty meetings," he says. To avoid going into a meeting with his mind made up, hearing only what he wants to hear, and pressuring people to conform, Seeley asks his group to identify all the possibilities, kick their ideas around for a while, then vote by secret ballot. "It's exactly what the swarm bees do, which gives a group time to let the best ideas emerge and win. People are usually quite amenable to that." In fact, almost any group that follows the bees' rules will make itself smarter, says James Surowiecki, author of The Wisdom of Crowds. "The analogy is really quite powerful. The bees are predicting which nest site will be best, and humans can do the
Slide 23: same thing, even in the face of exceptionally complex decisions." Investors in the stock market, scientists on a research project, even kids at a county fair guessing the number of beans in a jar can be smart groups, he says, if their members are diverse, independent minded, and use a mechanism such as voting, auctioning, or averaging to reach a collective decision. Take bettors at a horse race. Why are they so accurate at predicting the outcome of a race? At the moment the horses leave the starting gate, the odds posted on the parimutuel board, which are calculated from all bets put down, almost always predict the race's outcome: Horses with the lowest odds normally finish first, those with second lowest odds finish second, and so on. The reason, Surowiecki says, is that pari-mutuel betting is a nearly perfect machine for tapping into the wisdom of the crowd. "If you ever go to the track, you find a really diverse group, experts who spend all day perusing daily race forms, people who know something about some kinds of horses, and others who are betting at random, like the woman who only likes black horses," he says. Like bees trying to make a decision, bettors gather all kinds of information, disagree with one another, and distill their collective judgment when they place their bets. That's why it's so rare to win on a long shot. There's a small park near the White House in Washington, D.C., where I like to watch flocks of pigeons swirl over the traffic and trees. Sooner or later, the birds come to rest on ledges of buildings surrounding the park. Then something disrupts them, and they're off again in synchronized flight. The birds don't have a leader. No pigeon is telling the others what to do. Instead, they're each paying close attention to the pigeons next to them, each bird following simple rules as they wheel across the sky. These rules add up to another kind of swarm intelligence—one that has less to do with 22 making decisions than with precisely coordinating movement. Craig Reynolds, a computer graphics researcher, was curious about what these rules might be. So in 1986 he created a deceptively simple steering program called boids. In this simulation, generic birdlike objects, or boids, were each given three instructions: 1) avoid crowding nearby boids, 2) fly in the average direction of nearby boids, and 3) stay close to nearby boids. The result, when set in motion on a computer screen, was a convincing simulation of flocking, including lifelike and unpredictable movements. At the time, Reynolds was looking for ways to depict animals realistically in TV shows and films. (Batman Returns in 1992 was the first movie to use his approach, portraying a swarm of bats and an army of penguins.) Today he works at Sony doing research for games, such as an algorithm that simulates in real time as many as 15,000 interacting birds, fish, or people. By demonstrating the power of selforganizing models to mimic swarm behavior, Reynolds was also blazing the trail for robotics engineers. A team of robots that could coordinate its actions like a flock of birds could offer significant advantages over a solitary robot. Spread out over a large area, a group could function as a powerful mobile sensor net, gathering information about what's out there. If the group encountered something unexpected, it could adjust and respond quickly, even if the robots in the group weren't very sophisticated, just as ants are able to come up with various options by trial and error. If one member of the group were to break down, others could take its place. And, most important, control of the group could be decentralized, not dependent on a leader. "In biology, if you look at groups with large numbers, there are very few examples where you have a central agent," says Vijay Kumar, a professor of mechanical engineering at the University of
Slide 24: Pennsylvania. "Everything is very distributed: They don't all talk to each other. They act on local information. And they're all anonymous. I don't care who moves the chair, as long as somebody moves the chair. To go from one robot to multiple robots, you need all three of those ideas." Within five years Kumar hopes to put a networked team of robotic vehicles in the field. One purpose might be as first responders. "Let's say there's a 911 call," he says. "The fire alarm goes off. You don't want humans to respond. You want machines to respond, to tell you what's happening. Before you send firemen into a burning building, why not send in a group of robots?" Taking this idea one step further, Marco Dorigo's group in Brussels is leading a European effort to create a "swarmanoid," a group of cooperating robots with complementary abilities: "foot-bots" to transport things on the ground, "hand-bots" to climb walls and manipulate objects, and "eye-bots" to fly around, providing information to the other units. The military is eager to acquire similar capabilities. On January 20, 2004, researchers released a swarm of 66 pint-size robots into an empty office building at Fort A. P. Hill, a training center near Fredericksburg, Virginia. The mission: Find targets hidden in the building. Zipping down the main hallway, the footlong (0.3 meter) red robots pivoted this way and that on their three wheels, resembling nothing so much as large insects. Eight sonars on each unit helped them avoid collisions with walls and other robots. As they spread out, entering one room after another, each robot searched for objects of interest with a small, Web-style camera. When one robot encountered another, it used wireless network gear to exchange information. ("Hey, I've already explored that part of the building. Look somewhere else.") In the back of one room, a robot spotted something suspicious: a pink ball in an open closet (the swarm had been trained to look for anything pink). The robot froze, sending an image to its human supervisor. Soon several more robots arrived to form a perimeter around the pink intruder. Within half an hour, all six of the hidden objects had been found. The research team conducting the experiment declared the run a success. Then they started a new test. The demonstration was part of the Centibots project, an investigation to see if as many as a hundred robots could collaborate on a mission. If they could, teams of robots might someday be sent into a hostile village to flush out terrorists or locate prisoners; into an earthquake-damaged building to find victims; onto chemical-spill sites to examine hazardous waste; or along borders to watch for intruders. Military agencies such as DARPA (Defense Advanced Research Projects Agency) have funded a number of robotics programs using collaborative flocks of helicopters and fixed-wing aircraft, schools of torpedo-shaped underwater gliders, and herds of unmanned ground vehicles. But at the time, this was the largest swarm of robots ever tested. "When we started Centibots, we were all thinking, this is a crazy idea, it's impossible to do," says Régis Vincent, a researcher at SRI International in Menlo Park, California. "Now we're looking to see if we can do it with a thousand robots." In nature, of course, animals travel in even larger numbers. That's because, as members of a big group, whether it's a flock, school, or herd, individuals increase their chances of detecting predators, finding food, locating a mate, or following a migration route. For these animals, coordinating their movements with one another can be a matter of life or death. "It's much harder for a predator to avoid being spotted by a thousand fish than it is to avoid being spotted by one," says Daniel Grünbaum, a biologist at the University of 23
Slide 25: Washington. "News that a predator is approaching spreads quickly through a school because fish sense from their neighbors that something's going on." When a predator strikes a school of fish, the group is capable of scattering in patterns that make it almost impossible to track any individual. It might explode in a flash, create a kind of moving bubble around the predator, or fracture into multiple blobs, before coming back together and swimming away. Animals on land do much the same, as Karsten Heuer, a wildlife biologist, observed in 2003, when he and his wife, Leanne Allison, followed the vast Porcupine caribou herd (Rangifer tarandus granti) for five months. Traveling more than a thousand miles (1,600 kilometers) with the animals, they documented the migration from winter range in Canada's northern Yukon Territory to calving grounds in Alaska's Arctic National Wildlife Refuge. "It's difficult to describe in words, but when the herd was on the move it looked very much like a cloud shadow passing over the landscape, or a mass of dominoes toppling over at the same time and changing direction," Karsten says. "It was as though every animal knew what its neighbor was going to do, and the neighbor beside that and beside that. There was no anticipation or reaction. No cause and effect. It just was." One day, as the herd funneled through a gully at the tree line, Karsten and Leanne spotted a wolf creeping up. The herd responded with a classic swarm defense. "As soon as the wolf got within a certain distance of the caribou, the herd's alertness just skyrocketed," Karsten says. "Now there was no movement. Every animal just stopped, completely vigilant and watching." A hundred yards (90 meters) closer, and the wolf crossed another threshold. "The nearest caribou turned and ran, and that response moved like a wave through the entire herd until they were all running. Reaction times 24 shifted into another realm. Animals closest to the wolf at the back end of the herd looked like a blanket unraveling and tattering, which, from the wolf's perspective, must have been extremely confusing." The wolf chased one caribou after another, losing ground with each change of target. In the end, the herd escaped over the ridge, and the wolf was left panting and gulping snow. For each caribou, the stakes couldn't have been higher, yet the herd's evasive maneuvers displayed not panic but precision. (Imagine the chaos if a hungry wolf were released into a crowd of people.) Every caribou knew when it was time to run and in which direction to go, even if it didn't know exactly why. No leader was responsible for coordinating the rest of the herd. Instead each animal was following simple rules evolved over thousands of years of wolf attacks. That's the wonderful appeal of swarm intelligence. Whether we're talking about ants, bees, pigeons, or caribou, the ingredients of smart group behavior— decentralized control, response to local cues, simple rules of thumb—add up to a shrewd strategy to cope with complexity. "We don't even know yet what else we can do with this," says Eric Bonabeau, a complexity theorist and the chief scientist at Icosystem Corporation in Cambridge, Massachusetts. "We're not used to solving decentralized problems in a decentralized way. We can't control an emergent phenomenon like traffic by putting stop signs and lights everywhere. But the idea of shaping traffic as a self-organizing system, that's very exciting."
Slide 26: Social and political groups have already adopted crude swarm tactics. During mass protests eight years ago in Seattle, antiglobalization activists used mobile communications devices to spread news quickly about police movements, turning an otherwise unruly crowd into a "smart mob" that was able to disperse and re-form like a school of fish. The biggest changes may be on the Internet. Consider the way Google uses group smarts to find what you're looking for. When you type in a search query, Google surveys billions of Web pages on its index servers to identify the most relevant ones. It then ranks them by the number of pages that link to them, counting links as votes (the most popular sites get weighted votes, since they're more likely to be reliable). The pages that receive the most votes are listed first in the search results. In this way, Google says, it "uses the collective intelligence of the Web to determine a page's importance." Wikipedia, a free collaborative encyclopedia, has also proved to be a big success, with millions of articles in more than 200 languages about everything under the sun, each of which can be contributed by anyone or edited by anyone. "It's now possible for huge numbers of people to think together in ways we never imagined a few decades ago," says Thomas Malone of MIT's new Center for Collective Intelligence. "No single person knows everything that's needed to deal with problems we face as a society, such as health care or climate change, but collectively we know far more than we've been able to tap so far." Such thoughts underline an important truth about collective intelligence: Crowds tend to be wise only if individual members act responsibly and make their own decisions. A group won't be smart if its members imitate one another, slavishly follow fads, or wait for someone to tell them what to do. When a group is being intelligent, whether it's made up of ants or attorneys, it relies on its members to do their own part. For those of us who sometimes wonder if it's really worth 25 recycling that extra bottle to lighten our impact on the planet, the bottom line is that our actions matter, even if we don't see how. Think about a honeybee as she walks around inside the hive. If a cold wind hits the hive, she'll shiver to generate heat and, in the process, help to warm the nearby brood. She has no idea that hundreds of workers in other parts of the hive are doing the same thing at the same time to the benefit of the next generation. "A honeybee never sees the big picture any more than you or I do," says Thomas Seeley, the bee expert. "None of us knows what society as a whole needs, but we look around and say, oh, they need someone to volunteer at school, or mow the church lawn, or help in a political campaign." If you're looking for a role model in a world of complexity, you could do worse than to imitate a bee. National Geographic http://ngm.nationalgeographic.com/2007/07 /swarms/miller-text
Slide 27: Humour They’re Made Out of Meat They're Made Out of Meat is a Nebula Awardnominated short story by Terry Bisson. It was originally published in Omni magazine. It consists entirely of dialogue between two sentient beings capable of traveling faster than light, on a mission to "contact, welcome and log in any and all sentient races or multibeings in this quadrant of the Universe “They’re made out of meat.” “Meat?” “Meat. They’re made out of meat.” “Meat?” “There’s no doubt about it. We picked up several from different parts of the planet, took them aboard our recon vessels, and probed them all the way through. They’re completely meat.” “That’s impossible. What about the radio signals? The messages to the stars?” “They use the radio waves to talk, but the signals don’t come from them. The signals come from machines.” “So who made the machines? That’s who we want to contact.” “They made the machines. That’s what I’m trying to tell you. Meat made the machines.” “That’s ridiculous. How can meat make a machine? You’re asking me to believe in sentient meat.” “I’m not asking you, I’m telling you. These creatures are the only sentient race in that sector and they’re made out of meat.” “Maybe they’re like the orfolei. You know, a carbon-based intelligence that goes through a meat stage.” 26 “Nope. They’re born meat and they die meat. We studied them for several of their life spans, which didn’t take long. Do you have any idea what’s the life span of meat?” “Spare me. Okay, maybe they’re only part meat. You know, like the weddilei. A meat head with an electron plasma brain inside.” “Nope. We thought of that, since they do have meat heads, like the weddilei. But I told you, we probed them. They’re meat all the way through.” “No brain?” “Oh, there’s a brain all right. It’s just that the brain is made out of meat! That’s what I’ve been trying to tell you.” “So . . . what does the thinking?” “You’re not understanding, are you? You’re refusing to deal with what I’m telling you. The brain does the thinking. The meat.” “Thinking meat! You’re asking me to believe in thinking meat!” “Yes, thinking meat! Conscious meat! Loving meat. Dreaming meat. The meat is the whole deal! Are you beginning to get the picture or do I have to start all over?” “Omigod. You’re serious then. They’re made out of meat.” “Thank you. Finally. Yes. They are indeed made out of meat. And they’ve been trying to get in touch with us for almost a hundred of their years.” “Omigod. So what does this meat have in mind?” “First it wants to talk to us. Then I imagine it wants to explore the Universe, contact other sentiences, swap ideas and information. The usual.” “We’re supposed to talk to meat.”
Slide 28: “That’s the idea. That’s the message they’re sending out by radio. ‘Hello. Anyone out there? Anybody home?’ That sort of thing.” “They actually do talk, then. They use words, ideas, concepts?” “Oh, yes. Except they do it with meat.” “I thought you just told me they used radio.” “They do, but what do you think is on the radio? Meat sounds. You know how when you slap or flap meat, it makes a noise? They talk by flapping their meat at each other. They can even sing by squirting air through their meat.” “Omigod. Singing meat. This is altogether too much. So what do you advise?” “Officially or unofficially?” “Both.” “Officially, we are required to contact, welcome, and log in any and all sentient races or multibeings in this quadrant of the Universe, without prejudice, fear, or favor. Unofficially, I advise that we erase the records and forget the whole thing.” “I was hoping you would say that.” “It seems harsh, but there is a limit. Do we really want to make contact with meat?” “I agree one hundred percent. What’s there to say? ‘Hello, meat. How’s it going?’ But will this work? How many planets are we dealing with here?” “Just one. They can travel to other planets in special meat containers, but they can’t live on them. And being meat, they can only travel through C space. Which limits them to the speed of light and makes the possibility of their ever making contact pretty slim. Infinitesimal, in fact.” “So we just pretend there’s no one home in the Universe.” 27 “That’s it.” “Cruel. But you said it yourself, who wants to meet meat? And the ones who have been aboard our vessels, the ones you probed? You’re sure they won’t remember?” “They’ll be considered crackpots if they do. We went into their heads and smoothed out their meat so that we’re just a dream to them.” “A dream to meat! How strangely appropriate, that we should be meat’s dream.” “And we marked the entire sector unoccupied.” “Good. Agreed, officially and unofficially. Case closed. Any others? Anyone interesting on that side of the galaxy?” “Yes, a rather shy but sweet hydrogen-core cluster intelligence in a class-nine star in G445 zone was in contact two galactic rotations ago, wants to be friendly again.” “They always come around.” “And why not? Imagine how unbearably, how unutterably cold the Universe would be if one were all alone . . . “
Slide 29: Book Review Born to Rebel – Frank J Sulloway powerful interpersonal dynamics, is a cauldron for the great revolutionary advances that drive historical change. Through his analysis of revolutions in science and social thought, from the Reformation to Darwin's theory of natural selection, Sulloway demonstrates that the primary engine of history is located within families, not between them, as Marx believed. This landmark work illuminates the crucial influence that family niches have on personality, and documents the profound consequences of sibling competition--not only on individual development within the family, but on society as a whole. Born to Rebel's pathbreaking insights promise to revolutionize the nature of psychological, sociological, and historical inquiry. Creating rebels Review of and commentary on Frank J. Sulloway, Born to Rebel: Birth Order, Family Dynamics, and Creative Lives (New York: Pantheon, 1996) What makes people become rebels? Is there some way to encourage people to question unjust practices and act against them? These questions have long been of interest to social activists. One common view is that people are more likely to become activists if they are made aware of social problems. Hence there are continual efforts to expose the consequences of war, poverty, exploitation and the like. Another approach is to make social action a satisfying and bonding experience. This leads to efforts to improve group dynamics, build personal relationships and design actions that are emotionally uplifting for participants. Yet another approach is to encourage people to make ever larger commitments, beginning with signing a petition and progressing through meetings, rallies, selling newspapers and direct action. These and other approaches have been developed and applied in a pragmatic fashion for many decades. Synopsis: Why are individuals from the same family often no more similar in personality than those from different families? Why, within the same family, do some children conform to authority, whereas others rebel? The family, it turns out, is not a "shared environment" but rather a set of niches that provide siblings with different outlooks. At the heart of this pioneering inquiry into human development is a fundamental insight: that the personalities of siblings vary because they adopt different strategies in the universal quest for parental favor. Frank J. Sulloway's most important finding is that eldest children identify with parents and authority, and support for the status quo, whereas younger children rebel against it. Drawing on the work of Darwin and the new science of evolutionary psychology, he transforms our understanding of personality development and its origins in the family. Most persuasively, Sulloway's findings offer conclusive evidence that the family, with its 28
Slide 30: Every now and then an entirely new and provocative perspective becomes available. A book by Frank J. Sulloway fits this category. Entitled Born to Rebel: Birth Order, Family Dynamics, and Creative Lives, it argues that a child's experience in the family is the key factor in determining whether he or she is a supporter of the status quo or a rebel. Sulloway's main interest is in explaining support or opposition to revolutionary scientific theories, though he also addresses political attitudes. While not dealing with the practical question of how to create social activists, his perspective provides some important lessons. Sulloway's book is pioneering both in method and conclusion. His method is to collect extensive data on historical individuals. He analysed 121 historical events and used biographical data on more than 6,500 individuals. This data includes family background, social attitudes and career characteristics. He formulates hypotheses and then tests them using the data. laterborns are more likely to support revolutionary causes. Sulloway analysed 28 revolutions in science, such as the Copernican revolution, the Darwinian revolution, special relativity and continental drift. For each one, he collected data on scientists who took a leading role in supporting or opposing it. To assess scientists' personalities and positions, he asked expert historians of science to make judgements, which he then incorporated in his database. After collecting all this data, Sulloway had dozens of variables--such as nationality, social class, gender, personality, religious attitudes, political attitudes, education, age and scientific eminence--that he could test to see how much they helped explain a scientist's position on a revolution, Out of all these factors, Sulloway found that one stood out as a prime influence: birth order. Laterborn scientists were more likely to support revolutions in science. For example, of scientists prominent in the controversy over Darwinism between 1859 and 1875, laterborns were 4.6 times more likely than firstborns to be supporters rather than opponents of Darwinism. (Ratios such as this are corrected for the greater number of laterborns.) The only exceptions to this pattern are "conservative theories" such as eugenics. Firstborns are more likely to support conservative innovations. So important is birth order that it overwhelms other influences, being twice as important as all other factors combined. Why should one's birth rank--one's position in the sequence of children in a family--have such an influence on attitudes? To explain this, Sulloway introduces a Darwinian model of family dynamics. Essentially, children are in competition with each other for family resources, especially affection from their parents. The eldest child has a choice of strategies and is likely to choose the central niche of identifying with the parents and 29 The most dramatic conclusion from this analysis is the vital importance of family dynamics in shaping an individual's social stance. In particular, the key variable is a person's birth rank. Firstborns are more likely to support the status quo, whereas
Slide 31: authority generally. This is consistent with the personality characteristics of firstborns which include ambition, conscientiousness and achievement motivation. An only child develops similarly to a firstborn. Laterborns have a hard time competing with an older, stronger and more successful sibling in this niche, and are more likely to branch out into other areas where they can become higher achieving than older siblings, in this way increasing their odds of attracting support from parents. As a consequence, laterborns are more likely to question the status quo and to develop a "revolutionary personality." Other factors also enter into the picture. High conflict with parents increases the odds of rebellion. But these other factors must be considered in relation to birth order. Conflict with parents is more influential in changing firstborns (towards greater rebellion) than in changing laterborns. Other factors that are important are the total number of children, gender, age gaps, age when a parent is lost, social class and temperament. Each of these needs to be understood in a picture of a struggle within the family for resources. As well as analysing revolutions in science, Sulloway investigated the Protestant Reformation, the French Revolution and other political revolutions. For example, he analysed the percentage of firstborns in the legislature in different French political parties during the revolutionary period 1789-1794. This was high among the staunch royalists who had supported the monarchy. It was lowest among the parties devoted to liberal principles. But it was also high among the revolutionaries who launched the Reign of Terror. Sulloway says that "Firstborns sought to prove their revolutionary loyalties by their predilection for violence, not by their devotion to liberalism" (p. 313). A significant point is that social class explains almost nothing about the position of leading political figures during the French Revolution, whereas birth order explains quite a lot. The Revolution was struggle of brother against brother, with many siblings lined up on opposite sides of the chamber. Born to Rebel is a frontal challenge to Marxist theories of revolution, arguing that social class is of trivial significance compared to birth order in predicting who will rebel. It also challenges Freudian analysis in arguing that sex is much less significant than birth order in shaping personality. There are many objections that can be raised on first hearing of Sulloway's arguments. For example, perhaps the conservatism of firstborns was due to the practice of primogeniture, in which the family inheritance went to the firstborn son. Sulloway considered this and tested it, finding it not to be a major factor in the propensity to rebel. He has looked at many details and complicating factors, such as the removal of a child from a family. He finds that a laterborn who is removed and reared by a relative as a firstborn behaves like a typical firstborn. The key is functional birth order rather than biological birth order, because that is what affects the struggle for family 30
Slide 32: resources. Sulloway's book is the product of 25 years of work and is an impressive piece of scholarship. As well, it is engagingly written. He notes that while his findings are predictors of behaviour only in a statistical sense, they are remarkably robust, applying over 20 different countries in his sample and over a period of nearly five centuries. Few historical generalisations have a similar power. Even without passing judgement about the validity of Sulloway's analysis, it is still possible to draw some insights concerning the task of promoting progressive social change. Perhaps the most significant point is the importance of hypothesis testing. Sulloway is an historian who subscribes to the traditional scientific approach of formulating hypotheses and then using data to test them. For example, one of his hypotheses is that "Radical change is more acceptable to young people." He tested it using his data and found it confirmed. Social movements are not noted for their commitment to hypothesis testing. They are more likely to proceed on the basis of the good judgement of experienced activists. This may work, but how do we really know? Sulloway's task in Born to Rebel is to help explain the dynamics of scientific and other revolutions. The task of social movements is to change society, so the hypotheses proposed would need to involve variables that activists can control. It would be possible, for example, to produce two leaflets with differently presented appeals and to see which one was more effective-and with which sorts of people. It would be possible to try out different types of meeting formats to see which ones proved more attractive to new members. Activists make judgements about such matters routinely. Hypothesis testing could help sort out the helpful insights from wishful thinking and perhaps reveal some unexpected findings too. A key lesson from Sulloway's findings is the importance of material conditions in the development of a revolutionary personality. Marx emphasised material conditions but concentrated on social class. Sulloway emphasises a different set of material conditions, namely the social environment of the family as one grows up. This should give hope, since social environments can be changed. Activists can use Sulloway's approach to investigate how to design society to create more rebels who support progressive innovations. One obvious area to study is the life history of activists. Among "tender-minded" activists, especially those who reject violence, it is to be expected that laterborns will predominate. But there are some firstborns in this group. It would be revealing to find out what has changed these firstborns into tender-minded activists. Sulloway gives a few hints. He notes that Galileo was a firstborn and hence not likely to be a revolutionary scientist. Galileo was an exception to the rule because he was the son of a radical. "His father taught him to question authority and to do so, moreover, by experimental means." (p. 204). Group norms can also prevail over the influence of family dynamics. For example, "A prominent exception to the rule that 31
Slide 33: firstborns endorse violent methods is seen in groups like the Quakers ... whose pacifist philosophy became institutionalized as a group norm." (p. 538). Group norms also have an enormous influence in many of the kibbutzim in Israel, at least in the early years when children were reared in sameage groups with relatively little contact with parents. As families becom smaller, firstborns and only children become a larger fraction of the population, which, according to Sulloway, is likely to be a force against radical change. This is especially the case in China where there are strong pressures against large families. Large families with many laterborns would be more conducive to creating more rebels. Could this be fostered by more communal living, bringing many children together? It's hard to tell, especially if there are many adults in the communal home. Some hypothesis testing might help in determining the most suitable home environment for creating tender-minded rebels. More generally, the design of life experiences can be used as a way of creating preferred personality types. If the goal is to shape other people's lives, this can be seen as manipulative. But if family dynamics already shape people's personalities, is it so horrible to design life experiences to foster a perferred personality? Advertisers and public relations departments work hard at this already. Certainly it seems reasonable for a person to think about their own preferred personality and to choose life experiences to foster it. For example, Sulloway finds that extensive travel is correlated with revolutionary personality, so undertaking travel is a way to transform one's own attitudes. Closer to home is the environment of the social movement organisation. Like all organisations, social movement groups must deal continually with struggles between members. In some ways these groups, especially the more close-knit ones, are like 32 families, and so some of the strategies for obtaining group resources are likely to be common, including rebellion against the founders and leaders who are like surrogate parents. The question is, how can groups harness their own dynamics to foster their quest for a better society? What is the best structure to encourage members to become committed and autonomous activists? Again, testing of some hypotheses would be very helpful. Born to Rebel has an implication that birth is destiny, namely that one's birth rank and upbringing are determining influences. Some readers will resist this argument because, they say, they are exceptions to the rule. But the wider implication of Sulloway's argument is that life experiences are the major influence. An alternative title might be Learning to Rebel. Being a rebel should not be a goal in itself. If one's parents have enlightened attitudes, then it is better that children adopt them rather than rebelling and becoming terrorists or obedient functionaries. The wider challenge is to develop better insights into creating a better world and the sort of people who will help bring it about and maintain it. Whether or not one subscribes to Sulloway's views, his book is an important stimulus in pursuing this agenda. Excerpts from other reviews of Born to Rebel: "Dr. Sulloway has built a formidable case. . . . Forget Adam Smith's invisible hand, Karl Marx's class struggles and Sigmund Freud's Oedipal clashes, he says. Radical change in human affairs is wrought by the perennial rivalry between eldest children and their younger siblings." --David, Stipp, Wall Street Journal "This book represents a stunning achievement." --Derek Bickerton, The New York Times Book Review "Fascinating and persuasive. . . . Birth order places children in different 'niches,' requiring
Slide 34: disparate modes of competition for maximal success. Sulloway's substantial birth-order effects therefore provide our best and ultimate documentation of nurture's power."-Stephen Jay Gould, Natural History, June 1997. "An extraordinary new study. . . . Sulloway's argument demolishes all simplistic notions of nature and nurture." --Matt Ridley, The Times (London) "Fascinating and convincing." --Jared Diamond, The New York Review of Books "Bertrand Russel once stated that the power of a thinker's contribution lies less in the uniqueness of his ideas, more in the skill with which the thinker defends his vies against all possible criticism. Sulloway's approach is admirable in this respect--and particularly so for a work that is primarily historical and archival in nature. Throughout, he considers alternative explanations, produces relevant data where he can, and suggests further studies that could resolve paradoxes and contradictions. . . . Clearly, Sulloway intended to write a book 'in the grand tradition' and, by and large, he has succeeded in doing so." --Howard Gardner, Nature "Sulloway's birth order theory shares the parsimonious elegance of the Darwinian principles that were its inspiration. . . . Born to Rebel [has] an interpretive nuance rarely found in quantitative studies." --Robert Boynton, The New Yorker "An important and valuable study that will define research agendas for years to come. It is also hugely fun to read." --Chet Raymo, Boston Globe Reviews taken from the Internet Economics 33
Slide 35: Krugman reveals his four rules of research. their own to offer; so why pay attention to them? The result was that the profession overlooked evidence and stories that were right under its nose. The same story is repeated in geography. Geographers and regional scientists have amassed a great deal of evidence on the nature and importance of localized external economies, and organized that evidence intelligently if not rigorously. Yet economists have ignored what they had to say, because it comes from people speaking the wrong language. I do not mean to say that formal economic analysis is worthless, and that anybody's opinion on economic matters is as good as anyone else's. On the contrary! I am a strong believer in the importance of models, which are to our minds what spear-throwers were to stone age arms: they greatly extend the power and range of our insight. In particular, I have no sympathy for those people who criticize the unrealistic simplifications of model-builders, and imagine that they achieve greater sophistication by avoiding stating their assumptions clearly. The point is to realize that economic models are metaphors, not truth. By all means express your thoughts in models, as pretty as possible (more on that below). But always remember that you may have gotten the metaphor wrong, and that someone else with a different metaphor may be seeing something that you are missing. Question the question There was a limited literature on external economies and international trade before 1978. It was never, however, very influential, because it seemed terminally messy; even the simplest models became bogged down in a taxonomy of possible outcomes. What has since become clear is that this messiness arose in large part because the modelers were asking their models to do what traditional trade models Paul Krugman was in Stockholm recently to collect his Nobel Prize and in his acceptance speech he elaborated on his four rules of research. Which are :1. Listen to the Gentiles 2. Question the question 3. Dare to be silly 4. Simplify, simplify Listen to the Gentiles What I mean by this rule is "Pay attention to what intelligent people are saying, even if they do not have your customs or speak your analytical language." The point may perhaps best be explained by example. When I began my rethinking of international trade, there was already a sizeable literature criticizing conventional trade theory. Empiricists pointed out that trade took place largely between countries with seemingly similar factor endowments, and that much of this trade involved intra-industry exchanges of seemingly similar products. Acute observers pointed to the importance of economies of scale and imperfect competition in actual international markets. Yet all of this intelligent commentary was ignored by mainstream trade theorists -after all, their critics often seemed to have an imperfect understanding of comparative advantage, and had no coherent models of 34
Slide 36: do, which is to predict a precise pattern of specialization and trade. Yet why ask that particular question? Even in the Heckscher-Ohlin model, the point you want to make is something like "A country tends to export goods whose production is intensive in the factors in which that country is abundant"; if your specific model tells you that capital-abundant country Home exports capital-intensive good X, this is valuable because it sharpens your understanding of that insight, not because you really care about these particular details of a patently oversimplified model. It turns out that if you don't ask for the kind of detail that you get in the two-sector, twogood classical model, an external economy model needn't be at all messy. As long as you ask "system" questions like how welfare and world income are distributed, it is possible to make very simple and neat models. And it's really these system questions that we are interested in. The focus on excessive detail was, to put it bluntly, a matter of carrying over ingrained prejudices from an overworked model into a domain where they only made life harder. The same is true in a number of areas in which I have worked. In general, if people in a field have bogged down on questions that seem very hard, it is a good idea to ask whether they are really working on the right questions. Often some other question is not only easier to answer but actually more interesting! (One drawback of this trick is that it often gets people angry. An academic who has spent years on a hard problem is rarely grateful when you suggest that his field can be revived by bypassing it). Dare to be silly If you want to publish a paper in economic theory, there is a safe approach: make a conceptually minor but mathematically difficult extension to some familiar model. Because the basic assumptions of the model are already familiar, people will not regard them as strange; because you have done 35 something technically difficult, you will be respected for your demonstration of firepower. Unfortunately, you will not have added much to human knowledge. What I found myself doing in the new trade theory was pretty much the opposite. I found myself using assumptions that were unfamiliar, and doing very simple things with them. Doing this requires a lot of selfconfidence, because initially people (especially referees) are almost certain not simply to criticize your work but to ridicule it. After all, your assumptions will surely look peculiar: a continuum of goods all with identical production functions, entering symmetrically into utility? Countries of identical economic size, with mirror-image factor endowments? Why, people will ask, should they be interested in a model with such silly assumptions -- especially when there are evidently much smarter young people who demonstrate their quality by solving hard problems? What seems terribly hard for many economists to accept is that all our models involve silly assumptions. Given what we know about cognitive psychology, utility maximization is a ludicrous concept; equilibrium pretty foolish outside of financial markets; perfect competition a howler for most industries. The reason for making these assumptions is not that they are reasonable but that they seem to help us produce models that are helpful metaphors for things that we think happen in the real world. Consider the example which some economists seem to think is not simply a useful model but revealed divine truth: the Arrow-Debreu model of perfect competition with utility maximization and complete markets. This is indeed a wonderful model -not because its assumptions are remotely plausible but because it helps us think more clearly about both the nature of economic efficiency and the prospects for achieving efficiency under a market system. It is actually a piece of inspired, marvellous silliness.
Slide 37: What I believe is that the age of creative silliness is not past. Virtue, as an economic theorist, does not consist in squeezing the last drop of blood out of assumptions that have come to seem natural because they have been used in a few hundred earlier papers. If a new set of assumptions seems to yield a valuable set of insights, then never mind if they seem strange. Simplify, simplify The injunction to dare to be silly is not a license to be undisciplined. In fact, doing really innovative theory requires much more intellectual discipline than working in a wellestablished literature. What is really hard is to stay on course: since the terrain is unfamilar, it is all too easy to find yourself going around in circles. Somewhere or other Keynes wrote that "it is astonishing what foolish things a man thinking alone can come temporarily to believe". And it is also crucial to express your ideas in a way that other people, who have not spent the last few years wrestling with your problems and are not eager to spend the next few years wrestling with your answers, can understand without too much effort. Fortunately, there is a strategy that does double duty: it both helps you keep control of your own insights, and makes those insights accessible to others. The strategy is: always try to express your ideas in the simplest possible model. The act of stripping down to this minimalist model will force you to get to the essence of what you are trying to say (and will also make obvious to you those situations in which you actually have nothing to say). And this minimalist model will then be easy to explain to other economists as well. I have used the "minimum necessary model" approach over and over again: using a onefactor, one-industry model to explain the basic role of monopolistic competition in trade; assuming sector-specific labor rather than full Heckscher-Ohlin factor substitution to explain the effects of intraindustry trade; working with symmetric countries to assess 36 the role of reciprocal dumping; and so on. In each case the effect has been to allow me to tackle a subject widely viewed as formidably difficult with what appears, at first sight, to be ridiculous simplicity. The downside of this strategy is, of course, that many of your colleagues will tend to assume that an insight that can be expressed in a cute little model must be trivial and obvious -- it takes some sophistication to realize that simplicity may be the result of years of hard thinking. I have heard the story that when Joseph Stiglitz was being considered for tenure at Yale, one of his senior colleagues belittled his work, saying that it consisted mostly of little models rather than deep theorems. Another colleague then asked, "But couldn't you say the same about Paul Samuelson"? "Yes, I could", replied Joe's opponent. I have heard the same reaction to my own work. Luckily, there are enough sophisticated economists around that in the end intellectual justice is usually served. And there is a special delight in managing not only to boldly go where no economist has gone before, but to do so in a way that seems after the fact to be almost childs' play. Princeton http://www.princeton.edu/%7Epkrugman/ho wiwork.html