How people respond to rules: People Rationalize Situations They’re Stuck With, But Rebel When They Think There’s An Out
“People who feel like they’re stuck with a rule or restriction are more likely to be content with it than people who think that the rule isn’t definite. The authors of a new study, which will be published in an upcoming issue of Psychological Science, a journal of the Association for Psychological Science, say this conclusion may help explain everything from unrequited love to the uprisings of the Arab Spring.
Psychological studies have found two contradictory results about how people respond to rules. Some research has found that, when there are new restrictions, you rationalize them; your brain comes up with a way to believe the restriction is a good idea. But other research has found that people react negatively against new restrictions, wanting the restricted thing more than ever.
Kristin Laurin of the University of Waterloo thought the difference might be absoluteness—how much the restriction is set in stone. “If it’s a restriction that I can’t really do anything about, then there’s really no point in hitting my head against the wall and trying to fight against it,” she says. “I’m better off if I just give up. But if there’s a chance I can beat it, then it makes sense for my brain to make me want the restricted thing even more, to motivate me to fight” Laurin wrote the new paper with Aaron Kay and Gavan Fitzsimons of Duke University.
In an experiment in the new study, participants read that lowering speed limits in cities would make people safer. Some read that government leaders had decided to reduce speed limits. Of those people, some were told that this legislation would definitely come into effect, and others read that it would probably happen, but that there was still a small chance government officials could vote it down.
People who thought the speed limit was definitely being lowered supported the change more than control subjects, but people who thought there was still a chance it wouldn’t happen supported it less than these control subjects. Laurin says this confirms what she suspected about absoluteness; if a restriction is definite, people find a way to live with it.
This could help explain how uprisings spread across the Arab world earlier this year. When people were living under dictatorships with power that appeared to be absolute, Laurin says, they may have been comfortable with it. But once Tunisia’s president fled, citizens of neighboring countries realized that their governments weren’t as absolute as they seemed—and they could have dropped whatever rationalizations they were using to make it possible to live under an authoritarian regime. Even more, the now non-absolute restriction their governments represented could have exacerbated their reaction, fueling their anger and motivating them to take action.
And how does this relate to unrequited love? It confirms people’s intuitive sense that leading someone can just make them fall for you more deeply, Laurin says. “If this person is telling me no, but I perceive that as not totally absolute, if I still think I have a shot, that’s just going to strengthen my desire and my feeling, that’s going to make me think I need to fight to win the person over,” she says. “If instead I believe no, I definitely don’t have a shot with this person, then I might rationalize it and decide that I don’t like them that much anyway.””
Minority rules: Scientists discover tipping point for the spread of ideas
“The same mathematics of networks that governs the interactions of molecules in a cell, neurons in a brain, and species in an ecosystem can be used to understand the complex interconnections between people, the emergence of group identity, and the paths along which information, norms, and behavior spread from person to person to person.” — James Fowler is a political scientist at the University of California
“Scientists at Rensselaer Polytechnic Institute have found that when just 10 percent of the population holds an unshakable belief, their belief will always be adopted by the majority of the society. The scientists, who are members of the Social Cognitive Networks Academic Research Center (SCNARC) at Rensselaer, used computational and analytical methods to discover the tipping point where a minority belief becomes the majority opinion. The finding has implications for the study and influence of societal interactions ranging from the spread of innovations to the movement of political ideals.
“When the number of committed opinion holders is below 10 percent, there is no visible progress in the spread of ideas. It would literally take the amount of time comparable to the age of the universe for this size group to reach the majority,” said SCNARC Director Boleslaw Szymanski, the Claire and Roland Schmitt Distinguished Professor at Rensselaer. “Once that number grows above 10 percent, the idea spreads like flame.”
In this visualization, we see the tipping point where minority opinion (shown in red) quickly becomes majority opinion. Over time, the minority opinion grows. Once the minority opinion reached 10 percent of the population, the network quickly changes as the minority opinion takes over the original majority opinion (shown in green). Credit: SCNARC/Rensselaer Polytechnic Institute
As an example, the ongoing events in Tunisia and Egypt appear to exhibit a similar process, according to Szymanski. “In those countries, dictators who were in power for decades were suddenly overthrown in just a few weeks.”
An important aspect of the finding is that the percent of committed opinion holders required to shift majority opinion does not change significantly regardless of the type of network in which the opinion holders are working. In other words, the percentage of committed opinion holders required to influence a society remains at approximately 10 percent, regardless of how or where that opinion starts and spreads in the society.
To reach their conclusion, the scientists developed computer models of various types of social networks. One of the networks had each person connect to every other person in the network. The second model included certain individuals who were connected to a large number of people, making them opinion hubs or leaders. The final model gave every person in the model roughly the same number of connections. The initial state of each of the models was a sea of traditional-view holders. Each of these individuals held a view, but were also, importantly, open minded to other views.
Once the networks were built, the scientists then “sprinkled” in some true believers throughout each of the networks. These people were completely set in their views and unflappable in modifying those beliefs. As those true believers began to converse with those who held the traditional belief system, the tides gradually and then very abruptly began to shift.
“In general, people do not like to have an unpopular opinion and are always seeking to try locally to come to consensus. We set up this dynamic in each of our models,” said SCNARC Research Associate and corresponding paper author Sameet Sreenivasan. To accomplish this, each of the individuals in the models “talked” to each other about their opinion. If the listener held the same opinions as the speaker, it reinforced the listener’s belief. If the opinion was different, the listener considered it and moved on to talk to another person. If that person also held this new belief, the listener then adopted that belief.
“As agents of change start to convince more and more people, the situation begins to change,” Sreenivasan said. “People begin to question their own views at first and then completely adopt the new view to spread it even further. If the true believers just influenced their neighbors, that wouldn’t change anything within the larger system, as we saw with percentages less than 10.”
The research has broad implications for understanding how opinion spreads. “There are clearly situations in which it helps to know how to efficiently spread some opinion or how to suppress a developing opinion,” said Associate Professor of Physics and co-author of the paper Gyorgy Korniss. “Some examples might be the need to quickly convince a town to move before a hurricane or spread new information on the prevention of disease in a rural village.”“
Collective intelligence and the “genetic” structure of groups
“The average intelligence of the people in the group and the maximum intelligence of the people in the group doesn’t predict group intelligence.” (…)
“Just getting a lot of smart people in a group does not necessarily make a smart group.” Furthermore, the researchers found, group intelligence is also only moderately correlated with qualities you’d think would be pretty crucial when it comes to group dynamics — things like group cohesion, satisfaction, “psychological safety,” and motivation. It’s not just that a happy group or a close-knit group or an enthusiastic group doesn’t necessarily equal a smart group; it’s also that those psychological elements have only some effect on groups’ ability to solve problems together.
Group intelligence is correlated, Malone and his colleagues found, with the average social sensitivity — the openness, and receptiveness, to others — of a group’s constituents. The emotional intelligence of group members, in other words, serves the cognitive intelligence of the group overall. And this means that — wait for it — groups with more women tend to be smarter than groups with more men. (As Malone put it: “More females, more intelligence.”) That’s largely mediated by the researchers’ social sensitivity findings: Women tend to be more socially sensitive than men — per Science — which means that, overall, more women = more emotional intelligence = more group intelligence. (…)
Just as understanding humans’ genetic code can lead us to a molecular understanding of ourselves as individuals, mapping the genome of groups may help us understand ourselves as we behave within a broader collective. And that knowledge, just as with the human genome, might help us gain an ability to manipulate group structures. (…)
If you understand what makes groups smart, you can adjust their factors to make them even smarter.”
The Argumentative Theory: ‘Reason evolved to win arguments, not seek truth’
“For centuries thinkers have assumed that the uniquely human capacity for reasoning has existed to let people reach beyond mere perception and reflex in the search for truth. Rationality allowed a solitary thinker to blaze a path to philosophical, moral and scientific enlightenment.
Now some researchers are suggesting that reason evolved for a completely different purpose: to win arguments. Rationality, by this yardstick (and irrationality too, but we’ll get to that) is nothing more or less than a servant of the hard-wired compulsion to triumph in the debating arena. According to this view, bias, lack of logic and other supposed flaws that pollute the stream of reason are instead social adaptations that enable one group to persuade (and defeat) another. (…)
The idea, labeled the argumentative theory of reasoning, is the brainchild of French cognitive social scientists, and it has stirred excited discussion (and appalled dissent) among philosophers, political scientists, educators and psychologists, some of whom say it offers profound insight into the way people think and behave. The Journal of Behavioral and Brain Sciences devoted its April issue to debates over the theory, with participants challenging everything from the definition of reason to the origins of verbal communication.
“Reasoning doesn’t have this function of helping us to get better beliefs and make better decisions,” said Hugo Mercier, who is a co-author of the journal article, with Dan Sperber. “It was a purely social phenomenon. It evolved to help us convince others and to be careful when others try to convince us.” Truth and accuracy were beside the point.
Indeed, Mr. Sperber, a member of the Jean-Nicod research institute in Paris, first developed a version of the theory in 2000 to explain why evolution did not make the manifold flaws in reasoning go the way of the prehensile tail and the four-legged stride. Looking at a large body of psychological research, Mr. Sperber wanted to figure out why people persisted in picking out evidence that supported their views and ignored the rest — what is known as confirmation bias — leading them to hold on to a belief doggedly in the face of overwhelming contrary evidence.
Other scholars have previously argued that reasoning and irrationality are both products of evolution. But they usually assume that the purpose of reasoning is to help an individual arrive at the truth, and that irrationality is a kink in that process, a sort of mental myopia. Gary F. Marcus, for example, a psychology professor at New York University and the author of “Kluge: The Haphazard Construction of the Human Mind,” says distortions in reasoning are unintended side effects of blind evolution. They are a result of the way that the brain, a Rube Goldberg mental contraption, processes memory. People are more likely to remember items they are familiar with, like their own beliefs, rather than those of others.
What is revolutionary about argumentative theory is that it presumes that since reason has a different purpose — to win over an opposing group — flawed reasoning is an adaptation in itself, useful for bolstering debating skills.
Mr. Mercier, a post-doctoral fellow at the University of Pennsylvania, contends that attempts to rid people of biases have failed because reasoning does exactly what it is supposed to do: help win an argument.
“People have been trying to reform something that works perfectly well,” he said, “as if they had decided that hands were made for walking and that everybody should be taught that.”
Think of the American judicial system, in which the prosecutors and defense lawyers each have a mission to construct the strongest possible argument. The belief is that this process will reveal the truth, just as the best idea will triumph in what John Stuart Mill called the “marketplace of ideas.” (…)
“Imagine, at some point in the past, two of our ancestors who can’t reason. They can’t argue with one another. And basically as soon as they disagree with one another, they’re stuck. They can’t try to convince one another. They are bound to keep not cooperating, for instance, because they can’t find a way to agree with each other. And that’s where reasoning becomes important.
We know that in the evolutionary history of our species, people collaborated a lot. They collaborated to hunt, they collaborated to gather food, and they collaborated to raise kids. And in order to be able to collaborate effectively, you have to communicate a lot. You have to tell other people what you want them to do, and you have to tell them how you feel about different things.
But then once people start to communicate, a host of new problems arise. The main problem posed by communication in an evolutionary context is that of deceiving interlocutors. When I am talking to you, if you accept everything I say then it’s going to be fairly easy for me to manipulate you into doing things that you shouldn’t be doing. And as a result, people have a whole suite of mechanisms that are called epistemic vigilance, which they use to evaluate what other people tell them.
If you tell me something that disagrees with what I already believe, my first reaction is going to be to reject what you’re telling me, because otherwise I could be vulnerable. But then you have a problem. If you tell me something that I disagree with, and I just reject your opinion, then maybe actually you were right and maybe I was wrong, and you have to find a way to convince me. This is where reasoning kicks in. You have an incentive to convince me, so you’re going to start using reasons, and I’m going to have to evaluate these reasons. That’s why we think reasoning evolved. (…)
We predicted that reasoning would work rather poorly when people reason on their own, and that is the case. We predicted that people would reason better when they reason in groups of people who disagree, and that is the case. We predicted that reasoning would have a confirmation bias, and that is the case. (…)
The starting point of our theory was this contrast between all the results showing that reasoning doesn’t work so well and the assumption that reasoning is supposed to help us make better decisions. But this assumption was not based on any evolutionary thinking, it was just an intuition that was probably cultural in the West, people think that reasoning is a great thing. (…)
That’s important to keep in mind is that reasoning is used in a very technical sense. And sometimes not only laymen, but philosophers, and sometimes psychologists tend to use “reasoning” in an overly broad way, in which basically reasoning can mean anything you do with your mind.
By contrast, the way we use the term “reasoning” is very specific. And we’re only referring to what reasoning is supposed to mean in the first place, when you’re actually processing reasons. Most of the decisions we make, most of the inferences we make, we make without processing reasons. (…) When you’re shopping for cereals at the supermarket, and you just grab a box of cereal not because you’ve reasoned through all the alternatives, but just because it’s the one you always buy. And you’re just doing the same thing. There is no reasoning involved in that decision. (…)
It’s only when you’re considering reasons, reasons to do something, reasons to believe, that you’re reasoning. If you’re just coming up with ideas without reasons for these ideas, then you’re using your intuitions.”
“Reasoning is generally seen as a means to improve knowledge and make better decisions. However, much evidence shows that reasoning often leads to epistemic distortions and poor decisions. This suggests that the function of reasoning should be rethought. Our hypothesis is that the function of reasoning is argumentative. It is to devise and evaluate arguments intended to persuade. Reasoning so conceived is adaptive given the exceptional dependence of humans on communication and their vulnerability to misinformation. A wide range of evidence in the psychology of reasoning and decision making can be reinterpreted and better explained in the light of this hypothesis.
Poor performance in standard reasoning tasks is explained by the lack of argumentative context. When the same problems are placed in a proper argumentative setting, people turn out to be skilled arguers. Skilled arguers, however, are not after the truth but after arguments supporting their views. This explains the notorious confirmation bias. This bias is apparent not only when people are actually arguing, but also when they are reasoning proactively from the perspective of having to defend their opinions. Reasoning so motivated can distort evaluations and attitudes and allow erroneous beliefs to persist. Proactively used reasoning also favors decisions that are easy to justify but not necessarily better. In all these instances traditionally described as failures or flaws, reasoning does exactly what can be expected of an argumentative device: Look for arguments that support a given conclusion, and, ceteris paribus, favor conclusions for which arguments can be found. (…) p.1
Some of the evidence reviewed here shows not only that reasoning falls short of delivering rational beliefs and rational decisions reliably, but also that, in a variety of cases, it may even be detrimental to rationality. Reasoning can lead to poor outcomes not because humans are bad at it but because they systematically look for arguments to justify their beliefs or their actions. The argumentative theory, however, puts such well-known demonstrations of “irrationality” in a novel perspective. Human reasoning is not a profoundly flawed general mechanism; it is a remarkably efficient specialized device adapted to a certain type of social and cognitive interaction at which it excels. (…)
People are good at assessing arguments and are quite able to do so in an unbiased way, provided they have no particular axe to grind. In group reasoning experiments where participants share an interest in discovering the right answer, it has been shown that truth wins. (…) p.58
What makes [Sherlock] Holmes such a fascinating character is precisely his preternatural turn of mind operating in a world rigged by Conan Doyle, where what should be inductive problems in fact have deductive solutions. More realistically, individuals may develop some limited ability to distance themselves from their own opinion, to consider alternatives and thereby become more objective. Presumably this is what the 10% or so of people who pass the standard Wason selection task do. But this is an acquired skill and involves exercising some imperfect control over a natural disposition that spontaneously pulls in a different direction. (…)” p. 60
“…[a] numberless multitude of people, of whom no one was close, no one was distant. …” — Leo Tolstoy, War and Peace
“We live at a time when friendship has become both all and nothing at all. Already the characteristically modern relationship, it has in recent decades become the universal one: the form of connection in terms of which all others are understood, against which they are all measured, into which they have all dissolved. (…)
The Facebook phenomenon, so sudden and forceful a distortion of social space, needs little elaboration. Having been relegated to our screens, are our friendships now anything more than a form of distraction? When they’ve shrunk to the size of a wall post, do they retain any content? If we have 768 “friends,” in what sense do we have any? Facebook isn’t the whole of contemporary friendship, but it sure looks a lot like its future. Yet Facebook—and MySpace, and Twitter, and whatever we’re stampeding for next—are just the latest stages of a long attenuation. They’ve accelerated the fragmentation of consciousness, but they didn’t initiate it. They have reified the idea of universal friendship, but they didn’t invent it. In retrospect, it seems inevitable that once we decided to become friends with everyone, we would forget how to be friends with anyone. (…)
The idea of friendship in ancient times
How did we come to this pass? The idea of friendship in ancient times could not have been more different. Achilles and Patroclus, David and Jonathan, Virgil’s Nisus and Euryalus: Far from being ordinary and universal, friendship, for the ancients, was rare, precious, and hard-won. In a world ordered by relations of kin and kingdom, its elective affinities were exceptional, even subversive, cutting across established lines of allegiance. David loved Jonathan despite the enmity of Saul; Achilles’ bond with Patroclus outweighed his loyalty to the Greek cause. Friendship was a high calling, demanding extraordinary qualities of character—rooted in virtue, for Aristotle and Cicero, and dedicated to the pursuit of goodness and truth. And because it was seen as superior to marriage and at least equal in value to sexual love, its expression often reached an erotic intensity. Jonathan’s love, David sang, “was more wondrous to me than the love of women.” Achilles and Patroclus were not lovers—the men shared a tent, but they shared their beds with concubines—they were something greater. Achilles refused to live without his friend, just as Nisus died to avenge Euryalus, and Damon offered himself in place of Pythias.
The rise of Christianity put the classical ideal in eclipse. Christian thought discouraged intense personal bonds, for the heart should be turned to God. Within monastic communities, particular attachments were seen as threats to group cohesion. In medieval society, friendship entailed specific expectations and obligations, often formalized in oaths. Lords and vassals employed the language of friendship. “Standing surety”—guaranteeing a loan, as in The Merchant of Venice—was a chief institution of early modern friendship. Godparenthood functioned in Roman Catholic society (and, in many places, still functions) as a form of alliance between families, a relationship not between godparent and godchild, but godparent and parent. In medieval England, godparents were “godsibs”; in Latin America, they are “compadres,” co-fathers, a word we have taken as synonymous with friendship itself.
The classical notion of friendship was revived, along with other ancient modes of feeling, by the Renaissance. Truth and virtue, again, above all: “Those who venture to criticize us perform a remarkable act of friendship,” wrote Montaigne, “for to undertake to wound and offend a man for his own good is to have a healthy love for him.” His bond with Étienne, he avowed, stood higher not only than marriage and erotic attachment, but also than filial, fraternal, and homosexual love. “So many coincidences are needed to build up such a friendship, that it is a lot if fortune can do it once in three centuries.” The highly structured and, as it were, economic nature of medieval friendship explains why true friendship was held to be so rare in classical and neoclassical thought: precisely because relations in traditional societies were dominated by interest. Thus the “true friend” stood against the self-interested “flatterer” or “false friend,” as Shakespeare sets Horatio—”more an antique Roman than a Dane”—against Rosencrantz and Guildenstern. Sancho Panza begins as Don Quixote’s dependent and ends as his friend; by the close of their journey, he has come to understand that friendship itself has become the reward he was always seeking. (…)
“Don Quixote and Sancho Panza,” by Alexandre-Gabriel Decamps, The Gallery Collection, Corbis
Friendship in modern society
The growth of democracy, an ideology of universal equality and inter-involvement. We are citizens now, not subjects, bound together directly rather than through allegiance to a monarch. But what is to bind us emotionally, make us something more than an aggregate of political monads? One answer was nationalism, but another grew out of the 18th-century notion of social sympathy: friendship, or at least, friendliness, as the affective substructure of modern society. It is no accident that “fraternity” made a third with liberty and equality as the watchwords of the French Revolution. Wordsworth in Britain and Whitman in America made visions of universal friendship central to their democratic vistas. For Mary Wollstonecraft, the mother of feminism, friendship was to be the key term of a renegotiated sexual contract, a new domestic democracy.
Now we can see why friendship has become the characteristically modern relationship. Modernity believes in equality, and friendships, unlike traditional relationships, are egalitarian. Modernity believes in individualism. Friendships serve no public purpose and exist independent of all other bonds. Modernity believes in choice. Friendships, unlike blood ties, are elective; indeed, the rise of friendship coincided with the shift away from arranged marriage. Modernity believes in self-expression. Friends, because we choose them, give us back an image of ourselves. Modernity believes in freedom. Even modern marriage entails contractual obligations, but friendship involves no fixed commitments. The modern temper runs toward unrestricted fluidity and flexibility, the endless play of possibility, and so is perfectly suited to the informal, improvisational nature of friendship. We can be friends with whomever we want, however we want, for as long as we want.
Social changes play into the question as well. As industrialization uprooted people from extended families and traditional communities and packed them into urban centers, friendship emerged to salve the anonymity and rootlessness of modern life. (…)
Both look to friends to replace the older structures. Friends may be “the family we choose,” as the modern proverb has it, but for many of us there is no choice but to make our friends our family, since our other families—the ones we come from or the ones we try to start—have fallen apart. When all the marriages are over, friends are the people we come back to. And even those who grow up in a stable family and end up creating another one pass more and more time between the two. We have yet to find a satisfactory name for that period of life, now typically a decade but often a great deal longer, between the end of adolescence and the making of definitive life choices. But the one thing we know is that friendship is absolutely central to it.
Inevitably, the classical ideal has faded. The image of the one true friend, a soul mate rare to find but dearly beloved, has completely disappeared from our culture. We have our better or lesser friends, even our best friends, but no one in a very long time has talked about friendship the way Montaigne and Tennyson did. That glib neologism “bff,” which plays at a lifelong avowal, bespeaks an ironic awareness of the mobility of our connections: Best friends forever may not be on speaking terms by this time next month. We save our fiercest energies for sex. Indeed, between the rise of Freudianism and the contemporaneous emergence of homosexuality to social visibility, we’ve taught ourselves to shun expressions of intense affection between friends—male friends in particular, though even Oprah was forced to defend her relationship with her closest friend—and have rewritten historical friendships, like Achilles’ with Patroclus, as sexual. For all the talk of “bromance” lately (or “man dates”), the term is yet another device to manage the sexual anxiety kicked up by straight-male friendships—whether in the friends themselves or in the people around them—and the typical bromance plot instructs the callow bonds of youth to give way to mature heterosexual relationships. At best, intense friendships are something we’re expected to grow out of. (…)
We seem to be terribly fragile now. A friend fulfills her duty, we suppose, by taking our side—validating our feelings, supporting our decisions, helping us to feel good about ourselves. We tell white lies, make excuses when a friend does something wrong, do what we can to keep the boat steady. We’re busy people; we want our friendships fun and friction-free.
The group friendship or friendship circle
Yet even as friendship became universal and the classical ideal lost its force, a new kind of idealism arose, a new repository for some of friendship’s deepest needs: the group friendship or friendship circle. Companies of superior spirits go back at least as far as Pythagoras and Plato and achieved new importance in the salons and coffeehouses of the 17th and 18th centuries, but the Romantic age gave them a fresh impetus and emphasis. The idea of friendship became central to their self-conception, whether in Wordsworth’s circle or the “small band of true friends” who witness Emma’s marriage in Austen. And the notion of superiority acquired a utopian cast, so that the circle was seen—not least because of its very emphasis on friendship—as the harbinger of a more advanced age. The same was true, a century later, of the Bloomsbury Group, two of whose members, Woolf and Forster, produced novel upon novel about friendship. It was the latter who famously enunciated the group’s political creed. “If I had to choose between betraying my country and betraying my friend,” he wrote, “I hope I should have the guts to betray my country.” Modernism was the great age of the coterie, and like the legendary friendships of antiquity, modernist friendship circles—bohemian, artistic, transgressive—set their face against existing structures and norms. Friendship becomes, on this account, a kind of alternative society, a refuge from the values of the larger, fallen world.
The belief that the most significant part of an individual’s emotional life properly takes place not within the family but within a group of friends began to expand beyond the artistic coterie and become general during the last half of the 20th century. The Romantic-Bloomsburyan prophecy of society as a set of friendship circles was, to a great extent, realized. Mary McCarthy offered an early and tart view of the desirability of such a situation in The Group; Barry Levinson, a later, kinder one in Diner. Both works remind us that the ubiquity of group friendship owes a great deal to the rise of youth culture. Indeed, modernity associates friendship itself with youth, a time of life it likewise regards as standing apart from false adult values. “The dear peculiar bond of youth,” Byron called friendship, inverting the classical belief that its true practice demands maturity and wisdom. With modernity’s elevation of youth to supreme status as the most vital and authentic period of life, friendship became the object of intense emotion in two contradictory but often simultaneous directions. We have sought to prolong youth indefinitely by holding fast to our youthful friendships, and we have mourned the loss of youth through an unremitting nostalgia for those friendships. One of the most striking things about the way the 20th century understood friendship was the tendency to view it through the filter of memory, as if it could be recognized only after its loss, and as if that loss were inevitable.
The culture of group friendship reached its apogee in the 1960s. Two of the counterculture’s most salient and ideologically charged social forms were the commune—a community of friends in self-imagined retreat from a heartlessly corporatized society—and the rock’n’roll “band” (not “group” or “combo”), its name evoking Shakespeare’s “band of brothers” and Robin Hood’s band of Merry Men, its great exemplar the Beatles. Communes, bands, and other 60s friendship groups (including Woodstock, the apotheosis of both the commune and the rock concert) were celebrated as joyous, creative places of eternal youth—havens from the adult world. To go through life within one was the era’s utopian dream; it is no wonder the Beatles’ break-up was received as a generational tragedy. It is also no wonder that 60s group friendship began to generate its own nostalgia as the baby boom began to hit its 30s. The Big Chill, in 1983, depicted boomers attempting to recapture the magic of a late-60s friendship circle. (“In a cold world,” the movie’s tagline reads, “you need your friends to keep you warm.”) Thirtysomething, taking a step further, certified group friendship as the new adult norm. Most of the characters in those productions, though, were married.
It was only in the 1990s that a new generation, remaining single well past 30, found its own images of group friendship in Seinfeld, Sex and the City, and, of course, Friends. By that point, however, the notion of friendship as a redoubt of moral resistance, a shelter from normative pressures and incubator of social ideals, had disappeared. Your friends didn’t shield you from the mainstream, they were the mainstream. (…)
Friendship is devolving, in other words, from a relationship to a feeling—from something people share to something each of us hugs privately to ourselves in the loneliness of our electronic caves, rearranging the tokens of connection like a lonely child playing with dolls. The same path was long ago trodden by community. As the traditional face-to-face community disappeared, we held on to what we had lost—the closeness, the rootedness—by clinging to the word, no matter how much we had to water down its meaning. Now we speak of the Jewish “community” and the medical “community” and the “community” of readers, even though none of them actually is one. What we have, instead of community, is, if we’re lucky, a “sense” of community—the feeling without the structure; a private emotion, not a collective experience. And now friendship, which arose to its present importance as a replacement for community, is going the same way. We have “friends,” just as we belong to “communities.” Scanning my Facebook page gives me, precisely, a “sense” of connection. Not an actual connection, just a sense. (…)
The more people we know, the lonelier we get
Until a few years ago, you could share your thoughts with only one friend at a time (on the phone, say), or maybe with a small group, later, in person. And when you did, you were talking to specific people, and you tailored what you said, and how you said it, to who they were—their interests, their personalities, most of all, your degree of mutual intimacy. “Reach out and touch someone” meant someone in particular, someone you were actually thinking about. It meant having a conversation. Now we’re just broadcasting our stream of consciousness, live from Central Park, to all 500 of our friends at once, hoping that someone, anyone, will confirm our existence by answering back. We haven’t just stopped talking to our friends as individuals, at such moments, we have stopped thinking of them as individuals. We have turned them into an indiscriminate mass, a kind of audience or faceless public. We address ourselves not to a circle, but to a cloud.
It’s amazing how fast things have changed. Not only don’t we have Wordsworth and Coleridge anymore, we don’t even have Jerry and George. Today, Ross and Chandler would be writing on each other’s walls. Carrie and the girls would be posting status updates, and if they did manage to find the time for lunch, they’d be too busy checking their BlackBerrys to have a real conversation. Sex and Friends went off the air just five years ago, and already we live in a different world. Friendship (like activism) has been smoothly integrated into our new electronic lifestyles. We’re too busy to spare our friends more time than it takes to send a text. We’re too busy, sending texts. And what happens when we do find the time to get together? I asked a woman I know whether her teenage daughters and their friends still have the kind of intense friendships that kids once did. Yes, she said, but they go about them differently. They still stay up talking in their rooms, but they’re also online with three other friends, and texting with another three. Video chatting is more intimate, in theory, than speaking on the phone, but not if you’re doing it with four people at once. And teenagers are just an early version of the rest of us. A study found that one American in four reported having no close confidants, up from one in 10 in 1985. The figures date from 2004, and there’s little doubt that Facebook and texting and all the rest of it have already exacerbated the situation. The more people we know, the lonelier we get.
The new group friendship, already vitiated itself, is cannibalizing our individual friendships as the boundaries between the two blur. (…) Perhaps I need to surrender the idea that the value of friendship lies precisely in the space of privacy it creates: not the secrets that two people exchange so much as the unique and inviolate world they build up between them, the spider web of shared discovery they spin out, slowly and carefully, together. There’s something faintly obscene about performing that intimacy in front of everyone you know, as if its real purpose were to show what a deep person you are. Are we really so hungry for validation? So desperate to prove we have friends?
But surely Facebook has its benefits. Long-lost friends can reconnect, far-flung ones can stay in touch. I wonder, though. Having recently moved across the country, I thought that Facebook would help me feel connected to the friends I’d left behind. But now I find the opposite is true. Reading about the mundane details of their lives, a steady stream of trivia and ephemera, leaves me feeling both empty and unpleasantly full, as if I had just binged on junk food, and precisely because it reminds me of the real sustenance, the real knowledge, we exchange by e-mail or phone or face-to-face. And the whole theatrical quality of the business, the sense that my friends are doing their best to impersonate themselves, only makes it worse. The person I read about, I cannot help feeling, is not quite the person I know. [Facebook] As for getting back in touch with old friends—yes, when they’re people you really love, it’s a miracle. (…)
Facebook holds out a utopian possibility: What once was lost will now be found. But the heaven of the past is a promised land destroyed in the reaching. Facebook, here, becomes the anti-madeleine, an eraser of memory.Carlton Fisk has remarked that he’s watched the videotape of his famous World Series home run only a few times, lest it overwrite his own recollection of the event. Proust knew that memory is a skittish creature that peeks from its hole only when it isn’t being sought. Mementos, snapshots, reunions, and now this—all of them modes of amnesia, foes of true remembering. The past should stay in the heart, where it belongs.
Finally, the new social-networking Web sites have falsified our understanding of intimacy itself, and with it, our understanding of ourselves. The absurd idea, bruited about in the media, that a MySpace profile or “25 Random Things About Me” can tell us more about someone than even a good friend might be aware of is based on desiccated notions about what knowing another person means: First, that intimacy is confessional—an idea both peculiarly American and peculiarly young, perhaps because both types of people tend to travel among strangers, and so believe in the instant disgorging of the self as the quickest route to familiarity. Second, that identity is reducible to information: the name of your cat, your favorite Beatle, the stupid thing you did in seventh grade. Third, that it is reducible, in particular, to the kind of information that social-networking Web sites are most interested in eliciting, consumer preferences. Forget that we’re all conducting market research on ourselves. (…)
So information replaces experience, as it has throughout our culture. But when I think about my friends, what makes them who they are, and why I love them, it is not the names of their siblings that come to mind, or their fear of spiders. It is their qualities of character. This one’s emotional generosity, that one’s moral seriousness, the dark humor of a third. Yet even those are just descriptions, and no more specify the individuals uniquely than to say that one has red hair, another is tall. To understand what they really look like, you would have to see a picture. And to understand who they really are, you would have to hear about the things they’ve done. Character, revealed through action: the two eternal elements of narrative. In order to know people, you have to listen to their stories. (…)
Each evolved as a space for telling stories, an act that cannot usefully be accomplished in much less. Posting information is like pornography, a slick, impersonal exhibition. Exchanging stories is like making love: probing, questing, questioning, caressing. It is mutual. It is intimate. It takes patience, devotion, sensitivity, subtlety, skill—and it teaches them all, too. (…)
Now, in the age of the entrepreneurial self, even our closest relationships are being pressed onto this template. A recent book on the sociology of modern science describes a networking event at a West Coast university: “There do not seem to be any singletons—disconsolately lurking at the margins—nor do dyads appear, except fleetingly.” No solitude, no friendship, no space for refusal—the exact contemporary paradigm. At the same time, the author assures us, “face time” is valued in this “community” as a “high-bandwidth interaction,” offering “unusual capacity for interruption, repair, feedback and learning.” Actual human contact, rendered “unusual” and weighed by the values of a systems engineer. We have given our hearts to machines, and now we are turning into machines. The face of friendship in the new century.”
— William Deresiewicz, formerly an associate professor of English at Yale University, is a widely published literary critic, Faux Friendship, The Chronicle of Higher Education, Dec 6, 2009
Geoffrey West on Why Cities Keep Growing, Corporations and People Always Die, and Life Gets Faster
“What extent can biology and social organization (which are both quintessential complex adaptive systems) be put in a more quantitative, analytic, mathematizable, predictive framework so that we can understand them in the way that we understand “simple physical systems”?
It is very clear from the beginning that we will never have a theory of biological and social systems that is like physics — that is, something that’s precise that we can predict, like for example, the motion of the planets with great precision or the magnetic electron to 12 decimal places. Nothing approaching that can possibly be in these other sciences, because they are complex systems.
Nevertheless, that doesn’t mean that you couldn’t have a quantitative theory. It would simply mean that you would possibly have a theory that is cross-grained. Meaning that you would be able to ask questions, big questions, and answer them in an average idealized setting. (…)
I started working some years ago on questions in biology. I started using the very powerful techniques developed in physics, and that have run through the history of physics, to think about scaling phenomena. The great thing about scaling is that if you observe scaling (that is, how the various characteristics of a system change when you change its size) and if you see regularity over several orders of magnitude, that typically means that there are underlying generic principles, that it is not an accident. If you see that in a system, it is opening a window onto some underlying, let’s use the word, “universal principle”.
The remarkable thing in biology that got me excited and has led to all of my present work (which has now gone beyond biology and into social organizations, cities, and companies) is that there was data, quite old and fundamental to all biological processes, about metabolism: Here is maybe the most complex physical chemical process possibly in the universe, and when you ask how it is scaled with size across mammals (as an example to keep it simple) you find that there is an extraordinary regularity.
This is surprising because we believe in natural selection, and natural selection has built into it this idea that history plays an important role. There’s the environmental niche for every organism, every component of an organism, every cell type is unique and has its own unique history. So if you plotted, for example the metabolic rate on the Y axis and size on the X axis, because of the extraordinary diversity and complexity of the system and the historical contingency, you would expect points all over the map representing, of course, history and geography and so on.
Well, you find quite the contrary. You find a very simple curve, and that curve has a very simple mathematical formula. It comes out to be a very simple power law. In fact, the power law not only is simple in itself mathematically, but here it has an exponent that is extraordinarily simple. The exponent was very close to the number three quarters.
First of all, that was amazing in itself, that you see scaling. But more importantly was that the scaling is manifested across all of life into eco-systems and down within cells. So this scaling law is truly remarkable. It goes from intracellular up to ecosystems almost 30 orders of magnitude. They’re the same phenomenon. (…)
That is, it scales as a simple power law. The extraordinary thing about it is that the power law has an exponent, which is always a simple multiple of one quarter. What you determine just from the data is that there’s this extraordinary simple number, four, which seems to dominate all biology and across all taxonomic groups from the microscopic to the macroscopic.
This can hardly be an accident. If you see scaling, it is manifesting something that transcends history, geography, and therefore the evolved engineered structure of the organism because it applies to me, all mammals, and the trees sitting out there, even though we’re completely different designs.
The big question is where in the hell does that number come from? And what is it telling us about the structure of the biology? And what is it telling us about the constraints under which evolution occurred? That was the beginning of all this.
Are cities and companies just extensions of biology?
I’ll say a few words about what we propose as the solution. But to jump ahead, the idea was that once we had that body of work, understanding the origin of these scaling laws was to take it over into social organizations. And so the question that drove the extension of this work was, “are cities and companies just extensions of biology?”
They came out of biology. That’s where they came from. But is New York just actually, in some ways, a great big whale? And is Microsoft a great big elephant? Metaphorically we use biological terms, for example the DNA of the company or the ecology of the marketplace. But are those just metaphors or is there some serious substance that we can quantify with those?
There are two things that are very important that come out of the biology of the scaling —it’s theoretical and conceptual framework.
One: Since the metabolic rate scales non-linearly with size — all of these things scale non-linearly with size — and they scale with exponents that are less than one, what that means is that if the metabolic rate per cell is decreasing with size, the metabolic rate of our cells, my cells, are working harder than my horses. But my dogs are working even harder, in a systematic predictive way.
What does that say? That says there’s an extraordinary economy of scale.
Just to give you an example, if you increase the size of an organism by a factor of ten to the fourth, four is the magnitude, you would have expected naively to have ten to the fourth times as much energy. You would have the ten to the fourth times more cells. Ten thousand times more cells. Not true. You only need a thousand times. There’s an extraordinary savings in the energy use, and that cuts across all resources as well.
When we come to social organizations, there’s an interesting question. Do we have economies of scale or what? How do cities work, for example? How do companies work in this framework? That’s one thing.
The second thing is, (again, comes from the data and the conceptual framework explains it) the bigger you are, the slower everything is. The bigger you are, you live longer. Oxygen diffuses slower across your various membranes. You take longer to mature, you grow slower, but all in a systematic, mathematizable, predictable way. The pace of life systematically slows down following these quarter power scales. And again, we’ll ask those questions about life … social life and economies.
The work I got involved in was to try to understand these scaling laws. And to make it a very short story, what was proposed apart from the thinking was, look, this is universal. It cuts across the design of organisms. Whether you are insects, fish, mammals or birds, you get the same scaling laws. It is independent of design. Therefore, it must be something that is about the structure of the way things are distributed.
You recognize what the problem is. You have ten14cells. You have this problem. You’ve got to sustain them, roughly speaking, democratically and efficiently. And however natural selection solved it, it solved it by evolving hierarchical networks.
There is a very simple way of doing it. You take something macroscopic, you go through a hierarchy and you deliver them to very microscopic sites, like for example, your capillaries to your cells and so on. And so the idea was, this is true at all scales. It is true of an ecosystem; it is true within the cell. And what these scaling laws are manifesting are the generic, universal, mathematical, topological properties of networks.
The question is, what are the principles that are governing these networks that are independent of design? After a lot of work we postulated the following, just to give an idea.
First, they have to be space filling. They have to go everywhere. They have to feed every cell, every piece of the organism.
Secondly, they have things like invariant units. That is when you evolve from a human being to a whale (to make it a simple story) you do not change the basic units. The cells of the whale or the capillaries of whale, which are the kind of fundamental units, are pretty much indistinguishable from yours and mine. There is this invariance. When you evolve to a new species, you use the same units but you change the network. That’s the idea in this picture.
And the last one is of the infinitude of networks that have these properties - space filling and invariant total units. The ones that have actually evolved by the process of continuous feedback implicit in natural selection are those that have in some way optimized the system.
For example, the amount of work that your heart has to do to pump blood around your circulatory system to keep you alive is minimized with respect to the design of the system. You can put it into mathematics. You have a network theory, you mathematize the network, and then you make variations of the network and ask what is the one that minimizes the amount of energy your heart has to use to pump blood through it.
The principle is simple. Mathematically, it is quite complicated and challenging, but you can solve all of that. And you do that so that you can maximize the amount of energy you can put into fitness to make children. You want to minimize the amount of energy just to keep you alive, so that you can make more babies. That’s the simplest big picture.
All of those results about scaling are derived. A quarter, four, emerges. And what is the four? It turns out the four isn’t a four. The four is actually a “three plus one”, meaning it’s the dimensionality of the space we live in plus one, which is actually to do, loosely speaking, with the fractal nature of these networks, the fact that there’s a sub-similar property.
In D dimensions, you read D plus one (that’s my physicist self speaking). Instead of being three quarters for metabolic rate, it would be D over D plus one.
Life in some funny way is actually five dimensional. It’s three space, one time, and one kind of fractal. That’s five. So we’re kind of five dimensional creatures in some curious way, mathematically.
This network theory was used to predict all kinds of things. You can answer questions like why is it we sleep eight hours. Why does a mouse have to sleep 15 hours? And why does an elephant only have to sleep four and a whale two? Well, we can answer that. Why do we evolve at the rate we do? How does cancer work in terms of vasculature and its necrosis? And so on.
A whole bunch of questions can follow from this. One of the most important is growth. Understanding growth. How do we grow? And why do we stop growing, for example? Well, we can answer that. The theory answers that. And it’s quite powerful, and it explains why it is we have this so-called sigmoidal growth where you grow quickly and then you stop. And it explains why that is and it predicts when you stop, and it predicts the shape of that curve for an animal.
Here is this wonderful body of work that explains many things — some fundamental, some to do with very practical problems like understanding sleep, aging. The question is, can we take that over to other kinds of network systems. One of the obvious types of systems is a city. Another obvious one is a company. The first question you have to ask is, okay, this was based on the observation of scaling. Scaling was the window. It’s interesting of itself, but actually, it’s more interesting as a revelatory tool to open onto fundamental principles.
What did we learn from scaling in biology? We not only learned the network theory, but we learned that despite the fact that the whale lives in the ocean, the giraffe has a long neck, and the elephant a truck, and we walk on two feet and the mouse scurries around, at some 85, 90 percent level, we’re all scaled versions of one another.
There’s kind of one mammal, and every other mammal, no matter what size it is and where it existed, is actually some well-defined mathematically scaled version of that one master mammal, so to speak. And that is kind of amazing.
In other words, the size of a mammal, or any organism for that matter, can tell you how long it should live, how many children it should have, how oxygen diffuses across its lungs, what is the length of the ninth branch of its circulatory system, how its blood is flowing, how quickly it will grow, et cetera.
A provocative question is, is New York just a scaled up San Francisco, which is a scaled up Santa Fe? Superficially, that seems unlikely because they look so different, especially Santa Fe. I live in Santa Fe and it’s a bunch of dopey buildings, and here I am in New York overwhelmed by huge skyscrapers. On the other hand, a whale doesn’t look much like a giraffe. But in fact, they’re scaled versions of one another, at this kind of cross-grained 85, 90 percent level.
Of course, you can’t answer this question just by sitting in an armchair. You have to go out and get the data and ask, “If I look at various metrics describing a city, do they scale in some simple way?”
Is there one line, so to speak, upon which all of them sit? Or when I look at all these metrics and I plot them, do I just see this random mess, which says that each city is unique and dominated by its geography and its history? In which case there’s not much you can do, and you’ve got to attack and think about cities as individual.
I got into this work, because first of all, I believe it’s a truly challenging, fundamental, science problem.
I think this is very much science of the 21st century, because it is the kind of problem that scientists have ignored. It is under the umbrella of a complex adaptive system and we need to come to terms with understanding the structure and dynamics and organization of such systems because they’re the ones that determine our lives and our extraordinary phenomenon that we have developed on this planet.
Can we understand them as scientists? The prevailing way of investigating them is social sciences and economics — which have primarily less to do with generic principles and more to do with case studies and narrative (which is of course, very important). But the question is, can we complement them and make a science of cities, so to speak, and a science of corporations?
It is a very important question, certainly for scaling, because if it’s true that every city is unique, then of course, there’s no real science of cities. Every case would be special.
Another remarkable fact is that the planet has urbanizing at an exponential rate. Namely, 200 years ago, here sitting in Manhattan, almost everything around me would be a field. There would be a teeny settlement down at Wall Street somewhere of a small number of people. But most of the people would be living in these fields all the way up Manhattan into upstate New York. Indeed, at that time, less than four percent of the United States was urban. Primarily, it was agricultural. And now, only 200 years later, it’s almost the reverse. More like 82 percent is urban and less than 20 percent is agricultural. This has happened at an extraordinarily fast rate — and in fact, faster than exponential.
The point to recognize is that all of the tsunami of problems we’re facing, from global warming, the environment, to the questions of financial markets and risk, crime, pollution, disease and so forth, all of them are urban.
They all have their origin in cities. They have become dominant since the Industrial Revolution. Most importantly, they’ve been with us for the last two or 300 years, and somehow, we’ve only noticed them in the last ten or 15 years as if they’d never been here. Why? Because they’ve been increasing exponentially. We are on an exponential.
Cities are the cause of the problem, and they’re also the cause of the good life. They are the centers of wealth creation, creativity, innovation, and invention. They’re the exciting places. They are these magnets that suck people in. And that’s what’s been happening. And so they are the origin of the problems, but they are the origin of the solutions. And we need to come to terms with that, and we need to understand how cities work in a more scientific framework, meaning to what extent can we make it into a quantitative predictive, mathematizible kind of science.
Is that even possible? And is it useful? That’s quest.
The first thing was to ask the question, do they scale? I put together a wonderful team of people, and I’d like to mention their names, because they play an extremely important and seminal role.
One is a man named Luis Bettencourt also a physicist who is at Los Alamos and the Santa Fe Institute. A man named José Lobo, who was at Cornell when I first got him involved, an urban economist and now he’s at Arizona State. Another is a student, Deborah Strumsky, who was at Harvard when she joined us, and is now at the University of North Carolina. And there are others, but these were the main characters. Most importantly, they were people that were part of a trans-disciplinary kind of group. And they brought together the data. They did the data mining, the statistics, analysis, et cetera. They have the expertise and the credentials.
The result of all of that was a long, tedious kind of process. To make a long story short, indeed, we found that cities scaled. Just amazing. Cities do scale. Not only do they scale, but also there’s universality to their scaling. Let me just tell you a little bit about of what we discovered from the data to begin with.
The first result that we actually got was with my German colleagues, Dirk Helbing, and his then student, Christian Kuhnert, who then worked with me. One of the first results was a very simple one —the number of gas stations as a function of city size in European cities.
What was discovered was that they behaved sort of like biology. You found that they are scaled beautifully, and it scaled as a power law, and the power law was less than one, indicating an economy of scale. Not surprisingly, the bigger the city, the less gas stations you need per capital. There is an economy of scale.
But it’s scaled! That is, it was systematic! You tell me the size of a city and I’ll tell you how many gas stations it has — that kind of idea. And not only that, it’s scaled at exactly the same way across all European cities. Kind of interesting!
But then, we discovered two things later that were quite remarkable. First, every infrastructural quantity you looked at from total length of roadways to the length of electrical lines to the length of gas lines, all the kinds of infrastructural things that are networked throughout a city, scaled in the same way as the number of gas stations. Namely, systematically, as you increase city size, I can tell you, roughly speaking, how many gas stations there are, what is the total length of roads, electrical lines, et cetera, et cetera. And it’s the same scaling in Europe, the United States, Japan and so on.
It is quite similar to biology. The exponent, instead of being three quarters was more like .85. So it’s a different exponent, but similar. But it’s an economy of scale.
The truly remarkable result was when we looked at quantities that I will call “socioeconomic”. That is, quantities that have no analog in biology. These are quantities, phenomena that did not exist until about 10,000 years ago when men and women started talking to one another and working together and forming serious communities leading to what we now call cities, i.e. things like wages, the number of educational institutions, the number of patents produced, et cetera. Things that have no analog in biology, things we invented.
And if you ask, first of all, do they scale? The answer is yes, in a regular way. Then, how do they scale? And this was the surprise to me; I’m embarrassed to say. It should have been obvious prior, but they scaled in what we called a super linear fashion. Instead of being an exponent less than one, indicating economies of scale, the exponent was bigger than one, indicating what economists call increasing returns to scale.
What does that say? That says that systematically, the bigger the city, the more wages you can expect, the more educational institutions in principle, more cultural events, more patents are produced, it’s more innovative and so on. Remarkably, all to the same degree. There was a universal exponent which turned out to be approximately 1.15 which translated to English says something like the following: If you double the size of a city from 50,000 to a hundred thousand, a million to two million, five million to ten million, it doesn’t matter what, systematically, you get a roughly 15 percent increase in productivity, patents, the number of research institutions, wages and so on, and you get systematically a 15 percent saving in length of roads and general infrastructure.
There are systematic benefits that come from increasing city size, both in terms of the individual getting something — which attracts people to the city, and in terms of the macroscopic economy. So the big cities are good in this sense.
However, some bad and ugly come with it. And the bad and ugly are things like a systematic increase in crime and various diseases, like AIDS, flu and so on. Interestingly enough, it scales all to the same 15 percent, if you double the size. Or put slightly differently, another way of saying it is, if you have a city of a million people and you broke it down into ten cities of a hundred thousand, you would require for that ten cities of a hundred thousand, 30 to 40 percent more roads, and 30 to 40 percent general infrastructure. And you would get a systematic decrease in wages and productivity and invention. Amazing. But you’d also get a decrease in crime, pollution and disease, systematically. So there are these trade-offs.
What does this mean? What is this coming from? And what do they imply? Let me just say one of the things that they imply.
If cities are dominated by wealth creation and innovation, i.e. the super linear scaling laws, there’s increasing returns to scale. How does that impact growth? What does that do for growth? Well, it turns out, of course, had it been biology and it had been dominated by economies of scale, you would have got a sigmoid curve, and you would have stopped growing. Bad for cities, we believe, and bad for economies.
Economies must be, in a capitalist system, ever expanding. It’s good that we have super linear scaling, because what that says is you have open-ended growth. And that’s very good. Indeed, if you can check it against data, it agrees very well. But there’s something very bad about open-ended growth.
One of the bad things about open-ended growth, growing faster than exponentially, is that open-ended growth eventually leads to collapse. It leads to collapse mathematically because of something called finite times singularity. You hit something that’s called a singularity, which is a technical term, and it turns out as you approach this singularity, the system, if it reaches it, will collapse. You have to avoid that singularity in order to stop collapsing. It’s great on the one hand that you have this open ended growth. But if you kept going, of course, it doesn’t make any sense. Eventually, you run out of resources anyway, but you would collapse. And that’s what the theory says.
How do you avoid that? Well, how have we avoided it? We’ve avoided it by innovation. By making a major innovation that so to speak, resets the clock and you can kind of start over again with new boundary conditions. We’ve done that by making major discoveries or inventions, like we discover iron, we discover coal. Or we invent computers, or we invent IT. But it has to be something that really changes the cultural and economic paradigm. It kind of resets the clock and we start over again.
There’s a theorem you can prove that says that if you demand continuous open growth, you have to have continuous cycles of innovation. Well, that’s what people believe, and it’s the way people have suggested that’s how you get out of the Malthusian paradox. This all agrees within itself but there is a huge catch.
I said earlier that in biology you have economies of scale, scaling that is sub linear, three quarters less than one, and that the pace of life gets slower the bigger you are. In cities and social systems, you have the opposite. You have the super linear scaling. You have increasing returns to scale. The bigger you are, the more you have rather than less.
It turns out when you go through the theoretical framework that leads to the opposite to biology the pace of life increases with size. So everything that’s going on in New York today is systematically going faster than it is in San Francisco, than it is in Santa Fe, even the speed of walking.
There’s data, and if you plot it, you will see that the speed of walking in cities, actually, I said the data is actually taken primarily in European cities, but you can see this systematic increase in some reasonable agreement with the theory.
The first thing is that we have this increasing pace of life. We have open-ended growth, increase in pace of life, and the threat of collapse because of the singularity. But there’s a big catch about this innovation. Theory says, sure, you can get out of collapse by innovating, but you have to innovate faster and faster.
Something that took 10,000 years 20,000 years ago to make a change, now takes 25 years. So this is not the clock that is governing social life. There’s a clock that’s getting faster and faster. And so you have to innovate faster and faster in order to avoid the collapse. And it all comes out of this exponential growth driven by super linear scaling.
The question then is, is this sustainable? The system will collapse, because eventually you would have to be making a major innovation, like you know, IT every six months. Well, that’s completely crazy. First of all, we’re human beings. We can’t adapt to that, even. But we can’t do it, so this is very threatening.
This leads then to all kinds of questions about global sustainability and how can you construct a conceptual framework that gives rise to having wealth creation, innovation, this kind of quality and standard of life, wealth production, and yet, not grow in such a way that you are probing the singularity and collapsing. That’s the challenge. That’s certainly something that we have to face.
Let me just say a few words about ideas as to why it is there’s scaling in cities. What we’ve shown is that there’s universality that on the one hand, you have this sub linear scaling, economies of scale for infrastructure like biology. But the dominant part of the city, wealth creation, innovation and the socio economic kinds of quantities, that have no analog in biology, scale super linearly.
This is true for any metric you want to think of and across the world. If you look at Japanese data or Chinese data or data from Chile or Colombia or the Netherlands or Portugal or the United States, it all looks the same. Yet these cities have nothing to do with one another.
It says that geography and history played a subdominant role as it did in biology in a sense. And so if you tell me the size of a city in the United States, I can tell you with some 85 percent accuracy how many police it would have, how many AIDS cases, how long the length of the roads are, how many patents it’s producing and so on, on the average.
Of course, you can use that as a baseline for talking about actual individual cities, how they over and underperform relative to this idealized scaling number. But the question is, where in the hell does that come from? What is it that’s universal that transcends countries and cultures?
Well obviously, it’s what cities are really about, not these buildings and the roads and things, but the people. It’s people. What we believe is that the scaling laws are a manifestation of social networks, of the universality of the way human beings interact, what we’re doing now, talking to one another, exchanging ideas, and doing tasks together, and so on.
It is the nature of those networks and the clustering — very importantly, the hierarchical clustering of those networks, the family structure, the way families interact, and then all the way out through businesses and so on, that there’s a kind of universality to that that is representative of the kind of scale at which humans interact.
For example, even though families in China and the United States traditionally may look different, most people cannot interact seriously, in a serious, dedicated way with more than five or six people. It doesn’t matter how big the family is actually. Despite Facebook, you cannot have a hundred best friends anywhere in the world.
These things are representative of the universal nature of the social networking. Our belief is that it is the nature of that and the hierarchy of it. For example, not only the hierarchy in size, but the hierarchy in the fact that you’re strongest interaction is with your family. You have a much weaker interaction with your colleagues in your job, and in your job situation, you have a much weaker interaction even with the CEO of the company, and all the way around the hierarchy. There is this presumed self-similar structure that goes up through the hierarchy in terms of the size of the hierarchy and in terms of the strength of interaction.
We believe it is that hierarchy which is transcending all of the aspects of the city and is being represented by these kinds of laws. So how is it that when we plot, we can plot GDP of the city, the number of AIDS cases and wages on one plot, and they overlap one another? They’re just the same line. Well, that’s because from this viewpoint, they’re all manifestations of people interacting with one another.
Predominately companies are dominated by economies of scale rather than innovation
The last piece of this is to take it to companies. Again, I must say that when I first started working on this, I just assumed companies were little cities so to speak. I also assumed they were dominated by creativity and so on.
It took us a long time to get data for companies, because unlike cities, you have to pay for that data. But we’ve just done it. (…)
In fact, we’ve done it primarily without paying attention to sector, although we’ve done some decomposition into sector. What I’m going to talk about here is regardless of sector. If you just take all companies equally for a moment, indeed, what you see if you plot the various metrics of a company from sales and profits, taxation, assets versus company size, using the metric of employees (you could use others — you could use sales itself but we used employees) you find scaling.
There’s much more variation, many more outliers among companies than there are among cities, and more among cities than there are among organisms. But nevertheless, you see very good evidence of scaling. And the thing that surprised us about this scaling was that it was like biology, not like cities. It was sub linear predominately.
That was surprising because sub linear in the kind of conceptual framework we developed was a reflection of economies of scale, and super linear as a reflection of wealth creation and innovation. It is said that predominately companies are dominated by economies of scale rather than innovation.
If it were dominated by economies of scale, sub linear scaling, unlike cities (which have open ended growth) companies would grow and then stop growing. And not only that, if you extrapolated from biology, they would indeed, die, ultimately.
We looked at the growth curves as the metrics of the company, like its assets or its profits, as a function of time, or its number of employees as a function of time. Indeed, the generic behavior is a sigmoid. They grow fast and they stop. All the big companies stop at roughly the same value, which is intriguing of it self. I think that number is about half a trillion dollars.
We have a wonderful graph that has about ten thousand companies plotted on one graph and they are these growth curves. You see this kind of spaghetti looking graph by just eyeballing it. Everything grows and stops growing. That’s what it looks like. We’re still in the middle of analyzing a lot of this.
The picture emerges. Companies are more like organisms. They grow and asymptote. Cities are open ended.
More importantly, what we discovered is that on the one hand, sales increased linearly with company size. On the other hand, profits increased sub linearly of an exponent of about one eighth. This data is all U.S. data on publicly traded companies.
Sales to profits are systematically decreasing so that eventually, the profit to sales margin is going to zero. If you just extrapolate this, indeed, if you look at the data, you see that the fluctuations in all these quantities are proportional to the size of the company. The fluctuation is getting bigger and bigger. The profits are decreasing relative to sales. Even though the profits are increasing the bigger you are, where you think, “we made several billion dollars” what you realize is that you’re in an environment where the fluctuation is eventually bigger than that. This is possibly the mechanism by which companies die.
Let me tell you the interpretation. Again, this is still speculative.
The great thing about cities, the thing that is amazing about cities is that as they grow, so to speak, their dimensionality increases. That is, the space of opportunity, the space of functions, the space of jobs just continually increases. And the data shows that. If you look at job categories, it continually increases. I’ll use the word “dimensionality.” It opens up. And in fact, one of the great things about cities is that it supports crazy people. You walk down Fifth Avenue, you see crazy people, and there are always crazy people. Well, that’s good. It is tolerant of extraordinary diversity.
This is in complete contrast to companies, with the exception of companies maybe at the beginning (think of the image of the Google boys in the back garage, with ideas of the search engine no doubt promoting all kinds of crazy ideas and having maybe even crazy people around them).
Well, Google is a bit of an exception because it still tolerates some of that. But most companies start out probably with some of that buzz. But the data indicates that at about 50 employees to a hundred, that buzz starts to stop. And a company that was more multi dimensional, more evolved becomes one-dimensional. It closes down.
Indeed, if you go to General Motors or you go to American Airlines or you go to Goldman Sachs, you don’t see crazy people. Crazy people are fired. Well, to speak of crazy people is taking the extreme. But maverick people are often fired.
It’s not surprising to learn that when manufacturing companies are on a down turn, they decrease research and development, and in fact in some cases, do actually get rid of it, thinking “oh, we can get that back, in two years we’ll be back on track.”
Well, this kind of thinking kills them. This is part of the killing, and this is part of the change from super linear to sublinear, namely companies allow themselves to be dominated by bureaucracy and administration over creativity and innovation, and unfortunately, it’s necessary. You cannot run a company without administrative. Someone has got to take care of the taxes and the bills and the cleaning the floors and the maintenance of the building and all the rest of that stuff. You need it. And the question is, “can you do it without it dominating the company?” The data suggests that you can’t.
The question is, as a scientist, can we take these ideas and do what we did in biology, at least based on networks and other ideas, and put this into a quantitative, mathematizable, predictive theory, so that we can understand the birth and death of companies, how that stimulates the economy? How it’s related to cities? How does it affect global sustainability and have a predictive framework for an idealized system, so that we can understand how to deal with it and avoid it? If you’re running a bigger company, you can recognize what the metrics are that are driving you to mortality, and possibly put it off, and hopefully even avoid it.
Otherwise we have a theory that tells you when Google and Microsoft will eventually die, and die might mean a merger with someone else.
That’s the idea and that’s the framework, and that’s what this is.”
Geoffrey West: The surprising math of cities and corporations
Physicist Geoffrey West has found that simple, mathematical laws govern the properties of cities — that wealth, crime rate, walking speed and many other aspects of a city can be deduced from a single number: the city’s population. In this mind-bending talk from TEDGlobal he shows how it works and how similar laws hold for organisms and corporations.
Why Cities Keep on Growing, Corporations Always Die, and Life Gets Faster | Fora.tv
As organisms, cities, and companies scale up, they all gain in efficiency, but then they vary. The bigger an organism, the slower. Yet the bigger a city is, the faster it runs. And cities are structurally immortal, while corporations are structurally doomed. Scaling up always creates new problems; cities can innovate faster than the problems indefinitely, while corporations cannot.
These revolutionary findings come from Geoffrey West’s examination of vast quantities of data on the metabolic/economic behavior of organisms and organizations. A theoretical physicist, West was president of Santa Fe Institute from 2005 to 2009 and founded the high energy physics group at Los Alamos National Laboratory.
Smart phones are giving researchers a “god’s-eye view of human behavior”
Researchers are harvesting a wealth of intimate detail from our cellphone data, uncovering the hidden patterns of our social lives, travels, risk of disease—even our political views.
“Through these and other cellphone research projects, scientists are able to pinpoint “influencers,” the people most likely to make others change their minds. The data can predict with uncanny accuracy where people are likely to be at any given time in the future. Cellphone companies are already using these techniques to predict—based on a customer’s social circle of friends—which people are most likely to defect to other carriers.
The data can reveal subtle symptoms of mental illness, foretell movements in the Dow Jones Industrial Average, and chart the spread of political ideas as they move through a community much like a contagious virus, research shows. In Belgium, researchers say, cellphone data exposed a cultural split that is driving a historic political crisis there. (…)
By analyzing changes in movement and communication patterns, researchers could also detect flu symptoms before the students themselves realized they were getting sick.
“Phones can know,” said Dr. Pentland, director of MIT’s Human Dynamics Laboratory, who helped pioneer the research. “People can get this god’s-eye view of human behavior.” (…)
Advances in statistics, psychology and the science of social networks are giving researchers the tools to find patterns of human dynamics too subtle to detect by other means. At Northeastern University in Boston, network physicists discovered just how predictable people could be by studying the travel routines of 100,000 European mobile-phone users.
After analyzing more than 16 million records of call date, time and position, the researchers determined that, taken together, people’s movements appeared to follow a mathematical pattern. The scientists said that, with enough information about past movements, they could forecast someone’s future whereabouts with 93.6% accuracy.
The pattern held true whether people stayed close to home or traveled widely, and wasn’t affected by the phone user’s age or gender.
“For us, people look like little particles that move in space and that occasionally communicate with each other,” said Northeastern physicist Albert-Laszlo Barabasi, who led the experiment. “We have turned society into a laboratory where behavior can be objectively followed.” (…)
“We can quantify human movement on a scale that wasn’t possible before,” said Nathan Eagle, a research fellow at the Santa Fe Institute in New Mexico who works with 220 mobile-phone companies in 80 countries. “I don’t think anyone has a handle on all the ramifications.” His largest single research data set encompasses 500 million people in Latin America, Africa and Europe.
Among other things, Mr. Eagle has used the data to determine how slums can be a catalyst for a city’s economic vitality. In short, slums provide more opportunities for entrepreneurial activity than previously thought. Slums “are economic springboards,” he said.
Cellphone providers are openly exploring other possibilities. By mining their calling records for social relationships among customers, several European telephone companies discovered that people were five times more likely to switch carriers if a friend had already switched, said Mr. Eagle, who works with the firms. The companies now selectively target people for special advertising based on friendships with people who dropped the service. (…)
As more people access the Internet through their phones, the digital universe of personal detail funneled through these handsets is expanding rapidly, and so are ways researchers can use the information to gauge behavior. Dr. Bollen and his colleagues, for example, found that the millions of Twitter messages sent via mobile phones and computers every day captured swings in national mood that presaged changes in the Dow Jones index up to six days in advance with 87.6% accuracy. (…)
One study found that the U.K.’s happiest time is 8 p.m. Saturday; its unhappiest day is Tuesday.
European phone companies discovered their customers were five times more likely to switch carriers if friends had switched, allowing the companies to target their ads.
Another study was able to determine that two people were talking about politics—without the researchers hearing the call
“It is not just about observing what is happening; it is about shaping what is happening,” said Dr. Bollen. “The patterns are allowing us to learn how to better manipulate trends, opinions and mass psychology.” (…)
Environmental economist George MacKerron at the London School of Economics recruited 40,000 volunteers through an iPhone app he designed, called Mappiness, to measure emotions in the U.K.
At random moments every day, his iPhone app prompts the users to report their moods, activities, and surroundings. The phone also automatically relays the GPS coordinates of the user’s location and rates nearby noise levels by using the unit’s microphone. It asks permission to photograph the locale. (…)
On a more scholarly level, Mr. MacKerron is collecting the information to study the relationship between moods, communities and the places people spend time. To that end, Mr. MacKerron expects to link the information to weather reports, online mapping systems and demographics databases. (…)
When mathematician Vincent Blondel studied the location and billing data from one billion cellphone calls in Belgium, he found himself documenting a divide that has threatened his country’s ability to govern itself.
Split by linguistic differences between a Flemish-speaking north and a French-speaking south, voters in Belgium set a world record this year, by being unable to agree on a formal government since holding elections last June. Belgium’s political deadlock broke a record previously held by Iraq.
The calling patterns from 600 towns revealed that the two groups almost never talked to each other, even when they were neighbors.
This social impasse, as reflected in relationships documented by calling records, “had an impact on the political life and the discussions about forming a government,” said Dr. Blondel at the Catholic University of Louvain near Brussels, who led the research effort.
The MIT smartphone experiment is designed to delve as deeply as possible into daily life. For his work, Dr. Pentland gave volunteers free Android smartphones equipped with software that automatically logged their activities and their proximity to other people. The participants also filed reports on their health, weight, eating habits, opinions, purchases and other personal information, so the researchers could match the phone data to relationships and behavior.
The current work builds on his earlier experiments, beginning in 2004, conducted in an MIT dormitory that explored how relationships influence behavior, health, eating habits and political views. (…)
“Just by watching where you spend time, I can say a lot about the music you like, the car you drive, your financial risk, your risk for diabetes. If you add financial data, you get an even greater insight,” said Dr. Pentland. “We are trying to understand the molecules of behavior in this really complete way.”
Almost a third of the students changed their political opinions during the three months. Their changing political ideas were related to face-to-face contact with project participants of differing views, rather than to friends or traditional campaign advertising, the analysis showed.
“We can measure their daily exposure to political opinions,” said project scientist Anmol Madan at MIT’s Media Lab. “Maybe one day, you would be able to download a phone app to measure how much Republican or Democratic exposure you are getting and, depending on what side you’re on, give you a warning.”
“The way we talk about complex and abstract ideas is suffused with metaphor. In five experiments, we explore how these metaphors influence the way that we reason about complex issues and forage for further information about them. We find that even the subtlest instantiation of a metaphor (via a single word) can have a powerful influence over how people attempt to solve social problems like crime and how they gather information to make “well-informed” decisions. Interestingly, we find that the influence of the metaphorical framing effect is covert: people do not recognize metaphors as influential in their decisions; instead they point to more “substantive” (often numerical) information as the motivation for their problem-solving decision. Metaphors in language appear to instantiate frame-consistent knowledge structures and invite structurally consistent inferences. Far from being mere rhetorical flourishes, metaphors have profound influences on how we conceptualize and act with respect to important societal issues. We find that exposure to even a single metaphor can induce substantial differences in opinion about how to solve social problems. (…)
Even fleeting and seemingly unnoticed metaphors in natural language can instantiate complex knowledge structures and influence people’s reasoning in a way that is similar to the role that schemas, scripts, and frames have been argued to play in reasoning and memory. (…)
We find that the metaphors were most effective when they were presented early in the narrative and were then able to help organize and coerce further incoming information. (…)
Through analogical transfer in this way, systems of metaphors in language can encourage the creation of systems of knowledge in a wide range of domains. Our reasoning about many complex domains then can be mediated through these patchworks of analogically-created representations. A final question is how strong the influence of metaphorical framing really is? Focusing on a real-world social issue like crime allows us to compare the effects of metaphor we observe in the lab with the opinion differences that exist naturally in the population. People with different political affiliations hold different opinions on how to address societal problems like crime. (…)
Analysis reveals a striking effect of metaphor as measured against real-world differences in opinion that exist in the population and impact policy-making. Interestingly, we found that self-identified Republicans were also less likely to be influenced by the metaphors than were Democrats and Independents. (…)
The studies presented in this paper demonstrate that even minimal (one-word) metaphors can significantly shift people’s representations and reasoning about important real-world domains. These findings suggest that people don’t have a single integrated representation of complex issues like crime, but rather rely on a patchwork of (sometimes disconnected or inconsistent) representations and can (without realizing it) dynamically shift between them when cued in context.
Metaphor is incredibly pervasive in everyday discourse. By some estimates, English speakers produce one unique metaphor for every 25 words that they utter. Metaphor is clearly not just an ornamental flourish, but a fundamental part of the language system. This is particularly true in discussions of social policy, where it often seems impossible to “literally” discuss immigration, the economy, or crime. If metaphors routinely influence how we make inferences and gather information about the social problems that confront us, then the metaphors in our linguistic system may be offering a unique window onto how we construct knowledge and reason about complex issues. (…)
We find that metaphors can have a powerful influence over how people attempt to solve complex problems and how they gather more information to make “well-informed” decisions. Our findings shed further light on the mechanisms through which metaphors exert their influence, by instantiating frame-consistent knowledge structures, and inviting structurally-consistent inferences. Interestingly, the influence of the metaphorical framing is covert: people do not recognize metaphors as an influential aspect in their decisions. Finally, the influence of metaphor we find is strong: different metaphorical frames created differences in opinion as big or bigger than those between Democrats and Republicans.”
“Orientalism was ultimately a political vision of reality whose structure promoted the difference between the familiar (Europe, the West, ‘us’) and the strange (the Orient, the East, ‘them’)” — Edward Said, Orientalism (1978)
“Academics are thrilled with the “other” and the vagaries of how we represent the foreign. By profession, anthropologists are visitors from afar. We are outsiders, writes an anthropologist, “seeking to understand unfamiliar cultures.” Humanists and social theorists also have fallen in love with the “other.” A recent paper by the literary critic Toril Moi is titled “Literature, Philosophy, and the Question of the Other.” In a recent issue of Signs, a philosopher writes about “Occidental Dreams: Orientalism and History in ‘The Second Sex.’”
The romance with the “other,” the Orient, and the stranger, however, diverts attention from something less sexy: the familiar. For those concerned with strife and violence in the world, like Said, the latter may, in fact, be more critical than the strange and the foreign. If the Lebanese Civil War, which lasted 15 years, can highlight something about how the West represents the East, it can also foreground a neglected truth: The most decisive antagonisms and misunderstandings take place within a community. The history of hatred and violence is, to a surprising degree, a history of brother against brother, not brother against stranger. From Cain and Abel to the religious wars of the 16th and 17th centuries and the civil wars of our own age, it is not so often strangers who elicit hatred, but neighbors.
This observation contradicts both common sense and the collective wisdom of teachers and preachers, who declaim that we fear—sometimes for good reason—the unknown and dangerous stranger. Citizens and scholars alike believe that enemies lurk in the street and beyond the street, where we confront a “clash of civilizations” with foreigners who challenge our way of life.
The truth is more unsettling. From assault to genocide, from assassination to massacre, violence usually emerges from inside the fold rather than outside it. (…)
We may obsess about strangers piloting airplanes into our buildings, but in the United States in any year, roughly five times the number of those killed in the World Trade Center are murdered on the streets or inside their own homes and offices. These regular losses remind us that most criminal violence takes place between people who know each other. Cautious citizens may push for better street lighting, but they are much more likely to be assaulted, even killed, in the light of the kitchen by someone familiar than in a parking garage by a stranger. Like, not unlike, prompts violence.
Civil wars are generally more savage, and bear more lasting consequences, than wars between countries. Many more people died in the American Civil War—at a time when the population was a tenth of what it is today—than in any other American conflict, and its long-term effects probably surpass those of the others. Major bloodlettings of the 20th century—hundreds of thousands to millions of deaths—occurred in civil wars such as the Russian Civil War, the Chinese Civil Wars of 1927-37 and 1945-49, and the Spanish Civil War. More Russian lives were lost in the Russian Civil War that followed World War I than in the Great War itself, for instance.
But who cares about the Russian Civil War? A thousand books and courses dwell on World War I, but few on the Russian Civil War that emerged from it. That war, with its fluid battle lines, uncertain alliances, and clouded beginning, seems too murky. The stew of hostilities is typical of civil wars, however. With some notable exceptions, modern civil wars resist the clear categories of interstate wars. The edges are blurred. Revenge often trumps ideology and politics.
Yet civil strife increasingly characterizes the contemporary world. “Most wars are now civil wars,” announces the first sentence of a World Bank publication. Not only are there more civil wars, but they last longer. The conflicts in southern Sudan have been going on for decades. Lengthy battles between states are rare nowadays. And when states do attack, the fighting generally doesn’t last long (for example, Israel’s monthlong incursion into Lebanon in 2006). The recent wars waged by the United States in Iraq and Afghanistan are notable exceptions.
We live in an era of ethnic, national, and religious fratricide. A new two-volume reference work on “the most severe civil wars since World War II” has 41 entries, from Afghanistan and Algeria to Yemen and Zimbabwe. Over the last 50 years, the number of casualties of intrastate conflicts is roughly five times that of interstate wars. The number of refugees from these conflicts similarly dwarfs those from traditional state-versus-state wars. “Cases such as Afghanistan, Somalia, and Lebanon testify to the economic devastation that civil wars can produce,” note two political scientists. By the indexes of deaths, numbers of refugees, and extent of destruction, they conclude that “civil war has been a far greater scourge than interstate war” in recent decades. In Iraq today—putting aside blame and cause—more Iraqis are killed by their countrymen than by the American military.
“Not surprisingly, there is no treatise on civil war on the order of Carl von Clausewitz’s On War,” writes the historian Arno Mayer, “civil wars being essentially wild and savage.”
The iconic book by Carl von Clausewitz, the Prussian military thinker, evokes the spirit of Immanuel Kant, whose writings he studied. Subheadings such as “The Knowledge in War Is Very Simple, but Not, at the Same Time, Very Easy” suggest its philosophical structure. Clausewitz subordinated war to policy, which entailed a rational evaluation of goals and methods. He compared the state to an individual. “Policy” is “the product of its brain,” and war is an option. “No one starts a war—or rather, no one in his senses ought to do so—without first being clear in his mind what he intends to achieve by that war and how he intends to conduct it.” If civilized nations at war “do not put their prisoners to death” or “devastate cities,” he writes, it is because “intelligence plays a larger part in their methods of warfare … than the crude expressions of instinct.”
In civil wars, by contrast, prisoners are put to death and cities destroyed as a matter of course. The ancient Greeks had already characterized civil strife as more violent than traditional war.Plato distinguishes war against outsiders from what he calls factionalized struggles, that is, civil wars. He posits that Greeks practice war against foreigners (“barbarians”), a conflict marked by “enmity and hatred,” but not against one another. When Greeks fight Greeks, he believes, they should temper their violence in anticipation of reconciliation. “They will not, being Greeks, ravage Greek territory nor burn habitations,” nor “lay waste the soil,” nor treat all “men, women, and children” as their enemies. Such, at least, was his hope in the Republic, but the real world often contradicted it, as he knew. His proposition that Greeks should not ravage Greeks challenged the reality in which Greeks did exactly that.
Plato did not have to look further than Thucydides’ account of the Peloponnesian War to find confirmation of the brutality of Greek-on-Greek strife. In a passage often commented on, Thucydides wrote of the seesaw battle in Corcyra (Corfu) in 433 BC, which prefigured the larger war. When the Athenians approached the island in force, the faction they supported seized the occasion to settle accounts with its adversaries. In Thucydides’ telling, this was a “savage” civil war of Corcyrean against Corcyrean. For the seven days the Athenians stayed in the harbor, Corcyreans “continued to massacre those of their own citizens” they considered enemies. “There was death in every shape and form,” writes Thucydides. “People went to every extreme and beyond it. There were fathers who killed their sons; men were dragged from the temples or butchered on the very altars.” Families turned on families. “Blood ties became more foreign than factional ones.” Loyalty to the faction overrode loyalty to family members, who became the enemy.
Nearly 2,500 years after Thucydides, the presiding judge at a United Nations trial invoked the Greek historian. The judge reflected on what had occurred in the former Yugoslavia. One Duško Tadić stood accused of the torture and murder of Muslims in his hometown in Bosnia-Herzegovina. His actions exemplified a war of ethnic cleansing fueled by resentment and hatred. “Some time ago, yet not far from where the events in this case happened,” something similar occurred, stated a judge in his 1999 opinion. He cited Thucydides’ description of the Corcyrean civil war as one of “savage and pitiless actions.” Then as today, the judge reminded us, men “were swept away into an internecine struggle” in which vengeance supplanted justice.
Today’s principal global conflicts are fratricidal struggles—regional, ethnic, and religious: Iraqi Sunni vs. Iraqi Shiite, Rwandan Tutsi vs. Rwandan Hutu, Bosnian Muslim vs. Balkan Christians, Sudanese southerners vs. Sudanese northerners, perhaps Libyan vs. Libyan. As a Rwandan minister declared about the genocide in which Hutus slaughtered Tutsis: “Your neighbors killed you.” A reporter in northeastern Congo wrote that in seven months of fighting there, several thousand people were killed and more than 100,000 driven from their homes. He commented, “Like ethnic conflicts around the globe, this is fundamentally a fight between brothers: The two tribes—the Hema and the Lendu—speak the same language, marry each other, and compete for the same remote and thickly populated land.”
Somalia is perhaps the signal example of this ubiquitous fratricidal strife. As a Somalian-American professor observed, Somalia can claim a “homogeneity rarely known elsewhere in Africa.” The Somalian people “share a common language (Somali), a religion (Islam), physical characteristics, and pastoral and agropastoral customs and traditions.” This has not tempered violence. On the contrary.
The proposition that violence derives from kith and kin overturns a core liberal belief that we assault and are assaulted by those who are strangers to us. If that were so, the solution would be at hand: Get to know the stranger. Talk with the stranger. Reach out. The cure for violence is better communication, perhaps better education. Study foreign cultures and peoples. Unfortunately, however, our brother, our neighbor, enrages us precisely because we understand him. Cain knew his brother—he “talked with Abel his brother”—and slew him afterward.
We don’t like this truth. We prefer to fear strangers. We like to believe that fundamental differences pit people against one another, that world hostilities are driven by antagonistic principles about how society should be constituted. To think that scale—economic deprivation, for instance—rather than substance divides the world seems to trivialize the stakes. We opt instead for a scenario of clashing civilizations, such as the hostility between Western and Islamic cultures. The notion of colliding worlds is more appealing than the opposite: conflicts hinging on small differences. A “clash” implies that fundamental principles about human rights and life are at risk.
Samuel Huntington took the phrase “clash of civilizations” from the Princeton University historian Bernard Lewis, who was referring to a threat from the Islamic world. “We are facing a mood and a movement far transcending the level of issues and policies,” Lewis wrote in 1990. “This is no less than a clash of civilizations” and a challenge to “our Judeo-Christian heritage.” For Huntington, “the underlying problem for the West is not Islamic fundamentalism. It is Islam, a different civilization.” (…)
Or consider the words of a Hindu nationalist who addressed the conflict with Indian Muslims. How is unity to come about, she asks? “The Hindu faces this way, the Muslim the other. The Hindu writes from left to right, the Muslim from right to left. The Hindu prays to the rising sun, the Muslim faces the setting sun when praying. If the Hindu eats with the right hand, the Muslim with the left. … The Hindu worships the cow, the Muslim attains paradise by eating beef. The Hindu keeps a mustache, the Muslim always shaves the upper lip.”
Yet the preachers, porte-paroles, and proselytizers may mislead; it is in their interest to do so. What divided the Protestants and Catholics in 16th-century France, the Germans and Jews in 20th-century Europe, and the Shia and Sunni today may be small, not large. But minor differences rankle more than large differences. Indeed, in today’s world, it may be not so much differences but their diminution that provokes antagonism. Here it can be useful to attend the literary critic René Girard, who also bucks conventional wisdom by signaling the danger in similitude, not difference: “In human relationships, words like ‘sameness’ and ‘similarity’ evoke an image of harmony. If we have the same tastes and like the same things, surely we are bound to get along. But what will happen when we share the same desires?” However, for Girard, “a single principle” pervades religion and literature. “Order, peace, and fecundity depend on cultural distinctions; it is not these distinctions but the loss of them that gives birth to fierce rivalries and sets members of the same family or social group at one another’s throats.”
Likeness does not necessarily lead to harmony. It may elicit jealousy and anger. Inasmuch as identity rests on what makes an individual unique, similitude threatens the self. The mechanism also operates on social terrain. As cultural groups get absorbed into larger or stronger collectives, they become more anxious—and more prone to defend their dwindling identity. French Canadians—living as they do amid an ocean of English speakers—are more testy about their language than the French in France. Language, however, is just one feature of cultural identification.
Assimilation becomes a threat, not a promise. It spells homogenization, not diversity. The assimilated express bitterness as they register the loss of an identity they wish to retain. Their ambivalence transforms their anger into resentment. They desire what they reject and are consequently unhappy with themselves as well as their interlocutor. Resentment feeds protest and sometimes violence. Insofar as the extreme Islamists sense their world imitating the West, they respond with increased enmity. It is not so much the “other” as it is the absence of otherness that spurs anger. They fear losing themselves by mimicking the West. A Miss World beauty pageant in Nigeria spurred widespread riots by Muslims that left hundreds dead. This could be considered a violent rejection of imitation.
We hate the neighbor we are enjoined to love. Why? Why do small disparities between people provoke greater hatred than the large ones? Perhaps the work of Freud helps chart the underground sources of fratricidal violence. Freud introduced the phrase the “narcissism of minor differences” to describe this phenomenon. He noted that “it is precisely the little dissimilarities in persons who are otherwise alike that arouse feelings of strangeness and enmity between them.”
Freud first broached the narcissism of minor differences in “The Taboo of Virginity,” an essay in which he also took up the “dread of woman.” Is it possible that these two notions are linked? That the narcissism of minor differences, the instigator of enmity, arises from differences between the sexes and, more exactly, man’s fear of woman? What do men fear? “Perhaps,” Freud hazards, the dread is “founded on the difference of woman from man.” More precisely, “man fears that his strength will be taken from him by woman, dreads becoming infected with her femininity” and that he will show himself to be a “weakling.” Might this be a root of violence, man’s fear of being unmanned?
The sources of hatred and violence are many, not singular. There is room for the findings of biologists, sociobiologists, and other scientists. For too long, however, social and literary scholars have dwelled on the “other” and its representation. It is interesting, even uplifting, to talk about how we see and don’t see the stranger. It is less pleasant, however, to tackle the divisiveness and rancor of countrymen and kin. We still have not caught up to Montaigne, with his famous remarks about Brazilian cannibals. He reminded his 16th-century readers not only that the mutual slaughter of Huguenots and Catholics eclipsed the violence of New World denizens—it was enacted on the living, and not on the dead—but that its agents were “our fellow citizens and neighbors.”
Stephen M. Walt on What Does Social Science Tell Us about Intervention in Libya
“Recent research suggests that we are likely to be disappointed by the outcome. A 2006 study by Jeffrey Pickering and Mark Peceny found that military intervention by liberal states (i.e., states like Britain, France and the United States) “has only very rarely played a role in democratization since 1945.”Similarly, George Downs, and Bruce Bueno de Mesquita of New York University found that U.S. interventions since World War II led to stable democracies within ten years less than 3 percent of the time, and a separate study by their NYU colleague William Easterly and several associates found that both U.S and Soviet interventions during the Cold War generally led to “significant declines in democracy.” Finally, a 2010 article by Goran Piec and Daniel Reiter examines forty-two “foreign imposed regime changes” since 1920 and finds that when interventions “damage state infrastructural power” they also increase the risk of subsequent civil war.
The best and most relevant study I have yet read on this question is an as-yet unpublished working paper by Alexander Downes of Duke University, which you can find on his website here. Using a more sophisticated research design, Downes examined 100 cases of “foreign imposed regime change” going all the way back to 1816. In particular, his analysis takes into account “selection effects” (i.e., the fact that foreign powers are more likely to intervene in states that already have lots of problems, so you would expect these states to have more problems afterwards too). He finds that foreign intervention tends to promote stability when the intervening powers are seeking to restore a previously deposedruler. But when foreign interveners oust an existing ruler and impose a wholly new government (which is what we are trying to do in Libya), the likelihood of civil war more than triples.
Why? According to Downes, because deposing an existing regime and bringing new leaders to power “disrupts state power and foments grievances and resentments.” To make matter worse, the probability of civil war in the aftermath of foreign imposed regime change increases even more when it is accompanied by defeat in inter-state war, and when it occurs in poor and ethnically heterogeneous countries.” This isn’t reassuring either, given that Libya’s is still a poor society (because the Qaddafi family monopolizes the oil revenues) and it remains divided into potentially fractious tribes.
Here’s the bottom line:
“[Foreign imposed regime change] is likely to spur resistance and civil war in those countries where the United States and other advanced democracies are most likely to undertake such intervention [i.e., poor, weak states]; the situation is made even bleaker if war is needed to overthrow the existing regime… [O]verthrowing other governments (and bringing new leaders to power rather than restoring previous rulers) is a policy instrument with limited utility because of its potential to ignite civil wars. These conflicts may in turn result in the imposed regime’s ouster or draw interveners into costly occupations.”
By the way, Downes also has another paper (co-authored with Jonathan Monten of the LSE) which finds that “states that have their governments removed by a democracy gain no significant democratic benefit compared to similar states that do not experience intervention.” Democratic intervention does have positive effects (on average) in relatively wealthy and homogeneous societies, but “evidence from past experience suggests that imposed regime change by democratic states is unlikely to be an effective means of spreading democracy,” especially when one factors in the costs.
We should all hope that Libya proves to be an exception to this tendency, but these various scholarly studies suggest that the probability that our intervention will yield a stable democracy is low, and that our decision to intervene has increased the likelihood of civil war. Heading off that possibility is likely to require a costly and extended international commitment, which is precisely what the people who launched this operation promised they would not do. We’ll see.”
Sam Harris on the ‘selfish gene’ and moral behavior
“Many people imagine that the theory of evolution entails selfishness as a biological imperative. This popular misconception has been very harmful to the reputation of science. In truth, human cooperation and its attendant moral emotions are fully compatible with biological evolution. Selection pressure at the level of ‘selfish’ genes would surely incline creatures like ourselves to make sacrifices for our relatives, for the simple reason that one’s relatives can be counted on to share one’s genes: while this truth might not be obvious through introspection, your brother’s or sister’s reproductive success is, in part, your own. This phenomenon, known askin selection, was not given a formal analysis until the 1960s in the work of William Hamilton, but it was at least implicit in the understanding of earlier biologists. Legend has it that J.B.S. Haldane was once asked if he would risk his life to save a drowning brother, to which he quipped, ‘No, but I would save two brothers or eight cousins.’
The work of evolutionary biologist Robert Trivers on reciprocal altruismhas gone a long way toward explaining cooperation among unrelated friends and strangers. Trivers’s model incorporates many of the psychological and social factors related to altruism and reciprocity, including friendship, moralistic aggression (i.e., the punishment of cheaters), guilt, sympathy, and gratitude, along with a tendency to deceive others by mimicking these states. As first suggested by Darwin, and recently elaborated by the psychologist Geoffrey Miller, sexual selection may have further encouraged the development of moral behavior. Because moral virtue is attractive to both sexes, it might function as a kind of peacock’s tail: costly to produce and maintain, but beneficial to one’s genes in the end.
Clearly, our selfish and selfless interests do not always conflict. In fact, the well-being of others, especially those closest to us, is one of our primary (and, indeed, most selfish) interests. While much remains to be understood about the biology of our moral impulses, kin selection, reciprocal altruism, and sexual selection explain how we have evolved to be, not merely atomized selves in thrall to our self-interest, but social selves disposed to serve a common interest with others.”
The “weak evidence effect”. Weak supporting evidence can undermine belief in an outcome
“New research shows that people who receive weak but supportive evidence about a proposition are less optimistic about the outcome than people who receive no evidence at all. The “weak evidence effect” could be a useful tool in communications, from marketing to political discourse. (…)
Consider the following statement: “Widespread use of hybrid and electric cars could reduce worldwide carbon emissions. One bill that has passed the Senate provides a $250 tax credit for purchasing a hybrid or electric car. How likely is it that at least one-fifth of the U.S. car fleet will be hybrid or electric in 2025?”
That middle sentence is the weak evidence. People presented with the entire statement — or similar statements with the same three-sentence structure but on different topics — answered the final question lower than people who read the statement without the middle sentence. They did so even though other people who saw the middle statement in isolation rated it as positive evidence for, in this case, higher adoption of hybrid and electric cars.
“It’s not a conscious choice to behave this way,” said Sloman. “When people are thinking forward in a causal direction, they just think about the cause they have in mind and the mechanism by which that would lead to the consequence they have in mind. They neglect alternative causes.”
Fernbach, the paper’s first author, put it this way: “People take what you suggest and run with it.”
Give people a weak reason and they’ll focus too much on it. Give people no evidence and they’ll supply their own probably more convincing reason to believe that the outcome is likely.”
“We attribute the weak evidence effect to the process by which people use their causal knowledge to predict effects from their causes. People do so by retrieving relevant causal variables and embedding them in a mental model that supports forward inference via simulation. No judge can be expected to consider every relevant cause. Instead, people tend to restrict attention to a single mechanism. When reasoning about a conditional probability, people focus on the conditioned-on cause leading to low judgments. When judging a marginal probability however, people begin at a different point, by retrieving more available causes, leading to higher judgments.
A similar logic explains why unpacking a hypothesis into atypical constituents decreases judgment. Unpacking the description of an event, like ‘‘death from disease’’, into constituents, like ‘‘death from heart disease or some other disease’’ usually increases the judged probability of the event. This is analogous to the present case in which mentioning a weak cause leads to neglect of alternative causes. Rottenstreich and Tversky (1997) showed that a causal partition leads to a greater unpacking effect than a temporal partition, consistent with the claim that causes crowd one another out.
One explanation for this is that people focus too much on the mechanism connecting the cause and the effect when assessing the conjunction. Focusing on the strength of the causal relation leads people to neglect the base rate and judge the conjunction fairly high. In the marginal case however, the absence of readily available causes leads to low judgments. (…)
McKenzie, Lee, and Chen (2002) have shown that when reasoning in the context of an argument with opposing sides, weak evidence of innocence will sometimes increase belief in guilt. They argue that this phenomenon emerges because sides in a dispute are motivated to provide the strongest possible case; a weak case implies an inability to amass strong evidence. Evaluating evidence relative to the strength of an expectation is often called for, but our results cannot be explained in this way. (…)
Lopes (1985) reports that in a Bayesian updating task, observing weak evidence favoring a hypothesis after having just seen strong evidence leads some people to (incorrectly) adjust their judgment downward (for evidence concerning a related phenomenon, the ‘dilution effect,’ see Nisbett, Zukier, & Lemley, 1981; Shanteau, 1975). This could reflect a general tendency to evaluate evidence with respect to comparisons in the immediate environment rather than with respect to its absolute value. The analogy to the current findings is tenuous though because the weak evidence effect emerges from considering a single piece of evidence and not from integrating over multiple samples. (…)
Awareness of the weak evidence effect may help people avoid being persuaded when it is used as a rhetorical tool. (…)
The law of total probability implies that if event A raises the probability of event B, the probability of event B must be higher when A is present than when it is unknown. The weak evidence effect is a violation of this basic norm of probability theory. This violation arises because people focus on what they perceive in their immediate environment and neglect other information, a tendency that is ubiquitous in human cognition. It arises when people reason, test hypotheses, understand language, troubleshoot, and make categorical judgments. Such focus may often be a reasonable approximation strategy, but it sometimes leads to error.”
Malcolm Gladwell, Adam Gopnik and Evgeny Morozov on the role of social networking technology in social activism
Malcolm Gladwell - Why the revolution will not be tweeted:
“The new tools of social media have reinvented social activism. (…) Where activists were once defined by their causes, they are now defined by their tools. (…)
As the historian Robert Darnton has written, “The marvels of communication technology in the present have produced a false consciousness about the past—even a sense that communication has no history, or had nothing of importance to consider before the days of television and the Internet.” (…)
One study of the Red Brigades, the Italian terrorist group of the nineteen-seventies, found that seventy per cent of recruits had at least one good friend already in the organization. The same is true of the men who joined the mujahideen in Afghanistan. Even revolutionary actions that look spontaneous, like the demonstrations in East Germany that led to the fall of the Berlin Wall, are, at core, strong-tie phenomena. The opposition movement in East Germany consisted of several hundred groups, each with roughly a dozen members. Each group was in limited contact with the others: at the time, only thirteen per cent of East Germans even had a phone. All they knew was that on Monday nights, outside St. Nicholas Church in downtown Leipzig, people gathered to voice their anger at the state. And the primary determinant of who showed up was “critical friends”—the more friends you had who were critical of the regime the more likely you were to join the protest. (…)
The Internet lets us exploit the power of these kinds of distant connections with marvellous efficiency. It’s terrific at the diffusion of innovation, interdisciplinary collaboration, seamlessly matching up buyers and sellers, and the logistical functions of the dating world. But weak ties seldom lead to high-risk activism. (…)
In a new book called “The Dragonfly Effect: Quick, Effective, and Powerful Ways to Use Social Media to Drive Social Change,” the business consultant Andy Smith and the Stanford Business School professor Jennifer Aaker wrote: “Social networks are particularly effective at increasing motivation”. But that’s not true. Social networks are effective at increasing participation—by lessening the level of motivation that participation requires. The Facebook page of the Save Darfur Coalition has 1,282,339 members, who have donated an average of nine cents apiece. The next biggest Darfur charity on Facebook has 22,073 members, who have donated an average of thirty-five cents. Help Save Darfur has 2,797 members, who have given, on average, fifteen cents. A spokesperson for the Save Darfur Coalition told Newsweek, “We wouldn’t necessarily gauge someone’s value to the advocacy movement based on what they’ve given. This is a powerful mechanism to engage this critical population. They inform their community, attend events, volunteer. It’s not something you can measure by looking at a ledger.” In other words, Facebook activism succeeds not by motivating people to make a real sacrifice but by motivating them to do the things that people do when they are not motivated enough to make a real sacrifice. (…)
There are many things, though, that networks don’t do well. Car companies sensibly use a network to organize their hundreds of suppliers, but not to design their cars. No one believes that the articulation of a coherent design philosophy is best handled by a sprawling, leaderless organizational system. Because networks don’t have a centralized leadership structure and clear lines of authority, they have real difficulty reaching consensus and setting goals. They can’t think strategically; they are chronically prone to conflict and error. How do you make difficult choices about tactics or strategy or philosophical direction when everyone has an equal say? (…)
The drawbacks of networks scarcely matter if the network isn’t interested in systemic change—if it just wants to frighten or humiliate or make a splash—or if it doesn’t need to think strategically. But if you’re taking on a powerful and organized establishment you have to be a hierarchy. (…)
Enthusiasts for social media would no doubt have us believe that King’s task in Birmingham would have been made infinitely easier had he been able to communicate with his followers through Facebook, and contented himself with tweets from a Birmingham jail. But networks are messy: think of the ceaseless pattern of correction and revision, amendment and debate, that characterizes Wikipedia. If Martin Luther King, Jr., had tried to do a wiki-boycott in Montgomery, he would have been steamrollered by the white power structure. And of what use would a digital communication tool be in a town where ninety-eight per cent of the black community could be reached every Sunday morning at church? The things that King needed in Birmingham—discipline and strategy—were things that online social media cannot provide. (…)
It is simply a form of organizing which favors the weak-tie connections that give us access to information over the strong-tie connections that help us persevere in the face of danger. It shifts our energies from organizations that promote strategic and disciplined activity and toward those which promote resilience and adaptability. It makes it easier for activists to express themselves, and harder for that expression to have any impact. The instruments of social media are well suited to making the existing social order more efficient. They are not a natural enemy of the status quo. If you are of the opinion that all the world needs is a little buffing around the edges, this should not trouble you. But if you think that there are still lunch counters out there that need integrating it ought to give you pause.
Shirky ends the story of the lost Sidekick by asking, portentously, “What happens next?”—no doubt imagining future waves of digital protesters. But he has already answered the question. What happens next is more of the same. A networked, weak-tie world is good at things like helping Wall Streeters get phones back from teen-age girls.”
“In claiming that all social networks are good for is “helping Wall Streeters get phones back from teenage girls”, Gladwell ignores the true significance of social media, which lies in their ability to rapidly spread information about alternative points of view that might otherwise never reach a large audience. (…)
The answer, as supplied by a friend from Tehran in June last year, is simple: “We need to be seen and heard by the world, we need all the support we can get. If the governments [of the west] refuse to accept the new government, it’s gonna be meaningful for the movement, somehow.” (…)
If activism is defined only as taking direct action and protesting on the streets, he might be right. But if activism extends to changing the minds of people, to making populations aware of what their governments are doing in their name, to influencing opinion across the world, then the revolution will be indeed be tweeted.”
Adam Gopnik answering the question if Egypt’s revolution wouldn’t have happened without social networking technology:
“The issue isn’t whether people in Egypt or wherever used Twitter or whatever to communicate. Of course they did. But they used cassettes or faxes or pamphlets or whispers in years past and would have used them now if that was the easiest tech available.
The issue—the only issue—is whether the availability of those new media actually changed the likelihood of their fomenting social revolutions, or altered the outcomes of the ones they did. And there is no evidence of any kind, that I’ve seen at least, to suggest they have. In truth, every popular social revolution/movement/regime change due to since at least the French Revolution has followed the same pattern: a government weakened by war or financial crisis or both meets popular resistance which for the first time takes in members of the elite and the masses; they find a meeting space and occupy it—could be the Square or the Tennis Court—then, in the crucial moment, the army, called on to disperse the “mob”, identifies with the cause and refuses; the government is forced to surrender. Sometimes the army—Peking 1989 does—sometimes—Moscow, 1991—it doesn’t. On that decision—complicated in motive—turns the outcome of the revolution. (Then, most often, in depressing truth the best organized and most motivated of the parties on the opposition side—Jacobins or Bolsheviks or Mullahs—no matter how unrepresentative takes over in the period of chaos that follows the revolution). This is the pattern that was in place in Tunisia and Cairo, as it was in St. Petersburg in 1917 or Paris in 1830 and 1848 and 1871. Why the army, who the regime had trained and fed and paid to do just that, didn’t disperse, i.e. massacre the “mob”is always the fascinating question. In Egypt, it seems to have been prudence; in France, widespread dissatisfaction with the economic conditions.
Historians and sociologists in fifty years time may see that more social movements were begun, or fewer—or that more that did begin succeeded. If that’s the case then for good or ill (because after all, most popular movement do not have beneficent outcomes for the people who started them) social media will have had an outcome. If the number is about the same, and the outcomes about the same, then the truth that revolutionaries used Twitter or Facebook will be of the same consequence as that they once wore Phrygian caps and now wear tee-shirts—an interesting detail about the décor of the time, but not a crucial determinant of anything. The notion that because people used Twitter therefore twitter made the revolution is so nakedly ridiculous that it is hard to believe that grown-up people are seriously proposing it.”
Digital power and its discontents — Evgeny Morozov & Clay Shirky Edge Conversation
EVGENY MOROZOV: “If the question we are asking is “How does the Internet impact the chances for democratization in a country like China?”, we have to look beyond what it does to citizens’ ability to communicate with each other or their supporters in the West. I recently found a very fascinating piece of statistics: apparently, the Chinese government spent $120 billion by 2003 on e-government and something like $70 million on the Golden Shield, the censorship project. You compare those two numbers — $120 billion on e-government and $70 million on censorship — and you can sense that the Chinese are really excited by e-government. No surprises here: it can make their government more efficient, making it seem more transparent and resistant to corruption. This would only strengthen the government’s legitimacy. Will it modernize the Chinese Communist Party? It will. Will it result in the establishment of democratic institutions that we expect in liberal democracies? It may not. If we want to know whether China is moving closer to embracing fully functioning democratic institutions and what kind of role the Internet would play in this process, there are no easy clear cut answers here. (…)
Whatever the bias, the truth is that we did have revolutions before Twitter. (…) And we did support those forces somehow, whether it was by smuggling technology, which did happen in Poland smuggling in those Xerox machines, or just by making sure that the Polish political dissidents could link up with the Catholic Church. (…)
People like Stephen Kotkin, for example — who argue that the reason why communism collapsed was because its elites badly mismanaged the situation and the governments simply imploded from within. That’s Kotkin’s “Uncivil Society” thesis: communist government just ran out of money and resources and couldn’t support themselves, so whatever was happening at the grassroots level — with or without Xerox machines — didn’t matter all that much. This, of course, overstates the case but I think Kotkin is asking some important questions. You probably see the implications of his argument to the role of the smuggled Xerox machines: they may not have been all that important, for it was the fundamental economic unsustainability of communism that precipitated its collapse. So how many tweets are now being smuggled into Iran may not really matter in the long run.
(…) In Belarus in 2006. One of the reasons why protests happened in the first place had to do with the fact that, yes, there were presidential elections, and one of the candidates in those elections was actually imprisoned shortly after the elections,. It had nothing to do with social media. You know, if people had no Internet, they would still show up in the Square in the numbers that they did, probably. So, to me, the case of Belarus is even more unambiguous than the case of Iran: social media didn’t really play any role whatsoever in generating protests in the streets. (…)
My biggest problem with these flashmobbing kids in Belarus was that they had erroneously thought that the Internet presents an entirely new way of doing politics. They thought that they would build up and operate a fully virtual movement, that they would not need to bother with the dirty and bloody business of opposing a dictator, a business that often entails harassments of all kinds, as well as bloodshed, intimidation, expulsion from universities. Let’s not kid ourselves: that’s what being in an opposition in authoritarian country entails. It’s never a pretty picture. So I do fear that some of these kids thought that the Internet offered a nice shortcut that would allow them to meaningfully challenge the dictator without having to go through any of that unpleasant stuff. They thought they could just blog the dictatorship away. I even know why some of them had such high hopes for virtual politics: it promised a viable alternative to the otherwise moribund oppositional politics of the country. In the particular case of Belarus, the country simply has a terrible, disorganized, always squabbling and extremely unappealing opposition. No wonder so many smart young people do not want to be part of it. But the Internet presents them with a false choice; the reality is that they don’t have any alternatives — they can either join and reshape this opposition from within, perhaps even using the Internet — or stay on the sidelines and get lost in free and abundant online entertainment. (…)
But you look at Iran, you look at China, those are very focal points of interest for the U.S. government, And yet the Iranian police were still cracking down on protestors, killing people despite the fact that everyone was armed with mobile phones. Could they have killed more? Probably. But I didn’t see technology as a very effective deterrent. Neda was still killed despite the fact that there were people taking those videos.
But my concerns also have to do with how the Internet is changing the nature of political opposition under authoritarianism. I don’t know if you’ve read Kierkegaard, but there are quite a few subtle undertones of Kierkegaard in my critique of Twitter-based activism. Kierkegaard happened to live during the very times that were celebrated by Habermas: cafes and newspapers were on the rise all over Europe, a new democratized public sphere was emerging. But Kiergeaard was growing increasingly concerned that there were too many opinions flowing around, that it was too easy to rally people behind an infinite number of shallow causes, that no one had strong commitment to anything. There was nothing that people could die for. Ironically, this is also one of my problems with the promiscuous nature of online activism: it cheapens our commitment to political and social causes that matter and demand constant sacrifice. (…)
The kind of ordinary apolitical people that we are talking about — those who eventually muster up the courage to go and defy authorities in the streets — they need to be led by people who are ready to take a brave stand, to sacrifice themselves, to go to prison, and become the next Havels, Sakharovs, or Solzhenitsyns. (…)
I do think that the mass protest needs a charismatic leader — i.e. a Sakharov — to truly realize its potential. My fear is that a Solzhenitsyn would not be possible in the age of Twitter. He would probably end up in prison much sooner — and for much longer period — than he actually did. I am not sure that Twitter would help him become a stronger and more charismatic public figure or to gain the courage to write the first page of his book.”
Douglas Rushkoff’s comment on Morozov & Shirky, Edge Conversation:
Douglas Rushkoff (Media Analyst; Documentary Writer; Author, Life, Inc.): “The function of Twitter in Iran may not have been to launch a successful challenge to a corrupt election — but rather to help those in Iran experience at least momentary solidarity with one another and the rest of the world. As easily wiped off our iPhones by the death of Michael Jackson as it may have been, it still happened. It registered in the fledgling collective consciousness. (…)
Mozorov observes: “Well, I do think that the mass protest needs a charismatic leader — i.e. a Sakharov — to truly realize its potential. My fear is that a Solzhenitsyn would not be possible in the age of Twitter.”
This misses the point. It’s not that the Net doesn’t allow for the creation of the required charismatic leader. It’s such a leader is no longer necessary. The ground rules have changed with the landscape.
The 20th Century was about movements — movements with leaders. A networked era actually has the potential to transcend movements as a means of change. We don’t get behind a charismatic leader and follow him along his heroic journey (and eventual martyrdom). Instead, change happens from the bottom up — or the outside in. It happens spontaneously, less like the French Revolution, and more like a chaotic system changing state.
So the decline of the recognizable features of revolution may indicate the end of activism as we know it — but it may also indicate the end of repression as we know it.” — The Reality Club, Edge
See also: Evgeny Morozov: The Internet in Society: Empowering or Censoring Citizens?
Does the internet actually inhibit, not encourage democracy? In this new RSA Animate, Evgeny Morozov presents an alternative take on ‘cyber-utopianism’ - the seductive idea that the internet plays a largely empancipatory role in global politics. Exposing some idealistic myths about freedom and technology (during Iran’s ‘twitter revolution’ fewer than 20,000 Twitter users actually took part), Evgeny argues for some realism about the actual uses and abuses of the internet.