Imagine: How Creativity Works

  2.

  Geoffrey West doesn’t eat lunch. His doctor says he has a mild allergy to food; meals make him sleepy and nauseated. When West is working — when he’s staring at some scribbled equations on scratch paper or gazing out his window at the high desert — he subsists on caffeinated tea and the occasional sugar cookie. His gray hair is tousled, and his beard has the longish look of neglect. It’s clear that West regards the mundane needs of everyday life — feeding the body, trimming the whiskers — as little more than annoying distractions that draw him away from much more interesting problems. Sometimes, West can seem jealous of his computer, this silent machine with no hungers or moods. All it needs is a power cord.

  For West, the world is most compelling at its most abstract. He likes to compare himself to Kepler, Galileo, and Newton, since he’s also a theoretical physicist in search of fundamental laws. But West isn’t trying to decode the physical universe; he’s not interested in deep space, black holes, or string theory. Although West worked for decades as a physicist at Stanford University and Los Alamos National Laboratory — his specialty was the behavior of elementary particles — he left the field after the Texas superconducting supercollider was canceled by Congress in 1993. “At first, I was devastated,” West says. “I had all these great experiments planned.” West wasn’t ready to retire, however, and so he began thinking about what to study next. “I realized that what physicists are very good at is finding laws,” he says. “We’re good at making sense of complexity.”

  And so West began searching for a subject that needed his skill set. He eventually settled on cities. For the physicist, the urban jungle seemed like one of those systems that looked chaotic — all those taxi horns and traffic jams — but might actually be obeying a short list of cosmic rules. “We spend all this time thinking about cities in terms of their local details, in terms of their neighborhoods and restaurants and museums,” West says. “I had this hunch that there was something more, that every city was also shaped by a set of hidden laws.”

  But West realized that no one was looking for these laws. He saw modern urban theory as akin to physics before Kepler; he ridiculed it as a field without principles. “It’s all just speculation,” West says. “It’s storytelling. There is no rigor.” If he was going to dispense advice and tell mayors how to run their cities, then he wanted his advice to be wholly empirical, rooted in the strictness of facts. West was tired of urban theory — he wanted to invent urban science.

  Of course, before West could solve the city — transforming the speculations of Jane Jacobs into a quantitative discipline — he needed data. Massive amounts of data. Along with Luis Bettencourt, another physicist who had given up on physics, West began scouring the libraries for urban statistics. The scientists downloaded huge files from the U.S. Census, learned about the intricacies of German infrastructure, and spent several thousand dollars on a thick almanac featuring the provincial cities of China. (Unfortunately, the book was in Mandarin.) They looked at a dizzying array of variables, from the length of electrical wire in Frankfurt to the number of college graduates in Boise to the average income in Shenzhen. They amassed stats on gas stations and personal income, sewer pipes and murders, coffee shops and the walking speed of pedestrians.

  After two years of careful analysis, West and Bettencourt discovered that all of these urban variables could be described by a few exquisitely simple equations. These are the laws that automatically emerge whenever people “agglomerate,” cramming themselves into apartment buildings, subway cars, and sidewalks. It doesn’t matter if the city is Manhattan, New York, or Manhattan, Kansas; the urban patterns remain the same. West isn’t shy about describing the magnitude of this accomplishment. “What we found are the constants that describe every city,” West says.

  “I can take these laws and make very accurate predictions about the number of violent crimes and the surface area of roads and the average income in a city in Japan with two hundred thousand people. I don’t know anything about this city. I don’t know where it is, or its history, or what it produces, but I can tell you all about it. And the reason I can do that is because every city is really the same. They’re all the same damn thing, and that’s why the equations work.”

  The existence of these equations depends on the ballet of Hudson Street. While Jacobs could only speculate on the value of our urban interactions, West insists that his equations confirm her theory. He describes his data as a scientific version of Jacobs’s sidewalk dance, since it quantifies the value of urban spaces. “One of my favorite compliments is when people come up to me and say, ‘You have done what Jane Jacobs would have done, if only she could do mathematics,’ ” West says. “What the numbers clearly show, and what she was clever enough to anticipate, is that when people come together they become much more productive per capita. They exchange more ideas and generate more innovations. What’s truly amazing is how predictable this is. It happens automatically, in city after city.”

  According to the equations of West and Bettencourt, every socioeconomic variable that can be measured in cities — from the production of patents to per capita income — scales to an exponent of approximately 1.15. What’s interesting here is the size of the exponent, which is greater than 1. This means that a person living in a metropolis of one million should generate, on average, about 15 percent more patents and make 15 percent more money than a person living in a city of five hundred thousand. (The one living in the bigger city should also have 15 percent more restaurants in his neighborhood and create 15 percent more trademarks.) The correlations remain the same even when the numbers are adjusted for levels of education, work experience, and IQ scores. “This remarkable equation is why people move to the big city,” West says. “Because you can take the same person, and if you just move them from a city of fifty thousand to a city of six million, then all of a sudden they’re going to do three times more of everything we can measure. It doesn’t matter where the city is or which cities you’re talking about. The law remains the same.”

  West and Bettencourt refer to this phenomenon as “superlinear scaling,” which is a fancy way of describing the increased output of people living in big cities. When a superlinear equation is graphed, it looks like a roller coaster climbing into the sky. The steep slope emerges from the positive-feedback loop of urban life — a growing city makes everyone in that city more productive, which encourages more people to move to the city, and so on. According to West, these superlinear patterns demonstrate why cities are the single most important invention in human history. They are the idea, he says, that enabled our economic potential and unleashed our ingenuity. Once people started living in dense clumps, they created a kind of settlement capable of reinventing itself, so a city founded on the fur trade could one day give birth to Wall Street, and an island in the Seine chosen for its military advantages might eventually become a place full of avant-garde artists. “Cities are this inexhaustible source of ideas,” West says. “And that’s entirely because of these equations. As cities get bigger, everything starts accelerating. Each individual unit becomes more productive and more innovative. There is no equivalent for this in nature. Cities are a total biological anomaly. But you can’t understand modern life without understanding cities. They are the force behind everything interesting. They are where everything new is coming from.”

  After West and Bettencourt discovered the superlinear laws that define every city, they became interested in what the equations couldn’t explain. While the math was able to predict the approximate performance of a given urban area, it failed to describe the local deviations, those slight differences that made Bridgeport feel distinct from Brooklyn, or New Orleans distinct from Seattle, or Austin distinct from Houston. “When I tell people about our urban laws, the first question they always ask is about these differences,” West says. “They say: ‘If every city is the same, then why does my city seem so unique?’ Eventually, we got so sick of this question that we decided to find the answer.?
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  The first thing the physicists discovered is that these deviations persisted over time. Bridgeport, for instance, has been abnormally wealthy for at least a century, while New Orleans has always had an extremely high crime rate, and Austin has consistently produced many more patents per capita than Houston. “That’s when I realized it wasn’t such a silly question after all,” West says. “These deviations aren’t just fluky things or random short-term trends. Instead, they seem to refl ect something real about the city itself.”

  Furthermore, the endurance of these differences means that it’s possible to uncover the hidden correlations of urban life. What is it about Austin, for instance, that makes it the most innovative city in Texas? Why has Cleveland always been so poor? Why does Santa Monica generate so many trademarks? While West and Bettencourt have discovered many interesting patterns — the best way to reduce crime, for instance, is to attract young college graduates — one of their most surprising findings comes from an old survey led by the Princeton psychologists Marc and Helen Bornstein. In the early 1970s, the Bornsteins began measuring the average walking speed of pedestrians in dozens of different cities all across the world, from Geneva to Jerusalem. The research itself was straightforward: the Bornsteins measured out a sixty-foot stretch of sidewalk and then timed thousands of random pedestrians as they walked down the street. Interestingly, the psychologists discovered that the pace of life closely tracked the population of cities, so the more people in the city, the faster they walked.

  While the physicists cite this paper as yet another piece of evidence in support of superlinear scaling — density speeds us up — they’ve also discovered an unexpected correlation. There seems to be a consistent link between walking speed and the production of patents: cities with unusually fast pedestrians create more new ideas. (Both urban measurements are extremely consistent over time.) West and Bettencourt attempt to explain this peculiar link by invoking the language of physics. They compare urban residents to particles with velocity bouncing off one another and careening in unexpected directions. The most creative cities are simply the ones with the most collisions.

  Of course, these interpersonal collisions — the human friction of a crowded space — can also feel unpleasant. We don’t always want to talk with strangers on the subway or jostle with other pedestrians. Nevertheless, West insists that all successful cities are a little uncomfortable. He describes the purpose of urban planning as finding a way to minimize people’s distress while maximizing their interactions. The residents of Hudson Street, after all, didn’t mind talking to one another on the sidewalk or chatting with the butcher while buying their meat. As Jacobs pointed out, the layout of her Manhattan neighborhood — the irregular grid, the density of brownstones — meant that it didn’t feel like the center of a vast metropolis that was overstuffed with strangers. It maintained an intimate feel and facilitated the most meaningful kind of mingling. That’s why it’s called the Village.

  In recent decades, however, many of the fastest-growing cities in America, such as Phoenix and Riverside, have pursued a very different urban model. These places have focused on mitigating unwanted interactions, trading away crowded public spaces and knowledge spillovers for single-family homes. However, West and Bettencourt point out that these suburban comforts are closely associated with poor performance on a variety of urban metrics. (Several economic studies have found that doubling urban density raises productivity by up to 28 percent.) Phoenix, for instance, has had below-average levels of income and innovation for the last forty years. “When you look at some of these fast-growing cities, they look like tumors on the landscape,” West says with his usual bombast. “They have these extreme levels of growth, but it’s not sustainable growth. That’s because they haven’t developed the necessary kind of interactions that lead to new ideas. You can’t grow forever on the promise of cheap land.”

  West contrasts the long-term underperformance of Phoenix with San Jose, a city that has been an unusually innovative place for the last hundred years. (The data is compelling: while Phoenix was ranked 146th among American cities in the production of patents per capita, San Jose was second. (According to West and Bettencourt, the most innovative city in America is Corvallis, Oregon. However, this ranking is slightly misleading, since a disproportionate number of the patents generated in Corvallis come from a single Hewlett-Packard lab that conducts research on laser printers.)) In fact, even when the San Jose region was mostly walnut and apricot farms, and decades before it became the center of Silicon Valley, the area still produced an abnormally large number of patents per capita. “There is just something about this city that makes it really good at generating patents,” West says. “This local culture is why Silicon Valley is in that particular valley. It’s not a historical or geographical accident — it’s because of these numbers. Now, the equations can’t tell you why the San Jose area has always been so innovative. All they can show is that Silicon Valley is an unusually creative place. It’s a real outlier.”

  3.

  Route 128 is a highway around Boston. It begins as a two-lane road in the fishing port of Gloucester, Massachusetts, and then bends inland toward the suburbs. In the early 1950s, the highway became shorthand for the American high-tech industry, which was scattered along its off ramps. (In 1955, BusinessWeek referred to Route 128 as “the Magic Semicircle,” while Forbes called it “America’s Technology Highway.”) This was particularly true around Waltham and Newton, two towns that were soon populated by industrial parks and glassy office towers. By 1970, the area bounded by Route 128 contained six of the ten largest technology firms in the world, including Digital Equipment Corporation and Raytheon. The “Massachusetts Miracle” was under way.

  While Route 128 was undergoing a postwar boom, the San Jose region remained heavily agricultural; the main local industry was small-scale food-processing plants. This is why it was so surprising when, in 1956, William Shockley, the eccentric co-inventor of the transistor, established the Shockley Transistor Corporation in a small town called Mountain View. (Shockley had tried to start a transistor company in the Route 128 region, but the large Boston firms weren’t interested in his product.) Because Shockley couldn’t convince any of his former colleagues from Bell Labs to join his new venture — nobody wanted to move to a farming town in California — he ended up recruiting grad students from Caltech and Stanford. Unfortunately, Shockley turned out to be a terrible manager, and in 1957, eight of his researchers left the company. This group of refugee engineers — they called themselves the Traitorous Eight — founded the Fairchild Semiconductor Company in a San Jose garage. They sold their very first batch of transistors to IBM, and by 1963, they had sales of more than $130 million a year. A few years later, two of these engineers — Robert Noyce and Gordon Moore — left Fairchild to start their own microchip company. They called it Intel. (A third member of the Traitorous Eight went on to form the venture-capital giant Kleiner Perkins (now KPCB), which was an early investor in many of the most successful tech companies, including Amazon, AOL, Compaq, EA, Genentech, Google, Netscape, and Sun Microsystems.)

  By the early 1980s, Silicon Valley was home to dozens of success stories like Intel, including Apple Computer, Cisco, Oracle, and Sun Microsystems. In fact, these young start-ups were so successful that by 1985, Silicon Valley had nearly twice as many people working in high-tech as the Route 128 area. In the years since, the West Coast advantage has only grown: Internet companies like Netscape, Google, Netfl ix, and Facebook have all emerged from the suburbs around San Jose. (Although Facebook was founded in a Harvard dorm room in February of 2004, Mark Zuckerberg moved the company to Palo Alto that summer. He said he wanted to be close to the action.) And the original tech stalwarts of the Boston area — those massive companies like Digital Equipment Corporation and Wang Laboratories — have all gone out of business. In fewer than fifty years, the walnut farms of San Jose have become the technology center of the world.

  The astonishing success of
Silicon Valley raises an interesting question: What happened to Route 128? As Vivek Wadhwa, a business professor at Duke, notes: “If you were betting on an area to dominate [the tech sector] in 1975, you’d have been wise to bet on Route 128. It had a giant head start over everywhere else.” The region had several elite research universities, such as MIT and Harvard, and a long list of successful technology firms. These companies had big contracts with the Defense Department and controlled the market for microchips and electronic hardware.

  And yet, this head start wasn’t enough: after a few decades of domination, the Boston high-tech sector began to fall apart. This decline was primarily rooted in the inability of Route 128 companies to keep pace with the innovations of the San Jose region. AnnaLee Saxenian, a professor of city planning at UC-Berkeley, compares the postwar performance of these two regions in her insightful book Regional Advantage. She argues that by the mid-1970s, the Boston area was already “several years behind the curve . . . set by California companies. They couldn’t compete with the new designs and products coming out of Silicon Valley.”

  What caused this innovation gap? The downfall of the Boston tech sector was caused by the very same features that, at least initially, had seemed like such advantages. As Saxenian notes, the Route 128 area had been defined for decades by the presence of a few large firms. (At one point, Digital Equipment Corporation alone employed more than a hundred and twenty thousand people.) These companies were so large, in fact, that they were mostly self-sufficient. Digital Equipment Corporation didn’t make just minicomputers — it also made the microchips in its computers, and it designed the software that ran on those microchips. (Gordon Bell, the vice president in charge of research at Digital, described the company as “a large entity that operates as an island in the regional economy.”) As a result, the Boston firms took secrecy very seriously — a scientist at Digital wasn’t allowed to talk about his work with a scientist at Wang or share notes with someone at Lotus. These companies strictly enforced noncompete clauses and nondisclosure agreements; former employees couldn’t work for competitors, and scientists weren’t allowed to publish articles in peer-reviewed journals. This meant that at the Route 128 companies, information tended to flow vertically, as ideas and innovations were transferred within the firms.