The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies

by Erik Brynjolfsson

Gordon and Cowen are world-class economists, but they’re not giving digital technologies their due.

The economic statistics underscore the dichotomy of bounty and spread. The economist Jared Bernstein, a senior fellow at the Center on Budget and Policy Priorities, brought our attention to the way productivity and employment have become decoupled, as shown in Figure 11.1. While these two key economic statistics tracked each other for most of the postwar period, they became decoupled in the late 1990s. Productivity continued its upward path as employment sagged.

Today the employment-to-population ratio is lower than any time in at least 20 years, and the real income of the median worker is lower today than in the 1990s. Meanwhile, like productivity, GDP, corporate investment, and after-tax profits are also at record highs.

Technology is certainly not the only force causing this rise in spread, but it is one of the main ones. Today’s information technologies favor more-skilled over less-skilled workers, increase the returns to capital owners over labor, and increase the advantages that superstars have over everybody else.

In America, the income of the median worker is lower in real dollars than it was in 1999 and the story largely repeats itself when we look at households instead of individual workers, or total wealth instead of annual income. Many people are falling behind as technology races ahead.

However American households are spending their money, many of them are left without a financial cushion. The economists Annamaria Lusardi, Daniel J. Schneider, and Peter Tufano conducted a 2011 study asking people about “their capacity to come up with $2,000 in 30 days.” Their findings are troubling. They concluded that, “Approximately one quarter of Americans report that they would certainly not be able to come up with such funds, and an additional 19% would do so by relying at least in part on pawning or selling possessions or taking payday loans. . . . [In other words, we] find that nearly half of Americans are financially fragile. . . . [A] sizable fraction of seemingly ‘middle class’ Americans . . . judge themselves to be financially fragile.”8

Many Americans believe that they still live in the land of opportunity—the country that offers the greatest chance of economic advancement. But this is no longer the case. As The Economist sums it up, “Back in its Horatio Alger days, America was more fluid than Europe. Now it is not. Using one-generation measures of social mobility—how much a father’s relative income influences that of his adult son—America does half as well as Nordic countries, and about the same as Britain and Italy, Europe’s least-mobile places.”11

So the spread is not only large, but also self-perpetuating. Too often, people at the bottom and middle stay where they are over their careers, and families stay locked in across generations. This is not healthy for an economy or society.

According to Acemoglu and Robinson, the true origins are not geography, natural resources, or culture. Instead, they’re institutions like democracy, property rights, and the rule of law; inclusive ones bring prosperity, and extractive ones—ones that bend the economy and the rules of the game to the service of entrenched elite—bring poverty. The authors make a compelling case, and when they turn their attention to America’s current condition, they offer important insights and cautions:

Their analysis hits on a final reason to be concerned about the large and growing inequality of recent years: it could lead to the creation of extractive institutions that would slow our journey into the second machine age. We think this would be something more than a shame; it would be closer to a tragedy. We also believe, based on the work of Acemoglu and Robinson and others, that it is a plausible scenario. Instead of being confident that the bounty from technology will more than compensate for the spread it generates, we are instead concerned about something close to the reverse: that the spread could actually reduce the bounty in years to come.

Thus in a very real sense, as long as there are unmet needs and wants in the world, unemployment is a loud warning that we simply aren’t thinking hard enough about what needs doing. We aren’t being creative enough about solving the problems we have using the freed-up time and energy of the people whose old jobs were automated away. We can do more to invent technologies and business models that augment and amplify the unique capabilities of humans to create new sources of value, instead of automating the ones that already exist. As we will discuss further in the next chapters, this is the real challenge facing our policy makers, our entrepreneurs, and each of us individually.

Businesses can identify and hire workers with skills they need anywhere in the world. If a worker in China can do the same work as an American, then what economists call “the law of one price” demands that they earn essentially the same wages, because the market will arbitrage away differences just as it would for other commodities. That’s good news for the Chinese worker, and for overall economic efficiency. But is not good news for the American worker who now faces low-cost competition. A number of economists have made exactly this argument. Michael Spence, in his brilliant book The Next Convergence, explains how the integration of global markets is leading to enormous dislocations, especially in labor markets.

These activities have one thing in common: ideation, or coming up with new ideas or concepts. To be more precise, we should probably say good new ideas or concepts, since computers can easily be programmed to generate new combinations of preexisting elements like words. This however, is not recombinant innovation in any meaningful sense. It’s closer to the digital equivalent of a hypothetical room full of monkeys banging away randomly on typewriters for a million years and still not reproducing a single play of Shakespeare’s.

Scientists come up with new hypotheses. Journalists sniff out a good story. Chefs add a new dish to the menu. Engineers on a factory floor figure out why a machine is no longer working properly. Steve Jobs and his colleagues at Apple figure out what kind of tablet computer we actually want. Many of these activities are supported and accelerated by computers, but none are driven by them.

In other words, we believe that employers now and for some time to come will, when looking for talent, follow the advice attributed to the Enlightenment sage Voltaire: “Judge a man by his questions, not his answers.”6

So ideation, large-frame pattern recognition, and the most complex forms of communication are cognitive areas where people still seem to have the advantage, and also seem likely to hold on to it for some time to come. Unfortunately, though, these skills are not emphasized in most educational environments today. Instead, primary education often focuses on rote memorization of facts, and on the skills of reading, writing, and arithmetic—the ‘three Rs,’ as Tory MP Sir William Curtis named them around 1825 (incidentally, it’s unlikely that a machine would have given them a moniker as memorable, if technically inaccurate, as the ‘three Rs’).9

Sugata Mitra,

We probably shouldn’t be too surprised by this; SOLEs have been around for a while, and have produced many people who have excelled at racing with machines. In the early years of the twentieth century, the Italian physician and researcher Maria Montessori developed the primary educational system that still bears her name. Montessori classrooms emphasize self-directed learning, hands-on engagement with a wide variety of materials (including plants and animals), and a largely unstructured school day. And in recent years they’ve produced alumni including the founders of Google (Larry Page and Sergey Brin), Amazon (Jeff Bezos), and Wikipedia (Jimmy Wales).

Management researchers Jeffrey Dyer and Hal Gregersen interviewed five hundred prominent innovators and found that a disproportionate number of them also went to Montessori schools, where “they learned to follow their curiosity.” As a Wall Street Journal blog post by Peter Sims put it, “the Montessori educational approach might be the surest route to joining the creative elite, which are so overrepresented by the school’s alumni that one might suspect a Montessori Mafia.”

Our recommendations about how people can remain valuable knowledge workers in the new machine age are straightforward: work to improve the skills of ideation, large-frame pattern recognition, and complex communication instead of just the three Rs. And whenever possible, take advantage of self-organizing learning environments, which have a track record of developing these skills in people.

Collegiate Learning Assessment (CLA), a recently developed test given to college students to assess their abilities in critical thinking, written communication, problem solving, and analytic reasoning.

In short, the performance task is a good test of ideation, pattern recognition, and complex communication.

They also find, however, that at every college studied some students show great improvement on the CLA. In general, these are students who spent more time studying (especially studying alone), took courses with more required reading and writing, and had more demanding faculty. This pattern fits well into conclusions by education researchers Ernest Pascarella and Patrick Terenzini, who summarized more than twenty years of research in their book How College Affects Students. They write that “the impact of college is largely determined by individual effort and involvement in the academic, interpersonal, and extracurricular offerings on a campus.”14

One of the best known of these resources is Khan Academy, which was started by then–hedge fund manager Salman Khan as a series of online doodles and YouTube video lectures intended to teach math to his young relatives. Their immense popularity led him to quit his job in 2009 and devote himself to creating online educational materials, freely available to all. By May 2013, Khan Academy included more than 4,100 videos, most no more than a few minutes long, on subjects ranging from arithmetic to calculus to physics to art history. These videos had been viewed more than 250 million times, and the Academy’s students had tackled more than one billion automatically generated problems.15

Across good Econ 101 textbooks, and across good economists, there’s far more agreement about government’s role in promoting economic growth than you might expect from the more vitriolic public debates in the media.

Goldin documents that by 1955, for example, almost 80 percent of American children between the ages of fifteen and nineteen were enrolled in high schools, a level more than twice as high as that in any European country at the time.

The head of MITx, Anant Agarwal, says that he was surprised when the data revealed that half of his students started working on their homework assignments before watching the video lectures. Students were more motivated to really understand the content of the lecture once they saw the specific challenges that they would learn how to overcome.

Part of the bargain should also be longer school hours, longer school years, more after-school activities and more opportunities for preschool education. Studies of successful charter schools by Harvard economist Roland Fryer and others have found that the formula for success is simple, if not easy: longer hours, additional school days, and a no-excuses philosophy that tests students and, implicitly, their teachers.7 This approach has helped Singapore and South Korea do well in the PISA rankings—both rely heavily on standardized tests for children of all ages.8 Lengthening the school year may be especially beneficial for poor kids, since research suggests that rich and poor children learn at a similar rate when school is in session, but that poor children fall behind over the summer when they are not in school.

Entrepreneurship has been an important part of the Econ 101 playbook at least since economist Joseph Schumpeter’s landmark work, written in the middle of the twentieth century, on the nature of capitalism and innovation. Schumpeter put forward our favorite definition of innovation—“the market introduction of a technical or organisational novelty, not just its invention”—and, like us, believed that it was an essentially recombinant process, “the carrying out of new combinations.”

For instance, economists Leora Klapper, Luc Laeven, and Raghuram Rajan found that higher levels of regulation reduce startup activity.17 Their research was conducted using European data, but it seems likely that its conclusions are at least in part applicable to the United States as well.

Although job sites like Monster.com and Aftercollege.com and networking sites like LinkedIn have made it easier for employers and employees to find one another, the vast majority of our students that graduate each year still rely primarily on word of mouth recommendations from friends, relatives, and, yes, professors, to make introductions. We must find ways to reduce the friction and search costs that make it unnecessarily difficult to match people with jobs.

Entrepreneurship in America, particularly in technology-intensive sectors of the economy, is fueled by immigration to an extraordinary degree. Foreign-born people make up less than 13 percent of the country’s population in recent years, but between 1995 and 2005 more than 25 percent of all new engineering and technology companies had at least one immigrant cofounder, according to research by Wadhwa, Saxenian, and their colleagues.

That means that a tax on the revenues from that good (in other words the ‘economic rents’ from it) will not reduce its supply. As a result, such taxes are relatively efficient—they don’t distort incentives or activities. The nineteenth-century economist Henry George took this insight and argued that we should have just a single tax, a land tax.

We do not find much evidence supporting the counter-argument that higher taxes on this population will harm economic growth by eroding high earners’ initiative.

In fact, research by our MIT colleague and Nobel Prize–winning economist Peter Diamond, in partnership with Clark Medal winner Emmanuel Saez, suggests that optimal tax rates at the very top of the income distribution might be as high as 76 percent.38

Basic income is not part of mainstream policy discussions today, but it has a surprisingly long history and came remarkably close to reality in twentieth-century America. One of its early proponents was the English-American political activist Thomas Paine, who advocated in his 1797 pamphlet Agrarian Justice that everyone should be given a lump sum of money upon reaching adulthood to compensate for the unjust fact that some people were born into landowning families while others were not. Later advocates included philosopher Bertrand Russell and civil rights leader Martin Luther King, Jr., who wrote in 1967, “I am now convinced that the simplest approach will prove to be the most effective—the solution to poverty is to abolish it directly by a now widely discussed measure: the guaranteed income.”