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

"Read this book if you’re trying to understand what the economics of the future will look like. It doesn’t have all the answers, but the authors do a great job in the exposition. Tyler Cowen’s [b:Average Is Over: Powering America Beyond the Age of the Great Stagnation|17674998|Average Is Over Powering America Beyond the Age of the Great Stagnation|Tyler Cowen|https://d202m5krfqbpi5.cloudfront.net/books/1364849099s/17674998.jpg|24678733] is very similar.<br/><br/>Brynjolfsson and McAfee’s newest book follows in the footsteps of their last - explaining how advances in computers and robots are putting an increasing strain our society and challenging conventional economics about work and economics. They (correctly) overturn Tyler Cowen’s ridiculous [b:The Great Stagnation: How America Ate All The Low-Hanging Fruit of Modern History, Got Sick, and Will (Eventually) Feel Better|10276354|The Great Stagnation How America Ate All The Low-Hanging Fruit of Modern History, Got Sick, and Will (Eventually) Feel Better|Tyler Cowen|https://d202m5krfqbpi5.cloudfront.net/books/1296495889s/10276354.jpg|15176955] argument and lay out what they think are the drivers of the Second Machine Age: “sustained exponential improvement in most aspects of computing, extraordinarily large amounts of digitized information, and recombinant innovation.”<br/><br/>One of the best points in the book was something that I hadn’t really thought of before: “In addition to powerful and useful AI, the other recent development that promises to further accelerate the second machine age is the digital interconnection of the planet’s people. There is no better resource for improving the world and bettering the state of humanity than the world’s humans—all 7.1 billion of us.” I had gotten too hung up on the technical angle. It’s exciting (and depressing) to think of how many “Einsteins” humanity has lost out on because they were in some rural village disconnected from the rest of the world… but we can change that now.<br/><br/>But the same dynamics that help “lost Einsteins” reach their potential also widen the gap between them and everyone else - thanks in part to the “winner take all” dynamics of global markets. As the authors point out, “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.”<br/><br/>Brynjolfsson emphasizes the Importance of education for helping future workers adapt - but he also recognizes that there will likely come a point when technology changes so fast that most people can’t keep up. He’s also concerned about a massive future disruption for developing nations dependent on labor. He tries to assuage some of these concerns by pointing out that human labor will be in great surplus and that supply/demand dynamics will allocate that labor to new and efficient uses… but I’m skeptical. <br/><br/>The final part of his book is the most interesting but least satisfying. He tries to answer the question… what will humans do if they don’t have to work? What would that system look like? He touches on ideas like a guaranteed basic income and raises the right question - how will people find meaning in their lives if they don’t have to work? (Although this may be a more typically American problem, as we live with the legacy of the famous Protestant ethic). Brynjolfsson and McAfee could have gone farther, but perhaps the politics become a bit too fiery and radical for their taste.<br/><br/>Also… all of these guys (Brynjolfsson & McAfee, Tyler Cowen, etc.) are getting all jazzed up about “Freestyle Chess” (where you can use computers to help you win). They are trying to say that the future is about “racing with the machine” rather than “racing against the machine” - but I’m not sure the metaphor holds. The best freestyle chess players have a tremendously deep understanding of how the programs are working… and it seems highly unlikely that we’re going to be able to train the overwhelming majority of the human population to become PhD computer scientists. I don’t buy it.<br/><br/>Some of the best quotes below:<br/>###<br/><br/>And we can be even more precise about which technology was most important. It was the steam engine or, to be more precise, one developed and improved by James Watt and his colleagues in the second half of the eighteenth century.<br/><br/>Now comes the second machine age. Computers and other digital advances are doing for mental power—the ability to use our brains to understand and shape our environments—what the steam engine and its descendants did for muscle power.<br/><br/>Among economic historians there’s wide agreement that, as Martin Weitzman puts it, “the long-term growth of an advanced economy is dominated by the behavior of technical progress.”<br/><br/>As the roboticist Hans Moravec has observed, “It is comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” This situation has come to be known as Moravec’s paradox.<br/><br/>As the cognitive scientist Steven Pinker puts it, “The main lesson of thirty-five years of AI research is that the hard problems are easy and the easy problems are hard. . . . As the new generation of intelligent devices appears, it will be the stock analysts and petrochemical engineers and parole board members who are in danger of being replaced by machines. The gardeners, receptionists, and cooks are secure in their jobs for decades to come.”<br/><br/>One of the main reasons we cite digitization as a main force shaping the second machine age is that digitization increases understanding. It does this by making huge amounts of data readily accessible, and data are the lifeblood of science.<br/><br/>Paul Krugman speaks for many, if not most, economists when he says, “Productivity isn’t everything, but in the long run it is almost everything.” Why? Because, he explains, “A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker”—in other words, the number of hours of labor it takes to produce everything, from automobiles to zippers, that we produce... the only viable way for societies to become wealthier—to improve the standard of living available to its people—is for their companies and workers to keep getting more output from the same number of inputs, in other words more goods and services from the same number of people.<br/><br/>Most in the profession would agree with Joseph Schumpeter, the topic’s great scholar, who wrote that, “Innovation is the outstanding fact in the economic history of capitalist society . . . and also it is largely responsible for most of what we would at first sight attribute to other factors.”<br/><br/>But if there’s a big gap between major innovations, economic growth will eventually peter out. We’ll call this the ‘innovation-as-fruit’ view of things, in honor of Tyler Cowen’s imagery of all the low-hanging fruit being picked. In this perspective, coming up with an innovation is like growing fruit, and exploiting an innovation is like eating the fruit over time. Another school of thought, though, holds that the true work of innovation is not coming up with something big and new, but instead recombining things that already exist. And the more closely we look at how major steps forward in our knowledge and ability to accomplish things have actually occurred, the more this recombinant view makes sense.<br/><br/>...and Cowen are world-class economists, but they’re not giving digital technologies their due. The next great meta-idea, invoked by Romer, has already been found: it can be seen in the new communities of minds and machines made possible by networked digital devices running an astonishing variety of software. <br/><br/>If this recombinant view of innovation is correct, then a problem looms: as the number of building blocks explodes, the main difficulty is knowing which combinations of them will be valuable… This model has a fascinating result: because combinatorial possibilities explode so quickly there is soon a virtually infinite number of potentially valuable recombinations of the existing knowledge pieces. The constraint on the economy’s growth then becomes its ability to go through all these potential recombinations to find the truly valuable ones<br/><br/>Because the exponential, digital, and recombinant powers of the second machine age have made it possible for humanity to create two of the most important one-time events in our history: the emergence of real, useful artificial intelligence (AI) and the connection of most of the people on the planet via a common digital network. Either of these advances alone would fundamentally change our growth prospects. When combined, they’re more important than anything since the Industrial Revolution, which forever transformed how physical work was done.<br/><br/>“Most economic fallacies derive from the tendency to assume that there is a fixed pie, that one party can gain only at the expense of another.” —Milton Friedman<br/><br/>However, unlike the steam engine or electricity, second machine age technologies continue to improve at a remarkably rapid exponential pace, replicating their power with digital perfection and creating even more opportunities for combinatorial innovation.<br/><br/>When a business traveler calls home to talk to her children via Skype, that may add zero to GDP, but it’s hardly worthless. Even the wealthiest robber baron would have been unable to buy this service. How do we measure the benefits of free goods or services that were unavailable at any price in previous eras? ...Despite all the attention it gets from economists, pundits, journalist, and politicians, GDP, even if it were perfectly measured, does not quantify our welfare.<br/><br/>“An imbalance between rich and poor is the oldest and most fatal ailment of all republics.” —Plutarch<br/><br/>Rapid advances in our digital tools are creating unprecedented wealth, but there is no economic law that says all workers, or even a majority of workers, will benefit from these advances. For almost two hundred years, wages did increase alongside productivity. This created a sense of inevitability that technology helped (almost) everyone. But more recently, median wages have stopped tracking productivity, underscoring the fact that such a decoupling is not only a theoretical possibility but also an empirical fact in our current economy.<br/><br/>IN SHORT, median income has increased very little since 1979, and it has actually fallen since 1999. But that’s not because growth of overall income or productivity in America has stagnated; as we saw in chapter 7, GDP and productivity have been on impressive trajectories. Instead, the trend reflects a significant reallocation of who is capturing the benefits of this growth, and who isn’t.<br/><br/>To capture these distinctions, work by our MIT colleagues Daron Acemoglu and David Autor suggests that work can be divided into a two-by-two matrix: cognitive versus manual and routine versus nonroutine. They found that the demand for work has been falling most dramatically for routine tasks, regardless of whether they are cognitive or manual. This leads to job polarization: a collapse in demand for middle-income jobs, while nonroutine cognitive jobs (such as financial analysis) and nonroutine manual jobs (like hairdressing) have held up relatively well.<br/><br/>one CEO, and he explained that he knew for over a decade that advances in information technology had rendered many routine information-processing jobs superfluous. At the same time, when profits and revenues are on the rise, it can be hard to eliminate jobs. When the recession came, business as usual obviously was not sustainable, which made it easier to implement a round of painful streamlining and layoffs. As the recession ended and profits and demand returned, the jobs doing routine work were not restored. Like so many other companies in recent years, his organization found it could use technology to scale up without these workers.<br/><br/>“One machine can do the work of fifty ordinary men. No machine can do the work of one extraordinary man.” —Elbert Hubbard<br/><br/>Why are winner-take-all markets more common now? Shifts in the technology for production and distribution, particularly these three changes: a) the digitization of more and more information, goods, and services, b) the vast improvements in telecommunications and, to a lesser extent, transportation, and c) the increased importance of networks and standards.<br/><br/>Even as the technology destroys geography—a barrier that used to protect authors from worldwide competition—it opens up specialization as a source of differentiation. Instead of being the thousandth-best children’s book author in the world, it may be more profitable to be the number-one author in Science-Based Advice for Ecological Entrepreneurs, or Football Clock Management.<br/><br/>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.” 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.<br/><br/>First, the theory. There are three economic mechanisms that are candidates for explaining technological unemployment: inelastic demand, rapid change, and severe inequality.<br/><br/>KEYNES DISAGREED. He thought that in the long run, demand would not be perfectly inelastic. That is, ever lower (quality-adjusted) prices would not necessarily mean we would consume ever more goods and services. Instead, we would become satiated and choose to consume less. He predicted that this would lead to a dramatic reduction in working hours to as few as fifteen per week as less and less labor was needed to produce all the goods and services that people demanded.<br/><br/>As Arthur C. Clarke is purported to have put it, “The goal of the future is full unemployment, so we can play.”<br/><br/>Keynes was more concerned with short-term “maladjustments,” which brings us to the second, more serious argument for technological unemployment: the inability of our skills, organizations, and institutions to keep pace with technical change. When technology eliminates one type of job, or even the need for a whole category of skills, those workers will have to develop new skills and find new jobs. Of course, that can take time, and in the meantime they may be unemployed. The optimistic argument maintains that this is temporary. Eventually, the economy will find a new equilibrium and full employment will be restored as entrepreneurs invent new businesses and the workforce adapts its human capital. But what if this process takes a decade? And what if, by then, technology has changed again? This is the possibility that Wassily Leontief had in mind his 1983 article when he speculated that many workers could end up permanently unemployed, like horses unable to adjust to the invention of the tractors.<br/><br/>When engineers work to amplify these differences, building on the areas where machines are strong and humans are weak, then the machines are more likely to complement humans rather than substitute for them. Effective production is more likely to require both human and machine inputs, and the value of the human inputs will grow, not shrink, as the power of machines increases. A second lesson of economics and business strategy is that it’s great to be a complement to something that’s increasingly plentiful.<br/><br/>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.<br/><br/>In the long run, the biggest effect of automation is likely to be on workers not in America and other developed nations, but rather in developing nations that currently rely on low-cost labor for their competitive advantage. If you take most of the costs of labor out of the equation by installing robots and other types of automation, then the competitive advantage of low wages largely disappears. This is already beginning to happen. Terry Guo of Foxconn has been aggressively installing hundreds of thousands of robots to replace an equivalent number of human workers…. In other words, offshoring is often only a way station on the road to automation.<br/><br/>an excellent education is the best way to not be left behind as technology races ahead. The discouraging news is that today many students seem to be squandering at least some of their educational opportunities. The good news, though, is that technology is now providing more of these opportunities than ever before.<br/><br/>The United States was the clear leader in primary education in the first half of the twentieth century, having realized that inequality was a “race between education and technology,” to use a phrase coined by Jan Tinbergen (winner of the first Nobel Prize in Economic Sciences) and used by the economists Claudia Goldin and Lawrence Katz as the title of their influential 2010 book. When technology advances too quickly for education to keep up, inequality generally rises.<br/><br/>It seems sensible, then, for educational reforms in the United States to include renewed efforts to attract and retain well-qualified people in the teaching profession, and to remove or retrain consistent low performers. Part of the bargain should also be longer school hours, longer school years, more after-school activities and more opportunities for preschool education.<br/><br/>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.<br/><br/>And just about all the research and evidence we’ve looked at has convinced us that Voltaire was right. It’s tremendously important for people to work not just because that’s how they get their money, but also because it’s one of the principal ways they get many other important things: self-worth, community, engagement, healthy values, structure, and dignity, to name just a few.<br/><br/>In his book Drive, Daniel Pink summarizes the three key motivations from the research literature: mastery, autonomy, and purpose.<br/><br/>But in the long run, the real questions will go beyond economic growth. As more and more work is done by machines, people can spend more time on other activities. Not just leisure and amusements, but also the deeper satisfactions that come from invention and exploration, from creativity and building, and from love, friendship, and community. We don’t have a lot of formal metrics for those kinds of value, and perhaps we never will, but they will nonetheless grow in importance as we satisfy our more basic economic needs. If the first machine age helped unlock the forces of energy trapped in chemical bonds to reshape the physical world, the real promise of the second machine age is to help unleash the power of human ingenuity."