THE GLOBAL ECONOMY IS BEING TRANSFORMED BY CHANGES FAR greater in speed and scale than any in human history. We are living with, and in, Earth Inc.:* national policies, regional strategies, and long accepted economic theories are now irrelevant to the new realities of our new hyper-connected, tightly integrated, highly interactive, and technologically revolutionized economy.
Many of the most successful large enterprises in the world now produce goods in “virtual global factories,” with intricate spiderwebs of supply chains connecting to hundreds of other enterprises in dozens of countries. More and more markets for goods—and increasingly services that do not require face-to-face interaction—are now global in nature. Higher and higher percentages of wage earners must now compete not only with wage earners in every other country, but also with intelligent machines interconnected with other machines and computer networks.
The digitization of work and the dramatic and relatively sudden metastasis of what used to be called automation are driving two massive changes simultaneously:
1. The outsourcing of jobs from industrial economies to developing and emerging economies with large populations and lower wages; and
2. The robosourcing of jobs from human beings to mechanized processes, computer programs, robots of all sizes and shapes, and still rudimentary versions of artificial intelligence that are improving in their efficacy, utility, and power with each passing year.
The transformation of the global economy is best understood as an emergent phenomenon—that is, one in which the whole is not only greater than the sum of its parts, but very different from the sum of its parts in important and powerful ways. It represents something new—not just a more interconnected collection of the same national and regional economies that used to interact with one another, but a completely new entity with different internal dynamics, patterns, momentum, and raw power than what we have been familiar with in the past. There are limits to cross-border flows of people, of course, and trade flows are stronger among countries that are close to one another, but the entire global economy has been knit together much more tightly than ever before.
Just as the thirteen American colonies in North America emerged as a unified whole in the last quarter of the eighteenth century—and just as the ancient walled city-states of Italy eventually became a unified nation in the second half of the nineteenth century—the world as a whole has now emerged as a single economic entity that is moving quickly toward full integration. At least that is the reality in the world of commerce and industry, in the world of science, and in the rapid spreading of most new technologies to centers of commerce throughout the world.
In the world of politics and governmental policy, nation-states remain the dominant players. Psychologically, emotionally, and in the ways we frame our identity, most of us still think and act as if we are still living in the world we knew when we were young. In fact, however, where the economic realities of life are concerned, that world is receding from view.
This powerful driver of global change—sometimes loosely and inadequately referred to as “globalization”—marks not only the end of one era in history and the beginning of another, it marks the emergence of a completely new reality with which we as human beings must come to grips.
OUTSOURCING AND ROBOSOURCING have typically been seen as two separate and distinct phenomena—studied and discussed by different groups of economists, technologists, and policy experts. Yet they are deeply intertwined and represent two aspects of the same mega-phenomenon.
The tectonic shift toward robosourcing and IT-empowered outsourcing dramatically changes the ratio of capital inputs to labor inputs and weakens the ability of working people to demand higher wages in industrial countries.
The political battles over labor rights in the first half of the twentieth century were fought to determine the relative distribution of income from labor and capital in enterprises where workers were organized. But technology-driven changes are now playing a much larger role in determining the future of work and what people earn in return for it. Arguments that used to occur in a zero-sum context no longer seem as relevant or persuasive when employers have the readily available options to: (a) simply close the factory or business and replicate it in a low-wage country, or (b) replace the labor with robots and automated systems.
From the standpoint of factory workers in the United States or Europe whose jobs are eliminated, the impact of automation and outsourcing is essentially the same. From the standpoint of the factory owner, productivity figures typically go up as a result of both offshoring and robosourcing—whether the new technology is deployed in the existing facility or in some foreign country.
Policymakers often count the result as a success because increased productivity is regarded as equivalent to the Holy Grail of progress. Yet they are often blind to the full impact of this process on employment in the country where the companies credited with productivity growth are nominally located, even though the trend is now accelerating to the point where the fundamental role of labor in the economy of the future is being called into question.
One manifestation of how the accelerating interconnection of the global economy drives both outsourcing and robosourcing simultaneously is that robosourcing is also occurring more and more rapidly in emerging and developing economies, and is beginning to eliminate a growing percentage of the jobs that were so recently outsourced from the advanced industrial economies.
There is a big difference between the investment of money in an offshore factory to replicate the same jobs that used to be located in the West, and the provision of what economists are beginning to label “technological capital”—investments that not only increase the productivity of business and industry, but over time eliminate large numbers of jobs both in the countries that originally lose the factories as well as in the countries to which they are relocated.
The workers in lower-wage countries initially benefit from the new employment opportunities—until the improved living standards they help to produce lead them to demand higher wages themselves. Then they too become vulnerable to being replaced when the factory owners are able to purchase ever improved—and ever cheaper—robots and automated processes with the new profits they have freshly earned as a result of outsourcing from the West. One Chinese consumer electronics manufacturer, Foxconn, announced in 2012 that it would soon deploy one million new robots within two years.
A positive feedback loop has emerged between Earth Inc.’s increasing integration on the one hand, and the progressive introduction of interconnected intelligent machines on the other. In other words, both of these trends—increased robosourcing and the interconnectedness of the global economy driven by trade and investment—reinforce one another.
The impact of robosourcing on employment is sometimes misunderstood as a process in which entire categories of employment are completely eliminated when a technological breakthrough suddenly results in the replacement of people with intelligent interconnected machines. Far more common, however, is that the intelligent networked machines replace a significant percentage of the jobs while greatly enhancing the productivity of the smaller number of the employees remaining by empowering them to leverage the efficiency of the machines that are now part of the production process alongside them.
The jobs that remain sometimes command higher wages in return for the new skills required to work with the new technology. And this pattern reinforces our tendency to misunderstand the aggregate impact of this new acceleration of robosourcing and see it as part of the long familiar pattern by which old jobs are eliminated and replaced by new and better jobs.
But what is different today is that we are beginning to climb the steep part of this technology curve, and the aggregate impact of this same process occurring in multiple businesses and industries simultaneously produces a large decline in employment. Moreover, many employees lack skills (in decimal arithmetic, for example, which is necessary to operate many robots) that they need to fill the new jobs.
New companies have emerged to connect online workers with jobs that can be cheaply and efficiently outsourced over the Internet. Gary Swart, the CEO of one of the more successful online job brokerages, oDesk, said he is seeing increased demand across the board, including for “lawyers, accountants, financial executives, even managers.” And robosourcing is beginning to have an impact on journalism. Narrative Science, a robot reporting company founded by two directors of Northwestern University’s Intelligent Information Laboratory, is now producing articles for newspapers and magazines with algorithms that analyze statistical data from sporting events, financial reports, and government studies. One of the cofounders, Kristian Hammond, who is also a professor at the Medill School of Journalism, told me that the business is expanding rapidly into many new fields of journalism. The CEO, Stuart Frankel, said the few human writers who work for the company have become “meta-journalists” who design the templates, frames, and angles into which the algorithm inserts data. In this way, he said, they “can write millions of stories as opposed to a single story at a time.”
THE CUMULATIVE EFFECT of the accelerating introduction of machine intelligence and the relocation of work to low-wage countries is also creating much greater inequality of incomes and net worth—not only in developed countries, but in the emerging economies as well. Those who lose their jobs have less income, while those who benefit from the increasing relative value of technological capital have increased income.
As this shift in the relative value of technology to labor continues to accelerate, so too will the levels of inequality. This phenomenon is not in the realm of theory. It is happening right now on a large scale. As technological capital becomes more and more important compared to the value of labor, more and more of the income derived from productive activities is becoming more and more concentrated in the hands of fewer and fewer elites, while a much larger number of people suffer the harm of lost income.
There is a growing concentration of wealth at the top of the income ladder in almost every industrial country and emerging nations like China and India. Latin America is the rare exception. Globally, technological offshoring has at least temporarily improved the equality of income, because of the massive transfer of industrial—and now service—jobs to lower-wage countries as a group. On a nation by nation basis, though, inequality of income distribution—and of net worth—is increasing even faster in China and India than in the U.S or Europe. And income inequality reached a twenty-year high in 2012 in thirty-two developing countries surveyed by the global NGO Save the Children.
Over the past quarter century, the Gini coefficient—which measures inequality of income nation by nation on a scale from 0 to 100 (from everyone having the same income at 0 to one person having all the nation’s income at 100)—has risen in the United States from 35 to 45, in China from 30 to the low 40s, in Russia from the mid 20s to the low 40s, and in the United Kingdom from 30 to 36. These nationwide numbers can obscure even more dramatic impacts within the wage ladder. For example, according to the OECD, the Organisation for Economic Co-operation and Development, the top 10 percent of wage earners in India now make more than twelve times what the bottom 10 percent make compared to six times just two decades ago.
The growing inequality of income and net worth in the United States has also been driven by changes in tax laws that favor those in higher-income brackets, including the virtual elimination of inheritance taxes and especially the taxation of investment income at the lowest tax rate of all—15 percent. When the tax rate imposed on income from capital investments is significantly lower than the tax rates imposed on income earned in return for labor or from those who sell the natural resources used in the process, then the ratio of income flowing to those providing the capital naturally increases.
In the United States 50 percent of all capital gains income goes to the top one thousandth of one percent. The current political ideology that supports this distribution of income refers to these wealthy investors as “job creators,” but with robosourcing and outsourcing, the cumulative impact of the capital they provide is, whatever its beneficial effects, negative in terms of jobs.
It is interesting to note that the United States now has more inequality than either Egypt or Tunisia. The Occupy Wall Street movement caught fire because of a broad awakening to the dramatic increase in the concentration of wealth held by the top one percent, who now have more wealth than the people in the bottom 90 percent. The wealthiest 400 Americans—all of them billionaires—have more wealth as a group than the 150 million Americans in the bottom 50 percent. The five children and one daughter-in-law of Sam and Bud Walton (the founders of Walmart) have more wealth than the bottom 30 percent of Americans.
In terms of annual income, the top one percent now receive almost 25 percent of all U.S. income annually, up from 12 percent just a quarter century ago. While the after-tax income of the average American climbed only 21 percent over the last twenty-five years, the income of the top 0.1 percent increased over the same period by 400 percent.
Now that many jobs in services as well as manufacturing and agriculture are all subject to progressive dislocation by the innovation and productivity curves that measure the accelerating impact of the underlying technology revolution, the need for income replacement is becoming acute.
By 2011, the cumulative investment by industrial countries in the rest of the world had increased eightfold over the previous thirty years, in the process growing from 5 to 40 percent of the GDP in developed countries. While overall world GDP is projected to increase by almost 25 percent in the next five years, cross-border capital flows are expected to continue increasing three times faster than GDP.
The cumulative investment by the rest of the world in advanced economies is also growing—though not by as much. Stocks of foreign direct investment in industrialized countries like the United States increased from 5 to 30 percent of GDP from 1980 to 2011. Partly as a result, these global trends have not only eliminated jobs in the U.S. but also created many new ones. Foreign-owned automobile companies, for example, now employ almost a half million people in the United States, paying them wages that are 20 percent higher than the national average.
Overall, foreign-majority-owned companies now provide jobs for more than five million U.S. citizens. And many other jobs have been created in companies that serve as suppliers and subcontractors to foreign companies. For example, even though China now dominates the manufacture of solar panels, the United States has a positive balance of trade with China in the solar sector—because of U.S. exports to China of processed polysilicon and advanced manufacturing equipment.
Nevertheless, the impacts of this global economic revolution are already producing a tectonic reordering of the relative roles of the United States, Europe, China, and other emerging economies. China’s economy, one third the size of the United States’ economy only ten years ago, will surpass the U.S. as the largest economy in the world within this decade. Indeed, China has already moved beyond America in manufacturing output, new fixed investment, exports, steel consumption, energy consumption, CO2 emissions, car sales, new patents granted to residents, and mobile phones. It now has twice the number of Internet users. China’s rise has become the most powerful symbol of the new pattern in the global economy quickly supplanting the one long associated with U.S. dominance.
The consequences of this transformation in the global economy are beginning to be manifested in unusually high rates of persistent unemployment and underemployment—and a slowdown in the demand for goods and services in consumer-oriented economies. The loss of middle-income jobs in industrial countries can no longer be blamed primarily on the business cycle—the alternating periods of recession and recovery that bring jobs in and out like the tide. Cyclical factors still account for considerable job gains and losses, but virtually all industrial countries seem perplexed and powerless in their efforts to create jobs with adequate wages, and are struggling with how to replace consumer demand for goods and services to reignite and/or solidify another recovery phase in the business cycle.
In the United States, the last ten years represents the only decade since the Great Depression when there have been zero net jobs added to the economy. During the same ten years, productivity growth has been higher than in any decade since the 1960s. Along with productivity, corporate profits have resumed healthy rates of increase while unemployment has barely declined. U.S. business spending on equipment and software increased by almost 30 percent while spending on private sector jobs increased by only 2 percent. Significantly, orders for new industrial robots in North America increased 41 percent.
Overall, the technology-enhanced integration of the global economy is lifting the relative economic strength of developing and emerging countries. This year (2013) the GDP of this group of countries (as measured by their purchasing power) will surpass the combined GDP of advanced economies for the first time in the modern era. The potential incapacity of these countries to maintain political and social stability and to deal with governance and corruption challenges may yet interrupt this trend. But the technological drivers of their ascent are powerful and are likely to prevail in consolidating and increasing a dramatic and truly fundamental change in the balance of global economic power. Already, in the aftermath of the Great Recession, it is the emerging economies that have become the principal engines of global growth. As a group they are growing much faster than the developed countries. Some analysts doubt the sustainability of these growth rates. But whatever their rate of growth, it is only a matter of time before these economies experience the same hemorrhaging of jobs to intelligent machines that is well under way in the West.
MOST PEOPLE AND political leaders in advanced industrial countries still attribute the disappearance of middle-income jobs simply to offshoring, without focusing on the underlying cause: the emergent reality of Earth Inc., and the deep interconnection between outsourcing and robosourcing. This misdiagnosis has led in turn to divisive debates over proposals to cut wages, impose trade restrictions, drastically change the social compact between old and young and rich and poor, and cut taxes on wealthy investors to encourage them to build more factories in the West.
These distracting and almost pointless arguments over labor policies are echoed in similarly misguided debates over the impact of national policies on financial flows in the age of Earth Inc. The nature and volume of capital movements in the ever more tightly interconnected global economy are being transformed by supercomputers and sophisticated software algorithms that now handle the vast majority of financial transactions with a destructive emphasis on extremely short-term horizons. One consequence of this change is a new level of volatility and contagion in the global economy as a whole. Major market disruptions are occurring with greater frequency and are reverberating more widely throughout the world.
The sudden disruption in credit markets that began in 2008, and the global recession it triggered, resulted in the loss of 27 million jobs worldwide. When the period of weak recovery began one year later, global output started to increase again but the number of jobs restored—particularly in industrial countries—lagged far behind. Many economists attributed the jobless nature of the recovery to a new eagerness by employers to introduce new technology instead of hiring back more people.
Exotic, computer-driven “manufactured financial products” like the ones that led to the Great Recession now represent capital flows with a notional value twenty-three times larger than the entire global GDP. These so-called derivatives are now traded every day in volumes forty times larger than all of the daily trades in all of the world’s stock markets put together. Indeed, even when the larger market in bonds is added to the market in stocks, the estimated value of derivatives is now thirteen times larger than the combined value of every stock and every bond on Earth.
The popular image of trading floors is still one where people yell at one another while making hand signals, but human beings have a much smaller role in the flows of capital in global markets now that they are dominated by high-speed, high-frequency trades made by supercomputers. In the United States, high-speed, high-frequency trading represented more than 60 percent of all trades in 2009. By 2012, in Europe as well as the U.S., it represented more than 60 percent of all trades. Indeed, stock exchanges now compete with one another with propositions like one from the London Exchange, which recently advertised its ability to complete a transaction in 124 microseconds (millionths of a second). More advanced algorithms will soon make trades in nanoseconds (billionths of a second), which according to some experts will further increase the risks of market disruptions.
An academic expert in automated trading at the University of Bristol, John Cartlidge, said recently that the result of the increasing speed of trades “is that we now live in a world dominated by a global financial market of which we have virtually no sound theoretical understanding.” In the first week of October 2012, a single “mystery algorithm” accounted for 10 percent of the bandwidth allowed for trading on the U.S. stock market—and 4 percent of all traffic in stock quotes. Experts suspected the motivation was to slow down data speeds in order to enhance the advantage for the high-speed computer trader.
Advantages in the speed of information flow have played an important role in markets for at least 200 years, since the Rothschild bank used carrier pigeons to get early word of Napoleon’s defeat at Waterloo, enabling them to make a fortune by shorting French bonds. Fifty years later, an American investor chartered faster sailboats to gain earlier knowledge of key battles in the U.S. Civil War and make a similar fortune by shorting bonds from the Confederacy. But the emphasis on speed has now reached absurd levels. Trading firms routinely place their supercomputers adjacent to their trading floors—because even at the speed of light, the amount of time it takes for the information to cross the street from another building would confer a competitive disadvantage.
A few years ago, a business friend in Silicon Valley told me about an opportunity to invest in an unusual project to build a straight-as-an-arrow fiber optic cable from Chicago’s trading center in the inner Loop to the New York Stock Exchange’s trading center in Mahwah, New Jersey. The inherent value of the project—since completed—came from its promise to shave three milliseconds off the time it took to transmit information over the 825 miles (from 16.3 to 13.3 milliseconds). Traders at the other end of the cable gain such a significant advantage with a three-millisecond head start over their competitors that access to this new cable is being sold at premium prices. An even newer microwave system with even faster data speeds (though less reliability in bad weather) is now being built along the same route.
The melting of the North Polar Ice Cap has led to the start of a new project to connect markets in Tokyo and New York with faster financial information flows via a fiber cable along the bottom of the Arctic Ocean. Three other projects have commenced to link Japan and Europe under the Arctic, and a new transatlantic cable being built for another $300 million is expected to increase the speed of data flows between New York and London by 5.2 milliseconds.
The spending of $300 million to save a few milliseconds in the flow of information is but one tiny example of how much of the wealth that used to be allocated to inherently productive activities is now diverted instead toward what many economists call the financialization of the economy. The share of the American economy now devoted to the financial sector has doubled from around 4 percent in 1980 to more than 8 percent at present.
Part of this startling increase reflected the large investments that financed the information technology explosion up to April of 2000, and part represented the rapid growth in mortgages that accompanied the buildup of the housing bubble up to 2008. Yet even after the bursting of the dot-com bubble, and later, the housing bubble, the financial services sector continued to gain a larger share of GDP. The driving force behind this historic shift has been the application of powerful supercomputers and algorithms to the manufacture of exotic financial derivatives—and the capitulation by government in the face of lobbying by the financial services industry for the relaxation of regulatory standards that used to impede the marketing of such instruments.
An estimated 82 percent of derivatives are exotic instruments based on interest rates, almost 11 percent are based on foreign exchange contracts, and roughly 6 percent are based on credit derivatives. Less than one percent are based on the value of actual commodities. But the overall flows are so incredibly large that, to pick one example, the value of oil derivatives traded on a typical day is an astonishing fourteen times the value of all the actual barrels of oil traded on that same day.
In theory, these high-volume, high-frequency computer-driven flows are justified by the assertion that they improve the liquidity and efficiency of markets. Many economists and bankers hold the view that the large flows of capital represented by derivatives actually add to the stability of markets and do not increase systemic risk, in part because banks hold collateral equal to a large percentage of what they are trading.
Others, however, point out that this view is based on the now obsolete assumption that more liquidity is always better—an assumption that is in turn based on two theories about markets that are part of the long discredited “standard model”: that markets tend toward equilibrium (they don’t), and that “perfect information” is implicitly reflected in the collective behavior found in the market (it isn’t). Nobel Prize–winning economist Joseph Stiglitz says that high-speed trading produces only “fake liquidity.”
Unlike trades in the stock and bond markets, derivatives trades are almost completely and totally unregulated. That adds to the risk of increased volatility in markets, especially when the daily volume of electronic transfers of capital now exceeds the combined total of all of the reserves in the central banks of all advanced countries. In practice, the progressive displacement of human decision making from the process and the explosion in the trading of artificial financial instruments in volumes that dwarf the transactions of real value in the global economy has contributed to the increased frequency of major dislocations in the role of capital as a reliable and efficient factor of production. Some of the artificial instruments now being traded in high volumes are difficult to distinguish from gambling.
There are two factors that explain the underlying reason why the management of global capital flows by supercomputers in microsecond intervals creates new systemic risks in markets: extreme complexity and tight coupling. And they work in combination. First, the complexity of the system sometimes produces large and troublesome anomalies caused by a form of “algorithmic harmonics” (essentially computer programs reacting to one another’s simultaneous operations rather than underlying market realities). This complexity means that the problems thus introduced into the system’s operation can be extremely difficult for any actual human being to understand without taking a considerable amount of time to get to the bottom of what has gone wrong. Second, the tight coupling of multiple supercomputers ensures that no one will have the luxury of time to figure out what’s gone wrong, much less the time to address it.
One example: on May 6, 2010, the value of the New York Stock Exchange fell a thousand points and rebounded almost as much—all in the time span of sixteen minutes—for no apparent reason. There was no market-sensitive news of the kind normally associated with a sharp drop of that magnitude in such a short timespan. As The New York Times reported the following day, “Accenture fell more than 90 percent to a penny, P&G plunged to $39.37 from more than $60 within minutes.” The Times quoted one trader as saying “it was almost like ‘the Twilight Zone.’ ”
It required five months of intensive work by specialists to understand what had happened to cause this so-called Flash Crash, which they eventually found was the result of the complex interaction between automatic trading algorithms used by a large number of supercomputers in a way that created, in effect, an algorithmic echo chamber that caused prices to suddenly crash.
When one of these experts, Joseph Stiglitz, recommended remedies to prevent the recurrence of the Flash Crash, he suggested a new rule to require that offers to buy or sell must remain open for one second. The captains of finance in charge of the financial companies with the most at stake in the current pattern of business, however, reacted with horror to this proposal, claiming that the one-second requirement would bring the global economy to its knees. The proposal was then rejected.
The global market crisis of 2008 was primarily caused by a particular kind of derivatives: securitized subprime mortgages hedged with an exotic form of insurance that turned out to be illusory. Supercomputers sliced and diced the subprime mortgages into derivatives that were so complex that no human being could possibly understand them. And once again, the robosourcing of these exotic financial instruments aided and abetted the marketing of those same products to buyers throughout the global economy.
When the actual quality and real value of the mortgages in question were belatedly examined, they were suddenly repriced on a mass basis—triggering the credit crisis and bursting the housing bubble in the United States. The fact that they had been linked to a complex web of other computer-driven financial transactions (collateralized debt obligations, or CDOs) led to the credit crisis, a massive disruption in the availability of capital as a basic factor of production in the global economy—essentially, a global run on banks. This led, in turn, to the Great Recession, the effects of which we are still struggling to escape.
Incidentally, after the manufacturing of these derivatives gained momentum and scale, virtually the only remaining role for human beings in the process resulted from the legal requirement for a signature on each underlying mortgage by someone with the responsibility for reviewing the integrity of each mortgage that had been sliced, diced, securitized, and rubber-stamped with a AAA rating by corrupted and captive ratings agencies, then sold around the world.
As the subsequent lawsuits revealed, this requirement for signatures by actual human beings could not keep up with the speed of the supercomputers—so low-wage employees were hired to forge the signatures of loan officers a hundred times a minute, without the slightest attention to the substance and meaning of the documents they were signing—a practice that’s been popularly labeled “robosigning.” Though no robots were involved, the very term illustrates the intertwining of robosourcing and outsourcing.
Until the crisis of 2008, the volume of trading in derivatives had been increasing since 2000 at an average of 65 percent per year. Since banks in the U.S. have been earning roughly $35 billion per year off these derivatives trades, there is no reason to believe that the growth in volumes will not once again resume; and no reason to expect that the banks will not continue to use their lobbying power and campaign contributions to prevent them from being regulated.
The causes of this unprecedented acceleration in the integration of the global economy have included several factors simultaneously: the collapse of communism and the introduction of more market-oriented policies in the former communist bloc countries; the opening and modernization of China under Deng Xiaoping (a process that has also continued to accelerate with the rapid rise of China’s economic strength); and revolutionary changes in transportation, communications, and information technology.
Perhaps most significantly, trade barriers were lowered in the liberalization process that began with the General Agreement on Tariffs and Trade (GATT) at the end of World War II (a process that has accelerated in the years since). International trade flows have increased tenfold over the last thirty years—from $3 trillion annually to $30 trillion annually—and are continuing to grow at a rate half again faster than global production.
There have, of course, been previous periods when new surges of global trade resulted in significant changes in the pattern of the global economy. The famous though brief voyages of the legendary Chinese eunuch Admiral Zheng He during the first three decades of the fifteenth century to East Africa prefigured the Voyages of Discovery by Christopher Columbus to the New World, by Vasco da Gama around the Cape of Good Hope, and by Cortés, Pizarro, and all the others that linked Europe to the New World and to Asia.
Prior to the development of intercontinental ocean trade routes, the establishment of the Mongol Empire in the thirteenth century and the Pax Mongolica that followed opened land routes for then unprecedented trade flows between China, India, Central Asia, Russia, and Eastern Europe. Following the Black Death in the mid-fourteenth century, and the weakening of Mongol rule, the closing of overland routes between Europe and Asia once again created a bottleneck that flowed through the Middle East, trade flows that were largely controlled by Venice and Egypt.
It was, in part, the intense economic pressure in Western Europe that contributed to the daring effort to find an ocean route to India and China. The influx of gold and silver from the New World to Europe—and not long after, the sharp gains in agricultural productivity that accompanied the introduction of maize (corn) and other New World food crops into Europe and Africa—revolutionized the old pattern of the global economy, such as it was.
Economic historians also remind us that China and India together accounted for half or more of world GDP from at least the year 1 through the beginning of the Second Industrial Revolution midway through the nineteenth century. China’s economy was the single largest in the world in 1500 and again in the early nineteenth century prior to the First Opium War, which began in 1839.
Seen in that perspective, the dominance of the United States and Europe in the global economy over the last 150 years was the interruption of a much longer period of Asian dominance in the share of world GDP. That century-and-a-half period represented a breakout by those nations that first embraced the Industrial Revolution—the United Kingdom, then the United States and northwestern Europe—while four fifths of the world’s population was left behind. In the modern era, it appears that China and other emerging and developing economies are the ones breaking out. Prior to the nineteenth century, the distribution of wealth in the world roughly correlated with population, but the surge in productivity enhancement that accompanied the Industrial Revolution and the Scientific and Technology Revolution led to much faster accumulations of wealth in the West. Then, when the East gained more access to the new technologies, the older pattern began to reassert itself.
Some economic experts attribute the rise of China and its imminent displacement of the United States as the world’s largest economy to advantages inherent in their system of state-guided capitalism, which they claim is superior to the much freer form of capitalism in the United States. If that were truly the explanation, the United States could take comfort from the fact that similar warnings about the advantages of an allegedly superior form of economic organization turned out to be false alarms in the late 1950s (when the Soviet Union was seen as an economic as well as military threat) and the 1970s and 1980s (when Japan Inc. was feared as a new economic hegemon).
However, if the emergence of Earth Inc. is more responsible for this phenomenon, as I believe it is, this time really is different. All over the developing world, nations like India that have long been mired in poverty are now beginning to unlock their vast potential as young entrepreneurs connect to their counterparts in countries throughout Earth Inc. and discover and develop innovations, large and small.
IN THE PAST, centers of expertise in a particular technology or industry usually emerged in specific locations where a cluster of people with similar skills and experience developed a local network of connections with one another, learned from one another, and improved one another’s innovations with incremental advances, sometimes called “tweaks.” British-Canadian journalist Malcolm Gladwell, writing in The New Yorker, gives a powerful example of this phenomenon:
In 1779, Samuel Crompton, a retiring genius from Lancashire, invented the spinning mule, which made possible the mechanization of cotton manufacture. Yet England’s real advantage was that it had Henry Stones, of Horwich, who added metal rollers to the mule; and James Hargreaves, of Tottington, who figured out how to smooth the acceleration and deceleration of the spinning wheel; and William Kelly, of Glasgow, who worked out how to add water power to the draw stroke; and John Kennedy, of Manchester, who adapted the wheel to turn out fine counts; and, finally, Richard Roberts, also of Manchester, a master of precision machine tooling—and the tweaker’s tweaker. He created the “automatic” spinning mule: an exacting, high-speed, reliable rethinking of Crompton’s original creation. Such men, the economists argue, provided the “micro inventions necessary to make macro inventions highly productive and remunerative.”
When the Industrial Revolution gained momentum in the United Kingdom during the eighteenth century, there was a proximate connection between the inventors, tinkerers, blacksmiths, and engineers who contributed to the improvement of a large cluster of technologies that later spread throughout the world. The revolution they started was at first confined to one country and then, slowly at first, spread throughout the North Atlantic region.
It’s true that technology clusters still matter. Silicon Valley, in Northern California, is one of the premier examples. Face-to-face, personal interactions among cutting-edge experts focused on the same set of technologies is still one of the most powerful ways to advance innovation. Yet global connectivity is speeding up the application of new technologies to ever more fields of endeavor, simultaneously pointing the way toward ever more frequent macro- and micro-inventions that accelerate the replacement of human jobs by connected intelligent machines. And seemingly small improvements in automation and efficiency often have outsized consequences for the overall efficiency and productivity in a particular sector.
To illustrate this point, consider two examples: one from the late stages of the mechanization of agriculture, in the 1950s, and the second a seemingly mundane but highly significant example from the late stages of the global Transportation Revolution, also from the 1950s, that marked a significant empowerment of much higher levels of connectivity in the global economy.
When I was a boy spending my summers on our family farm, I sometimes helped retrieve eggs from the chicken coop—one by one—when the hens had left the coop for their morning chicken feed. I remember being slightly amazed less than twenty years later when my father automated this process by building two new large chicken houses, each one containing 5,000 chickens, according to a design that was then spreading quickly on many American farms with chickens. In each house, the chickens roamed on wire mesh and then retreated to the only dark and inviting place where they could lay their eggs—which happened to be located directly above a conveyer belt. All of the eggs thus automatically collected were then funneled to a relatively simple sorting machine near the front of the building where the eggs rolled precisely into cartons. When each carton was filled, the next moved automatically into place for the collection of its designated allocation of eggs.
Out of deference to the chickens’ need for a rudimentary social life—so that they would remain sufficiently contented to lay eggs every day—heavily drugged roosters were placed approximately every fifteen square feet inside each chicken house. When they recovered from their stupor, they each established rule over their respective segments of the roost, and the hens in their immediate vicinity were happy. It also turned out that placing all the chickens in a confined area also conferred the operator of the chicken houses with a new ability (mildly disturbing to me at the time) to make the sun rise more than once per day—with artificial lighting—and thereby stimulate a greater production of eggs. (Note to PETA: I no longer have any connection to chicken houses.)
But what was most startling to me was that one employee was all that was needed to collect the daily output of eggs from 10,000 chickens. It was amazing that a single person could gather so many eggs, but why was a person involved at all? Sometimes an egg would be cracked and would have to be removed from the carton; sometimes a mechanical problem would interrupt the process and would require human intervention; it required a person to coordinate the transfer of the cartons to the truck that would regularly pick them up, to keep track of the total number of cartons per day, and so forth.
But it’s easy to see how the introduction of rudimentary layers of intelligence into the machinery and the connection over the Internet of the chicken house and its various components to quality control programs, computers scheduling the delivery trucks, and mechanics on call to respond to the rare interruptions in the process could easily displace that sole remaining job.
Is it possible to imagine any set of government policies that could protect the jobs lost in this process? Consider the earliest efforts to stem the loss of agricultural jobs: at the beginning of the second half of the nineteenth century in the United States, the loss of jobs on farms was already well under way, but few could imagine the transformation that was in store during the decades that followed. In a speech prior to becoming president, Abraham Lincoln noted on September 30, 1859: “farmers, being the most numerous class, it follows that their interest is the largest interest. It also follows that that interest is most worthy of all to be cherished and cultivated—that if there be inevitable conflict between that interest and any other, that other should yield.”
By the time of his inauguration, the percentage of all jobs represented by farm jobs had steadily declined from 90 percent at the beginning of the republic in 1789 to a little under 60 percent. The following year, in the spring of 1862, President Lincoln established the U.S. Department of Agriculture, and six weeks later signed the Morrill Land Grant College Act, providing public land for states to establish colleges of agriculture and the mechanical arts. Every state did so.
The crowding of cities with farm hands looking for work in factories led to a wholesale transformation of the nature of work for the vast majority in the U.S. The reforms of the Progressive Era, and later the New Deal, were introduced to address the human consequences of this transformation and, in part, to replace the lost flows of income with income transfer systems such as unemployment compensation and Social Security and disability payments.
When I became vice president in 1993, there were, on average, four different offices representing the Department of Agriculture located in every one of the 3,000 counties in the United States—yet the percentage of total jobs represented by farm jobs had declined to 2 percent. In other words, a determined and expensive national policy to promote agriculture for a century and a half did little or nothing to prevent the massive loss of employment opportunities on farms, although these policies arguably contributed to the massive increase in agricultural productivity. But the larger point is that many systemic technology-driven changes are simply too powerful for any set of policies to hold back.
Today, in fact, what is now referred to as factory farming has led to the mass introduction of partially automated systems for raising chickens, cattle, pigs, and other livestock—and for producing eggs. Over the last forty years, global production of eggs has increased by 350 percent. (China is by far the largest producer of eggs, with 70 million tons annually—four times the production of the United States.) Global trade in poultry meat has increased over the same period by more than 3,200 percent.
Here is a second example of a seemingly mundane advance that led to truly revolutionary progress in the efficiency of an entire industrial sector: the containership revolution began on October 4, 1957—on the very day that the first space satellite, Sputnik, was launched by the Soviet Union. Malcom McLean, a businessman who owned a trucking company in North Carolina, had wondered for almost twenty years why the cargo coming into U.S. ports from foreign countries was carried in boxes and enclosures of every size, shape, and description, which then had to be lifted and sorted individually onto the dock and moved from there to whatever conveyance was available to deliver each box to its ultimate destination—rather than packaged into enclosed symmetrical containers of the exact same size that could be lifted from each ship onto trains and trailer trucks and then transported to their destination.
In the spring of 1956, McLean experimented with his revolutionary idea by equipping one special deck on a ship bound from Newark, New Jersey, to Houston, Texas, with the bodies of fifty-eight trailer truck units that had been detached from the cab and chassis and loaded into slots on the ship. The experiment was so successful that eighteen months later he made history by outfitting an entire ship to carry 226 containers that were sent from port Newark and offloaded a week later in Houston onto the chassis of 226 trucks waiting to carry them to their destinations. The “containership revolution” that began in the fall of 1957 has had such an impact on global trade that in 2013 more than 150 million trailer-truck-sized containers will carry goods from one country to another.
The progressive introduction of intelligence and networking is accelerating this same process in almost all areas of manufacturing. High-quality large-screen television sets, for example, have come down more than 5 percent in price each year and are now in surplus supply (much as food grains were a few decades ago). The first color television set was sold in 1953 at a price that, in today’s dollars, would be $8,000. The cheapest color television sets for sale today—with the same or larger screen size, much greater picture clarity, and the ability to play hundreds of channels instead of only three—are available for as little as $50—or approximately one half of one percent of the cost in return for a product of much higher quality and much higher capacity.
We take such dramatic price reductions (and simultaneous quality improvements) for granted these days, but on a cumulative basis the impact for the world of work can no longer be ignored. Indeed, many consumer products that were once described as high-tech are now referred to by economists as commodities. The massive increase in world trade, combined with outsourcing, robosourcing, the new flows of information and investment connecting virtually all locations in the world to one another have all reinforced each other in a massive global feedback loop.
This pattern of progressive improvement in the effectiveness and utility of machine intelligence is under way in thousands of industries and it is the cumulative impact that is driving the global change in the nature and purpose of work in the world. Look, for example, at the coal industry in the United States. In the last quarter century, production has increased by 133 percent, even as jobs have decreased by 33 percent.
To take another example, jobs in the U.S. copper mining industry have declined precipitously in the last half century even as output increased significantly over much of that period. As is often the case when new technology replaces jobs, the pattern was not an even and steady decline, but a decline that lurched downward from one plateau to the next as new innovations became available and were implemented. In one six-year period—from 1980 to 1986—the number of hours of labor required to produce a ton of copper fell by 50 percent. In that same decade, one of the largest companies, Kennecott, increased labor productivity in one of its largest mines by 400 percent.
Looking more closely at this industry as an illustrative example of the broad trend, the new technologies that replaced jobs included much larger trucks and shovels, much broader use of computers for micromanaging the schedule of the trucks and the operation of the mills, much more efficient crushers connected to better conveyer belts, and the introduction of new chemical and electrochemical processes to automatically separate the pure copper from the ore.
The copper mining industry in the United States also illustrates changes from robosourcing and outsourcing that impact the third classical factor of production—resources. As technology increased labor productivity and the number of tons of copper produced year by year, the industry eventually reached a tipping point when the available supplies of economically recoverable copper ore began to diminish. New sources of copper were developed in other countries, principally Chile. Sharp increases in the efficiency of production, coupled with increasing consumption rates driven by population growth and increased affluence, are driving many industries toward constraints in the supplies of natural resources essential to their production processes.
In a process that is further reducing jobs and demand in the industrial world, robosourcing and IT-empowered outsourcing are now also beginning to have a major impact on jobs in the largest category of employment: services. Consider the impact of intelligent programs for legal and document research in law firms. Some studies indicate that with the addition of these programs, a single first-year associate can now perform with greater accuracy the volume of work that used to be done by 500 first-year associates.
Indeed, many predict that the impact of robosourcing will be even more pronounced in services than in manufacturing. Much has been written about Google’s success in developing self-driving automobiles, which have now traveled 300,000 miles in all driving conditions without an accident. If this technology is soon perfected—as many predict—consider the impact on the 373,000 people employed in the United States alone as taxi drivers and chauffeurs. Already, some Australian mining companies have replaced high-wage truck drivers with driverless trucks.
Where services are concerned, we are also seeing a third trend, which might be called “self-sourcing”: individual consumers of services, empowered with laptops, smartphones, tablets, and other productivity-enhancing devices, are interacting with intelligent programs to effectively partner with machine intelligence to effectively replace many of the people who used to be employed in service jobs. Many airline travelers routinely make their own reservations, pick their own seats, and print their boarding passes. Many supermarkets and other stores enable shoppers to handle the checkout and payment process on their own. Banks began to provide cash with ATM machines and now offer extensive online banking services. Customers of many businesses now routinely deal with computers on the telephone. National postal services in many countries, including the U.S., are being progressively disintermediated (that is, their “middleman” role is being made obsolete) by email and social media.
This self-sourcing trend is still in its early stages and will accelerate dramatically as artificial intelligence improves year by year. One obvious problem is that there is no compensation for all the new work done by individuals, even as the compensation formerly paid to those in firms who lost their jobs is also lost to the economy as a whole. The enhanced convenience associated with self-sourcing improves efficiency and saves time, to be sure, but on an aggregate basis, the overall reduction in income for middle-income wage earners is beginning to have a noticeable impact on aggregate demand—particularly in consumer-oriented societies.
ON A GLOBAL basis, offshoring and robosourcing are together pushing the economy toward a simultaneous weakening of demand and surplus of production. The use of Keynesian stimulus policies—that is, government borrowing to finance temporary increases in aggregate demand—may become less effective over time as the secular, systemic shift to an economy with far fewer jobs relative to production represents a larger cause of declining incomes, and thus declining consumption and demand. In addition, as I’ll detail later, unprecedented demographic shifts include a larger proportion of older, retired people in industrial countries whose incomes are already replaced by programs such as Social Security—thereby limiting the ability of governments to replace income indefinitely to working age people.
Unless the lost income of the unemployed and underemployed factory workers in industrial countries can somehow be replaced, global demand for the products of the new highly automated factories will continue to decline. The industrial economies, after all, continue to provide the greatest share of global demand and consumption. Higher wages paid to workers in developing and emerging economies are far more likely—in part for cultural reasons—to go into savings instead of consumption. While both labor and capital have been globalized, the bulk of consumption in the world economy remains in wealthy industrial countries. This results in a mismatch between the distribution of income and the central role of consumption in driving global economic growth.
These accelerating changes will therefore require us to reimagine the now central role of consumption in our economy and simultaneously replace the flows of income to workers that presently empower consumption. The current connection between ever rising levels of consumption and the health of the global economy is increasingly unstable in any case.
The accelerating technology revolution is not only transforming the role of labor and capital as factors of production in the global economy, it is also transforming the role of resources. The new technologies of molecular manipulation have led to revolutionary advances in the materials sciences and brand-new hybrid materials that possess a combination of physical attributes far exceeding those of any materials developed through the much older technologies of metallurgy and ceramics. As Pierre Teilhard de Chardin predicted more than sixty years ago, “In becoming planetized, humanity is acquiring new physical powers which will enable it to super-organize matter.”
The new field of advanced materials science involves the study, manipulation, and fabrication of solid matter with highly sophisticated tools, almost on an atom-by-atom basis. It involves many interdisciplinary fields, including engineering, physics, chemistry, and biology. The new insights being developed into the ways that molecules control and direct basic functions in biology, chemistry, and the interaction of atomic and subatomic processes that form solid matter is speeding up the emergence of what some experts are calling the molecular economy.
Significantly, the new molecules and materials created need not be evaluated through the traditional, laborious process of trial and error. Advanced supercomputers are now capable of simulating the way these novel creations interact with other molecules and materials, allowing the selection of only the ones that are most promising for experiments in the real world. Indeed, the new field known as computational science has now been recognized as a third basic form of knowledge creation—alongside inductive reasoning and deductive reasoning—and combines elements of the first two by simulating an artificial reality that functions as a much more concrete form of hypothesis and allows detailed experimentation to examine the new materials’ properties and analyze how they interact with other molecules and materials.
The properties of matter at the nanometer scale (between one and 100 nanometers) often differ significantly from the properties of the same atoms and molecules when they are clustered in bulk. These differences have allowed technologists to use nanomaterials on the surfaces of common products in order to eliminate rust, enhance resistance to scratches and dents, and in clothes to enhance resistance to stains, wrinkles, and fire. The single most common application thus far is the use of nanoscale silver to destroy microbes—a use that is particularly important for doctors and hospitals guarding against infections.
The longer-term significance that attaches to the emergence of an entirely new group of basic materials with superior properties is reflected in the names historians give to the ages of technological achievement in human societies: the Stone Age, the Bronze Age, and the Iron Age. As was true of the historical stages of economic development that began with the long hunter-gatherer period, the first of these periods—the Stone Age—was by far the longest.
Archaeologists disagree on when and where the reliance on stone tools gave way to the first metallurgical technologies. The first smelting of copper is believed to have taken place in eastern Serbia approximately 7,000 years ago, though objects made of cast copper emerged in numerous locations in the same era.
The more sophisticated creation of bronze—which is much less brittle and much more useful for many purposes than copper—involves a process in which tin is added to molten copper, a technique that combines high temperatures and some pressurization. Bronze was first created 5,000 years ago in both Greece and China, and more than 1,000 years later in Britain.
Though the first iron artifacts date back 4,500 years ago in northern Turkey, the Iron Age began between 3,000 and 3,200 years ago with the development of better furnaces that achieved higher temperatures capable of heating iron ore into a malleable state from which it could be made into tools and weapons. Iron, of course, is much harder and stronger than bronze. Steel, an alloy made from iron, and often other elements in smaller quantities, depending upon the properties desired, was not made until the middle of the nineteenth century.
The new age of materials created at the molecular level is leading to a historic transformation of the manufacturing process. Just as the Industrial Revolution was launched a quarter of a millennium ago by the marriage of coal-powered energy with machines in order to replace many forms of human labor, nanotechnology promises to launch what many are calling a Third Industrial Revolution based on molecular machines that can reassemble structures made from basic elements to create an entirely new category of products, including:
• Carbon nanotubes invested with the ability to store energy and manifest previously unimaginable properties;
• Ultrastrong carbon fibers that are already replacing steel in some niche applications; and
• Ceramic matrix nanocomposites that are expected to have wide applications in industry.
The emerging Nanotechnology Revolution, which is converging with the multiple revolutions in the life sciences, also has implications in a wide variety of other human endeavors. There are already more than 1,000 nanotechnology products available, most of them classified as incremental improvements in already known processes, mostly in the health and fitness category. The use of nanostructures for the enhancement of computer processing, the storage of memory, the identification of toxics in the environment, the filtration and desalination of water, and other uses are still in development.
The reactivity of nanomaterials and their thermal, electrical, and optical properties are among the changes that could have significant commercial impact. For example, the development of graphene—a form of graphite only one atom thick—has created excitement about its unusual interaction with electrons, which opens a variety of useful applications.
Considerable research is under way on potential hazards of nanoparticles. Most experts now minimize the possibility of “self-replicating nanobots,” which gave rise to serious concerns and much debate in the first years of the twenty-first century, but other risks—such as the accumulation of nanoparticles in human beings and the possibility of consequent cell damage—are taken more seriously. According to David Rejeski, director of the Science and Technology Innovation Program at the Woodrow Wilson International Center for Scholars, “We know very little about the health and environmental impacts [of nanomaterials] and virtually nothing about their synergistic impacts.”
In a sense, nanoscience has been around at least since the work of Louis Pasteur, and certainly since the discovery of the double helix in 1953. The work of Richard Smalley on buckminsterfullerene molecules (“buckyballs”) in 1985 triggered a renewed surge of interest in the application of nanotechnology to the development of new materials. Six years later, the first carbon nanotubes offered the promise of electrical conductivity exceeding that of copper and the possibility of creating fibers with 100 times the strength and one sixth the weight of steel.
The dividing line between nanotechnology and new materials sciences is partly an arbitrary one. What both have in common is the recent development of new more powerful microscopes, new tools for guiding the manipulation of matter at nanoscales, the development of new more powerful supercomputer programs for modeling and studying new materials at the atomic level, and a continuing stream of new basic research breakthroughs on the specialized properties of nanoscale molecular creations, including quantum properties.
Humankind’s new ability to manipulate atoms and molecules is also leading toward the disruptive revolution in manufacturing known as 3D printing. Also known as additive manufacturing, this new process builds objects from a three-dimensional digital file by laying down an ultrathin layer of whatever material or materials the object is to be made of, and then adds each additional ultrathin layer—one by one—until the object is formed in three-dimensional space. More than one different kind of material can be used. Although this new technology is still early in its development period, the advantages it brings to manufacturing are difficult to overstate. Already, some of the results are startling.
Since 1908, when Henry Ford first used identical interchangeable parts that were fitted together on a moving assembly line to produce the Model T, manufacturing has been dominated by mass production. The efficiencies, speed, and cost savings in the process revolutionized industry and commerce. But many experts now predict that the rapid development of 3D printing will change manufacturing as profoundly as mass production did more than 100 years ago.
The process has actually been used for several decades in a technique known as rapid prototyping—a specialized niche in which manufacturers could produce an initial model of what they would later produce en masse in more traditional processes. For example, the designs for new aircraft are often prototyped as 3D models for wind tunnel testing. This niche is itself being disrupted by the new 3D printers; one Colorado firm, LGM, that prototypes buildings for architects, has already made dramatic changes. The company’s founder, Charles Overy, told The New York Times, “We used to take two months to build $100,000 models.” Instead, he now builds $2,000 models and completes them overnight.
The emerging potential for using 3D printing is illuminating some of the inefficiencies in mass production: the stockpiling of components and parts, the large amount of working capital required for such stockpiling, the profligate waste of materials, and of course the expense of employing large numbers of people. Enthusiasts also contend that 3D printing often requires only 10 percent of the raw material that is used in the mass production process, not to mention a small fraction of the energy costs. It continues and accelerates a longer-term trend toward “dematerialization” of manufactured goods—a trend that has already kept the total tonnage of global goods constant over the past half century, even as their value has increased more than threefold.
In addition, the requirement for standardizing the size and shape of products made in mass production leads to a “one size fits all” approach that is unsatisfactory for many kinds of specialized products. Mass production also requires the centralization of manufacturing facilities and the consequent transportation costs for delivery of parts to the factory and finished products to distant markets. By contrast, 3D printing offers the promise of transmitting the digital information that embodies the design and blueprint for each product to widely dispersed 3D printers located in all relevant markets.
Neil Hopkinson, senior lecturer in the Additive Manufacturing Research Group at Loughborough University, said, “It could make offshore manufacturing half way round the world far less cost effective than doing it at home, if users can get the part they need printed off just round the corner at a 3D print shop on the high street. Rather than stockpile spare parts and components in locations all over the world, the designs could be costlessly stored in virtual computer warehouses waiting to be printed locally when required.”
At its current stage of development, 3D printing focuses on relatively small products, but as the technique is steadily improved, specialized 3D printers for larger parts and products will soon be available. One company based in Los Angeles, Contour Crafting, has already built a huge 3D printer that travels on a tractor-trailer to a construction site and prints an entire house in only twenty hours (doors and windows not included)! In addition, while the 3D printers now available have production runs of one item up to, in some cases, 1,000 items, experts predict that within the next few years these machines will be capable of turning out hundreds of thousands of identical parts and products.
There are many questions yet to be answered about the treatment of intellectual property in a 3D printing era. The three-dimensional design will make up the lion’s share of the value in a 3D printing economy, but copyright and patent law were developed without the anticipation of this technology and will have to be modified to account for the new emerging reality. In general, “useful” physical objects often do not have protection against replication under copyright laws.
Although there are skeptics who question how fast this new technology will mature, engineers and technologists in the United States, China, and Europe are working hard to exploit its potential. Its early use in printing prosthetics and other devices with medical applications is gaining momentum rapidly. Inexpensive 3D printers have already found their way into the hobbyist market at prices as low as $1,000. Carl Bass, the CEO of Autodesk, which has invested in 3D printing, said in 2012, “Some people see it as a niche market. They claim that it can’t possibly scale. But this is a trend, not a fad. Something seismic is going on.” Some advocates of more widespread gun ownership are promoting the 3D printing of guns as a way to circumvent regulations on gun sales. Opponents have expressed concern that any such guns used in crimes could be easily melted down to avoid any effort by law enforcement authorities to use the guns as evidence.
THE WAVE OF automation that is contributing to the outsourcing and robosourcing of jobs from developed countries to emerging and developing markets will soon begin to displace many of the jobs so recently created in those same low-wage countries. 3D printing could accelerate this process, and eventually could also move manufacturing back into developed countries. Many U.S. companies have already reported that various forms of automation have enabled them to bring back at least some of the jobs they had originally outsourced to low-wage countries.
The emergence of Earth Inc. and its disruption of all three factors of production—labor, capital, and natural resources—has contributed to what many have referred to as a crisis in capitalism. A 2012 Bloomberg Global Poll of business leaders around the world found that 70 percent believe capitalism is “in trouble.” Almost one third said it needs a “radical reworking of the rules and regulations”—though U.S. participants were less willing than their global counterparts to endorse either conclusion.
The inherent advantages of capitalism over any other system for organizing economic activity are well understood. It is far more efficient in allocating resources and matching supply to demand; it is far more effective at creating wealth; and it is far more congruent with higher levels of freedom. Most fundamentally, capitalism unlocks a larger fraction of the human potential with ubiquitous organic incentives that reward effort and innovation. The world’s experimentation with other systems—including the disastrous experiences with communism and fascism in the twentieth century—led to a nearly unanimous consensus at the beginning of the twenty-first century that democratic capitalism was the ideology of choice throughout the world.
And yet publics around the world have been shaken by a series of significant market dislocations over the last two decades, culminating in the Great Recession of 2008 and its lingering aftermath. In addition, the growing inequality in most large economies in the world and the growing concentration of wealth at the top of the income ladder have caused a crisis of confidence in the system of market capitalism as it is presently functioning. The persistent high levels of unemployment and underemployment in industrial countries, added to unusually high levels of public and private indebtedness, have also diminished confidence that the economic policy toolkit now being used can produce a recovery that is strong enough to restore adequate vitality.
As Nobel Prize–winning economist Joseph Stiglitz put it in 2012:
It is no accident that the periods in which the broadest cross sections of Americans have reported higher net incomes—when inequality has been reduced, partly as a result of progressive taxation—have been the periods in which the U.S. economy has grown the fastest. It is likewise no accident that the current recession, like the great Depression, was preceded by large increases in inequality. When too much money is concentrated at the top of society, spending by the average American is necessarily reduced—or at least it will be in the absence of an artificial prop. Moving money from the bottom to the top lowers consumption because higher-income individuals consume, as a fraction of their income, less than lower-income individuals do.
While developing and emerging economies are seeing increases in productivity, jobs, incomes, and output, inequality within these countries is also increasing. And of course, many of them still have significant numbers of people experiencing extreme poverty and deprivation. More than one billion people in the world still live on less than $2 a day, and almost 900 million of them still live in “extreme poverty”—defined as having an income less than $1.25 per day.
Most important of all, among the failures in the way the global market system is operating today is its almost complete refusal to include any recognition of major externalities, starting with its failure to take into account the cost and consequences of the 90 million tons of global warming pollution spewed every twenty-four hours into the planet’s atmosphere. The problem of externalities in market theory is well known but has never been so acute as now. Positive externalities are also routinely ignored, leading to chronic underinvestment in education, health care, and other public goods.
In many countries, including the United States, the growing concentration of wealth in the hands of the top one percent has also led to distortions in the political system that now limit the ability of governments to consider policy changes that might benefit the many at the (at least short-term) expense of the few. Governments have been effectively paralyzed and incapable of taking needed action. This too has undermined public confidence in the way market capitalism is currently operating.
With the tightly coupled and increasingly massive flows of capital through the global economy, all governments now feel that they are hostage to the perceptions within the global market for capital. There are numerous examples—Greece, Ireland, Italy, Portugal, and Spain, to name a few—of countries’ confronting policy choices that appear to be mandated by the perceptions of the global marketplace, not by the democratically expressed will of the citizens in those countries. Many have come to the conclusion that the only policies that will prove to be effective in restoring human influence over the shape of our economic future will be ones that address the new global economic reality on a global basis.
Along with my partner and cofounder of Generation Investment Management, David Blood, I have advocated a set of structural remedies that would promote what we call Sustainable Capitalism. One of the best-known problems is the dominance of short-term perspectives and the obsession with short-term profits, often at the expense of the buildup of long-term value. Forty years ago, the average holding period for stocks in the United States was almost seven years. That made sense because roughly three quarters of the real value in the average business builds up over a business cycle and a half, roughly seven years. Today, however, the average holding period for stocks is less than seven months.
There are many reasons for the increasing reliance on short-term thinking by investors. These pressures are accentuated by the larger trends in the transformed and now interconnected global economy. As one analyst noted in 2012, “our banks, hedge funds and venture capitalists are geared toward investing in financial instruments and software companies. In such endeavors, even modest investments can yield extraordinarily quick and large returns. Financing brick-and-mortar factories, by contrast, is expensive and painstaking and offers far less potential for speedy returns.”
This short-term perspective on the part of investors puts pressure on CEOs to adopt similarly short-term perspectives. For example, a premier business research firm in the United States (BNA) conducted a survey of CEOs and CFOs a few years ago in which it asked, among other things, a hypothetical question: You have the opportunity to make an investment in your company that will make the firm more profitable and more sustainable, but if you do so, you will slightly miss your next quarterly earnings report; under these circumstances, will you make the investment? Eighty percent said no.
A second well-known problem in the way capitalism currently operates is the widespread misalignment of incentives. The compensation of most investment managers—the people that make most of the daily decisions on the investment of capital—is calculated on a quarterly, or at most annual, basis. Similarly, many executives running companies are compensated in ways that reward short-term results. Instead, compensation should be aligned temporally with the period over which the maximum value of firms can be increased, and should be aligned with the fundamental drivers of long-term value.
In addition, companies should be encouraged to abandon the default practice of providing quarterly earnings guidance. These short-term metrics capture so much attention that they end up heavily penalizing firms that try to build sustainable value, and fail to take into account the usefulness of investments that pay for themselves handsomely over longer periods of time.
One thing is certain: the transformation of the global economy and the emergence of Earth Inc. will require an entirely new approach to policy in order to reclaim humanity’s role in shaping our own future. What we are now going through bears little relation to the problems inherent in the business cycle or the kinds of temporary market disruptions to which global business has become accustomed. The changes brought about by the emergence of Earth Inc. are truly global, truly historic, and are still accelerating.
Although the current changes are unprecedented in speed and scale, the pattern of productive activity for the majority of human beings has of course undergone several massive changes throughout the span of human history. Most notably, the Agricultural and Industrial revolutions both led to dramatic changes in the way the majority of people in the world spent their days.
The first known man-made tools, including spear points and axes, were associated with a hunting and gathering pattern that lasted, according to anthropologists, almost 200 millennia. The displacement of that dominant pattern by a new one based on agriculture (beginning not long after the last Ice Age receded) took less than eight millennia, while the Industrial Revolution required less than 150 years to reduce the percentage of agricultural jobs in the United States from 90 to 2 percent of the workforce. Even when societies still based on subsistence agriculture are included in the global calculation, less than half of all jobs worldwide are now on farms.
The plow and the steam engine—along with the complex universe of tools and technologies that accompanied the Agricultural and Industrial revolutions respectively—undermined the value of skills and expertise that had long been relied upon to connect the meaning of people’s lives to the provision of subsistence and material gains for themselves, their families, and communities. Nevertheless, in both cases, the disappearance of old patterns was accompanied by the emergence of new ones that, on balance, made life easier and retained the link between productive activity and the meeting of real needs.
To be sure, the transformation of work opportunities required large changes in social patterns, including mass internal migrations from rural areas to cities, and the geographic separation of homes and workplaces, to mention only two of the most prominent disruptions. But the net result was still consistent with the hopeful narrative of progress and was accompanied by economic growth that increased net incomes dramatically and sharply reduced the amount of work necessary to meet basic human needs: food, clothing, shelter, and the like. In both cases, formerly common pursuits became obsolete while new ones emerged that called for new skills and a reconception of what it meant to be productive.
Both of these massive transformations occurred over long periods of time covering multiple generations. In both revolutions, new technologies opened up new opportunities for reorganizing the human enterprise into a new dominant pattern that was in each case disruptive and, for many, disorienting—but produced massive increases in productivity, large increases in the number of jobs, higher average incomes, less poverty, and historic improvements in the quality of life for most people.
Consider again the larger pattern traced in the history of these three epochs: the first lasted 200,000 years, the next lasted 8,000 years, and the Industrial Revolution took only 150 years. Each of these historic changes in the nature of the human experience was more significant than its predecessor and occurred over a radically shorter time span. All were connected to technological innovations.
Taken together, they trace the long gestation, infancy, and slow development of a technology revolution that eventually grew to play a central role in the advance of human civilization—then gradually but steadily gained speed and momentum in each of the last four centuries, jolted into a higher gear, and began to accelerate at an ever faster rate until it seemed to take on a life of its own. It is now carrying us with it at a speed beyond our imagining toward ever newer technologically shaped realities that often appear, in the words of Arthur C. Clarke, “indistinguishable from magic.”
Because the change under way is one not only of degree but of kind, we are largely unprepared for what’s happening. The structure of our brains is not very different from that of our ancestors 200,000 years ago. Because of the radical changes induced by technology in the way we live our lives, however, we are forced to consider making adaptations in the design of our civilization more rapidly than seems possible or even plausible.
We have difficulty even perceiving and thinking clearly about the pace of change with which we are now confronted. Most of us struggle with the practical meaning of exponential change—that is, change that is not only increasing but is increasing at a steadily faster pace. Consider the basic shape of all exponential curves. The pattern of change measured by such curves is slow at first, and then ascends at a gradually but ever increasing rate as the angle of ascent steepens. The steep phase of the curve drives changes at a far more rapid rate than the flat part of the curve—and it is this phase that has consequences not only of degree but of kind. As explained by Moore’s Law, the fourth-generation iPad now has more computing power than the most powerful supercomputer in the world thirty years ago, the Cray-2.
The implications of this new period of hyper-change are not just mathematical or theoretical. They are transforming the fundamental link between how we play a productive role in life and how we meet our needs. What people do—their work, their careers, their opportunities to exchange productive activity for income to meet essential human needs and provide a sense of well-being, security, honor, dignity, and a sense of belonging as a member of the community: this basic exchange at the center of our lives is now changing on a global scale and at a speed with no precedent in human history.
In modern societies we have long since used money and other tangible symbols of credit and debit as the principal means of measuring and keeping track of this ongoing series of exchanges. But even in older forms of society where money was not the medium of exchange, productive work also was connected to the ability to meet one’s needs, with a tacit recognition by the community of those who contributed to the needs of the group, and whose needs were then met partly by others in the group. It is that basic connection at the heart of human societies that is beginning to be radically transformed.
Many economists comfort themselves with the idea that this is actually an old and continuing story that they know and understand well—a story that has generated unnecessary alarm since Ned Ludd, a weaver, smashed the new knitting frames invented in the late eighteenth century, which he realized were making the jobs of weavers obsolete. The “Luddite fallacy”—a phrase coined to describe the mistaken belief that new technologies will result in a net reduction of good jobs for people—was validated on a large scale when the mechanization of farming eliminated all but a tiny fraction of farm-related jobs, and yet the new jobs that emerged in factories not only outnumbered those lost on farms but produced higher incomes, even as farms became far more productive and food prices sharply declined. Until recently, the large-scale automation of industry seemed to be repeating the same pattern again: routine, repetitive, and often arduous jobs were eliminated, while better jobs with higher wages more than replaced those that were eliminated.
Yet what we believe we learned during the early stages of this technology revolution may no longer be relevant to the new hyper-accelerated pace of change. The introduction of networked machine intelligence—and now artificial intelligence—may soon put a much higher percentage of employment opportunities at risk in ever larger sectors of the global economy. In order to adapt to this new emergent reality we may soon have to reimagine the way we as human beings exchange our productive potential for the income necessary to meet our needs.
Many scholars who have specialized in the study of technology’s interaction with the pattern of society, including Marshall McLuhan, have described important new technologies as “extensions” of basic human capacities. The automobile, in the terms of this metaphor, is an extension of our capacity for locomotion. The telegraph, radio, and television are, in the same way, described as extensions of our ability to speak with one another over a greater distance. Both the shovel and the steam shovel are extensions of our hands and our ability to grasp physical objects. New technologies such as these made some jobs obsolete, but on balance created more new ones—often because the new technologically enhanced capacities had to be operated or used by people who could think clearly enough to be trained to use them effectively and safely.
In this context, the emergence of new and powerful forms of artificial intelligence represents not just the extension of yet another human capacity, but an extension of the dominant and uniquely human capacity to think. Though science has established that we are not the only sentient living creatures, it is nevertheless abundantly obvious that we as a species have become dominant on Earth because of our capacity to make mental models of the world around us and manipulate those models through thought to gain the power to transform our surroundings and exert dominion over the planet. The technological extension of the ability to think is therefore different in a fundamental way from any other technological extension of human capacity.
As artificial intelligence matures and is connected with all the other technological extensions of human capacity—grasping and manipulating physical objects, recombining them into new forms, carrying them over distance, communicating with one another utilizing flows of information of far greater volume and far greater speed than any humans are capable of achieving, making their own abstract models of reality, and learning in ways that are sometimes superior to the human capacity to learn—the impact of the AI revolution will be far greater than that of any previous technological revolution.
One of the impacts will be to further accelerate the decoupling of gains in productivity from gains in the standard of living for the middle class. In the past, improvements in economic efficiency have generally led to improvements in wages for the majority, but when the substitution of technology capital for labor creates the elimination of very large numbers of jobs, a much larger proportion of the gains go to those who provide the capital. The fundamental relationship between technology and employment is being transformed.
This trend is now nearing a threshold beyond which so many jobs are lost that the level of consumer demand falls below the level necessary to sustain healthy economic growth. In a new study of the Great Depression, Joseph Stiglitz has argued that the massive loss of jobs in agriculture that accompanied the mechanization of farming led to a similar contraction of demand that was actually a much larger factor in causing the Depression than has been previously recognized—and that we may be poised for another wrenching transition with the present ongoing loss of manufacturing jobs.
New jobs can and must be created, and one of the obvious targets for new employment is the provision of public goods in order to replace the income lost by those whose employment is being robosourced and outsourced. But elites who have benefited from the emergence of Earth Inc. have thus far effectively used their accumulated wealth and political influence to block any shift of jobs to the public sector. The good news is that even though the Internet has facilitated both outsourcing and robosourcing, it is also providing a new means to build new forms of political influence not controlled by elites. This is a major focus of the next chapter.
* This term was first coined by Buckminster Fuller in 1973, but he used it to convey a completely different meaning.