The Technology Trap

August 9, 2019

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Carl Benedikt Frey. The Technology Trap: Capital, Labor, and Power in the Age of Automation. Princeton: Princeton University Press, 2019

Economic historian Carl Frey deepens our understanding of the current technology revolution by comparing it to previous technology-driven transitions. Although the author is perhaps best known for his estimate that 47% of American jobs are vulnerable to automation, his general view is fairly optimistic. He does not doubt the long-run benefits of the Industrial Revolution, which has doubled per-capita income every 50 years since 1750. He expects similar benefits from the new digital technologies, eventually. But he is concerned about the loss of jobs due to automation and the resistance to change it may generate.

Two sides of technology

For many years, the conventional wisdom in economics was that new technologies create as many jobs as they destroy, and do so fairly quickly. More recent thinking distinguishes two different effects of technology, either of which may dominate.

The extent to which labor-saving technologies will cause dislocation depends on whether they are enabling or replacing. Replacing technologies render jobs and skills redundant. Enabling technologies, in contrast, make people more productive in existing tasks or create entirely new jobs for them.

A classic example of a replacing technology is the early industrial power loom, which replaced the hand loom for weaving cloth and put a lot of weavers out of work. An example of an enabling technology is an X-ray machine, which improves a physician’s ability to diagnose disease.

Which side of technology is more prevalent has implications for labor demand, wages, and the share of national income going to labor as opposed to capital.

If technology replaces labor in existing tasks, wages and the share of national income accruing to labor may fall. If, in contrast, technological change is augmenting labor, it will make workers more productive in existing tasks or create entirely new labor-intensive activities, thereby increasing the demand for labor.

Just because a technology is available does not mean that people will want to adopt it. That depends on how they expect it to impact their income. And since different groups can be affected differently, technological change depends on who stands to gain or lose and the distribution of power among competing interests.

Technology traps

Societies fall into a technology trap when they are unable to implement a potentially useful technology due to social resistance. Frey uses the term mainly in reference to preindustrial societies, although he fears that we could fall into a similar trap today. “One reason economic growth was stagnant for millennia is that the world was caught in a technology trap, in which labor-replacing technology was consistently and vigorously resisted for fear of its destabilizing force.”

During the period that he calls “The Great Stagnation,” the problem was not so much that innovations didn’t appear, but that people lacked the incentive to implement them, especially for purposes of saving labor in economic production. He characterizes the Renaissance as both a cultural movement and “a force of profound technological change,” but a period with “plenty of imagination, but little realization.” One reason why industrialization didn’t occur earlier than it did was that landed elites were living comfortably off cheap labor they controlled, and had no interest in seeing them go to town to work in a factory. In the late eighteenth century, 96% of the world’s population were slaves, serfs, servants, or vassals. Many monarchs also preferred the status quo to the uncertainties of a social upheaval.

The fear among the ruling classes that labor displacement would cause hardship, social unrest, and at worst a challenge to the political status quo meant that worker-replacing technologies frequently were resisted or even banned. This dynamic, in which the politically powerful had more to lose than they could gain from progress, kept the Western world in a technology trap where technologies that threatened people’s skills were forcefully resisted.

Who gained from industrialization?

When the Industrial Revolution did begin in Britain, it was in someone’s interest to make it happen.

The hegemony of landed wealth was challenged by the mobile fortunes of merchants, who came to form a new industrial class with growing political influence. The mechanized factory was deemed critical to Britain’s competitive position in trade and thus to merchants’ fortunes, which its government would do nothing to jeopardize.

The position of the merchants was strengthened by profits from the Atlantic trade, which were not as monopolized by royal trading companies as they were in other parts of Europe. Merchants also got some support from a stronger Parliament, after the Civil War and the Glorious Revolution. “In eighteenth-century England, the polity and judiciary, which had previously supported the cause of workers and guilds and opposed replacing technologies, began to side with the innovators.”

At first, industrialization benefited neither the artisans who had been spinning, weaving and sewing in cottage industries, nor the workers in the early textile mills. The main effect of innovations like the spinning jenny and the power loom was to replace skilled artisan labor with something cheaper. The new factory jobs paid less, required less skill, and were done by children about half the time. It took about seventy years, from about 1770 to 1840, before the British working class started to share the benefits from industrialization. But they were helpless to stop the process because of their weak political position. In 1769, Parliament made it a capital crime to destroy machinery, as some protesters had been doing.

The situation during the “Second Industrial Revolution,” when the United States emerged as the leading industrial power, was very different. Here Frey says that the new technologies, especially electric power and the internal combustion engine, “were predominantly of the enabling sort.” They raised worker productivity and created new jobs more than they replaced workers. He cites the work of another economic historian:

Alexander Field has argued that productivity growth in the period 1919–73 can be thought of as “a tale of two transitions.” The first involved the redesign of the factory to take advantage of the virtues of electricity, whereas the second constituted a shift toward the horseless age, as motorized vehicles revolutionized transportation and distribution.

In this case, the benefits did come to be shared with the workers in the form of higher wages, shorter hours, safer workplaces, and earlier retirement. Although the workers’ struggles to organize were often violent, they were focused on winning a better share of the benefits of higher productivity, not on destroying the machines that made it possible.

Technology in social context

One question that I had throughout the book was how economists make the distinction between replacing and enabling in practice. Since Frey uses those terms as adjectives describing technologies, the reader could easily get the impression that the effect of a technology is readily observable as soon as it is introduced. That may be true for some specialized machines, that either clearly do or clearly don’t replace what a worker is currently doing. More generalized technologies with many applications can have mixed effects, replacing some workers while enabling others, as Frey’s discussion of twentieth-century electrical machines makes clear. “Clearly, technology did cause some occupations to vanish–like those of lamplighters, elevator operators, laundresses and so on–yet these jobs employed only a fraction of the workforce relative to the new machine-aided occupations that emerged.”

Another example of mixed effects is the internal combustion engine. On the one hand, it gave the drivers of motor vehicles the power of many horses, enabling them to cover greater distances, move more goods, or plow more fields. It created the occupation of truck driver, which is still the largest single occupation in many states. On the other hand, the tractor and other farm machinery dramatically reduced the demand for farm labor.

Now as Frey points out, many of the laborers who left farm work in the twentieth century did so more voluntarily than the displaced artisans of early industrial times. They chose to leave because they could get higher wages in manufacturing. In that case, the same workers were replaced in the agricultural sector after they were enabled in another. Similarly, workers who left domestic service for manufacturing were replaced by electrical appliances. But that raises the question of why labor demand was so high in manufacturing. Was it simply in the nature of assembly-line technology to enhance rather than replace labor?  Wasn’t it also because there was now a mass market for manufactured goods, supported by a system that routinely passed along the benefits of high productivity to consumers (as low prices) and to workers (as high wages). Without expanding markets, wouldn’t assembly-line technology replace many workers and not just empower them?

Another factor affecting whether workers are replaced or enhanced is their skill level. “One reason that the horseless age was not accompanied by a jobless age is that human workers, unlike horses, have the means of acquiring new skills, which allows them to take on tasks outside the realm of machines.” If the effect of a machine depends on what happens outside the realm of machines, then classifying the machine as replacing or enabling is no simple matter.

The conclusion I come to is that whether a technology is replacing or enhancing may not be at all obvious when it is first introduced. It depends on how its applications unfold over the course of many years, in a social context that includes things like corporate policies, markets, labor organization, and access to education.

What seems clear is that very early industrial technologies were more replacing than enabling, and that the potential of technology to empower workers was realized only gradually over the course of industrial history. Harnessing the power of nature with such innovations as the steam engine and electrical machinery had a lot to do with this. But rather than seeing technologies as either inherently replacing or enabling, I would call attention to the continued potential for both, as well as to the many decisions that influenced how technologies were actually used. Was it the assembly line itself that made Henry Ford raise wages and reduce car prices, or was it his vision of a path to a prosperous industry?

A new technology trap?

Frey’s concerns about a new technology trap arise from his observation that new technologies are more like those of the First Industrial Revolution than the Second; they are more replacing than enabling. (But again I ask: Is that a feature of the technology itself or of the social context in which we are using it?)

After reviewing many recent technological developments, including in machine learning, machine vision, sensors, various subfields of AI, and mobile robotics, my conclusion is that while these technologies will spawn new tasks for labor, they are predominantly replacing technologies and will continue to worsen the employment prospects for the already shattered middle class.

Like some other economists, Frey sees a similarity between the plight of workers today and that of early textile workers, whose skills and incomes were more replaced by machinery than enhanced by it. That accounts for a lot of the backlash against automation and global trade, which could impede technological change. “The mere existence of better machines is not sufficient for long run growth.” Growth will depend on “policy choices made in the short run.” At the very least, steps must be taken to ease the transition to a hi-tech society for workers who are experiencing dislocations.

Frey remains a long-run optimist, believing that eventually productivity growth will resume–it’s been sluggish lately despite the new technologies–and that more good jobs will be created involving tasks that are hard to automate. These will usually be the more creative, more skilled areas of human activity. Frey rejects as a “widespread misconception…that automation is coming for the jobs of the skilled.” From my perspective, that means that information technologies may not turn out to be as “predominantly replacing” as it now seems.

I will elaborate on many of these points in upcoming posts.

Continued

 


Democracy and Prosperity (part 4)

July 22, 2019

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Previous posts on Iversen and Soskice’s Democracy and Prosperity have discussed the symbiotic relationship between democracy and capitalism, democratic support for capitalism during the revolution in information and communications technology, and variations among advanced capitalist democracies (ACDs) in their original path to democracy, electoral systems, economic inequality and educational opportunity.

This final post will discuss three challenges facing ACDs today: global financial instability, populism, and artificial intelligence/robotics. The focus will be on the United States as a country with a relatively weak and politically fragmented labor movement; a two-party, majority-rule electoral system; and a recent trend toward high inequality and low social mobility.

Global financial instability

The financial crisis of 2008 occurred around the time that “governments were implementing the broad set of reforms that we have argued created the foundation for the knowledge economy.” That raises the question, “If the reforms were intended to produce prosperity, how did the crisis happen?”

Iversen and Soskice focus on the fact that different democracies responded to the opportunities presented by technological change by promoting different segments of their economies. While Germany and Japan promoted their “high value-added export sectors,” the U.S. and U.K. promoted their “high-risk financial sectors.” In the U.S., loose financial regulations allowed highly leveraged financial institutions (HLFIs) to accumulate high-risk assets such as bundles of shaky mortgages. Americans became global debtors, consuming more than they produced, while exporting countries became global creditors. This could work because creditor nations were willing to accept payment for their goods in dollars and then lend those dollars back to us, often providing “short-term loans to the HLFIs to cover the acquisition of a large proportion of the risky assets–that is, securitized loans–that financed the consumption.” Government fiscal policy sustained the imbalance by running deficits–also partly financed by foreigners–spending more dollars than it took out in taxes. Government too thus enabled Americans to consume more than they produced.

The market value of risky financial assets collapsed once debtors became overextended and started to default, triggering the global financial crisis. Although the global economy has recovered–more or less–from the Great Recession that followed, the fundamental imbalance remains, portending additional instability in the future.

How could the U.S. economy be put on a more solid footing? If all that the government would do is balance the budget by cutting spending, the result might only be lower incomes and economic contraction, without a real increase in national production. Sustainable economic growth may require both more private investment in productivity-enhancing innovations and public investment in education and training. However, such changes may lack the support of capitalists who are already making money accumulating financial assets they think are sound, or those workers who already have good educations and incomes.

Populism

The authors define populism as:

…a set of preferences and beliefs that rejects established parties and elites, that sees established politicians as gaming the system to their own advantage, and that at the same time sees the poor as undeserving of government support. Above all it opposes immigrants, who are always counted among the undeserving…,and it rejects the cosmopolitan outlook associated with the rising cities in favor of the traditional family, conforming sexual orientations, and nationalism.

The authors see the re-emergence of populism as the most important shift in politics of the last forty years. They see growing economic inequality, falling social mobility, and the aftermath of a major economic crisis as especially conducive conditions. They find populist values especially widespread in democracies relatively low on educational opportunity, such as the United States, South Korea, Japan and Italy.

The adherents of populism are usually members of the “old middle classes,…those who have experienced stagnating wages because of skill-biased technological change, outsourcing, or import competition.” Although populism is not simply a backlash against cultural changes like racial integration, feminism, or gay rights, it does have a cultural dimension that is related to economic change. The urban “agglomerations of knowledge” that are at the center of the new economy encourage a “tolerance of diversity and cosmopolitan values.” The industrial work ethic that encouraged simple conformity and submission to authority has given way to a more flexible lifestyle, one that is open to new ideas wherever they come from. But workers who lack the education and income to live in the cities remain in–or move to–smaller towns containing old middle-class enclaves. There they practice “a nativist version of the old social contract, which is based on notions of working hard…, obeying the rules, observing traditional family values, and attachment to the nation.” They may become encapsulated, and feel both economically and culturally devalued outside of those enclaves.

In electoral systems with proportional representation, populists can achieve influence by forming a minority party, just as socialists often do. In a majoritarian system like the U.S., populists need the support of a major party, and they have currently found it in the Republican Party. Iversen and Soskice see populists as a minority even there, and they do not explain why so many Republicans would find common ground with Donald Trump. I think it’s because Republican economic policies are increasingly blamed for growing inequality–their previous presidential candidate ran on trickle-down economics and lost–and they have increasingly appealed to white nativists and Christian conservatives in the hope of saving their Reagan-Bush era majority.

The authors do not regard populism as a serious threat to the technologically advanced economy or the democratic state, for several reasons:

  1. Populist economic resentments are directed less at the advanced economy itself than at poor people and immigrants, who I would say get unfairly blamed for middle-class status anxiety;
  2. Too many people are benefiting from economic and cultural change to give the populists a sustained majority;
  3. “Populism can be readily undermined by public policies designed to open educational opportunities for more people.”

I suspect that mainstream political parties will need to address the legitimate opportunity concerns that are fueling populism, but also repudiate many of its reactionary and undemocratic sentiments. If a major party can remain popular while doing neither of those things, as the Republicans are attempting, then democracy is in more trouble than this book acknowledges.

Artificial intelligence and robotics

The revolution in information and communications technology is only in its early stages. Further transformations of work and economic organization are to be expected, especially in the areas of artificial intelligence and automated mechanical systems.

Many of those who try to anticipate further change are technological optimists but social pessimists. Writers such as Martin Ford (The Rise of the Robotshave a very expansive view of what AI can do, but are very worried about the prospects for human displacement and unemployment. On the other hand, Robert Gordon (The Rise and Fall of American Growth) sees information and communication technologies as only modest contributions to the history of economic change, not transformative enough to make huge difference to human work or productivity.

Iversen and Soskice take an intermediate position. They do think that new technologies can substantially change how work is done, but they stress their potential to complement human labor rather than substitute for it. As they pose the issue, “[I]f AI and robots can replicate the cospecificity of skill clusters by essentially generating de novo the knowledge that otherwise emerges from human inter-action and exchange of ideas, then educated workers and technology would no longer be necessary complements to technology.” What computers do best is implementing algorithms, that is, slavishly following a routine that humans have already come up with. But “a key function of decentralized production networks is to develop new solutions to complex problems in uncertain environments. The objective of innovation is to develop new algorithms, as opposed to merely optimizing old ones.”

Only when and if computers can be taught to think as creatively as humans can we speak of massive substitution rather than complementarity. The authors don’t even rule out a merger of humans and machines into a new species through bioengineering, but such dreams seem a long way off.

In the meantime, workers will increasingly need the education and skills to work with the machines. There will be winners and losers, but ultimately the results will depend on democratic politics, not just technology.

This points to an optimistic conjecture: even as new technology replaces more jobs, the advanced sectors are location-specific and can support policies that ensure broad sharing of the benefits of a more productive economy based on broad, although never all-encompassing, electoral coalitions.

What those coalitions can demand is public investments in human capital to make citizens productive contributors to the knowledge economy. The authors see that as the key to sustaining the mutually beneficial relationship between capitalism and democracy. “What ultimately makes democratic capitalism resilient in the face of technological change and the rise of the populist challenge is the continued expansion of education combined with opportunity in the advanced sectors.”

Even if the number of workers displaced by technology becomes very large, democratic politics could demand a new form of welfare state, not to pay people not to work, but to support them in meaningful forms of work that are not rewarded by the market. Maybe they could stay home and care for their children, and yet share the benefits of a high-productivity, automated society, because society agreed that they deserved to.


Democracy and Prosperity (part 2)

July 18, 2019

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In Democracy and Prosperity, Iversen and Soskice contrast the emerging knowledge economy with the system that preceded it in the mid-20th century.

The “Fordist” political economy

What many economists call the “Fordist” system was dominated by giant manufacturing corporations such as the Ford Motor Company. They performed a range of functions from “production to logistics and sales and marketing,” and usually had a very hierarchical structure of decision-making.

Assembly-line technology featured “strong complementarities in production between skilled and semiskilled workers. The companies needed large numbers of both, and either of them could obstruct production if they were well organized but dissatisfied. By the 1970s, unionization was at a peak in the advanced capitalist democracies, and so was “wage coordination,” the cooperation of large numbers of workers and companies in setting wages and working conditions.

Economic inequality declined during this period, as even workers with limited educations could quickly acquire the skills needed for many industrial jobs. Poverty declined, even for segregated racial and ethnic groups. “The Fordist economy was…by and large a force of integration and equalization of incomes across industries, skill groups, and geographic space.” The most advanced companies were concentrated in big cities, but peripheral areas often supplied them with materials or components for their products.

National governments helped organize and maintain the system. They supported the collective bargaining rights of labor. They provided a safety net of unemployment and retirement benefits, which gave workers a source of security in addition to short-term wage demands. They invested in public goods like infrastructure and education. They often engaged in Keynesian economic policies, using government spending to stimulate the economy and maintain low unemployment. It was a period of rapid economic growth and relative harmony among business, labor and government.

The knowledge economy

Much of this has changed since around 1980. Information and communication technologies have not affected all jobs equally, but have most easily substituted for routine semiskilled tasks. In some ways, this is a blessing, as such work was often deadly dull and uncreative. But, “As less-skilled workers became increasingly segregated into a growing tier of low-productivity service sector occupations–especially in low-end personal and social services–the complementarities between high- and low-skilled workers unraveled.” Inequality generally increased in advanced capitalist democracies, although with important variations to be discussed later.

New technologies can put a lot of computational power into the hands of individual workers, if they have the analytic skills to use it. In organizations of knowledge workers, decision-making becomes less vertical (hierarchical) and more horizontal (network-based), and relational skills also become more important. Knowledge workers benefit by participating in skill clusters, in which they can play specialized roles, and yet find other work within the cluster when and if a particular role is no longer needed.

These skill clusters are also embedded in larger social networks in which educated workers participate. “Big-city agglomerations” of knowledge are the “dynamic drivers” of the knowledge economy. They are usually places that already had a range of professional services and a strong university or two. Fordist-era cities whose prosperity rested on a single manufacturing industry, such as steel, have had trouble adapting, and many smaller cities have been left behind altogether. (Rapid transit between thriving cities and peripheral areas would help, but people who are already doing fine in the city may not have much incentive to support it with their tax dollars.)

The fact that education, urbanization and high incomes tend to go together increases the inequality among both households and places. Educated people live and work with other educated people, and also socialize with them and marry them, often forming affluent, two-income households. By clustering together, affluent households drive up the cost of good schools and housing in the successful cities, creating barriers to entry for the less educated.

The dynamic cities in the advanced economies of America, Europe and Asia compete with one another to attract capital and market their innovations. “Multinationals play a central role in tapping into multiple skill clusters and tying together complementarities of knowledge. The result is a major increase in multinational investment, trade and competition.

The “embedded knowledge”-based political economy

A central point of Iversen and Soskice’s argument is that knowledge within the knowledge economy is geographically embedded in innovative urban centers within the advanced democratic countries. That gives governments some power over activities that cannot easily be moved from where they are. It also gives them an incentive to support the knowledge sectors of their economies, for the good of the nations where they reside.

The availability of information and communication technologies does not automatically transform an economy. The authors believe that the Soviet Union collapsed partly because it resisted the decentralizing power implied by the new technologies. “It was felt necessary to maintain prohibitions on personal computers until the late 1980s.” The lesson to be drawn: “Without politically initiated reforms economies stagnate, even when they possess the necessary technologies and know-how.”

Beginning in the 1980s, advanced capitalist democracies made a number of “strategic choices” to promote the growth of their knowledge sectors. “Knowledge economies have been enabled by a different political economic framework from that which supported Fordism. We describe this framework as “embedded knowledge-based liberalism.” (In Britain and the United States, many of the leaders in this effort–Thatcher, Reagan–are known as conservatives, but they were working to liberate economic activity from what they saw as outdated restrictions. In that way, they were acting in the tradition of classical liberalism.)

Governments generally worked to reduce barriers to competition, free trade and international flows of capital. The authors measure this with an index of regulation covering eighteen regulatory domains, including such matters as trade barriers, differential treatment of foreign suppliers, and administrative burdens on creating new enterprises. The U.S. and Britain led the way toward competitiveness and away from protectionism, and the rest of Europe followed.

Governments also worked to transform the financial and insurance sectors, so that they went beyond their traditional financial products to provide more complex and customized services for knowledge workers and enterprises. Greater access to credit was important for new businesses, but also for workers following more complicated careers, with many changes in jobs, periods of schooling, and shifts in work/family arrangements.

Governments shifted their macroeconomic priorities from fighting unemployment to fighting inflation. One reason for this was the decline of unions and large-scale wage coordination, which had provided a degree of predictability and moderation to wage demands. A tight monetary policy was a more centralized way of curbing wage-price spirals. Another reason was to stabilize the exchange rates among national currencies for purposes of global trade and investment. Other countries would not be eager to invest in America if they couldn’t count on receiving their returns in dollars with a stable value.

And of course, governments continued to work for an educated workforce, again with important variations to be discussed later. Over the past twenty-five years, attainment of higher education has more than doubled in the ACDs.

Such policies have been most responsive to the needs of knowledge industries and knowledge workers, but less so to the needs of less-educated workers displaced or threatened by new technologies. “Unlike the Fordist economy, there is nothing that binds together the interest of the main social classes. A majority gains, and a small minority gains a great deal, but a large minority loses.” Whether that continues to be the case is an important question for the future.

Continued

 


Automation and New Tasks

February 22, 2019

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Daron Acemoglu and Pascual Restrepo, “Automation and New Tasks: The Implications of the Task Content of Production for Labor Demand.” Prepared for Journal of Economic Perspectives, November 6, 2018.

This paper really helped me think more systematically about the impact of automation on the demand for labor, something I’ve been thinking a lot about lately. My last post on the subject, which also featured a paper by Acemoglu and Restrepo, is here.

Technology and labor demand

One of the key issues is how to reconcile the recent concern that robotics will destroy too many good jobs with the traditional optimism of economists about the effects of technology. Throughout most of U.S. history, new technologies like farm machinery or industrial assembly lines have not stood in the way of economy-wide gains in labor demand, as reflected in real wages per capita. And yet, too many workers today are experiencing unemployment or wage loss because of automation. How do we sort this out in a way that enables us to anticipate where we may be headed and formulate sensible policy responses?

Acemoglu and Restrepo conceptualize the labor demand of an industry as a product of “value added” and “labor share”:

Labor demand = Value added x Labor share

Value added is an industry’s addition to economic output and income. Labor share is the portion of that added value that is received by labor. Labor demand is the resulting wages per capita.

The authors say that economists have primarily conceptualized technological progress as “factor-augmenting.” That is, new technologies increase the productivity of labor or machinery or both. More productive factors of production mean more value added. Assuming that labor’s share doesn’t decline, labor demand as reflected in real wages ought to increase. “Factor augmenting technologies affect labor demand mostly via the productivity effect and have a small impact on the labor share of an industry.” That was the experience, for example, of manufacturing industries in the mid-20th century.

However, an analysis that focuses on value added while holding labor share constant is not complete. Technological change can also effect how much labor is needed in a particular process of production, and how much of the income from that process goes to workers.

The task content of production

The authors’ key concept is the task content of production, which involves the allocation of tasks between labor and capital (the latter including machines and software). Focusing on the potential of new technologies to add value “often misses the major implications of technological changes that directly alter the allocation of tasks to factors.”

What makes the implications of automation hard to assess is that it has contradictory effects on labor demand–a productivity effect and a displacement effect. By raising productivity and increasing value added, it increases the potential income to be distributed to the human workers who remain. But by replacing labor with machinery, it reduces labor’s share of income. Whether wages actually rise or fall depends on the relative strength of the two effects.

To complicate things further, displaced labor does not necessarily go missing from an industry, let alone the economy as a whole. The introduction of new tasks for humans to do has a reinstatement effect that raises the labor share of production and therefore labor demand. (Personally, I’m not too fond of the term “reinstatement”, since it sounds as if workers are getting their old jobs back, which is not at all what is intended. I would prefer the term “redeployment”.) But whatever term is used, the point is important. As machines take over familiar tasks, humans can move into new economic activities where they have some advantage over machines, especially because of their general intelligence, flexibility and creativity. This has been true in the past, and how much it remains true in the robotic age is an important question for the future of work.

Labor demand in a multi-sector economy

When the authors move from discussing individual industries to discussing the entire economy, they introduce an additional effect on labor demand, the composition effect. This occurs when labor moves from one economic sector to another, and the sectors differ in labor demand. If workers move out of a sector where wages and labor’s share of added value are falling, and into a sector where they are higher, that contributes positively to labor demand.

The classic example of this process is the mechanization of agriculture, “which started in the first half of the 19th century with the cotton gin and continued with horse-powered reapers, harvesters and plows later in the century and with tractors and combine harvesters in the 20th century.” That process displaced massive amounts of farm labor and reduced labor’s share of agricultural activity and income. Much of that displaced labor went into manufacturing. Manufacturing was mechanizing too, but it maintained labor demand by increasing output and creating new manufacturing tasks. “The composition and reinstatement effects explain why, despite the mechanization of a sector making up a third of the economy [agriculture in 1850], labor demand increased and the share of labor in national income remained stable during this period.”

Labor demand 1947-1987

For two recent periods, Acemoglu and Restrepo analyze changes in labor demand, measuring the relative contributions of the effects they have discussed. They chart developments in six industries: agriculture, mining, manufacturing, construction, transportation and services.

The postwar era of 1947-1987 was a period of strong labor demand and rising real wages, which grew at an average rate of 2.4% per year.

Nothing comparable to the displacement of labor by the mechanization of agriculture occurred during this time. The only industries to suffer a loss of labor share were the relatively small industries of mining and transportation.

There was some displacement of labor due to automation in the large manufacturing industry, but it was offset by the creation of new manufacturing jobs, such as managerial and clerical jobs in corporate bureaucracies, as well as jobs in the expanding service industries. “[T]here was plenty of automation, especially in manufacturing, but this was accompanied with the introduction of new tasks (or other changes increasing the task content of production in favor of labor) in both manufacturing and the rest of the economy that offset the adverse labor demand consequences of automation.”

With displacements due to automation balanced by reinstatements due to the creation of new tasks, labor’s share of output and income remained steady. The increase in actual real wages that occurred is accounted for almost entirely by the other effect that supports labor demand, higher productivity. New technologies added value, and labor got its share of that added value in the form of higher real wages.

If technological change always worked that way, we wouldn’t be so worried about the future. But there was trouble ahead. In their data for those years, we can already see labor’s share within manufacturing peaking around 1980 and starting downward.

Labor demand 1987-2017

In this more recent period, wage growth was slower, averaging only 1.3% per year.

Labor demand suffered in both ways suggested by the same formula:

Labor demand = Value added x Labor share

Value added increased more slowly because of slower growth in productivity. In addition, labor’s share of value added declined in manufacturing, construction and mining. That was because labor displacement due to automation accelerated, while labor reinstatement due to new task creation slowed down.

Deeper explanations for these trends are harder to agree on. One puzzle is why the accelerating automation hasn’t done more to raise productivity. The authors point out that productivity gains from automation depend on the actual superiority of machines over humans for a given task. A rush to automate because a company gets caught up in a wave of technological enthusiasm or receives a tax break on new equipment may not be that helpful.

This analysis clarifies that automation will reduce labor demand when the productivity effect is not very large. Contrary to a common presumption in popular debates, it is not the “brilliant” automation technologies but those that are “so-so” and generate only small productivity improvements that will reduce labor demand. This is because the positive productivity effect of so-so technologies is not sufficient to offset the decline in labor demand due to displacement.

Favoring machines over human workers may also result in a lack of investment in education and training:

…[T]here may be a mismatch between the available skills of the workforce and the needs for new technologies, which could further reduce productivity gains from automation and hamper the introduction of new tasks—because the lack of requisite skills reduces the efficiency with which new technologies can be deployed.

The future of work

By considering a variety of things affecting labor demand, Acemoglu and Restrepo avoid a simple preoccupation with a positive factor like the productivity effect or a negative factor like the displacement effect. “Our evidence and conceptual approach support neither the claims that the end of human work is imminent nor the presumption that technological change will always and everywhere be favorable to labor.” It will be the balance of the various effects that will matter.

The authors don’t make specific policy recommendations, but some very general prescriptions follow from their analysis. We shouldn’t be afraid to automate tasks where machines have a clear advantage, since the gains in value added are too good to pass up. But we should also enhance the value of human labor, both by giving the workers who remain in automating industries their share of the gains, and also by investing in the education and training workers need to perform new tasks that humans can do better than machines. Where private employers don’t find it profitable to nurture and reward human labor, government must play a strong role for the general good.

As it stands now, too much displaced labor is crowding into low-skill, low-tech, low-wage work. That is a waste of both our human and technological resources. A jobless future where robots work, their owners get rich, and most people live off public assistance is also a dismal prospect. If we are to have a hi-tech economy, let it be one where the average worker can reap the benefits in creative work, good pay, and rewarding leisure.


Effects of New Technologies on Labor

January 4, 2019

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David Autor and Anna Salomons, “Is automation labor share-displacing? Productivity growth, employment, and the labor share.” Brookings Papers on Economic Activity, Spring 2018.

Daron Acemoglu and Pascual Restrepo, “Robots and jobs: Evidence from US Labor Markets.” National Bureau of Economic Research, March 2017.

I have been interested in automation’s effects on the labor force for a long time, especially since reading Martin Ford’s Rise of the Robots. Ford raises the specter of a “jobless future” and a massive welfare system to support the unemployed.

Here I discuss two papers representing some of the most serious economic research on this topic.

The questions

To what extent do new technologies really displace human labor and reduce employment? The potential for them to do so is obvious. The mechanization of farming dramatically reduced the number of farm workers. But we can generalize only with caution. In theory, a particular innovation could either produce the same amount with less labor (as when the demand for a product is inelastic, often the case for agricultural products), or produce a larger amount with the same labor (when demand expands along with lower cost, as with many manufactured goods). An innovation can also save labor on one task, but reallocate that labor to a different task in the same industry.

Even if technological advances reduce the labor needed in one industry, that labor can flow into other industries. Economists have suggested several reasons that could happen. One involves the linkages between industries, as one industry’s productivity affects the economic activity of its suppliers and customers. If the computer industry is turning out millions of low-cost computers, that can create jobs in industries that use computers or supply parts for them. Another reason is that a productive industry affects national output, income and aggregate demand. The wealth created in one industry translates into spending on all sorts of goods and services that require human labor.

The point is that technological innovations have both direct effects on local or industry-specific employment, and also indirect effects on aggregate employment in the economy as a whole. The direct effects are more obvious, which may explain why the general public is more aware of job losses than job gains.

A related question is the effect of technology on wages, and therefore on labor’s share of the economic value added by technological change. Do employers reap most of the benefits of innovation, or are workers able to maintain their share of the rewards as productivity rises? Here too, aggregate results could differ from results in the particular industries or localities experiencing the most innovation.

The historical experience

American history tells a story of painful labor displacement in certain times, places and industries; but also a story of new job creation and widely shared benefits of rising productivity. Looking back on a century of technological change from the vantage point of the mid-20th century, economists did not find negative aggregate effects of technology on employment or on labor’s share of the national income. According to Autor and Salomons:

A long-standing body of literature, starting with research by William Baumol (1967), has considered reallocation mechanisms for employment, showing that labor moves from technologically advancing to technologically lagging sectors if the outputs of these sectors are not close substitutes. Further,…such unbalanced productivity growth across sectors can nevertheless yield a balanced growth path for labor and capital shares. Indeed, one of the central stylized facts of modern macroeconomics, immortalized by Nicholas Kaldor (1961), is that during a century of unprecedented technological advancement in transportation, production, and communication, labor’s share of national income remained roughly constant.

Such findings need to be continually replicated, since they might hold only for an economy in a particular place or time. In the 20th century, the success of labor unions in bargaining for higher wages and shorter work weeks was one thing that protected workers from the possible ill effects of labor-saving technologies.

Recent effects of technological change

Autor and Salomons analyze data for OECD countries for the period 1970-2007. As a measure of technological progress, they use the growth in total factor productivity (TFP) over that period.

They find a direct negative impact of productivity growth on employment within the most affected industries. However, they find two main indirect effects that offset the negative impact for the economy as a whole:

First, rising TFP within supplier industries catalyzes strong, offsetting employment gains among their downstream customer industries; and second, TFP growth in each sector contributes to aggregate growth in real value added and hence rising final demand, which in turn spurs further employment growth across all sectors.

To put it most simply, one industry’s productivity may limit its own demand for labor, but its contribution to the national output and income creates employment opportunities elsewhere.

With regard to labor’s share of the economic benefits, the findings are a little different. Here again, the researchers find a direct negative effect within the industries most affected by technological innovation. But in this case, that effect is not offset, for the most part, by more widespread positive effects.

The association between technological change and labor’s declining share varied by decade. Labor’s share actually rose during the 1970s, declined in the 1980s and 90s, and then fell more sharply in the 2000s. The authors mention the possibility that the newest technologies are especially labor-displacing, but reach no definite conclusion. Another possibility is that non-technological factors such as the political weakness of organized labor are more to blame.

The impact of robotics

Autor and Salomons acknowledge that because they used such a general measure of technological change, they couldn’t assess the impact of robotics specifically. They do cite work by Georg Graetz and Guy Michaels that did not find general negative effects of robots on employment or labor share in countries of the European Union. That’s important, since many European countries have gone farther than we have in adopting robots.

The paper by Acemoglu and Restrepo focuses on the United States for the period 1990-2007. (They deliberately ended in 2007 so that the impact of the Great Recession wouldn’t muddy the waters.)

The authors used the definition of robot from the International Federation of Robotics, “an automatically controlled, reprogrammable, and multipurpose [machine].” Over the period in question, robot usage increased from 0.4 to 1.4 per thousand workers. “The automotive industry employs 38 percent of existing industrial robots, followed by the electronics industry (15 percent), plastic and chemicals (10 percent), and metal products (7 percent).”

Adoption of industrial robots has been especially common in Kentucky, Louisiana, Missouri, Tennessee, Texas, Virginia and West Virginia. As Thomas B. Edsall titled his recent New York Times column, “The Robots Have Descended on Trump Country.”

Acemoglu and Restrepo classified localities–technically “commuter zones”–according to their “exposure” to robotics, based on their levels of employment in types of jobs most conducive to robotization.

Their first main finding was a direct negative effect of robotics on employment and wages within commuting zones:

Our estimates imply that between 1990 and 2007 the increase in the stock of robots…reduced the employment to population ratio in a commuting zone with the average US change in robots by 0.38 percentage points, and average wages by 0.71 percent (relative to a commuting zone with no exposure to robots). These numbers…imply that one more robot in a commuting zone reduces employment by about 6 workers.

The workers most likely to be affected are male workers in routine manual occupations, with wages in the lower-to-middle range of the wage distribution

In the aggregate, these local effects are partly offset by “positive spillovers across commuting zones”–positive effects on employment and wages throughout the economy. With these spillovers taken into account, the estimated effects of robotics on employment and on wages are cut almost in half, dropping to 0.20 percent and 0.37 percent respectively.

The authors state their conclusion cautiously, as “the possibility that industrial robots might have a very different impact on labor demand than other (non-automation) technologies.”

Summary

While there is little doubt that new technologies often displace labor in particular industries and localities, the aggregate effects on employment and wages are less consistent.  Historically (late 19th and early 20th centuries), employment and labor share of income held up very well. For developed countries in the period 1970-2007, Autor and Salomons found a mixed picture, with robust employment but declining labor share after 1980. With respect to robotics specifically, Graetz and Michaels did not find declines in employment or labor share in the European Union, but Acemoglu and Restrepo found some decline in both employment and wages in the U.S.

It seems fair to say that the jury is still out on the effects of automation on the labor force. It may be that automation has no inevitable effect, but that it depends on how we as a society choose to deal with it. We shouldn’t assume a world of mass unemployment and widespread government dependency on the basis of recent, preliminary results from one country. Authors such as Thomas Friedman, who are more optimistic than Martin Ford about the long-run effects of new technologies, have yet to be proved wrong.