The Technology Trap (part 4)

August 12, 2019

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In the last section of The Technology Trap, Carl Frey looks toward the future, trying to anticipate further impacts of technology on jobs, and suggesting policy measures to ease the transition for affected workers.

Smarter machines

Artificial intelligence is enabling machines to do even more of what humans used to do. “The fundamental difference is that instead of automating tasks by programming a set of instructions, we can now program computers to ‘learn’ from samples of data or ‘experience.’ When the rules of a task are unknown, we can apply statistics and inductive reasoning to let the machine learn by itself.” When a computer beat the world’s best player of the game Go in 2016, it did it not just by following a fixed set of rules, but by inferring its own rules from a series of trials using a large data set.

The range of tasks that smart machines can perform is broadening to include jobs like driving a truck, answering phone calls, picking up and packing products, taking consumer orders and accepting payments.

Still, there remain things that humans do better:

Even if we assume that algorithms at some point will be able to effectively reproduce human social intelligence in basic texts, many jobs center on personal relationships and complex interpersonal communication. Computer programmers consult with managers or clients to clarify intent, identify problems, and suggest changes. Nurses work with patients, families, or communities to design and implement programs to improve overall health. Fund-raisers identify potential donors and build relationships with them. Family therapists counsel clients on unsatisfactory relationships. Astronomers build research collaborations and present their findings in conferences. These tasks are all way beyond the competence of computers.

In 2013, the author and his Oxford colleague Michael Osborne reported on their detailed analysis of tasks and their estimate of the automation possibilities for 702 occupations covering 97% of the American workforce. They found the greatest risk of automation in the occupational categories of office and administrative support, production, transport and logistics, food preparation, and retail jobs. Overall, they classified 47% of jobs as vulnerable to automation.

Other research has yielded somewhat different percentages. But one general principle that has emerged from such research is that a job’s probability of automation varies inversely with the education it requires and the wages it pays. A study by the President’s Council of Economic Advisers found that “83 percent of workers in occupations that paid less than $20 an hour were at high risk of being replaced, while the corresponding figure for workers in occupations that paid more than $40 per hour was only 4 percent.” That could be good news, as long as we can keep expanding the good jobs and help workers acquire the skills they need to do them.

Unemployment, leisure, or new jobs?

Frey describes a “widespread dystopian belief” that technology will create a future of mass unemployment and low wages. Others envision a utopian future in which technology enables us to produce so much so easily that we can work very little and live lives of affluent leisure. Neither mass unemployment nor lives of leisure are evident in today’s society, and Frey doesn’t expect them. Instead people will have jobs for the foreseeable future, both because there remain things people do better than machines, and because people generally choose to take the benefits of high productivity in the form of more goods and services rather than more leisure.

Although new technologies have been replacing more middle-class jobs than they have been creating, Frey suggests that this may be just a “first-order effect.” He believes that the greatest gains in productivity and job creation are yet to come. That reinforces my belief that whether a new technology turns out to be replacing or enabling depends on how we use it in a social context. Replacing existing jobs may happen first because it’s easier than creating new jobs and upgrading skills, which requires some social reorganization. Frey points out that “it took roughly four decades for electricity to appear in the productivity statistics, after the construction of Thomas Edison’s first power station in 1882….[H]arnessing the mysterious force of electricity required a complete reorganization of the factory.” And of society, I would add, considering the changes required to turn workers and their families into affluent consumers of the products coming off the assembly lines.

Public policy

In the end, Frey remains optimistic about technology, but concerned about the divisions between current winners and losers and their immediate effects on society. Mitigating those effects is the main challenge for public policy. Among his recommendations:

  • Investments in education, especially early childhood education to offset the disadvantages of children from low-income, low-education families; such education pays for itself in better health outcomes, higher productivity and reduced crime
  • Wage insurance, especially for middle-aged workers who lose good jobs
  • Expanded tax credits to supplement low wages
  • Easing of licensing requirements that make it too difficult to move into new occupations
  • Vouchers to pay for moving to areas with better job opportunities
  • More affordable housing in thriving communities, supported by an easing of zoning restrictions like minimum lot sizes

I see a role for government not only in helping disadvantaged workers, but in creating economic demand for the good jobs they need. If the manufacturing sector is no longer expanding, and if the low-wage service sector is most vulnerable to the next wave of automation, then that leaves the skilled services as the most likely frontier of job creation. But skilled services like education, health care, counseling, mental health services and quality child care are also what people need to enhance their human capital and qualify for good jobs. Public investment in those services pays off in two ways–better jobs and more qualified workers to do them. It also strengthens democracy because successful workers are more politically active and less alienated.

Why public investment rather than private investment? Because the families most in need of such services often cannot afford them. And because employers have only limited incentive to develop the human capital of their own workers. Employers own the machines they buy, but not the workers they hire. The workers can take their enhanced human capital and go to work for someone else. For that reason, human capital is a public good that cannot be entirely privatized. A healthy, well-educated population is good for all of us. So, of course, are other public goods like a solid infrastructure and renewable energy.

But can the country afford new investments in health or education? If the government seems tapped out, it’s not because the country is poorer than it used to be, but because the wealth and income are so unevenly distributed, and those who have them support such low taxes on themselves. From the Reagan administration on, the tax cuts were supposed to stimulate the economy from the top down, by making more money available for private investment. The results have been disappointing, with slower economic growth than in the mid-twentieth century, when taxes were higher. Now we should consider the possibility that we can grow the economy faster with high domestic spending than with low taxes, if the spending is concentrated on human capital development and needed public goods. In order to make human services affordable for consumers and for the taxpayers, they need to be cost-effective. Providers will need to apply new technologies not to replace labor–which would defeat the purpose of creating jobs–but to enable labor to serve clients as efficiently as possible. In the predominantly service economy, a productivity revolution in skilled services is the key to fulfilling the positive potential of information technology.

Advocates of new government spending have their work cut out for them to mobilize public support. They need to convince the less educated half of the population that they will receive more benefits than costs, since their incomes are too low to be targeted for tax increases. If they can also convince the more educated middle class to vote in the public interest, they can achieve a democratic majority. As Frey says, “Redistributive taxing and spending depend on whether the middle-income voters feel an affinity with people with lower incomes.”

Although my interpretations and policy preferences differ from Frey’s in a few respects, I found this book enormously helpful in thinking through the relationship between technology and employment. I highly recommend it.

The Technology Trap (part 3)

August 11, 2019

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Having described an era in which the middle class expanded and more good jobs were created than destroyed, Frey turns to what he calls the “Great Reversal” in the period since 1980. In recent decades, new technologies have done more to replace workers than enable them, resulting in a shrinking middle class.

The computer revolution

The main difference between the age of automation and the previous era of mechanization is that the automated machine can replace the machine operator. “The great reversal…is in large part a consequence of computers making the skills of machine-tending workers obsolete.”

The most routine forms of work are most easily automated, and that includes some white-collar jobs like mortgage underwriter. Many jobs that paid enough to put their workers into the middle class are routine enough to be reduced to a computer program.

Many other kinds of jobs, however, are harder to automate:

[T]here are many tasks humans are able to perform intuitively but that are hard to automate because we struggle to define rules that describe them. For activities that demand creative thinking, problem solving, judgment, and common sense, we understand the skills only tacitly.

For many of the more creative jobs, computers complement human skills but don’t replace them.

Furthermore, humans have perceptual and manipulative abilities that allow even an unskilled worker to do things that machines have trouble with, such as “distinguishing a pot that is dirty and needs to be cleaned from a pot holding a plant.”

Consider the impact of computer technology on three types of workers:

  1. A highly educated professional uses computer software to become even more productive
  2. A semi-skilled machine operator is replaced by a robot
  3. An unskilled cleaning service worker still has a job, but it’s a low-wage job

That, in a nutshell, is why middle-skill jobs are the ones disappearing, and the middle class has been shrinking. Men have been hit the hardest, since they are most likely to hold the kind of semi-skilled manufacturing jobs that are no longer needed.

Although new technologies have created some entirely new jobs, such as computer programmers, Frey finds that more middle-class jobs have been lost than gained. “Technological change has become more worker replacing in recent years.”

The impact on incomes

Wage inequality has been increasing, and educational qualifications matter more than ever. Inflation-adjusted wages for college educated workers have been rising, especially for women, while wages for workers with high school degrees or less have been falling, especially for men. Frey quotes Erik Brynjolfsson and Andrew McAfee:

There’s never been a better time to be a worker with special skills or the right education, because these people can use technology to create and capture value. However, there’s never been a worse time to be a worker with only ‘ordinary’ skills and abilities to offer, because computers, robots, and other digital technologies are acquiring these skills and abilities at an extraordinary rate.

While the logical thing for future workers to do is acquire as much education as possible, college education is much more expensive–and becoming more so recently–than secondary education.

During this period, wage growth in general has fallen behind productivity growth, and the share of national income going to labor rather than capital has fallen from around 64% to around 58%.

To me, many of these facts seem to cry out for explanations that go beyond the technology itself to the social context in which we are applying it. Since Frey is focused mainly on the American context, he does not discuss how countries like Finland or Sweden are computerizing at least as fast as we are while maintaining more educational opportunity and economic equality. See, for example, Iversen and Soskice’s Democracy and Prosperity, especially post 3.

Social divisions

Displaced workers tend to be concentrated in certain places, especially economically depressed manufacturing cities. These are often far removed from the places where educated people congregate and create new hi-tech enterprises. As Enrico Moretti said in The New Geography of Jobs:

America’s new economic map shows growing differences, not just between people but between communities. A handful of cities with the “right” industries and a solid base of human capital keep attracting good employers and offering high wages, while those at the other extreme, cities with the “wrong” industries and a limited human capital base, are stuck with dead-end jobs and low average wages.

Communities with large job losses also experience declining marriage rates, rising rates of birth outside of marriage, and rising mortality from suicide and substance abuse. The unemployment rate may remain fairly low, either because downwardly mobile workers settle for jobs in low-wage services, or because they drop out of the labor force and stop being counted.

The downwardly mobile are often the politically alienated as well, feeling that neither political party is responsive to their problems. The Democratic Party was once considered the party of labor, but today it represents many constituencies–people of color, women, the LGBTQ community and environmentalists. Frey notes that Rust Belt states teeming with industrial robots tipped the 2016 election to Trump and the Republicans. I would add, however, that rather than appeal to displaced workers as a class, which would be awkward for the party that still favors capital over labor, Trump Republicans often appeal to them as white males, thus gaining their votes without doing much to address their underlying problems. Job losses in manufacturing have hit black workers hard too, but you don’t see Trump holding rallies in their communities!

The economy still grows as technology marches on, although slower than in the previous era and with far less equally distributed benefits. Frey’s concern is that those who are not benefiting will somehow impede the process, by supporting special taxes on robots or tariffs on foreign goods. Frey’s ideas for having technological progress with more widely shared benefits will be the subject of the final post.


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.



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.”


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.

Thank You for Being Late (part 2)

November 15, 2018

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Today I’ll discuss two chapters of Thomas Friedman’s Thank You for Being Late that I found especially insightful: Ch. 8 on the implications of new technologies for employment, and Ch. 9 on the problem of global order.

The future of work

Friedman begins his discussion of work with a bold pronouncement: “Let’s get one thing straight: The robots are not destined to take all the jobs. That happens only if we let them–if we don’t accelerate innovation in the labor/education/start-up realms, if we don’t reimagine the whole conveyer belt from primary education to work and lifelong learning.”

I was pleased to find that Friedman’s position is similar to the one I laid out in my critique of Martin Ford’s The Rise of the Robots Ford predicted a future of massive unemployment, with millions of displaced workers relying on government for a minimal income. We could get a taste of that during a transitional period, but I don’t think that’s a very good description of where we are ultimately headed.

Friedman doesn’t deny that smart machines can now perform many tasks currently or formerly performed by humans. But he makes a sharp distinction between automating tasks and automating whole jobs so as to eliminate the human contribution altogether. The upside of automation is increased productivity. Workers aided by new technologies can produce more per hour, reducing the unit cost of what they produce. That can create a larger market for the product, increasing the demand for labor in a given occupation. A car was an expensive luxury item before the assembly line cut costs to create a mass market and a booming industry. Friedman reports that “employment grows significantly faster in occupations that use computers more,” as in banking and paralegal work.

To give an example from my own experience, financial planning software has automated many of the most tedious tasks involved in preparing a retirement plan, such as mathematically projecting future income from savings rates and asset allocation choices. But that hasn’t resulted in a reduced need for financial planners. On the contrary, it has made the services of a planner affordable for more people. Planners can spend less time doing calculations but more time relating to their clients.

Friedman says, “Jobs are not going away, but the needed skills for good jobs are going up.” What are disappearing are well-paid jobs with only modest skill requirements, like twentieth-century manufacturing jobs.

Retooling education

In general, today’s good jobs require more education; yet it does not follow that a college education necessarily qualifies a person for a good job. That’s not because a liberal education is a waste of time, but because it is only a foundation that must be built upon with lifelong job-relevant learning.

Friedman quotes MIT economist David Autor, who stresses the need for more than one kind of learning: “If it’s just technical skill, there’s a reasonable chance it can be automated, and if it’s just being empathetic or flexible, there’s an infinite supply of people, so a job won’t be well paid. It’s the interaction of both that is virtuous.”

Friedman is a strong believer in a broad, basic education that includes “strong fundamentals in writing, reading, coding, and math; creativity, critical thinking, communication, and collaboration; grit, self-motivation, and lifelong learning habits; and entrepreneurship and improvisation….” Even a robotics enthusiast like Martin Ford acknowledges that humans surpass robots in general intelligence, as opposed to specialized task capabilities.

However, recipients of this basic education will also have to cope with rapidly changing workplace requirements. Technology will play a central role here, both in creating the automated systems with which workers interact, and in enhancing learning processes themselves. Friedman wants to “turn AI into IA,” by which he means turning artificial intelligence into intelligent assistance to support lifelong learning. “Intelligent assistance involves leveraging artificial intelligence to enable the government, individual companies, and the nonprofit social sector to develop more sophisticated online and mobile platforms that can empower every worker to engage in lifelong learning on their own time, and to have their learning recognized and rewarded with advancement.” When the time comes to pick up a new skill, you can probably find an app to help you learn it.

Friedman describes AT&T as one company that is demanding more lifelong learning of its employees, but supporting it with measures like tuition reimbursements, online courses developed in collaboration with online providers, and promotions for those who acquire new skills. This represents a new social contract between employer and employee–“You can be a lifelong employee if you are ready to be a lifelong learner.”

Every major economic shift has involved the rise of a new asset class, such as land in the agrarian economy and physical capital in the industrial economy. The rising asset class today is human capital, and that is where society’s investments must be increasingly concentrated.

The threat of global disorder

In the immediate aftermath of the Cold War, after the collapse of the Soviet Union, The U.S. remained the only superpower and the most obvious model for other countries to emulate. Many thinkers expressed the hope that the world could move faster in the direction of American-style democracy and capitalism. But then the interventions in such places as Iraq and Afghanistan failed to produce stable democracies, the Great Recession called into question capitalist progress, and Americans lowered their expectations for world leadership.

What Friedman calls the post-post-Cold War world is characterized by shrinking American power, especially in the Middle East, and new challenges arising from the accelerations in technological change, globalization and environmental degradation.  In large areas of the less developed world, the danger is that states will fail and societies will sink into disorder, dragging the global political order and economy down. Environmental disasters like deforestation in Central America or drought and desertification in sub-Sahara Africa are uprooting people from their traditional relationship to the land. And while some poorer countries are advancing by providing cheap labor to the global economy, the future may belong to those who can provide smarter labor, and that requires greater investments in human capital.

Friedman says that during the Cold War, superpower competition gave America a reason to assist developing countries, in order to keep them in our camp. The mid-twentieth century economic boom also gave us the means to do so. While many Americans are now inclined to turn their back on the rest of the world, Friedman makes a case for renewed global involvement: “While we cannot repair the wide World of Disorder on our own, we also cannot just ignore it. It metastasizes in an interdependent world. If we don’t visit the World of Disorder in the age of accelerations, it will visit us.” The dislocated people in failed states can become refugees or terrorists. The same technologies that can empower people to learn and produce more can empower them to build improvised explosive devices triggered by cell phones, or perhaps a weapon of mass destruction.

In Friedman’s view, the best thing the U.S. could do to “help stabilize the World of Disorder and widen the islands of decency” would be to help fund schools and universities. He would also like to see us help the poorest people make a living in their own villages by assisting them with their environmental problems. He points out that it costs only 100-300 dollars to restore a hectare of degraded land.

In a world of enhanced interdependence, the haves would do well to invest in the development of the have-nots, domestically and globally. If we do not rise together, we will very likely fall together.