“Job losses in manufacturing due to automation do create fertile territory for continued populist appeal,” Daron Acemoglu, an economist at M.I.T., said by email:

In fact, some of the places where Trump made the biggest gains relative to McCain or Romney are in the heartland of heavy manufacturing where robots did lead to losses of manufacturing jobs.

Hostile voter reaction to automation, according to three scholars at the Oxford Martin School at Oxford University — Carl Benedikt Frey, Thor Berger and Chinchih Chen — was crucial to Trump’s victory.

In their October 2017 paper, “Political Machinery: Did Robots Swing the 2016 U.S. Presidential Election?” the authors demonstrate that

Support for Donald Trump was significantly higher in local labor markets more exposed to the adoption of robots. Other things equal, a counterfactual analysis shows that Michigan, Wisconsin, and Pennsylvania would have swung in favor of the Hillary Clinton if robot adoption had been two percent lower over the investigated period, leaving the Democrats with a majority in the Electoral College.

Along similar lines, Frank Levy, also an economist at M.I.T., wrote in a December 2017 paper:

AI (artificial intelligence) is helping to slowly polarize the occupational structure as it both creates high wage work and displaces men and women from certain blue collar and clerical (‘mid-skilled’) jobs into lower wage work. The result is similar to the displacement caused by manufactured imports and off-shored services.

In his paper, “Computers and Populism: Artificial Intelligence, Jobs and Politics in the Near Term,” Levy writes:

On balance, near-term AI will have the greatest effect on blue collar work, clerical work and other mid-skilled occupations. Given globalization’s effect on the 2016 presidential election, it is worth noting that near-term AI and globalization replace many of the same jobs.

Take the case of truck drivers. Driverless trucks are already in use abroad in ports and mines, and, according to Levy, “there should be a sizable number of fully automated U.S. port facilities, mines and other industrial facilities” by 2024. With these developments, he estimated, there will be 76,000 fewer truck driving jobs in 2024 than the Bureau of Labor Statistics currently projects.

Surveying the trucking industry recently in “The Future of Work: Robots, AI, and Automation,” Darrell West, a scholar at Brookings, warns that full adoption of driverless vehicles “would put at least 2.5 million drivers out of work.”

Assessing the full range of employment, West observes that

Robots, autonomous vehicles, virtual reality, artificial intelligence, machine learning, drones and the Internet of Things are moving ahead rapidly and transforming the way businesses operate and how people earn their livelihoods. For millions who work in occupations like food service, retail sales and truck driving, machines are replacing their jobs.

Levy argues that if the use of industrial robots on assembly and production lines continues to grow at the current pace,

the stock of robots in the U.S. would be 105,000 higher in 2024 than in 2014. If I conservatively assume that each robot replaces two assemblers and fabricators, the 105,000 additional robots would result in 210,000 fewer assembler and fabricator jobs in 2024 than otherwise would have been the case.

Where do these displaced workers look for a way to make a living? Levy’s answer is: farther down the ladder:

AI’s near-term effect will not be mass unemployment but occupational polarization resulting in a slowly growing number of persons moving from mid-skilled jobs into lower wage work

into such fields as food preparation and serving, building and grounds cleaning and maintenance and personal care and services.

For many men, moving from the manufacturing or comparable job he took pride in to a job in a fast-food operation or in caring for the elderly is tough to swallow. (Not to mention the dislocating effects of the technological innovations in contraception that helped usher in the women’s and reproductive rights movements.)

Levy points out that the cuts resulting from A.I. and automation in middle skill employment will be relatively modest in the short term, but the cuts will resonate far beyond their limited numbers:

Job losses will appear as accelerating trends. Over time, trucks driving in dedicated lanes will appear on the roads and in multiple news stories. Increased numbers of people will be working side-by-side with robots. When a media story describes an AI-induced layoff in occupation, other persons in that occupation will assume they are also at risk. These developments will occur against a backdrop of monopoly-like firms like Alphabet (Google), Amazon, Apple, Microsoft and Facebook.

What is the political significance of the A.I.-driven changes in the work force? They are the grist for the populist mill.

Levy writes:

A populist politician who campaigned on AI-induced job loss would start with ready-made definitions of the "people” and the “elite” based on national fault lines that were sharpened in the 2016 presidential election. This politician also would have a ready-made example of disrespect: the set of highly educated coastal “elites” who make a very good living developing robots to put “the people” out of work.

While Levy looks at the issue from the vantage point of those harmed by A.I., robotics and information technology, Kurz, the Stanford economist, examines the economic winners. In a recent essay for Project Syndicate, he writes:

IT-driven automation proceeded at the same time that corporate market power was rising. Because technological improvements are the crucial engine of rising productivity and growth, IT advances are universally viewed as economically beneficial.

The favorable view, according to Kurz, masks the

dark side: by enabling and supporting the rise of corporate monopoly power, IT innovations have caused the rise in inequality and contributed to the slowdown in wage growth.

While operating legally — indeed with the full support of the legal system — contemporary corporate technology leaders, including Brin, Jeff Bezos, Steve Jobs (who died in 2011) and Mark Zuckerberg, accumulated unprecedented amounts of wealth. According to Kurz:

Once an IT monopoly is established, it endows the company with the advantage of first mover. A combination of associated factors — additional patents, intellectual-property rights, trade secrets, falling computing and storage costs, and decreasing network user costs — then enable the company to consolidate market power, raise barriers to competition, and make it virtually impossible for potential competitors to break its power. IT networks endow a market leader with economies of scale that allow it to grow rapidly. Using their market power, such firms choke off innovations that threaten their position, often by purchasing competing firms.

According to Kurz, the concentration of economic power, and with it political power, in the major technology companies has dangerous consequences:

Monopoly profits have risen dramatically in the last three decades, from near zero in the early 1980s to $2.1 trillion — equivalent to 23 percent of total US corporate income — in 2015. During the same period, monopoly power caused the combined shares of wages and interest paid to capital to decline by 23 percentage points.

The result is a cascading effect caused

both by fueling the rise of corporate monopoly power and also by undermining the position of labor. It has altered the balance of market power in favor of corporations and against their customers, workers, and suppliers. And it has had a profoundly negative impact on lower-skill workers, in particular.

Jason Furman, an economist at Harvard who served as chairman of the Council of Economic Advisers under President Barack Obama, pointed out in a December 2017 paper, “Should We Be Reassured If Automation in the Future Looks Like Automation in the Past?” that

The history of automation — and how the U.S. economy has handled it over the last several decades — suggests that even if AI is similar to previous waves of automation, that should not be entirely comforting since technological advances in recent decades have brought tremendous benefits but have also contributed to increasing inequality and falling labor force participation.

Furman rejects the argument that automation will lead to the permanent elimination of jobs:

The concern is not that robots will take human jobs and render humans unemployable. The traditional economic arguments against that are borne out by centuries of experience.

Instead, Furman contends that the problem lies in “the process of turnover,” which “could lead to sustained periods of time with a large fraction of people not working.” In the short run,

not all workers will have the training or ability to find the new jobs created by AI. Moreover, this “short run” could last for decades and, in fact, the economy could be in a series of “short runs” for even longer.

A short run that lasts for decades — or a series of short runs that last even longer — would seem to warrant grave alarm.