Why Trump Still Has Millions of Americans in His Grip

Beginning in the mid-1960s, the priorities of the Democratic Party began to shift away from white working and middle class voters — many of them socially conservative, Christian and religiously observant — to a set of emerging constituencies seeking rights and privileges previously reserved to white men: African-Americans, women’s rights activists, proponents of ethnic diversity, sexual freedom and self-expressive individualism.

By the 1970s, many white Americans — who had taken their own centrality for granted — felt that they were being shouldered aside, left to face alone the brunt of the long process of deindustrialization: a cluster of adverse economic trends including the decline in manufacturing employment, the erosion of wages by foreign competition and the implosion of trade unionism.

These voters became the shock troops of the Reagan Revolution; they now dominate Trump’s Republican Party.

Liberal onlookers exploring the rise of right-wing populism accuse their adversaries of racism and sexism. There is plenty of truth to this view, but it’s not the whole story.

In “The Bitter Heartland,” an essay in American Purpose, William Galston, a veteran of the Clinton White House and a senior fellow at Brookings, captures the forces at work in the lives of many of Trump’s most loyal backers:

Resentment is one of the most powerful forces in human life. Unleashing it is like splitting the atom; it creates enormous energy, which can lead to more honest discussions and long-delayed redress of grievances. It can also undermine personal relationships — and political regimes. Because its destructive potential is so great, it must be faced.

Recent decades, Galston continues, “have witnessed the growth of a potent new locus of right-wing resentment at the intersection of race, culture, class, and geography” — difficult for “those outside its orbit to understand.”

They — “social conservatives and white Christians” — have what Galston calls a “bill of particulars” against political and cultural liberalism. I am going to quote from it at length because Galston’s rendering of this bill of particulars is on target.

• “They have a sense of displacement in a country they once dominated. Immigrants, minorities, non-Christians, even atheists have taken center stage, forcing them to the margins of American life.”

• “They believe we have a powerful desire for moral coercion. We tell them how to behave — and, worse, how to think. When they complain, we accuse them of racism and xenophobia. How, they ask, did standing up for the traditional family become racism? When did transgender bathrooms become a civil right?”

• “They believe we hold them in contempt.”

• “Finally, they think we are hypocrites. We claim to support free speech — until someone says something we don’t like. We claim to oppose violence — unless it serves a cause we approve of. We claim to defend the Constitution — except for the Second Amendment. We support tolerance, inclusion, and social justice — except for people like them.”

Galston has grasped a genuine phenomenon. But white men are not the only victims of deindustrialization. We are now entering upon an era in which vast swaths of the population are potentially vulnerable to the threat — or promise — of a Fourth Industrial Revolution.

This revolution is driven by unprecedented levels of technological innovation as artificial intelligence joins forces with automation and takes aim not only at employment in what remains of the nation’s manufacturing heartland, but increasingly at the white collar, managerial and professional occupational structure.

Daron Acemoglu, an economist at M.I.T., described in an email the most likely trends as companies increasingly adopt A.I. technologies.

A.I. is in its infancy. It can be used for many things, some of them very complementary to humans. But right now it is going more and more in the direction of displacing humans, like a classic automation technology. Put differently, the current business model of leading tech companies is pushing A.I. in a predominantly automation direction.

As a result, Acemoglu continued, “we are at a tipping point, and we are likely to see much more of the same types of disruptions we have seen over the last decades.”

In an essay published in Boston Review last month, Acemoglu looked at the issue over a longer period. Initially, in the first four decades after World War II, advances in automation complemented labor, expanding the job market and improving productivity.

But, he continued, “a very different technological tableau began in the 1980s — a lot more automation and a lot less of everything else.” In the process, “automation acted as the handmaiden of inequality.”

Automation has pushed the job market in two opposing directions. Trends can be adverse for those (of all races and ethnicities) without higher education, but trends can also be positive for those with more education:

New technologies primarily automated the more routine tasks in clerical occupations and on factory floors. This meant the demand and wages of workers specializing in blue-collar jobs and some clerical functions declined. Meanwhile professionals in managerial, engineering, finance, consulting, and design occupations flourished — both because they were essential to the success of new technologies and because they benefited from the automation of tasks that complemented their own work. As automation gathered pace, wage gaps between the top and the bottom of the income distribution magnified.

Technological advancement has been one of the key factors in the growth of inequality based levels of educational attainment, as the accompanying graphic shows:

Acemoglu warns:

If artificial intelligence technology continues to develop along its current path, it is likely to create social upheaval for at least two reasons. For one, A.I. will affect the future of jobs. Our current trajectory automates work to an excessive degree while refusing to invest in human productivity; further advances will displace workers and fail to create new opportunities. For another, A.I. may undermine democracy and individual freedoms.

Mark Muro, a senior fellow at Brookings, contends that it is essential to look at the specific types of technological innovation when determining impact on the job market.

“Two things are happing at once, when you look at traditional ‘automation’ on the one hand and ‘artificial intelligence’ on the other,” Muro wrote in an email. “The more widespread, established technologies usually branded ‘automation’ very much do tend to disrupt repetitive, lower-skill jobs, including in factories, especially in regions that have been wrestling with deindustrialization and shifts into low-pay service employment.”

In contrast, Muro continued, “Artificial intelligence really is a very different set of technologies than those we label as ‘automation, and it will for a while mostly affect college educated workers.” But, and it’s a big but,

there is a greater chance that such white collar workers, with their B.A.s, will be better equipped to coexist with A.I. or even benefit from it than will non-B.A. workers impacted by other forms of automation. And yet, there’s no doubt A.I. will now be introducing new levels of anxiety into the professional class

In a November 2019 paper, “What jobs are affected by A.I.? Better-paid, better-educated workers face the most exposure,” Muro and two colleagues found that exposure to A.I. is significantly higher for jobs held by men, by people with college degrees or higher, by people in the middle and upper pay ranks and by whites and Asian-Americans generally.

In contrast, in a March 2019 paper, “Automation perpetuates the red-blue divide,” Muro and his colleagues found that automation, as opposed to A.I., hurts those who hold jobs that do not require college degrees the most, and that exposure to automation correlates with support for Trump:

The strong association of 2016 Electoral College outcomes and state automation exposure very much suggests that the spread of workplace automation and associated worker anxiety about the future may have played some role in the Trump backlash and Republican appeals.

More specifically, Muro and his colleagues found that

Heartland states like Indiana and Kentucky, with heavy manufacturing histories and low educational attainment, contain not only the nation’s highest employment-weighted automation risks, but also registered some of the widest Trump victory margins. By contrast, all but one of the states with the least exposure to automation, and possessing the highest levels of educational attainment, voted for Hillary Clinton.

How do the risks of automation, foreign trade-induced job loss and other adverse consequences of technological change influence politics?

In his 2020 paper “Why Does Globalization Fuel Populism? Economics, Culture and the Rise of Right-wing Populism,” Dani Rodrik, an economist at Harvard’s Kennedy School, explored what he called four political channels “through which globalization can stimulate populism.”

The four channels are

• 1) “a direct effect from economic dislocation to demands for anti-elite, redistributive policies”

• 2) “through amplification of cultural and identity divisions”

• 3) “through political candidates adopting more populist platforms in response to economic shocks”

• 4) “through adoption of platforms that deliberately inflame cultural and identity tensions.”

In order to get a better sense of what underpinned Trump’s populist appeal, Rodrik focused on a specific bloc of voters — those who switched from supporting Obama in 2012 to Trump in 2016. He found that

Switchers to Trump are different both from Trump voters and from other Obama voters in identifiable respects related to social identity and views on the economy in particular. They differ from regular Trump voters in that they exhibit greater economic insecurity, do not associate themselves with an upper social class and they look favorably on financial regulation. They differ from others who voted for Obama in 2012 in that they exhibit greater racial hostility, more economic insecurity and more negative attitudes toward trade agreements and immigration.

In an email, Rodrik wrote:

Automation hits the electorate the same way that deindustrialization and globalization have done, hollowing out the middle classes and enlarging the potential vote base of right-wing populists — especially if corrective policies are not in place. And the overall impact of automation and new technologies is likely to be much larger and more sustained, compared to the China shock. This is something to watch.

In their December 2017 paper, “Artificial intelligence, worker-replacing technological progress and income distribution,” the economists Anton Korinek, of the University of Virginia, and Joseph E. Stiglitz, of Columbia — describe the potential of artificial intelligence to create a high-tech dystopian future.

Korinek and Stiglitz argue that without radical reform of tax and redistribution politics, a “Malthusian destiny” of widespread technological unemployment and poverty may ensue.

Humans, they write, “are able to apply their intelligence across a wide range of domains. This capacity is termed general intelligence. If A.I. reaches and surpasses human levels of general intelligence, a set of radically different considerations apply.” That moment, according to “the median estimate in the A.I. expert community is around 2040 to 2050.”

Once parity with the general intelligence of human beings is reached, they continue, “there is broad agreement that A.I. would soon after become super‐intelligent, i.e., more intelligent than humans, since technological progress would likely accelerate.”

Without extraordinary interventions, Korinek and Stiglitz foresee two scenarios: both of which could have disastrous consequences:

In the first, “man and machine will merge, i.e., that humans will ‘enhance’ themselves with ever more advanced technology so that their physical and mental capabilities are increasingly determined by the state of the art in technology and A.I. rather than by traditional human biology.”

Unchecked, this “will lead to massive increases in human inequality,” they write, because intelligence is not distributed equally among humans and “if intelligence becomes a matter of ability‐to‐pay, it is conceivable that the wealthiest (enhanced) humans will become orders of magnitude more productive — ’more intelligent’ — than the unenhanced, leaving the majority of the population further and further behind.”

In the second scenario, “artificially intelligent entities will develop separately from humans, with their own objectives and behavior, aided by the intelligent machines.”

In that case, they write, “there are two types of entities, unenhanced humans and A.I. entities, which are in a Malthusian race and differ — potentially starkly — in how they are affected by technological progress.”

In this hypothetical race, “A.I. entities are becoming more and more efficient in the production of output compared to humans,” the authors write, because “human technology to convert consumption goods such as food and housing into future humans has experienced relatively little technological change.” By contrast, “the reproduction technology of A.I. entities — to convert A.I. consumption goods such as energy, silicon, aluminum into future A.I. — is subject to exponential progress.”

In their conclusion, Korinek and Stiglitz write:

The proliferation of A.I. and other forms of worker‐replacing technological change can be unambiguously positive in a 1st‐best economy in which individuals are fully insured against any adverse effects of innovation, or if it is coupled with the right form of redistribution. In the absence of such intervention, worker‐replacing technological change may not only lead to workers getting a diminishing fraction of national income, but may actually make them worse off in absolute terms.

There is no dearth of grim prediction. In “The Impact of Automation on Employment: Just the Usual Structural Change?” Ben Vermeulen of the University of Hohenheim in Germany, writing with three colleagues, puts it this way:

There is literature arguing that the pace at which employment is destroyed by the introduction of productivity-enhancing technology may exceed the pace at which mankind is able to find new uses for those becoming unemployed.

If fully enacted, could Biden’s $6 trillion-plus package of stimulus, infrastructure and social expenditure represent a preliminary step toward providing the social insurance and redistribution necessary to protect American workers from the threat of technological innovation? Can spending on this scale curb the resentment or heal the anguish over wrenching dislocations of race, culture and class?

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