The spread of intelligence machines will worsen geographic inequality, unless we take proactive measures
Historically, the worst times for labor have been those characterized by both worker-replacing technological change and slow productivity growth. If A.I. technologies turn out to be as brilliant as some of us think, we can expect some workers to see their incomes vanish in the process — even as new jobs are created elsewhere in the economy. That is what has happened in recent years, and it is also what happened during the most tumultuous years of industrialization.
If current trends continue in the coming years, the divide between the automation winners and losers will become even wider. And there are good reasons to think that it will. Looking at the automatability of existing jobs, we have seen that most occupations that require a college degree remain hard to automate, while many unskilled jobs — like those of cashiers, food preparers, call center agents, and truck drivers — seem set to vanish, though how soon is highly uncertain. But there are also unskilled jobs that remain outside the realms of A.I. Many in-person service jobs that center on complex social interactions — like those of fitness trainers, hairstylists, concierges, and massage therapists — will remain safe from automation.
Computers have created jobs for software engineers and programmers, which in turn have raised the demand for in-person service jobs in the places where they work and live. Thus, where skilled jobs are abundant, the unskilled earn better wages, too. In San Jose, California, fitness trainers and aerobics instructors made $57,230 on average in 2017. In Flint, Michigan, they averaged $35,550 annually. Of course, direct comparisons are complicated by a variety of factors. It is true that the cost of living in the Bay Area is higher than it is in Flint. But it is just as true that amenities are more plentiful, health outcomes and public services are better, and crime rates are lower.
Removing barriers to the expansion and development of skilled cities would help social mobility.
Automation then represents a double whammy. Where machines have replaced middle-class workers, the demand for local services has also suffered. Looking forward, even if new and improved substitutes for face-to-face interactions are developed, they cannot substitute for spontaneous encounters that require physical proximity. The value of proximity will probably increase as A.I. makes production more skill intensive. Thus, the curse of geography is likely to intensify.
Historically, migration was the mechanism by which cities adjusted to trade and technology shocks. Workers moved to areas where new industries, spawned by the Second Industrial Revolution, created an abundance of well-paying, semiskilled manufacturing jobs. But migration is no longer the equalizer it once was. The unskilled have become less likely to migrate since the dawn of the computer revolution. One reason might be financial. Even if skilled cities provide better employment opportunities, moving is an investment that requires liquidity up front.
Thus, as Enrico Moretti has convincingly argued, there is a case for subsidizing relocation. Mobility vouchers could pay for themselves by shifting the unemployed into paid employment elsewhere, while serving to equalize incomes across space. Some will argue that mobility vouchers might serve to accelerate the exodus from communities in decline, leaving parts of America in an even more dire state, but those who stayed put would likely benefit in terms of having a better chance of finding a job.
Another dilemma is that as skilled cities are becoming more attractive, rising housing prices makes them less affordable. To counteract this, the housing supply must be expanded where new jobs are being created. This will require getting rid of some zoning restrictions, such as minimum lot sizes, height limits, prohibitions on multifamily housing, lengthy permitting processes, and so on, which effectively cap the number of people who can live in thriving places. Because dynamic places like New York and the Bay Area have adopted stringent restrictions on new housing supply, they have effectively limited the number of workers who can participate in the growth created by tech industries. The consequence has been that tech companies find it more difficult to hire due to the rising cost of housing. But more importantly still, an unemployed unskilled worker in Flint who finds a job in Boston cannot afford to live there.
Economists have estimated that in the absence of zoning restrictions on housing supply, the American economy would be 9% larger today, which would mean an additional $6,775 in annual income for the average American worker. Abolishing land-use restrictions would also have welcome side effects. The breathtaking rise in wealth inequality that has been documented by Thomas Piketty stems almost entirely from housing. Inflated house prices due to land-use restrictions are surely part of the reason, and the abolition of those restrictions must therefore be part of the solution.
Removing barriers to the expansion and development of skilled cities would help social mobility, too. Because zoning restrictions are not distributed randomly but are much more prevalent in high-income cities and neighborhoods, they put people born into less affluent communities at a further disadvantage. Zoning, in other words, has priced lower-income families out of the places with more social capital and better schools.
Another benefit would be more innovation. Children growing up in places with more inventors, who are thus more exposed to innovation in their early years, are much more likely to become inventors themselves. This, we know, also has an impact on the types of inventions that they are likely to produce. Those growing up in Silicon Valley are more likely to drive innovation in computing, while those who spend their early years in places specializing in medical devices, like Minneapolis, for example, are more likely to invent related technologies.
Some readers might still think that we are entering a new era in which machines take all of the jobs, and of course, there is no way of knowing if that is true. But for now, our current trajectories suggest that the challenges ahead lie in the area of political economy, not in technology. In a world where technology creates few jobs and enormous wealth, the challenge is a distributional one. The bottom line is that regardless of what the future of technology holds, it is up to us to shape its economic and societal impact.