Holzer, agreeing that the current US tax code favors displacement, also notes that he doesn’t advocate any type of broad robot or A.I. tax, as it would be a tax on productivity growth.
He suggests instead a sort of displacement tax. “Every time you displace a worker because of A.I., they [companies] have to pay a tax on that,” he says. “And if you’re going to retrain them [employees], then maybe we subsidize that. So you use taxes to discourage displacement that isn’t necessary, and you use the subsidy system to subsidize retraining. You want there to be the right incentives.”
This matters at two levels—for the companies developing A.I. and for those adopting it—he says. “You want their incentive to be less toward pure replacement and more toward human-centered A.I.”
To that end, companies can strive to invest in A.I. that as much as possible augments rather than replaces the complex tasks that human workers can do. As Autor, Chin, Salomons, and Seegmiller conclude in their research, when technology augments rather than displaces human workers, we see more valuable new work created, labor demand boosted, and wages raised.
Governments can take the lead in funding A.I. research in “areas where A.I. can create new tasks that increase human productivity and new products and algorithms that can empower workers and citizens,” notes Acemoglu in additional research.
The Biden administration in 2023 indeed announced several measures to promote responsible A.I. innovation, including allotting $140 million in funding for research and development and issuing a wide-ranging executive order addressing A.I. topics from safety to ethics to potential job loss. And in June, the European Parliament agreed on a draft of the A.I. Act, which could become one of the first all-encompassing laws regulating the technology. The act focuses largely on stemming risks such as privacy violations and hazards to health or safety, and it includes protection proposals for workers subject to company A.I. platforms that are used to hire and manage them.
The Partnership on AI, as part of its shared prosperity guidelines, suggests that companies adopting A.I.-enabled tech should do thorough evaluations to ensure systems align with worker needs. Among the steps they prescribe: secure systems that improve job quality while eliminating undesirable tasks, recognize any extra work created by A.I. and ensure it’s acknowledged and compensated, create teams that test systems for misuse, establish transparency on worker data collection and use, and allow workers to opt out of those data practices.
Klinova says the Partnership on AI is working with unions, companies, and policy makers to refine, test, and encourage adoption of their shared prosperity guidelines.
2. Create opportunities for upskilling
In recent years, the idea of creating universal basic income programs to assist workers displaced by automation and A.I. gained some traction, including in the short-lived US presidential campaign of Andrew Yang. However, many economists prefer the idea of upskilling over passive income replacement. “Even if technology is diffusing fast,” Humlum says, “I’m much more supportive of investing in people than just income supporting them.”
University of Cambridge’s Diane Coyle is even more dismissive of UBI, calling it “a chimera advocated by Silicon Valley individualists who don’t want to take responsibility for the social consequences of their innovations.” She adds, “Nobody can buy a transportation system or infrastructure or good public schools with an individual income.”
Research suggests that reskilling programs can help those with lower-demand skills elevate their professional status. A 2022 White House report notes that government should be “investing in training and job transition services so that those employees most disrupted by A.I. can transition effectively to new positions where their skills and experience are most applicable.”
In the US, Holzer points to successful implementation of sector-based training, in which people prepare for jobs in high-demand areas that offer good pay to workers without college degrees.
Typically, an intermediary organization with knowledge on a specific industry brings training providers—most often community or technical colleges—together with employers and industry associations, providing support and services to disadvantaged students.
Harvard’s Lawrence F. Katz, Brown’s Jonathan Roth, and Richard Hendra and Kelsey Schaberg from the research organization MDRC studied several sector-based programs that focused on workers in industries including manufacturing, healthcare, transportation, and IT. They find that the programs (including WorkAdvance, Project QUEST, and Year Up) led to earnings gains of 14–38 percent in the year following training completion. Additionally, they find, earnings gains persisted for at least several years “with little evidence of the fade out of treatment impacts found in many evaluations of past employment programs.”
So far, Holzer says, these programs have been more for disadvantaged than displaced workers, but the model could work for employees who lose work due to A.I.
“You can imagine a worker who’s displaced, say in healthcare or in IT, that you might be able to retool them more quickly if it remains a growing field,” he says. And the place this should be happening most is at the community-college level, he suggests. But, he notes, while community colleges have the scale, lack of support—for one, they are given far fewer public subsidies than four-year colleges—is a major challenge to program quality.
Booth’s Humlum, through research with University of Copenhagen’s Jakob R. Munch and UCPH PhD student Pernille Plato Jørgensen, studied the effects of a reskilling program in Denmark for workers injured on the job. Workers were transitioned from physical to more cognitive occupations, and while this program focused on displacement due to injury, the researchers note it could potentially translate for workers displaced through automation.
The study followed workers who instead of receiving disability payments from the government took the same amount of money to either enroll in formal education courses or participate in an on-site training program. According to the study, the most common choice for those who enrolled in classroom training was a four-year bachelor’s degree that transitioned their physical work to more knowledge-based work in the same field—for example, a former construction worker would enter a degree program in construction architecture. Of those workers, 80 percent found new employment within seven years of their accidents, and on average earned 25 percent more than before they were injured.
Another study Humlum conducted in Denmark, with Munch and UCPH’s Mette Rasmussen, finds similar advantages to upskilling, which the researchers argue is more beneficial than on-the-job training programs. While their study focused largely on workers displaced due to offshoring, the key result could translate to job loss or downsizing due to A.I. and automation. The researchers find that unemployed workers whose jobs were at the most risk for offshoring and who were assigned to classroom training—which allowed them to learn new skills that could help them switch occupations—had gained, on average, 55 hours of work per month compared with their previous employment.
Similarly, the United Kingdom in 2017 announced the National Retraining Scheme program, eventually investing £100 million to train workers, particularly those displaced by A.I. and automation. And US companies are also taking notice. Amazon’s Upskilling 2025 program, for one, is investing $1.2 billion to provide employees access to training programs that prepare them for higher-level jobs.
“I do think reskilling will become increasingly important,” Humlum says, “just because technology is diffusing faster . . . and we are living longer, and those two facts combined mean that we have to confront more technologies during one single career.” In their research, Humlum, Munch, and Rasmussen note that while Denmark spends as much as 2 percent of its GDP on active labor-market policies, the US emphasizes more passive programs such as unemployment and disability insurance.
The White House report notes that “the increased prevalence of shorter contract durations lowers incentives for firms to invest in worker training,” and that it may therefore be useful to subsidize intermediaries such as public employment services and temporary-employment agencies to share the costs and benefits of training.
