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Jay Clayton, a former U.S. attorney, is now—in the president’s words—America’s “AI czar.” More formally, he is head of the White House’s new Super Intelligence Force. In that role, Clayton is responsible for developing “plans for responding to SI-enabled threats” to America.
That remit is a fine starting place for Washington, which, until very recently, been concerningly disengaged with regulating or overseeing the artificial-intelligence industry at all. Attending to concerns around AI threats to privacy, national security, and perhaps even civilization are of critical importance.
But there must be just as much attention placed on addressing the more immediate transition into the AI era—things like retraining workers, making sure displaced workers are supported, and ensuring government and private businesses have a way to work together through big economic changes. A failure to meaningfully address these shorter-run, more mundane concerns may mean we never reach the promised AI era at all.
Our economy is in the early stage of a large-scale transition that will disrupt and eliminate some jobs, create new ones, and necessitate skill shifts in others. We have experienced such transitions before, but they took place over decades. It is reasonable to believe this one will be much faster.
Therein lies the rub. Today’s business, economic, and monetary policy discussions around AI center on the durability of a tech-heavy stock market, expected productivity gains, and effects on wages and the labor market, all of which are important. But no one knows exactly how or when AI will create these huge shifts in our economy. Given this, a prudent policy stance is one of scenario planning and risk management, proactively taking steps that are flexible to different forms of disruption.
Those steps should be centered on a principle of promoting maximum participation—that is, individuals’ connection to meaningful participation in the economy. As we have recently learned amid the decline of manufacturing jobs, work is more than a paycheck: It provides a sense of purpose and identity. Disconnection from working to earn reasonable pay is painful for workers, their families, and their communities.
Policymakers should invest in institutions that can equip workers with new, economically valuable skills and to connect them to the new opportunities that AI will create. They would be wise to start with the community college system, which serves millions of students every year. Greater resources from the government will mean these institutions can serve more students and develop new curricula for AI-related training programs. American business leaders also have a stake in managing the labor transition: Maximizing long-term shareholder value requires them to be stewards of their workforce and the communities in which they operate.
If policymakers and business leaders fail to manage this transition well, all of society will bear the consequences. We are still dealing with the fallout of their failure to properly pay attention to previous economywide changes, such as opening of global trade to China.
On net and over the long run, expanding trade with China lowered prices for consumers, made new varieties of goods available, and created new service-sector jobs. But it also generated economic pain in places dependent on the manufacturing jobs that were eliminated. The failure to support workers whose livelihoods were disrupted and to reconnect them to economic participation created a political backlash against globalization that remains today. The growing, bipartisan turn against the data-center buildout necessary for AI diffusion may be a sign that a similar backlash to AI is already under way.
The next Congress should build on what efforts worked well in past episodes of disruption. Wage insurance, which replaces a portion of lost income when a laid-off worker takes a new, lower-paying job, was a shining element of the Trade Adjustment Assistance program. Enacted in 1962 as the U.S. began to lower trade barriers, it was never used robustly due to strict eligibility restrictions and should be reintroduced in an expanded form. Finally, bolstering elements of the tax code like the earned-income tax credit will raise the rewards to work by supplementing wage income for many workers.
Meanwhile, business leaders should aim to incorporate AI in a way that complements human tasks rather than replaces entire occupations. Over time, that means developing current employees’ skills to meet firms’ future talent needs, as AT&T did in the early 2000s through its successful “Workforce 2020” retraining program. The program proactively identified new and growing jobs in the coming years, given technology and business trends, and prepared workers for the skills necessary to succeed in those roles going forward, whether at AT&T or elsewhere.
Such work will involve coordination across agencies and between the public and private sector to develop the necessary data-collection infrastructure and shape a response. We can look to many examples of successful coordination efforts in the past, including the Committee for Economic Development, which aimed to address risks posed by America’s transition back to a peacetime economy after World War II. The SI Force that Clayton is chairing would be a natural spot for this coordination.
Establishing guardrails to ensure that AI doesn’t destroy humanity is important work, but it is the bare minimum. Policymakers should match their focus on AI doomsday scenarios with focus on the more mundane, more immediate economic issues at hand today. A failure to do so risks making those loftier concerns moot.
Guest commentaries like this one are written by authors outside the Barron’s newsroom. They reflect the perspective and opinions of the authors. Submit feedback and commentary pitches to ideas@barrons.com.
Glenn Hubbard, a professor of economics and finance at Columbia University, was chairman of the Council of Economic Advisers under President George W. Bush. Luke Pardue is the policy director of the Aspen Economic Strategy Group.
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