A group of 40 leading thinkers in economics, technology and public policy gathered in Washington, D.C., this week to game out policy responses to artificial intelligence’s economic risks, according to a report by The Wall Street Journal’s Lauren Weber. The exercise, organized by the nonprofit Windfall Trust, focused on a hypothetical 2030 scenario called “Paper Prosperity” in which AI’s speed and efficiency nearly doubled GDP and labor productivity growth rates while underemployment jumped from 8% to 14%.
The scenario described an economy with a soaring S&P 500 but a “simmering social and economic crisis” beneath the surface. Underemployment—workers in part-time jobs, gig work or roles for which they are overqualified—had reached the upper tiers of the middle class, a development that participants said would drive political unrest, widen generational divides, and erode the belief that hard work leads to prosperity.
Windfall Trust CEO Adrian Brown said the group chose to focus on AI’s economic implications rather than safety risks such as cyberattacks and bioweapons because “those are likely to have political consequences sooner as people’s anxiety grows about how AI will disrupt the economy and their jobs and their children’s jobs.”
Rep. George Whitesides (D., Calif.), a former NASA chief of staff and Virgin Galactic CEO, stopped by the event for a lunch Q&A. He said the group should “start to put down smart bets on some scenarios.” Later, describing the challenge facing Congress, he said: “Congress is slow-moving and technophobic.”
The exercise comes as public skepticism about AI runs high. A March Pew Research Center survey found that only 17% of Americans believe AI will have a net positive effect on the U.S. over the next 20 years.
During morning sessions, participants discussed possible upsides. Neil Thompson, director of MIT FutureTech, suggested healthcare and education costs could decline as AI-augmented tools deliver expertise more cheaply. Underemployed workers might gain more free time for creative pursuits—what one facilitator called “the crochet economy.” But the dominant theme was the need for proactive policy to redistribute AI’s gains and cushion displaced workers.
Worker reskilling was proposed repeatedly, though participants acknowledged that U.S. government-administered programs have a poor track record. Harry Holzer, a labor economist at Georgetown University, noted that “we don’t yet know what new tasks and occupations will be created because of AI, or which jobs will simply be augmented.”
Other policy ideas included universal basic income, taxes on AI companies and shareholders, and a sovereign-wealth fund owning half of AI companies’ stock—a concept proposed earlier this month by Sen. Bernie Sanders (I., Vt.). Participants also suggested universal health insurance, job guarantees, wage subsidies, and major investment in high-quality child care and eldercare.
One conclusion that emerged was that government dysfunction and public distrust of elected leaders pose a major obstacle to any proactive AI policy. Whitesides said he is particularly concerned about risks such as biological threats and digital safety, especially for children and teenagers. “How do we act as policymakers in a world where we don’t know what the future holds?” he asked.
He noted a bipartisan proposal released this month by Reps. Jay Obernolte (R., Calif.) and Lori Trahan (D., Mass.) called the Great American AI Act, which would require AI-specific workforce data and mandate that AI labs disclose catastrophic-risk assessments.
The United Kingdom launched its own AI Economics Institute last week, a government research group meant to inform public policy. Windfall Trust’s Brown called it “heartening that some governments are taking steps to put serious attention on these issues.”
The Windfall Trust has held similar scenario-planning exercises in cities around the world and plans to continue the effort, aiming to catalyze proactive strategies before the economic disruptions arrive.