Chris Lehane, OpenAI’s chief global affairs officer, argues that the 2028 presidential election could be a pivotal moment for policy on artificial intelligence (AI). In a new essay, Lehane urges politicians to develop concrete policies that address public concerns about AI rather than merely responding rhetorically to anti-AI sentiment and opposition to data centers.
Lehane compares AI’s potential economic impact to President Franklin D. Roosevelt’s New Deal of the 1930s — a set of federal programs and reforms enacted after industrialization and the Great Depression reshaped the U.S. economy. He says many Americans today feel anxious about losing control over their economic futures and calls for a “compelling third path” that would let people share in AI’s benefits. His essay outlines five policy priorities covering worker protections and education, AI safety, data center development, and related areas.
The piece appeared after the 2024 midterm elections, when Democrats made unexpected gains and flipped control of Congress amid widespread voter frustration over the cost of living. Kate Brennan, who leads AI and corporate power policy at the AI Now Institute, told TechCrunch that Lehane’s rhetoric represents a notable shift from OpenAI’s policy agenda last year, which emphasized accelerating AI development, lowering regulatory barriers, and expanding infrastructure.
Many of Lehane’s proposals would, unsurprisingly, encourage broader AI adoption and support the infrastructure expansion that companies like OpenAI need to grow. By contrast, the original New Deal included measures to protect workers and curb corporate power; it is less clear how Lehane’s proposals would hold AI companies accountable for economic disruption caused by their technology.
Brennan said invoking a New Deal metaphor implies state capacity to benefit the public, while Lehane’s essay was authored by a private company advocating policies that could align with its business interests. She described the approach as at best ahistorical and at worst harmful.
Although AI was not a dominant issue in the midterms, opposition to data centers emerged as a significant bipartisan concern in several races. Lehane warns that politicians backing data center moratoria risk jeopardizing U.S. competitiveness with China, even likening that stance to the 2002 congressional vote to authorize the Iraq war.
Affordability and the rising cost of living are shaping up as central issues for 2028. AI could increasingly figure into those debates as voters worry about data centers raising electricity bills, AI replacing jobs, and economic gains concentrating at a few wealthy firms.
Lehane acknowledges many of these worries but offers relatively few binding proposals to prevent concentration of AI-generated gains. His tax-code suggestions include incentives for workers to learn AI skills, easier capital access for entrepreneurs, and new approaches to employee ownership and profit-sharing. Those are incentives rather than enforceable requirements to ensure workers share in AI-generated wealth or that companies bear the costs of displacement.
Brennan suggested alternatives she believes would better address concentration and displacement: revising corporate tax rates, tax incentives for hiring humans instead of automating jobs, and mechanisms to limit outsized market power. She argued Lehane’s proposals assume mass AI adoption and widespread societal benefit — outcomes that have not yet been realized.
On data centers, Lehane acknowledges community concerns but emphasizes construction jobs and local tax revenues they can create, while warning that moratoria could cost U.S. leadership in AI infrastructure. This emphasis on expansion over restriction fits the broader pattern of his recommendations.
Lehane also centers child safety and education in his agenda, calling for age-appropriate protections and safeguards for AI companions used by minors. He warns against excluding AI from classrooms, saying that could widen inequalities between affluent students and “children in rural communities.” Critics note that the presumption that AI improves learning remains unproven and requires more rigorous study rather than default classroom deployment.
He calls for enforceable AI safety standards, independent evaluations, public oversight, and the ability to restrict or shut down systems — though recent studies show that OpenAI and other AI labs have not published comprehensive plans for how they would respond if a model escaped human control.
Brennan called these positions disingenuous given OpenAI’s prior opposition to measures that would have mandated such safeguards. For example, in 2024 OpenAI opposed California’s SB 1047, an AI safety bill that would have required catastrophic risk evaluations and shutdown capabilities. The company has also previously sought to limit state regulation on the grounds that states could undermine American innovation. More recently, OpenAI has shifted some positions: it has backed several state safety laws and said it would be open to embedding independent evaluators within the company.
Lehane further argues that people should retain control over consequential decisions that use AI rather than ceding judgment entirely to machines. That claim raises questions about what meaningful human control looks like in a society where AI is increasingly required in education, work, health care, and government.
Throughout his essay, Lehane frames AI as a technology that could restore agency and economic opportunity to Americans, while tying the middle-class success of average Americans to participation in an economy increasingly shaped by companies like OpenAI. Whether his proposals will redistribute power or subtly entrench it remains unclear.
TechCrunch contacted OpenAI for further details on Lehane’s proposals and the company’s stances; OpenAI had not responded by the time of publication.
