OpenAI’s chief global affairs officer, Chris Lehane, is urging politicians to shape policies for artificial intelligence before the 2028 presidential election. He argues that AI could become a defining political issue and that leaders should respond to public concerns with more than statements against the technology.
His proposal puts economic opportunity at the center. But while it recognizes worries about jobs, data centers and who gains from AI, critics say it offers limited detail on how to make companies bear the costs or ensure workers share in the benefits.
A New Deal comparison, with different questions
In a new essay, Lehane compares AI’s potential economic impact to President Franklin D. Roosevelt’s New Deal, a set of federal programs and reforms from the 1930s. He says Americans are anxious about losing control over their economic futures and calls for a “compelling third path” that would let people benefit from AI.
The comparison raises questions about what public policy should require of the companies developing the technology. The original New Deal established worker protections and constrained corporate power. Lehane’s vision, as described in the essay, emphasizes expanding AI’s economic opportunities, while leaving unclear how companies would be held responsible for disruption their systems might cause.
Kate Brennan, who leads AI and corporate power policy at the AI Now Institute, told TechCrunch that the framing represents a shift from OpenAI’s policy agenda last year, which emphasized accelerating development, reducing regulatory barriers and expanding infrastructure. She criticized the New Deal analogy as coming from a private company advocating policies that could serve its own interests.
Sharing AI’s gains is central, but mechanisms are limited
Lehane’s proposals include tax incentives for workers to learn AI skills, easier access to capital for entrepreneurs, and new approaches to employee ownership and profit-sharing. These measures could encourage people and businesses to take part in an AI-driven economy.
They do not, by themselves, establish binding requirements for companies to share AI-generated wealth or pay costs tied to workers being displaced. Brennan said the proposals assume that widespread AI adoption will benefit society, a result she said has not yet been demonstrated.
She suggested other policy approaches, including a revised corporate tax rate, tax incentives for hiring people instead of automating jobs, and measures to limit companies’ ability to accumulate excessive market power. The disagreement is about how to turn a promise of broad prosperity into concrete obligations and protections.
Data centers put local concerns beside national competition
Data center development is another point of tension. Opposition to data centers became a bipartisan concern in several midterm races, even though AI itself was not a dominant election issue. People worry that facilities could raise electricity bills, while companies and their advocates point to construction work and local tax revenue.
Lehane acknowledges concerns about data centers, but argues that a moratorium could put America’s lead over China at risk. He compares support for a moratorium to the 2002 vote to authorize the Iraq war. That argument makes infrastructure expansion part of a broader political choice: how to weigh local costs against claims about national competitiveness.
Affordability is already emerging as an issue for 2028 as Americans contend with inflation, tariffs and the rising cost of living. If voters connect electricity costs or job insecurity to AI, decisions about where data centers are built and who pays for their effects could become part of that debate.
Safety and education require more than access
Lehane also calls for age-appropriate protections for children and safeguards around AI companions for minors. On education, he warns that excluding AI from classrooms could widen inequality between wealthy students and “children in rural communities.” Critics say this argument assumes AI improves learning, a claim they believe deserves more scrutiny alongside questions about funding and individual attention from human teachers.
For AI safety, the essay calls for enforceable standards, independent evaluations, public oversight and the ability to restrict systems or shut them down with a kill switch. Brennan questioned the company’s position, pointing to OpenAI’s past opposition to legislation intended to impose such measures.
In 2024, OpenAI opposed California’s AI safety bill, SB 1047, which would have required catastrophic risk evaluations and shutdown capabilities. Last year, the company also sought to limit state regulation, arguing that states could undermine American innovation. More recently, OpenAI has backed several state safety laws and said it would be open to independent evaluators embedded in the company.
Lehane says people should retain control over consequential decisions made with AI. That principle becomes harder to define as AI use grows across education, work, health care and government. The central political question is whether people will have meaningful choices and oversight as these systems become more common.
Lehane presents AI as a possible source of renewed agency and economic opportunity. Whether his proposals would spread power and prosperity broadly, or reinforce the position of the companies building the technology, remains unresolved. TechCrunch said it contacted OpenAI for details on the proposals and the company’s positions, but received no response by publication.