OpenAI Charts Course for 2028 Election with Policy Shifts

OpenAI’s chief global affairs officer Chris Lehane views the 2028 presidential election as a pivotal moment for artificial intelligence. He urges politicians to develop policies addressing American concerns about the technology, moving beyond lip service to anti-AI sentiment and backlash against data centers.

In a new essay, Lehane compares AI’s potential to reshape the economy to President Franklin D. Roosevelt’s New Deal, the 1930s set of federal programs enacted after the Great Depression. He observes that Americans today share similar anxieties about losing economic control and calls for a “compelling third path” that allows people to share in AI’s benefits. The essay outlines five policy priorities covering worker protections, education, AI safety, and data center development.

This comes after a significant Democratic victory in the midterm elections, where Democrats gained control of Congress due to voter frustration over living costs. Kate Brennan, who leads AI and corporate power policy at the AI Now Institute, notes that Lehane’s rhetoric marks a shift from OpenAI’s previous agenda, which focused on accelerating development and reducing regulatory barriers.

Many of Lehane’s proposals support wider AI adoption and infrastructure expansion. However, it remains unclear how his vision will hold AI companies accountable for the economic disruption their technology creates. “Invoking a New Deal metaphor is to invoke state capacity to actually benefit the public,” Brennan said. “This is written by a private company that is trying to advocate for policies for its own benefit. It is ahistorical at best and harmful at worst.”

While AI was not a major midterm issue, opposition to data centers emerged as a bipartisan concern. Lehane anticipates AI will become a larger part of the conversation as affordability shapes the 2028 election. Voters worry about data centers increasing electricity bills, job automation, and concentrated economic gains.

Lehane acknowledges these concerns but offers few concrete proposals to prevent wealth concentration. His tax code suggestions include incentives for learning AI skills and easier capital access, rather than binding requirements to ensure workers share in AI-generated wealth. “I was struck by how much of this policy is for a future…that is already predicated on mass AI adoption and AI benefitting society, which we have yet to see,” Brennan said.

Regarding data centers, Lehane emphasizes construction jobs and local tax revenue while warning that moratoriums could jeopardize America’s lead over China. He also prioritizes child safety and education, arguing against excluding AI from classrooms to prevent inequality. However, this assumes AI improves learning, a claim critics say needs more examination.

Lehane calls for enforceable AI safety standards, independent evaluations, and the ability to use kill switches. Brennan criticizes these stances as “disingenuous,” citing OpenAI’s history of opposing legislation like California’s AI safety bill SB 1047. The company previously sought to limit state regulation but has recently shifted to supporting some state safety laws.

Lehane argues humans should maintain control over consequential AI decisions. Yet, critics question what human control looks like in a society increasingly reliant on AI. Ultimately, Lehane frames AI as a path to agency, but it is unclear if his policies meaningfully redistribute power or entrench it. TechCrunch reached out to OpenAI for specifics but received no response by publication.