OpenAI’s chief global affairs officer Chris Lehane thinks the 2028 presidential election could be a defining moment for AI. And he wants politicians to start developing policies that address Americans’ concerns about the technology, rather than simply paying lip service to anti-AI sentiment and the backlash against data centers.
Shaping the New Economic Order
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 and reforms enacted after industrialization and the Great Depression shattered the old economic order. He observes that Americans today feel similarly anxious about losing control over their economic futures and urges politicians to find a compelling third path that allows people to share in AI’s benefits. He lays out five policy priorities, spanning worker protections and education to AI safety and data center development.
The essay comes on the heels of a political shift, with widespread voter frustration over the cost of living. Critics note that Lehane’s rhetoric marks a notable shift from previous policy agendas that focused primarily on accelerating AI development, reducing regulatory barriers, and expanding infrastructure.
Unsurprisingly, many of Lehane’s proposals would encourage wider AI adoption and support the infrastructure expansion companies like OpenAI need to grow. The original New Deal established protections for workers and placed constraints on corporate power. It remains less clear how Lehane’s vision would hold AI companies accountable for the economic disruption their technology could create.
Invoking a New Deal metaphor is to invoke state capacity to actually benefit the public, policy analysts noted. Critics argue that proposals written by private companies seeking policies for their own benefit can often be viewed as self-serving rather than entirely historical.
While AI has not always been a dominant electoral issue, opposition to data centers has emerged as a major bipartisan concern in several regions. Observers suggest AI will inevitably become a bigger part of the political conversation over the coming years.
Economic Anxieties and Affordability
Affordability is already shaping up as a key issue as voters grapple with inflation, tariffs, and the rising cost of living. AI could become an increasingly large part of that conversation as voters stress about data centers hiking up electricity bills, AI replacing their jobs, and technology’s economic gains flowing only to a handful of wealthy entities.
Lehane acknowledges many of these concerns, but offers few concrete proposals to prevent AI’s gains from becoming concentrated. Instead, he largely pitches AI as a path to greater prosperity for those willing to embrace it.
His proposals for the tax code suggest incentives for workers to learn AI skills, easier capital access for entrepreneurs, and new approaches to employee ownership and profit-sharing. Critics point out these differ significantly from binding requirements that would ensure workers share in AI-generated wealth or require companies to pay the costs of displacing workers.
Much of this policy framework is predicated on a future featuring mass AI adoption and widespread societal benefit, outcomes that remain unproven according to labor and policy experts.
Alternative proposals often emphasize a revised corporate tax rate, tax incentives for hiring human workers rather than automating jobs, and measures to prevent companies from amassing outsize market power.
Infrastructure and Geopolitics
Lehane’s emphasis on expanding AI’s economic opportunities extends to data centers. He notes concerns about facilities while emphasizing construction jobs and local tax revenue. He also warns that politicians supporting data center moratoriums could jeopardize America’s technological standing.
Safety and Education
The proposed agenda also makes child safety and education central, stressing age-appropriate protections and safeguards around AI companions for minors. Furthermore, it warns against keeping AI out of classrooms. However, critics argue that the assumption that AI unconditionally improves learning remains debated and unproven.
Lehane also calls for enforceable AI safety standards, independent evaluations, public oversight, and shutdown capabilities, though critics note that major AI labs have often opposed rigid statutory frameworks in the past.
Observers have pointed out the apparent contradiction between calling for strict oversight and a history of corporate lobbying against specific state-level safety legislation, though major labs have recently expressed openness to certain independent evaluations.
The proposal also argues that humans should maintain control over consequential decisions made using AI. This raises questions about what genuine human control looks like in a society where individuals are increasingly required to use automated systems in education, work, healthcare, and government.
Ultimately, while Lehane frames AI as a technology that could restore American agency and economic opportunity, questions remain over whether proposed policies will meaningfully redistribute power or further entrench corporate influence.
Requests for comment regarding the specifics of these proposals were not immediately answered prior to publication.
