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NewsMaterial4 min readDisconfirmAI Editorial

OpenAI Global Affairs Head Chris Lehane Pushes AI Policy with New Deal Analogy; Critics Note Proposals Prioritize Promotion Over Constraints

Chris Lehane, OpenAI's chief global affairs officer, published a long-form essay comparing the economic reshaping potential of artificial intelligence to Franklin D. Roosevelt’s New Deal. He outlined five policy priorities covering worker protection, education, AI safety, and data center development, urging politicians to find a "third path" that allows the public to share in AI's benefits. Kate Brennan, policy director at the AI Now Institute, criticized the proposals for assuming mass AI adoption and societal benefit without including mandatory requirements to ensure workers share in the wealth or companies bear the costs of displacement, noting this stands in sharp contrast to the historical reality of the New Deal, which constrained corporate power.

2026-11-05 05:25 GMT+8

With the U.S. midterm elections just concluded and Democrats securing control of Congress, Chris Lehane, OpenAI’s chief global affairs officer, promptly released a lengthy essay attempting to set the tone for the AI policy debate. His core argument posits that AI’s potential to reshape the economy is comparable to the New Deal—the federal programs and reforms enacted in the 1930s after industrialization and the Great Depression shattered the old economic order. Lehane observes that Americans today harbor similar anxieties about losing control over their economic futures and urges politicians to find a compelling third path that enables the public to share in the dividends of AI.

Lehane listed five policy priorities spanning worker protection, education, AI safety, and data center development. On taxation, he suggested incentives for workers to learn AI skills, lowered barriers to capital access for entrepreneurs, and new models for employee ownership and profit-sharing. Regarding data centers, he acknowledged public concerns but emphasized job creation and local tax revenue, warning that politicians supporting a moratorium on data centers could jeopardize America’s technological lead over China, even likening such a stance to the 2002 vote authorizing the Iraq War. On AI safety, he called for enforceable safety standards, independent assessments, public oversight, and a kill switch to restrict or shut down systems if models were to go out of control.

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However, Kate Brennan, who leads AI and corporate power policy at the AI Now Institute, pointed out structural flaws in this narrative during an interview with TechCrunch. She argued that Lehane’s rhetoric marks a significant shift in OpenAI’s policy agenda—last year, the company focused on accelerating AI development, reducing regulatory barriers, and expanding infrastructure. Yet, Brennan noted that the essence of the New Deal was establishing worker protections and constraining corporate power, whereas it remains unclear how Lehane’s vision would hold AI companies accountable for the economic disruption their technology might cause.

Brennan’s core criticism is that all these policies presuppose the premise of mass AI adoption and AI benefiting society—a scenario that has not yet materialized. She pointed out that Lehane’s tax suggestions—skill-learning incentives, easier capital access for startups, and employee ownership—are not equivalent to binding requirements ensuring workers share in the wealth generated by AI or requiring companies to cover the costs of displacing workers. A more reasonable approach would involve revising corporate tax rates, providing tax incentives for hiring humans rather than automating jobs, and preventing companies from accumulating excessive market power.

Regarding the stance on safety standards, Brennan labeled it disingenuous. She cited OpenAI’s track record: in 2024, the company opposed California’s AI safety bill SB 1047, which required catastrophic risk assessments and shutdown capabilities; last year, OpenAI also attempted to limit state regulations, arguing that state-level rules could undermine American innovation. Although the company has recently adjusted some positions—supporting several state safety laws and expressing willingness to accept independent evaluators embedded within the company—Brennan believes there is clear tension between these shifts and its historical behavior.

Lehane also advocated that people should maintain control over major decisions made using AI, rather than handing judgment entirely over to machines. But TechCrunch’s article raised a follow-up question: what does human control actually mean in a society where humans are increasingly required to use AI in education, work, healthcare, and government?

Throughout his essay, Lehane frames AI as a technology that could restore Americans’ sense of agency and economic opportunity. However, he ties the middle-class success of average Americans to participation in an economy increasingly shaped by companies like OpenAI. It remains unclear whether his policies will meaningfully redistribute power or subtly entrench it.

The takeaway for readers is this: when an AI company begins packaging its policy proposals with historical metaphors like the New Deal, the question worth asking is not whether the rhetoric is moving, but whether it contains the core elements of the historical precedent it invokes—the use of state capacity to truly benefit the public and actual constraints on private power. Lehane’s proposals offer concrete pathways for expanding AI adoption and infrastructure but leave glaring gaps in constraining corporate power. This gap itself is key to understanding the trajectory of the AI governance debate.

Sources

  • techcrunch.comTechCrunch↗
  • axios.comAxios↗
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