OpenAI’s five policy priorities for the 2028 election — SkimNews
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- OpenAI is pressing U.S. politicians to develop AI policies before the 2028 presidential election through a new essay from chief global affairs officer Chris Lehane, who invokes Franklin D. Roosevelt’s New Deal and sets out five priorities spanning workers, education, safety and data centers.
- Democrats flipped control of Congress in the midterms amid widespread frustration over the cost of living; although AI was not a dominant issue, opposition to data centers emerged as a major bipartisan concern in several races.
- Kate Brennan, who leads AI and corporate power policy at the AI Now Institute, said the essay marked a shift from OpenAI’s prior focus on accelerating development, reducing regulatory barriers and expanding infrastructure, and called the New Deal framing “ahistorical at best and harmful at worst.”
- Chris Lehane proposed incentives for worker AI training, easier capital access, employee ownership and profit-sharing, but offered few concrete mechanisms to prevent AI gains from concentrating or require companies to cover displacement costs.
- Chris Lehane warned that data-center moratoria could jeopardize America’s lead over China, comparing a pro-moratorium stance to the 2002 vote authorizing the Iraq War.
- Chris Lehane calls for enforceable safety standards, independent evaluations, public oversight and a kill switch; Kate Brennan called those positions disingenuous because OpenAI opposed California’s SB 1047 in 2024 and sought to limit state regulation, though it has since backed several state safety laws.
- Chris Lehane made child safety and education central, calling for age-appropriate protections around AI companions for minors while arguing against classroom exclusions that could widen inequality between wealthy students and rural children; critics say his assumption that AI improves learning remains unproven.
Why it matters: OpenAI’s five-part agenda is entering the 2028 election cycle, when data-center opposition, job displacement and concentrated AI wealth are already voter concerns. Its reliance on adoption incentives, rather than binding redistribution or displacement-cost guarantees, leaves those costs unresolved for workers and communities while AI firms retain policies favoring the expansion they need.
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