OpenAI Executive Foresees 2028 as Defining AI Election, Urges Proactive Policy Development

Chris Lehane, OpenAI’s chief global affairs officer, has posited that the 2028 U.S. presidential election is poised to become a pivotal moment for artificial intelligence, necessitating the urgent development of comprehensive policies. Lehane advocates for political leaders to move beyond superficial anti-AI rhetoric and the burgeoning public backlash against data center construction, instead crafting concrete strategies to address Americans’ legitimate concerns about the technology’s societal impact.

In a recent essay, Lehane draws a striking parallel between AI’s transformative potential for the economy and President Franklin D. Roosevelt’s New Deal. The New Deal, a sweeping series of federal programs and reforms enacted in the 1930s, fundamentally reshaped the American economic landscape in response to the profound disruptions caused by rapid industrialization and the devastating Great Depression. Lehane observes that a similar pervasive anxiety about economic security and control over one’s future is palpable among Americans today. He urges politicians to forge a "compelling third path," one that enables the public to equitably share in the profound benefits that AI is expected to generate. To achieve this, Lehane outlines five key policy priorities, encompassing a broad spectrum from robust worker protections and educational reforms to stringent AI safety protocols and strategic data center development.

Lehane’s essay emerges in the aftermath of a significant Democratic triumph in the recent midterm elections, where the party secured control of Congress. This victory was largely fueled by widespread voter frustration over the escalating cost of living and economic uncertainty. Kate Brennan, who leads AI and corporate power policy at the AI Now Institute, noted to TechCrunch that Lehane’s current rhetoric represents a discernible shift from OpenAI’s policy agenda articulated last year. That earlier agenda primarily focused on accelerating AI development, dismantling regulatory impediments, and expanding critical infrastructure, signaling a more industry-centric approach.

Unsurprisingly, many of Lehane’s proposed policies are designed to foster broader AI adoption and support the extensive infrastructure expansion that companies like OpenAI require for their continued growth. The original New Deal, however, was characterized by its establishment of crucial protections for workers and the imposition of significant constraints on corporate power. It remains less clear how Lehane’s vision, as articulated, would genuinely hold AI companies accountable for the substantial economic disruption their technologies could potentially unleash.

Brennan was critical of the analogy, stating, "Invoking a New Deal metaphor is to invoke state capacity to actually benefit the public. 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." Her critique underscores the fundamental difference between government-led initiatives aimed at public welfare and corporate advocacy that, while framed in terms of public benefit, may ultimately serve private interests.

While AI was not a central issue dominating the midterm elections, opposition to the construction of data centers did emerge as a significant bipartisan concern in several key races. This suggests that Lehane’s prediction regarding AI’s increasing prominence in political discourse over the coming two years may indeed prove accurate. Affordability is already solidifying as a critical issue for the 2028 election, with Americans grappling with persistent inflation, the impact of tariffs, and the spiraling cost of living. AI could increasingly integrate into this broader conversation, as voters express apprehension about data centers driving up electricity bills, the potential for AI to displace their jobs, and the fear that technology’s economic gains will disproportionately flow to a select few wealthy corporations.

Lehane acknowledges many of these prevailing public anxieties, yet his essay offers relatively few concrete proposals specifically designed to prevent the concentration of AI’s benefits. Instead, he largely presents AI as a direct pathway to enhanced prosperity for Americans who are willing to embrace and adapt to its advancements. For instance, concerning the tax code, Lehane suggests incentives to encourage workers to acquire new AI-related skills, easier access to capital for aspiring entrepreneurs, and innovative approaches to employee ownership and profit-sharing schemes. However, these suggestions differ significantly from binding requirements that would legally mandate workers’ participation in AI-generated wealth or compel companies to bear the costs associated with displacing their workforce through automation.

Brennan further elaborated on her concerns, stating, "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. All of it is predicated on benefiting from AI’s upside." She argued that a more prudent approach would involve policies such as a revised corporate tax rate, tax incentives specifically designed to encourage the hiring of human beings rather than automating jobs, and measures to actively prevent companies from accumulating excessive market power.

Lehane’s overarching emphasis on expanding AI’s economic opportunities, rather than proactively mitigating its potential harms, also extends to his stance on data centers. While he acknowledges public concerns regarding these facilities, he concurrently highlights the significant construction jobs and local tax revenue they are capable of generating. He then issues a stern warning, cautioning that politicians who endorse a moratorium on data center construction could severely jeopardize America’s competitive lead over China in the AI race, going so far as to draw a controversial comparison between such a stance and the contentious 2002 vote to authorize the Iraq war.

Child safety and education are also central tenets of Lehane’s proposed agenda. He stresses the paramount importance of implementing age-appropriate protections and robust safeguards around AI companions designed for minors. Furthermore, he strongly cautions against excluding AI from educational institutions, arguing that such a move could exacerbate existing inequalities between students from affluent backgrounds and "children in rural communities." This argument, however, largely presumes that AI inherently improves learning outcomes, a claim that remains unsubstantiated and which critics contend warrants far more rigorous examination than simply allocating additional funding or diverting attention from individualized instruction by human teachers.

In the realm of AI safety, Lehane calls for the establishment of enforceable standards, independent evaluations, transparent public oversight, and the capability to restrict AI systems or activate a "kill switch" to shut them down if necessary. Yet, recent studies indicate that OpenAI and other leading AI laboratories have not yet published comprehensive plans detailing the protocols they would follow if an AI model were to escape human control.

Brennan characterized these safety stances as "disingenuous," citing OpenAI’s past track record of opposing legislation specifically designed to impose such measures. For example, in 2024, OpenAI publicly opposed California’s AI safety bill, SB 1047, which would have mandated catastrophic risk evaluations and the inclusion of shutdown capabilities in AI systems. The previous year, OpenAI also sought to limit state-level regulation, arguing that a patchwork of state laws could undermine American innovation. While the company has more recently adjusted some of these positions, expressing support for several state safety laws and indicating openness to embedding independent evaluators within the company, these shifts are viewed with skepticism by some critics.

Lehane further argues that human beings should maintain ultimate control over consequential decisions made with the assistance of AI, rather than entirely delegating judgment to machines. This raises a critical question: what constitutes genuine human control in a society where individuals are increasingly compelled to interact with and rely on AI across diverse sectors such as education, employment, healthcare, and government services?

Throughout his essay, Lehane consistently frames AI as a technology with the potential to restore Americans’ sense of agency and economic opportunity. However, he inextricably links the "middle class" success of average Americans to their active participation in an economy progressively shaped by influential companies like OpenAI. Whether his proposed policies will genuinely redistribute power and foster equitable growth or merely serve to subtly entrench existing power structures remains a subject of considerable debate.

TechCrunch attempted to reach out to OpenAI for more specific details regarding Lehane’s proposals and the company’s official stances on these matters, but did not receive a response by the time of publication.