El-Sayed Wants to Take Bernie’s Socialism Even Further

August 20, 2026

Abdul El-Sayed did not just echo Bernie Sanders’s call for public stakes in frontier AI firms; he staked out a position to go further, coupling public ownership with public control of how these systems are governed, arguing that a technology built from society’s data and infrastructure should be accountable to the public interest—not only to shareholders.

At a Glance

El-Sayed’s platform backs public ownership and democratic governance of major AI companies, positioning his plan as a step beyond Sanders’s proposal.
He has described a model with 50% public ownership and at least half of board seats democratically chosen, tying governance to safety oversight.
Campaign materials and public remarks frame AI as an existential-risk domain that warrants public-benefit obligations and stronger public power.
The proposal sits within a broader policy debate over whether frontier AI should be regulated as a utility, owned in part by the public, or left to conventional corporate control.

What El-Sayed Proposed, Plainly

Across campaign releases, interviews, and a full debate transcript, El-Sayed has argued for a package that links ownership and governance. His AI Under Democracy platform says the aim is to “bring the emerging technology into the hands of the people through democratic ownership and governance.” That phrase is not rhetorical garnish; it animates the structure he describes elsewhere: building on Sanders’s public equity concept, El-Sayed calls for 50% public ownership and at least half of board seats to be democratically selected, combining an economic stake with decision-rights inside the firm’s highest body. He has cast this as a safety-and-accountability intervention, not merely redistributionist symbolism, invoking AI’s “existential risk” as justification for public-benefit obligations and constraints on billionaire control.

Contemporaneous coverage across ideologically varied outlets converged on the same essentials. The New Republic summarized three planks—democratic governance, public ownership, and safety requirements—and characterized his plan as going beyond Sanders’s by adding governance mechanisms. Broadcast and local reporting likewise described his advocacy for public ownership or public stakes in frontier AI firms. El-Sayed’s own social posts reinforced the underlying theory of the case: AI was built from societal inputs and should therefore answer to society, with people having “clarity, control, and a say” over its direction.

Mechanism: Ownership, Control, and Safety in One Architecture

Ownership alone does not guarantee control, and control alone—via regulation—does not grant the public a financial claim on the upside. El-Sayed’s model attempts to weld both. First, a public equity stake aligns the financial windfall from AI with broad social benefit. Second, democratic board representation inserts public voice into corporate governance, where strategy, model release policies, and risk tolerances are actually set. Third, public-benefit corporation structures and safety guardrails aim to codify duties to non-shareholder stakeholders—the public that supplies data, grid capacity, and the civic stability within which these firms operate. In practice, these levers would interact: ownership creates leverage, seats create voice, and charter duties constrain the risk frontier a firm can legally traverse.

The Sanders baseline matters here. In his New York Times op-ed and subsequent bill framing, Sanders argued for a one-time 50% stock transfer into a sovereign wealth fund—public equity paid via a tax in kind—giving the public a durable claim on returns from the largest AI companies. El-Sayed’s step “beyond” is adding structured governance power rather than relying solely on the fund’s shareholder rights, which can be diluted or sidelined without formal board representation. In short: Sanders emphasizes public ownership; El-Sayed layers on public control.

How We Got Here: The Policy Lineage Behind “Public Ownership” in Tech

Proposals to socialize elements of strategic industries are not novel; what’s new is the specific coupling of public equity with board-level governance for computational platforms that may function like infrastructure. In the growing AI policy literature, options range from sovereign wealth funds holding golden shares, to public-utility regulation that imposes common-carriage and rate-setting analogs, to antitrust remedies that attack winner-take-most dynamics. Each tool changes who captures rents and who sets rules—and each carries distinct legal mechanics. El-Sayed’s plan borrows from multiple traditions: the sovereign-wealth approach for ownership, public-benefit charters for fiduciary reorientation, and utility-flavored safety requirements for operational constraints.

The bipartisan context is also real. In this policy window, Sanders and President Trump have both supported some form of public stake in top AI companies—albeit from very different ideological priors—on the theory that taxpayers should share the upside from a general-purpose technology that depends on public infrastructure and state-enabled research. That bipartisan echo has made the ownership idea harder to dismiss as a fringe flourish and easier to frame as a contested but mainstream policy option in the AI governance toolkit.

Where the Details Are Firm—and Where They Are Still Plastic

On the record, several anchors are firm. First, El-Sayed has said he wants to “go a step further” than Sanders, endorsing public ownership plus public control. Second, his platform declares democratic ownership and governance as ends. Third, he has specified a 50% ownership stake and at least 50% democratically selected board representation as a target design, bundled with a safety rationale. Those claims are supported by a campaign release and a full debate transcript, and they are reflected in a range of reporting. The through-line is consistent: public stakes and public voice in frontier AI.

Ambiguity remains at the engineering level of policy. “Public ownership” can mean many things—direct federal shares, a sovereign wealth fund, hybrid trusts at the state level, or mandated stock grants—and “democratic board selection” could be implemented via worker councils, citizen assemblies, or delegated public trustees. Reporting sometimes toggles among “ownership,” “control,” and “governance,” which blurs precision on enforcement, compensation, and constitutional posture. Those are implementational questions a legislative draft or model bill would ultimately have to specify; the public record to date is programmatic rather than statutory.

Why This Matters: Power, Risk, and the Allocation of AI’s Gains

AI’s general-purpose character means that whoever governs its deployment—profit-maximizing corporate boards alone, or boards infused with public trusteeship—will shape labor markets, national security posture, information ecosystems, and the distribution of wealth created by automation and new capabilities. El-Sayed’s bet is straightforward: when a technology can concentrate power quickly and externalize catastrophic downside risk, diffuse public authority must move upstream from after-the-fact regulation to ownership and control inside the firm itself. His rhetoric about existential risk ties that governance philosophy to the safety agenda—embedding risk management not as a compliance box but as a board-level duty anchored by the public stake.

The countervailing school argues that utility-style oversight or antitrust—without forced equity transfer—can achieve many of the same ends with less disruption to corporate governance and fewer constitutional collisions. But that is a different model of leverage. Utility regulation sets obligations from outside the corporate boundary; ownership and board representation operate from within it. El-Sayed’s contribution to the debate is to argue that the inside-out toolset is not an optional add-on—it is the point.

Abdul El-Sayed wants government ownership and control of artificial intelligence.

His own campaign says he wants to go further than Bernie Sanders’ proposal to force the largest AI companies to surrender 50% equity to a federal sovereign wealth fund. El-Sayed proposes public… pic.twitter.com/cZLh74tsa7

— Dan Holbrook (@DanHolbrook) August 16, 2026

The Broader Policy Landscape From Here

Expect “public ownership of AI” to remain a contested label because it compresses a family of mechanisms into a single phrase. In practice, future proposals will likely mix instruments: public equity stakes to align incentives, governance rights to steer strategy, public-benefit charters to hardwire duties, utility rules to guarantee access and resilience, and antitrust to prevent moat-building. The real design question is sequencing and scope: which firms, which thresholds, and which enforcement forum. El-Sayed has planted a flag on the ownership-and-control side of that spectrum—and he is not alone in arguing that a general-purpose technology with system-level risks requires system-level public power.