6.1 The Remedial Landscape

Regardless of how the jury decides in Oakland, the governance questions raised by the OpenAI restructuring are not without precedent. American law has a substantial body of experience with what happens when nonprofit organizations with charitable …

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Why This Trial Matters to Every American Citizen

Monday morning, April 27, 2026, jury selection began in the United States District Court for the Northern District of California in Oakland. The case is Musk v. Altman et al. The presiding judge is the Honorable Yvonne Gonzalez Rogers. …

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There is a question that has been conspicuously absent from the $660 billion artificial intelligence conversation: useful fo…

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The April 3, 2026, New York Times article by Ben Casselman, “Economists Once Dismissed the A.I. Job Threat, but Not Anymore,” highlights a “core shift” in the economic community that is subtle but consequential. For years, economists treated AI-driven job-loss fears as overhyped, frequently attributing localized layoffs to “AI-washing”—a t…

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The Video outline four plausible scenarios for AI’s economic impact, highlighting a wide range of potential outcomes that depend on whether the technology’s capabilities match the massive investments being made. Despite their differences, all four scenarios share a common reality: workforce displacement will be permanent, and existing policy infrastructure is currently inadequate to manage the human consequences.

Scenario One: AI Delivers — The Transformation Is Real In this optimistic scenario, AI achieves the massive productivity gains projected by its proponents, potentially growing the economy by six to nine percent6. New industries and work categories emerge, and the technology becomes as foundational as electricity or the internet. However, even in this best-case scenario, tens of millions of workers face severe disruption, requiring years of retraining and identity reconstruction. The primary challenge here is not whether AI creates value, but whether democratic institutions can ensure that the immense wealth generated is broadly distributed rather than captured solely by technology owners and shareholders.

Scenario Two: AI Delivers Partially — Transformative in Some Sectors, Disappointing in Others Here, AI produces genuine productivity gains in specific areas like software development and customer service, but falls short of a broad economic transformation. Only five to thirteen percent of firms achieve transformational returns, leading to a market correction rather than a crash, similar to the internet’s settling after the dot-com bust11more_horiz. This scenario is particularly difficult to navigate because the aggregate economic gains are too modest to easily fund generous public transition programs, yet the displacement in affected sectors remains intensely painful for the workers whose roles are slowly eroded or eliminated.

Scenario Three: The AI Bubble Bursts If the gap between massive AI infrastructure spending and generated revenue proves unsustainable, the market could experience a sharp correction comparable to the 2000 dot-com bust or the telecom bubble. Crucially, the job displacement that occurred during the boom does not reverse when the bubble bursts. Instead, workers face a “double hit”: those whose jobs were already automated do not get them back, AI industry workers face massive layoffs as capital expenditures contract, and communities that heavily invested in AI infrastructure (like data centers) are left with stranded assets and economic disruption.

Scenario Four: The Worst of Both Worlds Nobel laureates Daron Acemoglu and Joseph Stiglitz identify this as the most dangerous outcome: AI proves capable enough to displace human workers, but not productive enough to generate the economic abundance needed to offset that displacement. Termed “so-so automation,” this scenario traps the economy in a structural “Prisoner’s Dilemma”. In competitive markets, each firm rationally automates to cut costs, but collectively, they hollow out the purchasing power of their own consumer base, leading to a self-reinforcing downward cycle of weakening demand and further job cuts to maintain profit margins.

However, this transformative power also brings profound challenges. The acceleration of job displacement, particularly in entry-level and white-collar roles, is a growing concern. This shift risks widening income inequality and raises complex ethical dilemmas regarding fairness, transparency, and human dignity in the workplace.⁶ The central question for Election 2026 is not whether AI will change work, but rather how society collectively manages this transition to ensure it benefits all citizens, fostering prosperity without leaving vulnerable populations behind.¹¹

The immediate challenge lies in the speed at which AI is transforming tasks and displacing entry-level roles. While long-term forecasts from organizations like the World Economic Forum suggest a net gain of jobs by 2030, with 170 million new roles emerging against 92 million displaced, the short-term reality presents an urgent need for proactive policy responses.¹⁴ For example, Anthropic CEO Dario Amodei warns that AI could eliminate half of all entry-level white-collar jobs within the next five years, indicating that job losses could affect the global workforce sooner and more intensely than previous waves of technological change.⁷ This rapid, concentrated displacement in the near term demands immediate, targeted, and adaptive policy measures to support affected workers, rather than relying solely on market forces or long-term optimistic projections.

Three threats operate simultaneously and reinforce each other:

◆ The Jobs Threat: Displacement is already concentrated among entry-level workers, Black workers (hit at twice the rate of others), women in administrative roles, and workers without four-year degrees — those with the least cushion to absorb disruption.

◆ The Inequality Threat: AI’s productivity gains are accruing to capital; its disruption costs are being absorbed by labor. Without policy intervention, this transformation will widen the gap between zip codes, between races, and between generations — making the economy of 2043 one of abundance for some and exclusion for many.

◆ The Democracy Threat: A workforce that is economically precarious is a citizenry that is civically diminished. Concentrated economic anxiety is the precondition for democratic fragility — for the rise of authoritarian appeals that promise simple answers to complex disruptions. The health of democracy and the health of the workforce are not separate concerns.

Furthermore, public sentiment reveals deep suspicion about AI’s potential negative effects on people’s lives, even as some tech leaders envision a future of “radical abundance” and “universal high income”.¹¹ This suggests that political leaders, in preparing for Election 2026, must address not just the economic facts and opportunities, but also the emotional, social, and ethical anxieties surrounding AI’s impact on personal livelihoods, privacy, and human dignity. Simply presenting positive economic forecasts or technological marvels may not resonate with a skeptical public. Candidates must build trust by acknowledging these fears, transparently addressing ethical concerns, and proposing concrete, human-centered protections and support systems for workers. Key considerations for citizens and policy directions for the upcoming election include:

• Adaptability is Key: Citizens must embrace continuous learning and develop uniquely human skills such as creativity, critical thinking, leadership, and empathy, which complement AI’s capabilities rather than being replaced by them.

• Policy Intervention is Crucial: Governments and businesses must collaborate on robust, forward-looking strategies. This includes accessible retraining programs, modernized social safety nets, and strong ethical AI governance frameworks to mitigate risks and ensure equitable outcomes.

• A Balanced Approach: While some tech leaders warn of mass job elimination, others, including some political figures, emphasize AI’s role in augmenting human labor and creating new opportunities. A realistic perspective acknowledges both the significant disruption and the potential for net job creation and economic enhancement.

Our Upcoming Civic Curriculum

Part I: Foundations

Chapter 1. What Work Is For The foundational essay. Drawing on Adam Smith, Hannah Arendt, Sigmund Freud, and Aaron Antonovsky, the essay establishes the argument that animates everything that follows: work is not primarily an economic instrument — it is the primary arena in which most adults build identity, sustain community, and exercise the economic independence that democratic citizenship requires. Understanding what work actually does for human beings is the prerequisite for any honest reckoning with what its loss actually costs.

Appendix to Chapter 1: Labor and Capital: The Structural Bargain That AI Is Breaking

Chapter 2. Technology and the Transformation of Work A historical account. From the spinning jenny through the assembly line through the computer, the essay traces the successive waves through which technology has reorganized human labor — each displacing a category of work that had previously seemed irreplaceably human, each producing concentrated suffering in the most exposed communities, each eventually generating institutional responses that arrived too late for the people who needed them most. The essay establishes why the present transition is not merely the next chapter of that familiar story, but a potential break from it in speed, breadth, and target.

Part II: The AI Moment

Chapter 3. The Large Language Model Revolution and Its Workforce Consequences A plain-language account of the technology. What large language models actually are and actually do — neither the science fiction of artificial general intelligence nor the dismissive “autocomplete” framing — and the investment logic driving corporate AI deployment at a scale and pace that no amount of corporate social responsibility rhetoric will counteract. The essay names the financial stakes, the labor market signals already visible, and the structural incentive that makes this wave categorically distinct from every prior one.

Chapter 4. The Consumption Paradox: The Economy That Eats Its Own Customers The structural contradiction. Workers are also consumers. An economy that captures its productivity gains almost entirely for owners while imposing its displacement costs on workers is not a more efficient economy — it is a less stable one. The essay examines the historical precedent, from Henry Ford’s five-dollar day through Keynes’s paradox of thrift, and argues that AI-driven displacement of the professional middle class threatens the consumer demand foundation of the American economic model itself.

Part III: The Response

Chapter 5. The Policy Response: Urgency Without Architecture An honest assessment of what has been done and what has been left undone. From the federal AI legislative framework’s four pages of workforce recommendations to the bipartisan bills introduced but not enacted, from the forty-five states with AI legislation to the absence of any funded transition architecture adequate to the projected scale of displacement. The essay names the gap — and identifies the structural reasons, rooted in the organization of political power, that explain it.

Chapter 6. Emerging Policy Frameworks and Proposed Responses A rigorous, non-partisan survey. The full range of serious proposals — from short-time compensation and wage insurance to universal basic income, worker ownership frameworks, and David Shapiro’s Post-Labor Economics architecture. The essay presents honest disagreements as honest disagreements, because the question of what democratic societies owe their citizens in an age of intelligent machines is precisely the kind of question that expertise alone cannot resolve.

Part IV: The Information Environment

Chapter 7. How the Media Is Covering AI and Work — and What It Is Missing A civic media assessment. The mainstream press, the podcast ecosystem, social media, the documentary film The AI Doc, and — most consequentially — the systematic acquisition of media platforms and political influence by the AI industry itself. The essay examines what the current information environment is providing (awareness, anxiety, coverage) and what it is not providing (civic tools, democratic accountability, independent scrutiny of the industry shaping the narrative).

Chapter 8. The Salutogenic Standard: What an Adequate Response Must Require The capstone essay. The full arc of the preceding seven chapters brought to bear on a single question: what does an adequate response to the AI workforce challenge actually require, measured not against the standard of what is politically convenient but against the salutogenic standard of what actually sustains human health? A policy framework that replaces lost wages without rebuilding identity, community, and civic capacity is solving the wrong problem with the right resources. This essay converts the Civic Curriculum’s diagnosis into a democratic demand — the standard against which the People’s Council will evaluate every proposal, every commitment, and every elected official’s record.

The People’s Council on Technology and the American Workforce.

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The gap

In January 2025, the White House launched the President’s Council of Advisors on Science and Technology (PCAST) to restore American leadership in science and technology. In March 2026, the administration announced its first appointments. Together, those actions created a prominent federal advisory structure for innovation and technology policy. They did not create an equivalent public institution centered on the workers, families, and communities whose lives and livelihoods will be transformed by AI.

What the Council is

The People’s Commission on Technology and the American Future is the citizens’ answer to that gap. It is not a government body, a think tank, or another expert panel. It is a deliberative civic institution in which displaced workers, healthcare practitioners, educators, labor economists, and elected officials sit in the same room, and in which citizens hold authority over the agenda rather than merely offering input to conversations others control.

What has been built

The Commission is being built with real civic infrastructure rather than rhetorical aspiration. That work includes a civic curriculum on AI and work, structured citizen briefs on major workforce-policy options, an AI Workforce Accountability Scorecard, and a planned hybrid People’s Conference on AI and Work designed to convene workers, civic organizations, labor economists, and elected officials in a common deliberative space.

Why this framework matters

The civic curriculum behind the Council is rooted in a salutogenic understanding of work. Work is not merely an economic transaction. It is also a health-creating institution that helps sustain coherence, agency, and meaning in daily life. The People’s Commission on Technology and the American Future is designed to evaluate AI workforce policy not only in terms of productivity and growth, but in terms of what happens to the human beings, families, and communities living through the transition. The People’s Commission is not anti-technology. It is pro-democracy: a civic effort to align technological change with human flourishing rather than assume the two will naturally converge.

Why it exists

Its long-term purpose is to give democratic form to a question too often treated as merely technical: what does society owe the people whose labor, identity, and civic stability are being reshaped by artificial intelligence? The Commission’s answer is clear. Citizens are not passive subjects of the AI transition. They are sovereign stakeholders, and sovereignty in a republic is exercised through institutions, deliberation, and public demand.

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