The United States: The High-Variance Bet

📊 Full opportunity report: The United States: The High-Variance Bet on ThorstenMeyerAI.com — validation score, market gap, and execution plan.

TL;DR

The US is taking a hands-off stance on AI regulation, emphasizing market-driven growth and local social programs. This high-variance approach contrasts with European models and shapes global AI development. Uncertainty remains about the long-term impacts.

The United States is implementing a highly deregulated approach to artificial intelligence, actively challenging state-level AI laws and minimizing federal oversight. This strategy aims to foster innovation and economic growth, making it a significant shift in the country’s policy stance and influencing global AI development.

Since January 2025, the US administration has revoked previous AI oversight policies, replacing them with a focus on ‘Removing Barriers to American Leadership in Artificial Intelligence.’ By mid-2025, the White House introduced an ‘AI Action Plan’ emphasizing minimal regulation to maintain technological dominance. In December 2025, executive orders set up a Department of Justice task force to challenge state AI laws deemed burdensome, and by March 2026, the White House sought congressional authority to preempt state regulations altogether. This approach contrasts sharply with European models, which tend to impose heavier AI regulations.

Meanwhile, the federal social safety net remains minimal, with programs like the Earned Income Tax Credit (EITC) providing limited support only to working families with children. Local governments have stepped in, running over 150 guaranteed-income pilots and experiments, but these are fragmented and rely heavily on philanthropy and city budgets rather than federal programs. This creates a patchwork system that reflects a bottom-up response to the social impacts of AI and economic change, rather than a coordinated national strategy.

The United States: The High-Variance Bet · Post-Labor Atlas Phase 2 · Day 6/12
Post-Labor Atlas · Phase 2 · Day 6 / 12 ThorstenMeyerAI.com · The Response
The Response · Day 6 · United States

The High-Variance Bet

The country building the disruption made the most distinctive choice of all: bet on the dynamism, regulate it least — even block others from regulating it — and tie the floor to work. The thinnest row on the map.

01 Signature — a federal void, filled from below
▲ Federal — clear the path
Revoked prior AI oversight EO (Jan 2025) “AI dominance” Action Plan (Jul 2025) DOJ task force vs state AI laws (Jan 2026) push to preempt state rules floor tied to work (EITC)
↕   the federal void   ↕
▲ Local — fill the void
150+ city guaranteed-income pilots Stockton SEED · $500/mo Cook County · $500/mo made permanent (2026) philanthropic + city-budget no federal scale
The response is underway — bottom-up and patchy — while the center deregulates and moves to block the states.
02 The US five-lever profile — the sparest on the map
Income floor
minimal
EITC is real but entirely work-gated — near-zero for childless adults. No UBI; guaranteed income only in local pilots.
Capital & ownership
minimal
No state fund or dividend — the bet is private markets (401ks, retail) + nascent “Trump accounts”; equity ownership is concentrated.
Work & time
minimal
The most flexible labour market in the rich world — at-will, no job guarantee, no short-time-work scheme.
Skills & transition
partial
Community colleges + federal workforce programs — fragmented and modestly funded.
Institutions
minimal
Actively deregulatory — moving to preempt even state AI laws. The most market-led stance on the map.
03 The wager, in numbers
~$660 vs $8,231
EITC max for a childless worker vs a worker with 3+ kids (2026) — the floor is generous for working families, near-zero for childless adults.
150+ cities
running guaranteed-income pilots (Cook County made $500/mo permanent, 2026) — the floor improvised locally, no federal program.
preempt the states
a DOJ AI Litigation Task Force (2026) + a push to bar state AI laws — Washington isn’t light-touch; it’s moving to prevent regulation.
Sources: IRS / Center on Budget & Policy Priorities & Tax Policy Center (EITC); Mayors for a Guaranteed Income, Cook County (pilots); White House EOs & National Policy Framework (federal AI posture) · figures indicative, mid-2026.
04 The Response Matrix — row 5 of 10
Jurisdiction
Income floor
Capital
Work & time
Skills
Institutions
European Union
strong*
minimal
strong
strong
strong
The Nordics
strong
partial
partial
strong
strong
United Kingdom
partial
minimal
partial
partial
partial
Canada
partial
minimal
partial
partial
minimal
United States
minimal
minimal
minimal
partial
minimal
The Gulf
·
·
·
·
·
Singapore
·
·
·
·
·
China
·
·
·
·
·
India
·
·
·
·
·
Brazil
·
·
·
·
·
solid = pulled hard · outline = partial · grey = barely used · the market-led pole: minimal almost everywhere — bet on the engine, not the airbag. Highest upside, thinnest backstop.

Independent commentary, produced with AI assistance under human editorial oversight. The views are the author’s own and may change. This is analysis, not policy, economic, investment, or legal advice. Descriptions of US federal AI executive actions, the EITC, “Trump accounts,” and municipal guaranteed-income pilots reflect publicly reported information as of mid-2026 and may change as litigation and legislation evolve. This phase maps differing approaches and endorses none; characterizations of contested policies present competing views, not a verdict, and references to specific administrations and programs are factual and analytical, not partisan. Country and program names are referenced for analysis and imply no affiliation.

ThorstenMeyerAI.com · Post-Labor Transition Atlas · Phase 2 · Day 6 of 12 · © 2026 Thorsten Meyer

Implications of America’s Deregulated AI and Social Policies

This approach signifies a fundamental shift in how the US balances innovation, regulation, and social support. By prioritizing market freedom and local initiatives, the US aims to maintain its global leadership in AI, but it risks creating a fragmented regulatory environment and widening social inequalities. The minimal federal safety net and reliance on city-led experiments could lead to uneven social outcomes, raising questions about long-term stability and fairness. Globally, this strategy influences other nations, especially those considering lighter regulation, and shapes the future landscape of AI development and social policy.

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US Policy Shift and Global AI Leadership

Historically, the US has favored market-driven innovation, with substantial private investment fueling AI development. Since early 2025, the federal government has shifted away from regulation, emphasizing competitiveness over oversight. This contrasts with European and Nordic countries, which tend to impose stricter AI rules and social safety nets. The US’s approach reflects a belief that deregulation will accelerate economic growth and technological progress, building on two centuries of technological change that have historically created more opportunities than they have destroyed. Meanwhile, local governments are experimenting with guaranteed income and social programs, attempting to fill the void left by federal minimalism.

“Our goal is to maintain American leadership by removing unnecessary barriers and trusting the innovation engine.”

— White House spokesperson

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Long-Term Effects of Deregulation and Fragmented Support

It remains unclear how sustainable this deregulated, high-variance approach will be in the long term. Questions persist about whether the US can sustain its global AI leadership without stronger federal regulation and social safety nets. The potential for social inequality and regional disparities due to uneven local initiatives is also uncertain, as is the impact on innovation stability and public trust.

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Future Developments in US AI Policy and Social Programs

Expect ongoing federal efforts to preempt state AI laws and possibly introduce new legislation to formalize this deregulatory stance. Meanwhile, local governments will continue expanding guaranteed-income pilots and social experiments, potentially influencing national policy debates. Monitoring how these initiatives evolve and their impact on social equity and technological leadership will be critical in the coming months.

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Key Questions

Why is the US avoiding federal regulation of AI?

The US believes that minimal regulation will foster innovation, maintain competitiveness, and prevent slowing the growth engine that has historically created wealth and opportunities.

How are social safety nets being addressed?

The federal safety net remains minimal, with programs like the EITC limited to working families with children. Local governments are experimenting with guaranteed income pilots to fill this gap.

What are the risks of this high-variance approach?

Potential risks include increased social inequality, regional disparities, regulatory fragmentation, and uncertainty about long-term economic stability and innovation sustainability.

How does this US approach compare to Europe?

European countries tend to impose stricter AI regulations and maintain more comprehensive social safety nets, contrasting with the US’s deregulatory and market-driven strategy.

What is the likely next step in US AI regulation?

The federal government is expected to continue efforts to preempt state laws and possibly introduce new legislation aimed at formalizing its deregulatory stance and maintaining global competitiveness.

Source: ThorstenMeyerAI.com

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