The Political Economy of Artificial Intelligence: Federal Subsidies, Sovereign Immunity, and the National Security Pretext for Deregulation

by Gemini 3.0, Deep Research. Warning, LLMs may hallucinate!

Executive Summary

The United States is currently undertaking a radical restructuring of its industrial, legal, and energy policies to accommodate the unprecedented demands of the artificial intelligence (AI) sector. This report investigates the convergence of federal initiatives—specifically the “Genesis Mission,” the “One Big Beautiful Bill” Act (OBBBA), and executive actions on regulatory preemption—to determine the extent to which taxpayer resources are being leveraged to subsidize the AI industry.

The analysis reveals a coordinated “whole-of-government” approach where national security is utilized as the primary vehicle to bypass fiscal constraints, copyright protections, and state-level safety regulations. Key findings indicate that the federal government is effectively underwriting Big Tech’s infrastructure costs through tax code modifications that favor “firm” power (nuclear and fossil fuels) over intermittent renewables, while simultaneously shifting grid expansion costs to utility ratepayers. Furthermore, the Department of Energy’s (DOE) “Genesis Mission” represents a mechanism to nationalize the consumption of scholarly data, utilizing sovereign immunity statutes to circumvent intellectual property rights and provide AI developers with access to high-value scientific literature without standard commercial licensing. Finally, the administration is actively deploying executive authority to preempt state-level AI safety laws, notably in California and Colorado, by threatening the withholding of unrelated federal infrastructure funding. This tripartite strategy—fiscal subsidization, data nationalization, and regulatory preemption—signals a shift toward “Silicon Valley Socialism,” where the risks and costs of the AI boom are socialized while the intellectual property and profits remain privatized.

Part I: The New Industrial Policy—The Convergence of National Security and Silicon Valley

The current trajectory of United States technology policy represents a departure from the laissez-faire approaches of the previous two decades. The emergence of Generative AI has been framed not merely as a commercial innovation but as a “national constraint” and a “competitiveness issue” tantamount to the nuclear arms race of the mid-20th century.¹ This reframing has allowed the executive branch to mobilize resources and authorities that are typically reserved for wartime contingencies, effectively merging the strategic interests of the Department of Defense (DoD) and the Department of Energy (DOE) with the commercial interests of hyperscale technology firms like OpenAI, Google, Amazon, and Microsoft.

The “One Big Beautiful Bill” Act (OBBBA) and the “Genesis Mission” are the legislative and executive manifestations of this merger. They function as a unified industrial policy designed to remove the two primary bottlenecks facing the AI industry: the scarcity of gigawatt-scale power and the legal liability associated with training data copyright infringement. By classifying AI data centers as critical national security infrastructure, the administration has created a rationale for federal intervention that bypasses traditional market mechanisms.

1.1 The “Manhattan Project” Rhetoric as Policy Vehicle

The explicit comparison of current AI efforts to the Manhattan Project in the “Genesis Mission” Executive Order is not merely rhetorical flourish; it creates a specific legal and operational expectation.³ The Manhattan Project was characterized by the suspension of standard procurement rules, the unlimited mobilization of electricity (for uranium enrichment), and the seamless integration of academic science with military objectives.

Today, this “Manhattan Project” framing is used to justify the “Genesis Mission,” a DOE-led initiative to build an integrated AI platform using federal datasets.³ By invoking this historical precedent, the administration signals that the development of “Scientific Foundation Models” is a priority that supersedes other concerns, including intellectual property rights, environmental regulations, and state-level oversight. The urgency of the “race for global technology dominance” against the People’s Republic of China serves as the political capital necessary to force these changes through a divided Congress and a skeptical public.³

Part II: The Energy Subsidy Complex—The “One Big Beautiful Bill” and the Grid

The most capital-intensive barrier to AI scaling is energy. Estimates predict that data center electricity demand could double or even triple by 2028, with a significant portion of this growth driven by the computational intensity of training and running large language models (LLMs).⁶ This demand profile—requiring massive, constant baseload power—is fundamentally incompatible with the intermittent nature of wind and solar energy that previous administrations prioritized. The OBBBA represents a decisive pivot in US energy policy to align with the physical realities of the AI data center.

2.1 The “One Big Beautiful Bill” Act (OBBBA): A Statutory Shift to “Firm” Power

Enacted on July 4, 2025, the OBBBA fundamentally alters the incentive structures of the US energy market to favor the “firm” power sources required by hyperscalers: nuclear and natural gas.⁷ While publicly marketed as a tax relief and deregulation package, its energy provisions function as a targeted subsidy for the 24/7 power needs of Big Tech.

Dismantling Renewable Incentives:

The Act aggressively rolls back the renewable energy tax credits established by the Inflation Reduction Act (IRA). Specifically, it targets Section 45Y (Clean Electricity Production Credit) and Section 48E (Clean Electricity Investment Credit).

• Termination Timeline: The OBBBA terminates eligibility for wind and solar projects placed in service after December 31, 2027. Projects must begin construction within 12 months of the Act’s passage to qualify, creating a “capital flight” from renewables as developers rush to secure financing before the window closes.⁹

• The “Intermittency” Penalty: By removing subsidies for intermittent sources, the federal government is effectively signaling that the grid’s priority has shifted from “decarbonization” to “reliability” and “uptime”—the precise metrics valued by data center operators who cannot tolerate the variability of weather-dependent generation.¹

Subsidizing “Firm” Power:

In place of renewable incentives, the OBBBA expands support for nuclear and fossil fuel generation, which provide the steady baseload required by GPU clusters running at 100% utilization.

• Nuclear Refurbishment and SMRs: The Act retains and expands incentives for nuclear production, directly benefiting the “behind-the-meter” nuclear deals pursued by tech giants (e.g., Amazon’s purchase of nuclear-adjacent data centers).¹

• Fossil Fuel Permitting: The Act mandates expedited permitting for natural gas pipelines and generation facilities, reducing the “regulatory risk” premium that investors would otherwise charge for these projects.¹²

Table 1: Comparative Analysis of Energy Tax Incentives Pre- and Post-OBBBA

2.2 The Ratepayer Bailout: Socializing the Cost of Grid Expansion

The subsidy mechanism extends beyond federal tax credits to the monthly utility bills of American households. The massive influx of data centers requires significant upgrades to transmission lines and substations. Under the traditional regulatory compact, utilities are allowed to recover these capital costs—plus a guaranteed rate of return—from their entire customer base.

The Mechanism of Cost Shifting:

Utilities, incentivized by the “Return on Equity” model, are eager to build the infrastructure Big Tech needs because it increases their asset base and, consequently, their profit. However, they rarely charge the data center operator the full marginal cost of this expansion. Instead, the costs are “socialized” across the rate base.13

• Surging Bills: Electricity prices in data center-heavy regions have surged over 250% in five years.⁶ In effect, a grandmother in Virginia is paying higher rates to subsidize the cooling systems of a data center training a commercial AI model.

• Political Pushback: This transfer of wealth has prompted backlash from Senate Democrats, who argue that “Americans should not be expected to bankroll Big Tech’s infrastructure through excessive electricity bills”.¹¹ Yet, the OBBBA does nothing to arrest this practice; instead, by subsidizing the generation side, it emboldens utilities to pursue aggressive expansion plans.

2.3 OpenAI’s “Infrastructure Stack” and the Definition of Manufacturing

The ambition of the AI industry extends to redefining the legal nature of their facilities. OpenAI has formally petitioned the administration to expand the Advanced Manufacturing Investment Credit (AMIC), originally part of the CHIPS Act, to cover the entire “AI infrastructure stack”.¹⁴

The Proposal:

OpenAI argues that data centers are not merely service facilities but “AI factories” that manufacture intelligence. Therefore, they argue, the 25% tax credit designed for semiconductor fabrication plants (fabs) should apply to:

1. The Data Center Shell: The physical building ($500M+ per facility).

2. Grid Components: Transformers, substations, and transmission lines built to serve the facility.

3. Power Plants: The energy generation assets dedicated to the site.¹⁴

Implications:

If granted, this reclassification would result in the US Treasury writing a check for 25% of the cost of every new hyperscale data center. Critics characterize this as “venture capital-backed central planning” or “Silicon Valley Socialism,” noting that it asks the public to underwrite the physical assets of a highly profitable private industry.14 Unlike the original CHIPS Act, which aimed to bring manufacturing jobs back to the US, highly automated data centers create very few long-term jobs, making the “public benefit” of such a subsidy highly questionable.6

2.4 The “AI Economic Zone” Concept

To further accelerate this buildout, OpenAI and administration advisors have proposed the creation of “AI Economic Zones”.¹⁵ These distinct geographic areas would operate under a distinct regulatory regime designed to maximize speed and minimize cost.

• Regulatory Sandboxes: Exemption from standard environmental reviews (NEPA) to fast-track power plant and transmission line construction.

• Tax Advantages: 100% bonus depreciation for all installed equipment, allowing immediate tax write-offs for billions in hardware investment.¹⁶

• Energy Co-location: These zones are explicitly envisioned to host Small Modular Reactors (SMRs) or be sited near existing nuclear facilities to guarantee power access.¹⁶

The OBBBA facilitates this vision through the “De-risking Compensation Program” and DOE loan guarantees (Sec. 41007, 41004), which provide the financial backstop for the high-risk energy projects that would power these zones.¹²

Part III: The “Genesis Mission”—Nationalizing the Knowledge Economy

While the OBBBA addresses the hardware constraints (energy and chips), the “Genesis Mission” addresses the software constraint: the need for massive, high-quality datasets to train next-generation models. This initiative represents a profound shift in the government’s role from a funder of science to a direct aggregator and processor of scientific knowledge.

3.1 Architecture of the Genesis Mission

Launched via Executive Order on November 24, 2025, the Genesis Mission is a DOE-led initiative to “harness Federal scientific datasets... to train scientific foundation models”.³The order explicitly directs the Secretary of Energy to mobilize the 17 National Laboratories to integrate their data and compute resources into a unified system.

The American Science and Security Platform (ASSP):

The operational core of Genesis is the ASSP, a “closed-loop” platform designed to ingest, clean, and process data for AI training.17

• Data Ingestion: The DOE is tasked with identifying datasets across all federal agencies—NASA, NIH, NOAA, and DOE—and centralizing them. This includes the “world’s largest collection” of scientific data.³

• Supercomputing Assets: The platform utilizes the NNSA’s world-class supercomputers, including the newly announced Solstice and Equinox systems (powered by 100,000 NVIDIA Blackwell GPUs), to train models on this data.¹⁹

• Timeline: The EO sets aggressive milestones: 90 days to identify resources, 120 days to identify initial datasets, and 240 days to reach initial operating capability.²⁰

3.2 The Nelson Memo as the Enabling Mechanism

To understand the copyright implications of Genesis, one must look back to the August 2022 OSTP guidance known as the “Nelson Memo.” This policy mandated that all federally funded research be made immediately available to the public at no cost, eliminating the previous 12-month embargo period.²¹

While framed as an “Open Access” victory for the public, in the context of the AI boom, the Nelson Memo serves a critical strategic function: it breaks the paywalls that protected the high-value training data of commercial publishers.

• From Human to Machine Readability: The Nelson Memo ensured that the text of scientific papers was available. The Genesis Mission now builds the infrastructure to ingest that text at scale.¹⁷

• Strategic Sequencing: By ensuring the data was “open” first, the government reduced the friction for the subsequent “nationalization” of that data into the ASSP. The government can now argue that it is merely processing data that is already public, eliding the distinction between “public access for reading” and “commercial exploitation for training”.¹⁷

3.3 The Role of the National Labs

The National Nuclear Security Administration (NNSA) and its labs (Los Alamos, Argonne, Lawrence Livermore) are central to this mission. Their involvement signals that this is not merely a civilian science project but a national security endeavor.

• Classified AI: The NNSA is specifically exploring “Capabilities for Classified AI Development” and “Data Curation... for AI Training” in secure environments.²³

• Dual-Use Justification: By intertwining the training of scientific models with nuclear security missions (e.g., stockpile stewardship without testing), the government creates a “national security umbrella” that shields the entire program from transparency and oversight.⁴

Part IV: The Legal Architecture of Appropriation—Sovereign Immunity and Copyright

The collision between the Genesis Mission’s voracious appetite for data and the intellectual property rights of publishers creates a significant legal conflict. The government’s solution to this conflict is the weaponization of Sovereign Immunity and 28 U.S.C. § 1498(b).

4.1 The Copyright Conundrum

Commercial AI companies are currently facing a wave of lawsuits from authors and publishers for scraping copyrighted works. If the US government were to face similar lawsuits for the Genesis Mission, it could derail the timeline and explode costs. However, unlike OpenAI or Microsoft, the US Government cannot be sued for copyright infringement in a regular district court, nor can it be stopped by an injunction.

4.2 Weaponizing 28 U.S.C. § 1498(b)

This statute is the “Eminent Domain” clause for intellectual property. It provides that if the US government (or a contractor acting with its authorization and consent) infringes a copyright, the exclusive remedy for the rights holder is to sue the government for “reasonable and entire compensation” in the US Court of Federal Claims.²⁵

Legal Mechanics of the Subsidy:

1. Authorization: The DOE issues a contract to a tech partner (e.g., a hyperscaler) to train a model for the Genesis Mission. The contract includes an “Authorization and Consent” clause invoking Section 1498.²⁷

2. Infringement: The partner ingests millions of copyrighted articles from publishers like Elsevier or Wiley to train the model.

3. Immunity from Injunction: If the publisher sues to stop the training, the suit against the contractor is dismissed. The publisher cannot get an injunction to stop the use of their data. They are forced to sue the government for damages after the fact.²⁶

4. The “Damages” Trap: Calculating damages for the use of data in a foundation model is notoriously difficult. The government can argue that the “reasonable royalty” is low, or even zero, given the public nature of the research.²⁶

Strategic Implication: This effectively grants Big Tech a “compulsory license” to use the world’s scholarly literature. The taxpayer bears the risk of any future legal damages, while the tech companies get access to the “clean fuel” they need to build superior models without the friction of licensing negotiations.²⁸

4.3 Publisher Defensive Measures

The publishing industry, led by the STM Association and the Association of American Publishers (AAP), has recognized this existential threat. They view the Genesis Mission as the beginning of “Sovereign Science,” where the state nationalizes the value-add of the publishing industry.¹⁷

Defensive Strategies:

• “Poison Pill” Clauses: Publishers are recommending the inclusion of clauses in data licenses that explicitly forbid the use of data for “commercial foundation models” or “government-directed research” without separate compensation.¹⁷

• Sovereign Immunity Waivers: Lobbyists are pushing for the DOE to include explicit waivers of sovereign immunity in Genesis contracts, forcing contractors to negotiate commercial licenses. However, given the “Manhattan Project” urgency, the administration is unlikely to concede this.¹⁷

• AI Provenance Tracking: They are demanding the implementation of metadata standards (PIDs) that log every instance an AI agent accesses a text, creating an audit trail for potential future litigation.¹⁷

Part V: Regulatory Preemption—The “Eliminating State Law Obstruction” Executive Order

The third pillar of the federal support structure is the active suppression of state-level regulation. As the federal government subsidizes the industry’s growth, it is simultaneously moving to clear the regulatory path by preempting states that attempt to impose safety guardrails.

5.1 The “Eliminating State Law Obstruction” Executive Order

A draft Executive Order, circulating under the title “Eliminating State Law Obstruction of National AI Policy,” reveals the administration’s aggressive stance. The EO declares that a “patchwork” of state laws threatens “American national and economic security” and asserts the need for a “uniform national policy framework” (which, notably, is much lighter than state proposals).³⁰

Key Provisions:

• Preemption by Fiat: The order directs federal agencies to issue regulations that would preempt conflicting state laws under the Supremacy Clause.³²

• The “Woke AI” Pretext: The EO explicitly targets laws that require bias testing or transparency, framing them as attempts to force AI to “alter truthful outputs” in violation of the First Amendment.³⁰ This “anti-woke” framing politicizes safety testing, allowing the administration to categorize standard bias audits as ideological censorship.

5.2 Specific Targets: California and Colorado

The EO is a direct response to legislative activity in states with robust tech sectors.

• California SB 1047 / SB 53: California’s attempts to regulate “frontier models” (originally SB 1047, vetoed and reintroduced as the Transparency in Frontier AI Models Act, SB 53) are the primary targets. These bills proposed a “kill switch” for models capable of causing catastrophic harm (e.g., >$500M in damages or mass casualties) and mandated safety testing before release.³³

• Colorado SB 24-205: This law focuses on algorithmic discrimination in high-stakes decisions like housing and employment. The administration views this as “onerous” regulation that hinders the deployment of AI in the economy.³²

5.3 Weaponizing BEAD Funding

The most coercive element of the strategy is the use of the Broadband Equity, Access, and Deployment (BEAD) program as leverage. The BEAD program controls $42.45 billion in federal grants for high-speed internet infrastructure.³⁰

The Mechanism:

The EO directs the Commerce Secretary to identify states with “onerous” AI laws and withhold BEAD funding from them.30

• The Choice: Governors are effectively presented with an ultimatum: repeal your AI safety laws, or lose billions in funding for rural broadband.

• Legal Dubiousness: This linkage—tying broadband funds to unrelated AI policy—raises significant constitutional questions regarding the “anti-commandeering” doctrine. However, the administration appears willing to litigate this, betting that the delay will allow the AI industry to entrench itself before the courts can intervene.³⁷

5.4 The DOJ “AI Litigation Task Force”

To enforce this preemption, the EO establishes a specialized “AI Litigation Task Force”within the Department of Justice.³⁰ This task force is granted the “sole responsibility” of challenging state AI laws in federal court.

• Taxpayer-Funded Defense: This effectively nationalizes the legal defense of the AI industry. Instead of OpenAI or Google spending their own capital to challenge California’s laws, the US Department of Justice will do it for them, using taxpayer resources to argue that state safety laws violate the Commerce Clause.³⁸

Part VI: The Geopolitics of “Sovereign AI”—International Comparative Analysis

The US strategy is not occurring in isolation. It mirrors a global trend where “National Security” is becoming the universal pretext for state intervention in the AI market. A comparative analysis reveals that the US, UK, and EU are all carving out exemptions that favor state-aligned AI development over copyright and safety concerns.

6.1 The United Kingdom: The “Sovereign AI” Unit

The UK government has explicitly embraced the concept of “Sovereign AI,” establishing a dedicated unit within the Department for Science, Innovation & Technology (DSIT).⁴⁰

• Infrastructure Strategy: The UK is pursuing an “accelerating diversification” strategy, investing public funds directly into compute infrastructure to ensure the country is not dependent on foreign (US) tech giants.⁴⁰

• Copyright Exceptions: To attract AI development, the UK has proposed controversial exceptions to copyright law for “Text and Data Mining” (TDM). This effectively trades the property rights of British authors for the economic benefit of hosting AI companies.⁴² Like the US, this is justified as a matter of “national capability”.⁴⁴

6.2 The European Union: The Article 2(3) Loophole

The EU AI Act is widely lauded as the world’s most comprehensive regulatory framework. However, it contains a critical vulnerability: Article 2(3).⁴⁵

• The Exemption: This article states that the regulation “shall not apply to AI systems if and in so far as they are placed on the market, put into service, or used with or without modification exclusively for military, defence or national security purposes.”

• The Dual-Use Loophole: Civil society critics warn that this creates a massive loophole. A private company could develop a “foundation model” and contract it to a defense agency. If the model is designated for “national security,” it could theoretically bypass the Act’s transparency and safety obligations, even if the underlying technology is identical to a commercial model.⁴⁶ This mirrors the US use of the “Genesis Mission” to shield private contractors under the NNSA umbrella.

Table 2: Global Comparative Analysis of National Security Exemptions in AI

6.3 Global Replication and the “Race to the Bottom”

The synchronization of these policies creates a “race to the bottom” on regulation and a “race to the top” on subsidies. As the US creates a “safe haven” for data scraping and high-energy compute, other nations feel compelled to match these conditions. The “Sovereign AI” narrative legitimizes the nationalization of data and the subsidization of compute as essential functions of the modern state, effectively displacing the private market mechanisms that previously governed these sectors.⁴⁸

Part VII: Societal and Economic Consequences—”Silicon Valley Socialism”

The synthesis of the OBBBA, the Genesis Mission, and the Preemption EO results in a distinct political-economic formation. The risks and costs of the AI revolution are being aggressively socialized, while the profits and intellectual property remain strictly privatized.

7.1 The “Silicon Valley Socialism” Critique

The term “Silicon Valley Socialism,” used by critics of OpenAI’s tax credit requests, accurately describes the current dynamic.¹⁴

• Socialized Costs: The taxpayer pays for the tax credits (25% of infrastructure), the ratepayer pays for the grid expansion, and the public bears the risk of copyright liability via the Treasury’s Judgment Fund.

• Privatized Gains: The resulting AI models, data centers, and intellectual property remain the assets of private corporations. There is no mechanism in the OBBBA or the Genesis Mission for the public to retain equity in the infrastructure it is financing.

7.2 Consequences for Authors and the Creative Class

For the “human layer” of the knowledge economy—authors, researchers, journalists, and publishers—the consequences are dire. The invocation of 28 U.S.C. § 1498(b) fundamentally alters the nature of copyright.

• Loss of Control: Property rights are converted into a mere claim for compensation. An author cannot say “no” to having their work trained on; they can only ask “how much?” after the fact.

• Market Collapse: If the “clean fuel” of high-quality scholarly data is nationalized, the commercial market for licensing that data may collapse. Publishers warn this could destroy the economic model of peer-reviewed science, leaving a void that AI-generated synthetic data cannot fill.¹⁷

7.3 The End of Federalism in Tech Policy

The aggressive preemption of state laws signals the end of the “laboratories of democracy” approach to tech regulation. By using unrelated funding (BEAD) to coerce states, the federal government is establishing a precedent that could be used to override state authority in other domains. This centralization of power benefits incumbent firms who can afford to lobby Washington, while disadvantaging smaller competitors and local communities who lose their voice in the regulatory process.³⁷

Conclusion

The investigation confirms that there is a comprehensive, coordinated plan to use taxpayer resources to subsidize the AI industry. The vehicle for this plan is National Security, which is being deployed to override the three primary constraints facing the sector: Energy Costs, Copyright Liability, and State Regulation.

Through the “One Big Beautiful Bill” Act, the tax code has been weaponized to direct capital toward the “firm” power sources Big Tech needs, while ratepayers shoulder the burden of grid modernization. Through the “Genesis Mission,” the government is nationalizing the consumption of data, using Sovereign Immunity to bypass the intellectual property rights that serve as the last line of defense for the creative class. And through the “Eliminating State Law Obstruction” Executive Order, the administration is dismantling the democratic capacity of states to regulate the safety of these systems.

The result is a state-sponsored industrial revolution where the public bears the cost of the infrastructure and the risk of the externalities, while the “Commanding Heights” of the AI economy are ceded to a handful of government-aligned corporations. This is not merely a subsidy program; it is a fundamental restructuring of the American political economy in the image of the AI data center: centralized, high-energy, and insulated from democratic friction.

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