The “common sense” around artificial intelligence has become potent over the past two years, imbuing the technology with a sense of agency and momentum that make the current trajectory of AI appear inevitable, and certainly essential for economic prosperity and global dominance for the US. In this section, we break down the narratives propping up this “inevitability,” explaining why it is particularly challenging—but still necessary—to contest the current trajectory of AI, especially at this moment in global history.
The AI industry’s growth model, fueled by the assertion that infinitely increasing scale leads to superior products, has spawned AI firms that are positioned to be too big to fail. Americans are actively subsidizing this unstable system under the premise that the adoption of AI is a “national strategic priority.” As we illustrate in this chapter and in Chapter 1.4, though, this has enabled an industrial-policy approach that will ultimately undermine, rather than strengthen, our national security. Finally, we discuss how the abundance agenda, with its seemingly benign focus on what it calls “supply-side progressivism,” is a very convenient tool for big AI to justify expanding its energy needs.
Tech firms are deploying unprecedented amounts of capital to maintain their lead and advance in the current paradigm of “scale is all you need” AI, doubling down on infrastructure build-out and seeking federal funding and regulatory support across several dimensions: access to chips and associated hardware to equip data centers, approvals for the construction of the data centers themselves, and the energy necessary to power them. The stock market is riding this hype wave, and the “Magnificent Seven” stocks (Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla) now represent more than 30 percent of the S&P 500, the largest sector of the index—in prominent part because of the AI boom.1Jeran Wittenstein and Tom Contiliano, “Nvidia and Five Tech Giants Now Command 30% of the S&P 500 Index,” (<)em(>)Bloomberg(<)/em(>), May 30, 2024, (<)a href='https://www.bloomberg.com/news/articles/2024-05-30/nvidia-and-five-tech-giants-now-command-30-of-the-s-p-500-index'(>)https://www.bloomberg.com/news/articles/2024-05-30/nvidia-and-five-tech-giants-now-command-30-of-the-s-p-500-index(<)/a(>); Stephanie Stacey and George Steer, “Wall Street’s Magnificent Seven Lose Their Shine,” (<)em(>)Financial Times(<)/em(>), February 15, 2025, (<)a href='https://www.ft.com/content/fa5d3b2d-b3b3-4bb4-a5a4-765b7560e02c'(>)https://www.ft.com/content/fa5d3b2d-b3b3-4bb4-a5a4-765b7560e02c(<)/a(>).
It’s important to remember that the pursuit of scale was a choice that locked us into a future where a handful of Big Tech firms retained control of the market (see the Introduction). This is not the only way for AI to develop, nor is advancement measured on a narrow set of self-serving benchmarks2Shivalika Singh et al., “The Leaderboard Illusion,” arXiv, April 29, 2025, (<)a href='https://arxiv.org/abs/2504.20879'(>)https://arxiv.org/abs/2504.20879(<)/a(>). a meaningful proxy for evaluating the societal utility of these systems.3And, as recent model releases have shown, the pace of scale-based advancement may be slowing. See, e.g., Maxwell Zeff, “Current AI Scaling Laws Are Showing Diminishing Returns, Forcing AI Labs to Change Course,” (<)em(>)TechCrunch(<)/em(>), November 20, 2024, (<)a href='https://techcrunch.com/2024/11/20/ai-scaling-laws-are-showing-diminishing-returns-forcing-ai-labs-to-change-course'(>)https://techcrunch.com/2024/11/20/ai-scaling-laws-are-showing-diminishing-returns-forcing-ai-labs-to-change-course(<)/a(>). But because it is what these key market players have doubled down on, and because of their centrality to market indices, the success or failure of the AI bubble will now have a profound effect on the stock market as a whole.4See generally Bryan McMahon, “Bubble Trouble,” (<)em(>)American Prospect(<)/em(>), March 25, 2025, (<)a href='https://prospect.org/power/2025-03-25-bubble-trouble-ai-threat'(>)https://prospect.org/power/2025-03-25-bubble-trouble-ai-threat(<)/a(>).
This raises the stakes around the push for public investment in AI infrastructure—a move that is at best a hedge, and at worst a subsidy, for the profoundly risky and self-interested set of bets by AI firms. If successful, this effort will lock in infrastructures that the public will pay dividends on for years to come, in the form of financial and material costs (see Chapter 2: Heads I Win, Tails You Lose), creating a path dependency toward continued dominance by large AI firms.
Tech’s Capex Frenzy
Firms like Microsoft, Google, and Meta need AI to be profitable because they have funded the AI boom—at many orders of magnitude more than traditional venture capital5George Hammond, “Big Tech Outspends Venture Capital Firms in AI Investment Frenzy,” (<)em(>)Financial Times(<)/em(>), December 27, 2023, (<)a href='https://www.ft.com/content/c6b47d24-b435-4f41-b197-2d826cce9532'(>)https://www.ft.com/content/c6b47d24-b435-4f41-b197-2d826cce9532(<)/a(>).—boosting the valuations of startups that are far from demonstrating the kind of profitability that traditional investors would seek. They have gone all in on the most capital- and resource-intensive version of AI by adopting the “scale is all you need” paradigm as canon. This is not the only way to approach building AI models, and the companies leading AI development have occasionally gestured toward the need for model efficiency to address compute infrastructure bottlenecks. This was brought home especially by the release of DeepSeek’s R1, which demonstrated model capabilities on par with the leading-edge models of US firms, without anything like the scale US firms rely on.6See Stan Choe, “Tech Stocks Tank as a Chinese Competitor Threatens to Upend the AI Frenzy; Nvidia Sinks Nearly 17%,” Associated Press, January 27, 2025, (<)a href='https://apnews.com/article/stocks-markets-tariffs-trump-rates-52c54e361616509280bd2775674b6b4b'(>)https://apnews.com/article/stocks-markets-tariffs-trump-rates-52c54e361616509280bd2775674b6b4b(<)/a(>); and Natasha Solo-Lyons, “Nvidia Loses $589 Billion as DeepSeek Batters Stock,” Bloomberg, January 27, 2025, (<)a href='https://www.bloomberg.com/news/newsletters/2025-01-27/nvidia-loses-589-billion-as-deepseek-batters-stock-evening-briefing-americas'(>)https://www.bloomberg.com/news/newsletters/2025-01-27/nvidia-loses-589-billion-as-deepseek-batters-stock-evening-briefing-americas(<)/a(>).
But rather than make concerted efforts to build models differently, many dominant firms are doubling down on this approach by seeking public investment and the rollback of regulation to de-risk the expansion of the AI market. For example, within weeks of the DeepSeek announcement, OpenAI announced its Stargate investment with SoftBank, which will allocate a $100 billion investment into data center infrastructures for model training.7“Announcing the Stargate Project,” (<)em(>)OpenAI(<)/em(>), January 21, 2025, (<)a href='https://openai.com/index/announcing-the-stargate-project/'(>)https://openai.com/index/announcing-the-stargate-project/(<)/a(>).
Getting High on AI Supply
The US has adopted a position over the past two years that treats AI as an exceptional sector core to the nation’s economic and national security interests. This stance exists in tension with growing friction with Big Tech firms, most clearly articulated in the Biden administration’s Executive Order on Competition, which articulated the perpetuation of national monopolies as antithetical to the national interest.8“Executive Order 14036 of July 9, 2021, Promoting Competition in the American Economy,” Code of Federal Regulations, title 86 (2021): 36987-36999, (<)a href='https://www.federalregister.gov/documents/2021/07/14/2021-15069/promoting-competition-in-the-american-economy'(>)https://www.federalregister.gov/documents/2021/07/14/2021-15069/promoting-competition-in-the-american-economy(<)/a(>). The Trump administration has likewise bought into AI boosterism even as it has gestured toward the need for antitrust, mostly as a political tool for addressing firms it sees as adversarial to its interests.9JD Vance, “Remarks by the Vice President at the Artificial Intelligence Action Summit in Paris, France,” (speech, Paris, France, February 11, 2025) (<)em(>)American Presidency Project(<)/em(>), (<)a href='https://www.presidency.ucsb.edu/documents/remarks-the-vice-president-the-artificial-intelligence-action-summit-paris-france'(>)https://www.presidency.ucsb.edu/documents/remarks-the-vice-president-the-artificial-intelligence-action-summit-paris-france(<)/a(>). As chief case in point, Trump’s pick to head the FTC, Andrew Ferguson, vowed to go after tech monopolies while taking a hands-off approach to AI regulation, proving that attacks on corporate tech power reach their limit when it comes to AI.10Josh Sisco, “FTC Has the Resources to Take On Big Tech, Chairman Says,” (<)em(>)Bloomberg(<)/em(>), March 17, 2025, (<)a href='https://www.bloomberg.com/news/articles/2025-03-17/ftc-has-the-resources-to-take-on-big-tech-chairman-says'(>)https://www.bloomberg.com/news/articles/2025-03-17/ftc-has-the-resources-to-take-on-big-tech-chairman-says(<)/a(>). In tandem, a cadre of appointments related to the environment and energy—including Lee Zeldin as head of the EPA; Jacob Helberg as under secretary for economic growth, energy and the environment; Doug Burgum as dual interior secretary and “energy czar”; and David Sacks as a newly created “AI czar”—have inextricably tied support for a strong national AI industry to achieving energy dominance, positioning energy expansionism as the essential tool to achieve the administration’s economic nationalism agenda.11White House, “Fact Sheet: President Donald J. Trump Establishes the National Energy Dominance Council,” February 14, 2025, (<)a href='https://www.whitehouse.gov/fact-sheets/2025/02/fact-sheet-president-donald-j-trump-establishes-the-national-energy-dominance-council'(>)https://www.whitehouse.gov/fact-sheets/2025/02/fact-sheet-president-donald-j-trump-establishes-the-national-energy-dominance-council(<)/a(>).
Recent movements from within the federal government have backed this stance: The Department of Energy recently announced it had identified sixteen federal sites across the country positioned for rapid data center construction,12U.S. Department of Energy (DOE), “DOE Identifies 16 Federal Sites Across the Country for Data Center and AI Infrastructure Development,” US Department of Energy, April 3, 2025, (<)a href='https://www.energy.gov/articles/doe-identifies-16-federal-sites-across-country-data-center-and-ai-infrastructure'(>)https://www.energy.gov/articles/doe-identifies-16-federal-sites-across-country-data-center-and-ai-infrastructure(<)/a(>). and in April the Trump Administration signed an executive order ramping up domestic coal mining using growth in demand from AI data centers as justification.13Public Citizen, “Trump’s Abuse of Emergency Declaration to Force Ratepayers to Prop Up Inefficient Coal Power Plants Is Breathlessly Stupid,” April 8, 2025, (<)a href='https://www.citizen.org/news/trumps-eo-to-prop-up-coal-plant-inefficient-coal-power-plants-is-stupid'(>)https://www.citizen.org/news/trumps-eo-to-prop-up-coal-plant-inefficient-coal-power-plants-is-stupid(<)/a(>).
Small (AI) Is Beautiful?
Differentiating to Avoid Industry Co-Option
A growing number of technologists and civil society organizations advocate for smaller models as the alternative trajectory to the bigger-is-better paradigm.14See Yi Chen, JiaHao Zhao, and HaoHao Han, “A Survey on Collaborative Mechanisms Between Large and Small Language Models,” (<)em(>)arXiv(<)/em(>), May 12, 2025; and Gaël Varoquaux, Alexandra Sasha Luccioni, and Meredith Whittaker, “Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI,” (<)em(>)arXiv(<)/em(>), September 21, 2024, https://arxiv.org/abs/2409.14160. This makes sense, because many of the clearest pathologies within the AI industry are driven by scale: from climate impacts; to risks of contagion effects from privacy, security, and accuracy failures; to the ways in which scale breeds ultra-concentrated markets in AI. The dangerous impacts of the vague and all-encompassing “AGI” (see Chapter 1.1) also demonstrate the scale thesis taken to its logical end: a system that exists at a scale and level of universality that, hypothetically, displaces all other forms of expertise and value.
But industry is flocking to a version of the “small is beautiful” thesis, too, as part of their plans for market expansion, creating a familiar risk of co-option of the alternative by the same players who have driven and shaped this current paradigm. In the summer of 2024, Microsoft heralded “tiny but mighty” smaller language models that would provide impressive performance despite a reduced number of parameters.15Sally Beatty, “Tiny But Mighty: The Phi-3 Small Language Models with Big Potential,” Microsoft, April 23, 2024, (<)a href='https://news.microsoft.com/source/features/ai/the-phi-3-small-language-models-with-big-potential'(>)https://news.microsoft.com/source/features/ai/the-phi-3-small-language-models-with-big-potential(<)/a(>). Apple, Meta, and Google also released AI models with many fewer parameters, signaling that industry is incentivized to move away from simply bigger-is-better in pursuit of compute-efficient methods.16Cristina Criddle and Madhumita Murgia, “Artificial Intelligence Companies Seek Big Profits from ‘Small’ Language Models,” (<)em(>)Financial Times(<)/em(>), May 18, 2024, (<)a href='https://www.ft.com/content/359a5a31-1ab9-41ea-83aa-5b27d9b24ef9'(>)https://www.ft.com/content/359a5a31-1ab9-41ea-83aa-5b27d9b24ef9(<)/a(>). DeepSeek only propelled this trend, making it clear that frugality would be a key competitive advantage in this market.17Aili McConnon, “DeepSeek’s Reasoning AI Shows Power of Small Models, Efficiently Trained,” IBM, January 27, 2025, (<)a href='https://www.ibm.com/think/news/deepseek-r1-ai'(>)https://www.ibm.com/think/news/deepseek-r1-ai(<)/a(>).
This is only superficial common ground. Positioning “smaller” models as one of the options in an “all of the above” approach for the biggest AI companies should not be confused with a rejection of the bigger-is-better paradigm. As Satya Nadella said after the DeepSeek announcements, signaling that these efficiencies only consolidate benefits for the tech giants best placed to capture demand (see Chapter 2: Heads I Win, Tails You Lose): “As AI becomes more efficient and accessible, we will see exponentially more demand.”18Aditya Soni and Deborah Mary Sophia, “Microsoft, Meta Back Big AI Spending Despite DeepSeek’s Low Costs,” Reuters, January 30, 2025, (<)a href='https://www.reuters.com/technology/artificial-intelligence/microsoft-meta-ceos-defend-hefty-ai-spending-after-deepseek-stuns-tech-world-2025-01-30'(>)https://www.reuters.com/technology/artificial-intelligence/microsoft-meta-ceos-defend-hefty-ai-spending-after-deepseek-stuns-tech-world-2025-01-30(<)/a(>). It also ignores that pushing advancements at the “frontier” of this tech is still dictated by scale, even as firms play around with a mix of approaches across their portfolio to target different types of consumers. Most importantly, the large-scale version of this tech is what drives these firms’ policy lobbying around infrastructure expansion with deleterious impacts on the public. Movements that aim to disrupt the consensus around scale-driven AI must explicitly name and distance themselves from this industry-driven discourse.
AI Firms Want to Be Too Big To Fail
These infrastructure investments function to lock us into a world where US continued dominance in the AI market is guaranteed by the government, and, for now, largely supported by investors in the stock market seeking to avoid an end to the AI bubble—while taxpayers foot the bill (whether by taxes that contribute to these investments, or more directly through increased energy bills, as we unpack in Chapter 2: Heads I Win, Tails You Lose). AI industrial policy serves either to secure demand via procurement policies19Gov.UK, “Prime Minister Sets Out Blueprint to Turbocharge AI,” January 13, 2025, (<)a href='https://www.gov.uk/government/news/prime-minister-sets-out-blueprint-to-turbocharge-ai'(>)https://www.gov.uk/government/news/prime-minister-sets-out-blueprint-to-turbocharge-ai(<)/a(>). or to underwrite and attract continued investment (as is the case with the Stargate deal). This approach to AI is akin to industry bailouts—rarely a popular policy stance—but compared to the auto industry and banking, the AI market is much more speculative and its value to the public is unproven.
The Abundance Agenda: AI’s Fundamental
Incompatibility with Supply-Side Progressivism
The emergence of “abundance” as a narrative strategy and policy platform is being used by tech firms to get access to scarce public subsidies and energy. This stance has formed around a constellation of thinkers and organizations working across party lines to articulate a policy agenda premised on building a policy apparatus in support of more, and more efficient, construction of critical resources with low supply and high demand, including housing, healthcare, and energy. It operates under the presumption that (1) government regulation makes building too burdensome in these sectors, leading to cost inflation; and (2) progressives have focused too intently on subsidy programs that cut or block access, rather than on the underlying reasons for cost inflation. The solution, abundance movement advocates posit, is to push forward “supply-side progressivism,” or, as Ezra Klein puts it, “to take innovation as seriously as they take affordability”20Ezra Klein, “The Economic Mistake the Left Is Finally Confronting,” New York Times, September 19, 2021, (<)a href='https://www.nytimes.com/2021/09/19/opinion/supply-side-progressivism.html'(>)https://www.nytimes.com/2021/09/19/opinion/supply-side-progressivism.html(<)/a(>). by implementing regulatory reforms that speed development and solve scarcity.
Abundance proponents centrally contend with energy markets, in that they argue in favor of cutting regulation to enable an increase in energy production. For example, Jerusalem Demsas wrote in the Atlantic that the ability for NIMBY-minded community organizations and climate groups to shut down renewable development is hindering the US’s ability to meet its climate goals.21Jerusalem Demsas, “Why America Doesn’t Build,” (<)em(>)Atlantic(<)/em(>), October 27, 2023, (<)a href='https://www.theatlantic.com/ideas/archive/2023/10/wind-farms-community-opposition/675791'(>)https://www.theatlantic.com/ideas/archive/2023/10/wind-farms-community-opposition/675791(<)/a(>). Klein and Derek Thompson argue that overhauling energy infrastructure is crucial to mitigating climate change, emphasizing that the first step toward an abundant clean-energy future is reducing the current fossil fuel reliance from 60 percent as of 2022 to nearly 0 percent.22Ezra Klein and Derek Thompson, (<)em(>)Abundance(<)/em(>) (Avid Reader Press, 2025).
As a growing number of AI companies prioritize building and opening new data centers, more energy is needed to meet the staggering demand. One might think that AI-driven demand would concern abundance advocates, because AI firms soak up the available supply of renewable energy. Data centers already account for 4.59 percent of all energy used in the US. That number has doubled since 2018.23James O’Donnell, “AI’s Emissions Are About to Skyrocket Even Further,” (<)em(>)Technology Review(<)/em(>), December 13, 2024, (<)a href='https://www.technologyreview.com/2024/12/13/1108719/ais-emissions-are-about-to-skyrocket-even-further'(>)https://www.technologyreview.com/2024/12/13/1108719/ais-emissions-are-about-to-skyrocket-even-further(<)/a(>). Goldman Sachs estimates that data center power demand will grow 160 percent by 2030.24Goldman Sachs, “AI is Poised to Drive 160% Increase in Data Center Power Demand,” May 14, 2024, (<)a href='https://www.goldmansachs.com/insights/articles/AI-poised-to-drive-160-increase-in-power-demand'(>)https://www.goldmansachs.com/insights/articles/AI-poised-to-drive-160-increase-in-power-demand(<)/a(>). These are staggering numbers wreaking havoc on an already fragile energy grid.
Instead, we see a more uneasy alliance, where the abundance agenda potentially converges with the energy deregulation camp for whom the “urgent” need to advance AI is being used as a justification to fast-track and expand fossil fuel production and use. At the House Oversight Committee hearing on data centers, AI, and energy, legislators repeatedly threw renewables under the bus, even touting that China is powering their AI systems with coal-fired plants.25Committee on Oversight and Government Reform, “America’s AI Moonshot: The Economics of AI, Data Centers, and Power Consumption,” April 1, 2025, (<)a href='https://oversight.house.gov/hearing/americas-ai-moonshot-the-economics-of-ai-data-centers-and-power-consumption'(>)https://oversight.house.gov/hearing/americas-ai-moonshot-the-economics-of-ai-data-centers-and-power-consumption(<)/a(>). The fossil fuel company talking point that wind and solar are not a reliable source of energy to meet data centers’ 24/7 demands is deeply ingrained,26Brad Plumer, “Want Cheap Power, Fast? Solar and Wind Firms Have a Suggestion,” (<)em(>)New York Times(<)/em(>), March 17, 2025, (<)a href='https://www.nytimes.com/2025/03/17/climate/renewable-energy-trump-electricity.html?smid=nytcore-ios-share'(>)https://www.nytimes.com/2025/03/17/climate/renewable-energy-trump-electricity.html?smid=nytcore-ios-share(<)/a(>). with legislators and data center trade groups pivoting toward the expansion of nuclear—rather than renewable—energy to provide “reliable” and sturdy energy for AI. Despite the substantial evidence on hand, this sustainability critique has not been taken seriously by abundance advocates skeptical of the climate movement.