Matt Stoller exposes a dangerous opacity at the heart of the artificial intelligence boom, arguing that the entire sector is being propped up by financial black boxes that prevent any real assessment of risk or value. While the public fixates on chatbots and math problems, Stoller reveals a shadow economy of leveraged bets, insider networks, and unverified profit claims that could trigger a crash with systemic consequences. He demands a return to New Deal-era transparency, suggesting that without forced disclosure, we are flying blind into a potential bubble of unprecedented scale.
The Cult of Opacity
Stoller begins by dismantling the mythology of the AI investment world, pointing to the spectacular collapse of a $45 billion hedge fund called "Situational Awareness." The fund, led by 25-year-old former OpenAI employee Leopold Aschenbrenner, imploded after betting heavily on volatile AI stocks with borrowed money. Stoller uses this failure to illustrate a broader cultural rot within Silicon Valley, describing a closed loop of influence where financial speculation is driven by "cult-like claims about social transformations larger than the industrial revolution."
He highlights how this insular network operates, noting that Aschenbrenner is married to the chief of staff at Anthropic and lives with prominent AI boosters. This isn't just a story about one failed fund; it is evidence of a system where financial decisions are made by a small group of insiders who share a specific ideological worldview. Stoller writes, "Aschenbrenner's thesis was simple. He believed that he is among a select few who understand that AI is going to become unimaginably powerful, and he invested accordingly." This framing is crucial because it shifts the narrative from technological inevitability to human speculation. The danger here is that when a small, ideologically aligned group controls the narrative, they can detach market prices from economic reality.
The author then turns to the specific financial claims driving these valuations, specifically regarding profit margins for "inference"—the sale of computing power to run AI models. Stoller points out that while figures like Dwarkesh Patel have claimed margins jumped from 38% to over 70% in months, these numbers are unverified. "Is this margin story true? Maybe. But we don't know," Stoller writes. "And we should, as this information matters." This is the core of his argument: the market is operating on faith rather than data. The trillions of dollars invested in AI infrastructure are resting on assertions that no outsider can audit. Critics might argue that private companies have a right to protect trade secrets, but Stoller counters that when these firms are effectively running the economy's future, secrecy becomes a public hazard.
We are forced to rely on skeptics without access to this inside information... Insiders already know how much Anthropic is selling to corporate America, and how much it costs to provide it. It's just not public information.
The Policy Vacuum
Stoller connects this financial fog to a paralysis in governance. He recounts a conversation with a Congressional candidate who asked for antitrust ideas, only to find that the anti-monopolist himself had no clear policy solution because the market structure is unknowable. The problem is compounded by the fact that the current landscape is a "weird and confused netherworld, of guesses and spin, organized by gamblers."
He argues that the current market structure is a result of specific industrial policies that favored big tech, allowing them to build data centers with public subsidies while avoiding liability. Yet, without financial transparency, regulators cannot determine if these firms are truly profitable or if they are running a shell game. Stoller notes, "The state sanctioned big tech firms to gain monopoly profits, fostered uniquely permissive copyright and privacy rules for those firms, and prevented them from having to accept liability for harming their customers." This historical context is vital; it shows that the current opacity is not an accident but a feature of a regulatory environment designed to protect incumbents. The reference to the "effective altruism" movement, which permeates this circle, adds a layer of ideological motivation to the financial maneuvering, suggesting that the drive for AI dominance is as much about a specific worldview as it is about profit.
The New Deal Solution
To solve this, Stoller proposes a radical return to the transparency standards of the 1930s. He draws a direct line from the securities laws passed after the Great Depression to the current crisis, arguing that the "opaque financial tactics of financiers in the 1920s had led to a bubble and a crash." He contrasts this with the 2012 JOBS Act, signed by the Obama administration, which allowed private companies to grow massive without public disclosure. Stoller writes, "In 2012, however, the Obama administration worked with the GOP and a set of Democrats to roll this system back through a law called the JOBS Act."
He cites the WeWork collapse as a cautionary tale of what happens when private firms hide their true financial health until it is too late. "WeWork blew up when it tried to go public, and released its S-1 form with all that batshit stuff about Adam Neumann," Stoller notes. The lesson is clear: transparency works, and the lack of it enables fraud. He argues that repealing the JOBS Act or mandating disclosure for large private firms would force the AI industry to reveal its true state. "Fundamentally, there's something powerful about saying 'AI firms need to open their financials to the public,'" he asserts. Without this, we cannot know if we are in a bubble.
Stoller also points out the complexity of the current corporate web, where big tech giants like Google and Amazon invest in AI startups, which then pay those same giants for cloud computing. This circular flow of money makes it nearly impossible to track where the value is actually being created. "There are even a pretty good argument that it is impossible to sell compute at scale," he writes, highlighting the technical and economic contradictions that are being ignored in the rush to invest. The argument here is that the only way to govern this technology is to make its economics visible.
Bottom Line
Stoller's most compelling contribution is reframing the AI debate from a technical race to a financial transparency crisis, arguing that we cannot regulate what we cannot see. While his call to repeal the JOBS Act faces significant political headwinds and critics may argue it stifles innovation, the evidence of a speculative bubble driven by unverified data is too strong to ignore. The reader should watch for whether any Congressional candidates, including the Michigan Senate primary contenders mentioned, adopt this demand for financial disclosure as a core antitrust strategy.