NOTUS0%

Treasury Has an Internal Report Warning About the Dangers of an AI Bubble 49%

By Eric Katz0%

7/6/2026, 9:00:00 AM

BS Summary: This article contains 34 faulty reasoning types, including Appeal to Authority, Pessimism Bias, and Framing Effect, with Negativity Bias as the most egregious example at 21.9% saturation with 237 hits. Analysis detected 2,509 faulty-reasoning hits from 1,083 analyzed words, generating a BS Score of 49.8% and a BS Rank of 49% (11,183 of 21,886 articles). This article is better (less manipulative) than 51.10% of the article peer group.

A draft report inside the Treasury Department is set to warn of the risks posed by the artificial intelligence market, likening key aspects of it to the dotcom bubble that upended the U.S. economy when it burst in the early 2000s. 
The document, the existence and contents of which have not been previously reported but was obtained by NOTUS, is a significant departure from the Trump administration’s public tone, which has focused on encouraging unrelenting investment to unlock exponential growth. 
Career Treasury analysts found that AI firms are more deeply entrenched in the U.S. economy than their dotcom predecessors and pose significant risk to the entire system if financial conditions change, productivity goals are missed or various choke points stymie growth. 
A downturn in the AI market would send shockwaves throughout the entire economic ecosystem, the analysts wrote. 
DOGE Is Officially Ending. 
Agencies Are Hiring Again. 
It’s the Summer of Sports and Politics 
Trump’s Nutty State Fair Hijacked the Fourth of July. 
And My Pen. 
States Raised Concerns about the Great American State Fair’s Rush, Cost and Confusion 
The report concluded that the AI bubble’s popping would lead to less of an immediate crash than the U.S. economy experienced with dotcoms in the early 2000s. 
But the analysts predicted that companies would cut back, investors would lose confidence, and the economy would grow more slowly should the industry falter. 
Stock markets, private credit markets, companies financing data center buildouts, cloud providers, chip manufacturers and utilities would all feel the effect, according to the report. 
The report was prepared by Treasury analysts for Secretary Scott Bessent, Federal Reserve Board Chair Kevin Warsh and various federal financial regulators and offers a rare glimpse of how the Trump administration is examining the risks posed by AI. 
It has been completed for weeks and is awaiting formal approval before reaching its intended audience, which is eventually expected to include the public. 
The report stresses that AI companies maintain some fundamental differences from the businesses that dominated the dotcom boom of the late 1990s, which was defined by speculative excess and an overreliance on debt financing. 
Many of the top AI companies, by contrast, are more mature, profitable and maintain healthier balance sheets, which could blunt the impacts of the “bubble” bursting  or if it bursts at all. 
Still, the analysts said, AI investors are taking risks so significant that much of the financial system now rests upon AI meeting expectations for productivity gains and profitability. 
President Trump has floated procuring U.S. government stakes in AI companies so the American public could benefit from their growth, and the White House recently began meddling in the products that AI firms like Anthropic can release. 
Fears of an AI bubble have grown over the last year, including on Capitol Hill, among some Wall Street observers and executives, inside think tanks and even within the ranks of top AI principals. 
Prominent economists and institutions, including the Bank of England  the central bank of the United Kingdom  and the head of the International Monetary Fund have also raised concerns about overvaluation of AI firms and the risks they pose to the broader economic system. 
Trump administration officials have never voiced similar unease, and a Treasury Department spokesperson dismissed the report’s findings as unvetted and not representative of the agency’s policies or views. 
“The official position of the Secretary and the U.S. 
Treasury is that Artificial intelligence will be a key driver of America’s new Golden Age,” the spokesperson said. 
“AI has the potential to deliver unprecedented productivity gains, expand economic opportunity, and empower American workers and businesses.” 
The AI sector is vulnerable to funding for data centers and other infrastructure projects drying up and sustained growth expectations not being met, the analysts found in the report, saying that was reminiscent of the dotcom crash. 
That’s because the industry is increasingly concentrated within a small number of firms, heavily reliant on private-market financing and significantly invested in infrastructure  data centers  to support its future. 
Supply chain issues, geopolitical tensions, electricity bottlenecks, utilities shortfalls and other concerns could all block AI’s momentum. 
While AI companies’ valuations are less speculative and generate more revenue than those in the dotcom era, the analysts said, the industry is at risk if it fails to grow as fast as it says it can, or if companies can’t monetize their products. 
If AI companies fall short, the effects would ripple throughout the financial system as a whole, from big banks and hedge funds to private creditors, the analysts note. 
The largest AI firms are also all interconnected with each other and across different markets, which also points to widespread impacts if investment dries up or demand slows. 
In fact, fewer retail investors are backing AI than did dotcom ventures, so a sustained AI dip would have a greater impact on institutional investors fundamental to economic stability, the draft report indicates. 
Prominent politicians have repeatedly requested a similar type of analysis from the Treasury Department. 
Earlier this year, Sen. 
Elizabeth Warren (D-Mass.), ranking member on the Senate Banking Committee, and other Senate Democrats requested the Treasury Department demand non-public data to conduct a report on the risks of an AI debt bubble. 
Last month, proposed a bill requiring financial firms to disclose that information to Treasury and for the agency to report the various ways the financial world is exposed to AI companies’ buildouts. 
The report would detail how a downturn in AI could hurt the U.S. economy and suggest regulatory action to mitigate the effects. 
“AI and Big Tech companies are increasingly reliant on shadowy forms of debt and balance sheet magic to fund their multi-trillion dollar AI buildouts,” Warren said, stating that her bill would “give regulators and Congress the information they need to identify risks early and protect our economy from another preventable financial crisis.” 
The Treasury spokesperson said “Treasury will continue working with regulators and the private sector to ensure our regulatory framework keeps pace with innovation and supports the responsible adoption of AI in ways that strengthen the U.S. financial system.” 
In his recent New York address, Bessent noted that at a recent G7 meeting, he disagreed with other leaders who suggested risks of AI surrounded safety and job loss. 
“I think they were slightly stunned when I said the biggest risk to AI is China getting ahead of us,” he said. 
“We have to stay ahead.” 
Article reasoning-pattern comparisonThis article: 6.0%Eric Katz: 1.5%NOTUS: 2.3%Confirmation Bias6.0%This article: 2.5%Eric Katz: 3.0%NOTUS: 1.2%Anchoring Bias2.5%This article: 7.2%Eric Katz: 3.9%NOTUS: 2.2%Availability Heuristic7.2%This article: 9.4%Eric Katz: 2.4%NOTUS: 1.1%Representativeness Heuristic9.4%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.5%Hindsight Bias0.0%This article: 0.0%Eric Katz: 0.6%NOTUS: 1.4%Overconfidence Bias0.0%This article: 15.8%Eric Katz: 6.5%NOTUS: 6.6%Framing Effect15.8%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.1%Loss Aversion0.0%This article: 0.5%Eric Katz: 0.1%NOTUS: 0.9%Status Quo Bias0.5%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.1%Sunk Cost Effect0.0%This article: 9.9%Eric Katz: 5.8%NOTUS: 3.3%Optimism Bias9.9%This article: 18.0%Eric Katz: 13.8%NOTUS: 3.0%Pessimism Bias18.0%This article: 21.9%Eric Katz: 6.3%NOTUS: 10.5%Negativity Bias21.9%This article: 3.4%Eric Katz: 0.9%NOTUS: 2.2%Self-Serving Bias3.4%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.9%Fundamental Attribution Error0.0%This article: 2.7%Eric Katz: 0.7%NOTUS: 0.3%Actor-Observer Bias2.7%This article: 3.0%Eric Katz: 1.6%NOTUS: 2.1%In-Group Bias3.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.5%Out-Group Homogeneity Bias0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 1.3%Halo Effect0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.1%Horn Effect0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.0%Dunning-Kruger Effect0.0%This article: 6.5%Eric Katz: 1.6%NOTUS: 1.2%Recency Bias6.5%This article: 3.6%Eric Katz: 0.9%NOTUS: 0.3%Primacy Effect3.6%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.0%Blind-Spot Bias0.0%This article: 5.6%Eric Katz: 1.4%NOTUS: 1.0%Ad Hominem5.6%This article: 2.7%Eric Katz: 0.7%NOTUS: 0.3%Straw Man2.7%This article: 20.5%Eric Katz: 6.2%NOTUS: 4.7%Appeal to Authority20.5%This article: 4.1%Eric Katz: 1.0%NOTUS: 1.0%False Dilemma4.1%This article: 6.4%Eric Katz: 1.6%NOTUS: 0.5%Slippery Slope6.4%This article: 2.9%Eric Katz: 0.7%NOTUS: 0.2%Circular Reasoning2.9%This article: 10.1%Eric Katz: 5.3%NOTUS: 4.9%Hasty Generalization10.1%This article: 3.6%Eric Katz: 0.9%NOTUS: 0.8%Red Herring3.6%This article: 3.1%Eric Katz: 2.9%NOTUS: 0.9%Bandwagon3.1%This article: 11.4%Eric Katz: 6.2%NOTUS: 3.5%Appeal to Emotion11.4%This article: 2.6%Eric Katz: 0.6%NOTUS: 0.7%Begging the Question2.6%This article: 14.0%Eric Katz: 3.5%NOTUS: 2.6%Post Hoc (False Cause)14.0%This article: 3.4%Eric Katz: 0.9%NOTUS: 0.1%Tu Quoque3.4%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.4%Burden of Proof0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.2%Appeal to Nature0.0%This article: 2.6%Eric Katz: 0.6%NOTUS: 0.2%Composition/Division2.6%This article: 0.0%Eric Katz: 0.0%NOTUS: 1.5%Anecdotal0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.2%No True Scotsman0.0%This article: 6.1%Eric Katz: 1.5%NOTUS: 1.6%Ambiguity (Equivocation)6.1%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.0%Gambler’s Fallacy0.0%This article: 3.0%Eric Katz: 0.8%NOTUS: 0.2%Middle Ground3.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.1%Personal Incredulity0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.2%Special Pleading0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.1%Genetic Fallacy0.0%This article: 2.2%Eric Katz: 0.6%NOTUS: 2.2%Unattributed Quote2.2%This article: 6.5%Eric Katz: 1.8%NOTUS: 2.2%Quote-first Misdirection6.5%This article: 5.8%Eric Katz: 5.4%NOTUS: 4.1%Biased Writer Voice5.8%This article: 4.8%Eric Katz: 1.2%NOTUS: 0.8%Indoctrination4.8%This article: 0.0%Eric Katz: 2.0%NOTUS: 1.5%Politically Left Leaning Bias0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 0.6%Politically Right Leaning Bias0.0%This article: 0.0%Eric Katz: 0.0%NOTUS: 1.2%Attempt to Sell a Product or S…0.0%

1083 words analyzed.

Speakers

2speakers13%attributed speech942writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 13 words • 0.0% coverageWriter's voice • 41 words • 100.0% coverageWriter's voice • 39 words • 0.0% coverageWriter's voice • 41 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 39 words • 0.0% coverageWriter's voice • 24 words • 100.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 45 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 18 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 44 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageElizabeth Warren (D-Mass.) • 33 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageElizabeth Warren (D-Mass.) • 52 words • 100.0% coverageWriter's voice • 38 words • 0.0% coverageScott Bessent • 29 words • 0.0% coverageScott Bessent • 22 words • 100.0% coverageScott Bessent • 5 words • 0.0% coverage
100%flagged-word coverage
85 attributed words60% of attributed speech95% writer coverage
0%32.5%65.0%Indoctrination+61.2 ptsWriter: 0.0%Elizabeth Warren (D-Mass.): 61.2%61.2%Quote-first Misdirection+59.3 ptsWriter: 1.9%Elizabeth Warren (D-Mass.): 61.2%61.2%Biased Writer Voice-4.4 ptsWriter: 4.4%Elizabeth Warren (D-Mass.): 0.0%0.0%Unattributed Quote-2.5 ptsWriter: 2.5%Elizabeth Warren (D-Mass.): 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.