Fortune54%

Elon Musk says AI is the only way to fix the $40 trillion U.S. debt crisis—but a new study says even the most optimistic scenario won’t fill the hole 69%

By Eleanor Pringle67%

7/2/2026, 11:09:58 AM

BS Summary: This article contains 25 faulty reasoning types, including Pessimism Bias, Unattributed Quote, and Confirmation Bias, with Appeal to Authority as the most egregious example at 38.8% saturation with 309 hits. Analysis detected 1,747 faulty-reasoning hits from 796 analyzed words, generating a BS Score of 62.1% and a BS Rank of 69% (6,885 of 21,887 articles). This article is worse (more manipulative) than 68.50% of the article peer group.

In the great debate about rebalancing the United States’ debt to its economic growth, the optimists suggest that expanding the economy is preferable to cutting federal spending. 
It would certainly be less painful. 
Indeed, SpaceX founder CEO Elon Musk has suggested that the productivity gains thanks to AI may be the only way to save Uncle Sam from his growing debt burden—$39.5 trillion at the time of writing. 
Musk, the CEO of Tesla, has long been a debt hawk, even if it meant going against President Trump on the matter. 
Musk told the Nikhil Kamath podcast last year that AI and robotics used on a large scale is “pretty much the only thing that’s going to solve the U.S. debt crisis.” 
But new research from Brookings, authored by Ben Harris, Neil R. 
Mehrotra and William Overcash, suggests that while AI-driven economic growth might meaningfully shrink fiscal deficits, it is still unlikely to bridge the gap “even in more optimistic scenarios fully.” 
The suggestion that AI could be the silver bullet for a fiscal crisis is understandable, the trio writes, owing to the active capital expenditure into the transformative technology thus far, as well as “the unharnessed capacity of the technology to boost productivity.” 
Indeed, AI investment has continued at such a pace this year that it’s taking even Wall Street analysts by surprise. 
For example, BNP Paribas lifted its near-term U.S. 
GDP growth estimates earlier this year on the back of capex announcements indicating a larger impulse from the AI buildout than the banking giant had expected. 
While they estimated that growth for all of 2026 will stay the same at 2.6%, the markets team highlighted that on a Q4/Q4 comparison of this year to last, growth would be 2.6% rather than the 2.1% previously estimated. 
Likewise, AI—even in its early years of testing and adoption—seems to be having an impact on output. 
A June study from The Centre for Economic Policy Research (CEPR) found that the implied measure of AI-attributed labor productivity growth (derived from revenues and employment) for 2026 is 1.8%—gains are expected to be highest in high-skill services and finance, where they exceed 2%. 
AI could also meaningfully impact some of the most expensive aspects of the fiscal outlook: Outlays for Medicare and Medicaid in 2026 are expected to be $674 billion and $472 billion, respectively, according to estimates from the Congressional Budget Office. 
The report suggests that, in a positive scenario, AI could have a meaningful impact on the outlook because “the healthcare sector exhibits substantial misallocation and inefficiency that a productivity shock could reduce.” 
Likewise—in a perfect scenario—AI could lead to a more lucrative taxable workforce, the authors add: “Productivity growth tends to translate into higher tax revenues primarily through tax base expansion, with long-run responsiveness close to proportional in most advanced and emerging economies.” 
A victim of its own success 
However, even though the groundwork for a debt resolution in the form of a “once-in-a-lifetime” productivity boom appears to have been laid—across financing, early productivity gains, and efficiency and revenue opportunities—the Brookings report suggests that an AI productivity shock may mean the U.S. economy becomes a victim of its own success. 
A “traditional” productivity shock would be positive for the debt picture, the trio writes: primary deficits turn negative, the annual deficit falls by over $2 trillion, and deficit as a share of GDP declines by almost 5 percentage points. 
“Here, the techno-optimists are validated,” the authors add. 
However, AI has the potential to be so transformative that it “should give optimists pause,” the economists note. 
The first factor is that efficiencies in healthcare, which translate to lower costs, also mean that societies are likely to live longer and will draw more heavily on social security support as a result. 
Additionally, the report suggests the much-feared labor market shift means more unemployment, and more individuals relying on income support payments as the dust settles. 
Defense spending is also likely to increase as countries seek to win the AI arms race. 
Next, the authors write: “A changing composition of national income may push the tax base away from highly taxed labor income to less-taxed non-corporate capital and corporate profits. 
And lastly, increased demands for investment may raise the neutral rate of interest, which pushes up equilibrium interest rates and boosts interest expenditures.” 
As a result, while AI will improve the budget outlook somewhat, it can’t be relied upon to solve the U.S.’s fiscal problem. 
The team found that, at best, these factors offset AI’s potential to reduce budget deficits by half. 
At worst, these mitigating factors would knock two-thirds off any improvement. 
Article reasoning-pattern comparisonThis article: 14.9%Eleanor Pringle: 2.7%Fortune: 4.2%Confirmation Bias14.9%This article: 4.4%Eleanor Pringle: 1.8%Fortune: 1.4%Anchoring Bias4.4%This article: 7.5%Eleanor Pringle: 1.4%Fortune: 3.3%Availability Heuristic7.5%This article: 2.1%Eleanor Pringle: 0.4%Fortune: 1.4%Representativeness Heuristic2.1%This article: 3.3%Eleanor Pringle: 0.7%Fortune: 1.1%Hindsight Bias3.3%This article: 0.0%Eleanor Pringle: 2.0%Fortune: 2.7%Overconfidence Bias0.0%This article: 8.9%Eleanor Pringle: 7.3%Fortune: 6.7%Framing Effect8.9%This article: 0.0%Eleanor Pringle: 0.2%Fortune: 0.5%Loss Aversion0.0%This article: 0.0%Eleanor Pringle: 0.7%Fortune: 0.6%Status Quo Bias0.0%This article: 0.0%Eleanor Pringle: 0.1%Fortune: 0.3%Sunk Cost Effect0.0%This article: 8.0%Eleanor Pringle: 3.5%Fortune: 3.4%Optimism Bias8.0%This article: 19.5%Eleanor Pringle: 1.8%Fortune: 2.5%Pessimism Bias19.5%This article: 12.8%Eleanor Pringle: 5.8%Fortune: 7.0%Negativity Bias12.8%This article: 0.0%Eleanor Pringle: 1.7%Fortune: 1.7%Self-Serving Bias0.0%This article: 4.3%Eleanor Pringle: 1.1%Fortune: 0.9%Fundamental Attribution Error4.3%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.2%Actor-Observer Bias0.0%This article: 1.0%Eleanor Pringle: 1.1%Fortune: 0.8%In-Group Bias1.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Eleanor Pringle: 11.8%Fortune: 3.2%Halo Effect0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.0%Horn Effect0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.0%Dunning-Kruger Effect0.0%This article: 2.5%Eleanor Pringle: 2.4%Fortune: 1.5%Recency Bias2.5%This article: 2.8%Eleanor Pringle: 0.6%Fortune: 0.3%Primacy Effect2.8%This article: 0.0%Eleanor Pringle: 0.1%Fortune: 0.0%Blind-Spot Bias0.0%This article: 0.0%Eleanor Pringle: 0.4%Fortune: 0.7%Ad Hominem0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.2%Straw Man0.0%This article: 38.8%Eleanor Pringle: 8.0%Fortune: 4.8%Appeal to Authority38.8%This article: 14.7%Eleanor Pringle: 3.7%Fortune: 2.2%False Dilemma14.7%This article: 5.2%Eleanor Pringle: 1.7%Fortune: 1.3%Slippery Slope5.2%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.3%Circular Reasoning0.0%This article: 2.1%Eleanor Pringle: 2.6%Fortune: 6.0%Hasty Generalization2.1%This article: 0.0%Eleanor Pringle: 0.4%Fortune: 0.2%Red Herring0.0%This article: 0.0%Eleanor Pringle: 0.9%Fortune: 0.5%Bandwagon0.0%This article: 0.8%Eleanor Pringle: 2.7%Fortune: 3.1%Appeal to Emotion0.8%This article: 6.4%Eleanor Pringle: 1.1%Fortune: 1.2%Begging the Question6.4%This article: 12.2%Eleanor Pringle: 2.5%Fortune: 3.9%Post Hoc (False Cause)12.2%This article: 0.0%Eleanor Pringle: 0.2%Fortune: 0.1%Tu Quoque0.0%This article: 0.0%Eleanor Pringle: 0.1%Fortune: 0.3%Burden of Proof0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.2%Appeal to Nature0.0%This article: 0.0%Eleanor Pringle: 0.2%Fortune: 0.4%Composition/Division0.0%This article: 0.0%Eleanor Pringle: 2.9%Fortune: 2.5%Anecdotal0.0%This article: 0.0%Eleanor Pringle: 0.1%Fortune: 0.2%No True Scotsman0.0%This article: 12.8%Eleanor Pringle: 1.4%Fortune: 2.2%Ambiguity (Equivocation)12.8%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.2%Middle Ground0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.0%Personal Incredulity0.0%This article: 0.0%Eleanor Pringle: 0.1%Fortune: 0.1%Special Pleading0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.2%Genetic Fallacy0.0%This article: 19.2%Eleanor Pringle: 1.4%Fortune: 1.5%Unattributed Quote19.2%This article: 4.4%Eleanor Pringle: 1.5%Fortune: 1.3%Quote-first Misdirection4.4%This article: 10.1%Eleanor Pringle: 5.6%Fortune: 4.4%Biased Writer Voice10.1%This article: 0.8%Eleanor Pringle: 1.9%Fortune: 1.3%Indoctrination0.8%This article: 0.0%Eleanor Pringle: 0.9%Fortune: 0.3%Politically Left Leaning Bias0.0%This article: 0.0%Eleanor Pringle: 0.0%Fortune: 0.3%Politically Right Leaning Bias0.0%This article: 0.0%Eleanor Pringle: 0.4%Fortune: 1.3%Attempt to Sell a Product or S…0.0%

796 words analyzed.

Speakers

3speakers20%attributed speech635writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 29 words • 100.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 6 words • 100.0% coverageElon Musk • 35 words • 100.0% coverageWriter's voice • 22 words • 0.0% coverageElon Musk • 31 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 29 words • 100.0% coverageWriter's voice • 42 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 39 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageThe Centre for Economic Policy Research (CEPR) • 44 words • 0.0% coverageWriter's voice • 40 words • 0.0% coverageWriter's voice • 32 words • 100.0% coverageWriter's voice • 41 words • 100.0% coverageWriter's voice • 6 words • 0.0% coverageBrookings • 51 words • 100.0% coverageWriter's voice • 39 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 28 words • 100.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverage
Selected voice

Elon Musk

100%flagged-word coverage
66 attributed words41% of attributed speech93% writer coverage
0%27.5%55.0%Quote-first Misdirection+53.0 ptsWriter: 0.0%Elon Musk: 53.0%53.0%Unattributed Quote-24.1 ptsWriter: 24.1%Elon Musk: 0.0%0.0%Biased Writer Voice-4.6 ptsWriter: 4.6%Elon Musk: 0.0%0.0%Indoctrination-0.9 ptsWriter: 0.9%Elon Musk: 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.