Fortune52%

Billionaire Mike Bloomberg warns Trump’s AI ownership plan would make ‘George Orwell blush’ 82%

By Eva Roytburg94%

7/21/2026, 9:58:29 PM

BS Summary: This article contains 19 faulty reasoning types, including Hasty Generalization, Slippery Slope, and False Dilemma, with Biased Writer Voice as the most egregious example at 32.6% saturation with 109 hits. Analysis detected 739 faulty-reasoning hits from 334 analyzed words, generating a BS Score of 73.2% and a BS Rank of 82% (4,002 of 21,176 articles). This article is worse (more manipulative) than 81.10% of the article peer group.

The initial deal behind the American AI boom seems to be: private investors would help finance it, taking on the risk; private companies would initially own the benefits of the breakthroughs, then distribute them t​​o public markets later; and the government would help regulate the industry after the fact. 
In China, by contrast, the deal is that companies still have to compete for investment and customers, while the government provides the compute. 
That bargain is showing signs of collapse  on the U.S. side. 
As costs soar, Chinese competitors gain ground and Washington increasingly considers AI to be a national-security asset, President Donald Trump is considering taking a governmental stake into AI companies. 
While both the populist left and the right, and the AI companies themselves, have lauded the proposal, one person isn’t cheering: Billionaire Michael Bloomberg. 
In an opinion column published in Bloomberg Opinion on Monday, the media company’s founder attacked the proposal, arguing that it would turn Washington from an industry regulator into an investor with incentives for profit, leading to “cronyism.” 
“Somewhere, Karl Marx is smiling,” Bloomberg wrote of the centrally planned economy on offer, while the propaganda possibilities would “make George Orwell blush.” 
The former New York City mayor argued that Americans do not need their governments to own AI companies in order to share in the technology’s gains. 
For one, once they go public, they could just buy shares. 
But also, consumers and businesses already benefit from AI through fraud detection, medical research, bookkeeping and other helpful applications, he wrote, while the resulting economic growth could eventually generate more tax revenue for public services. 
If AI companies are failing to contribute enough to the public, Bloomberg argued, Washington should fix the tax code to serve the public; not buy them. 
Ultimately, he predicted, federal shareholders will likely lead to corruption as the market will transform into a “smoke-filled backroom.” 
This story was originally featured on Fortune.com 
Article reasoning-pattern comparisonThis article: 0.0%Eva Roytburg: 3.5%Fortune: 4.2%Confirmation Bias0.0%This article: 0.0%Eva Roytburg: 5.0%Fortune: 1.4%Anchoring Bias0.0%This article: 8.7%Eva Roytburg: 7.3%Fortune: 3.3%Availability Heuristic8.7%This article: 0.0%Eva Roytburg: 1.7%Fortune: 1.4%Representativeness Heuristic0.0%This article: 0.0%Eva Roytburg: 4.3%Fortune: 1.1%Hindsight Bias0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 2.7%Overconfidence Bias0.0%This article: 0.0%Eva Roytburg: 8.8%Fortune: 6.7%Framing Effect0.0%This article: 7.8%Eva Roytburg: 0.9%Fortune: 0.5%Loss Aversion7.8%This article: 7.8%Eva Roytburg: 1.8%Fortune: 0.6%Status Quo Bias7.8%This article: 0.0%Eva Roytburg: 1.4%Fortune: 0.3%Sunk Cost Effect0.0%This article: 3.3%Eva Roytburg: 2.2%Fortune: 3.3%Optimism Bias3.3%This article: 9.3%Eva Roytburg: 4.2%Fortune: 2.5%Pessimism Bias9.3%This article: 14.4%Eva Roytburg: 6.9%Fortune: 6.9%Negativity Bias14.4%This article: 10.5%Eva Roytburg: 1.2%Fortune: 1.7%Self-Serving Bias10.5%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.2%Actor-Observer Bias0.0%This article: 0.0%Eva Roytburg: 0.8%Fortune: 0.8%In-Group Bias0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 3.1%Halo Effect0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.0%Horn Effect0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.0%Dunning-Kruger Effect0.0%This article: 7.2%Eva Roytburg: 4.0%Fortune: 1.5%Recency Bias7.2%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.3%Primacy Effect0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.0%Blind-Spot Bias0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.7%Ad Hominem0.0%This article: 0.0%Eva Roytburg: 1.7%Fortune: 0.2%Straw Man0.0%This article: 0.0%Eva Roytburg: 7.1%Fortune: 4.8%Appeal to Authority0.0%This article: 15.6%Eva Roytburg: 3.5%Fortune: 2.2%False Dilemma15.6%This article: 16.8%Eva Roytburg: 4.1%Fortune: 1.3%Slippery Slope16.8%This article: 0.0%Eva Roytburg: 5.7%Fortune: 0.3%Circular Reasoning0.0%This article: 21.6%Eva Roytburg: 9.8%Fortune: 6.0%Hasty Generalization21.6%This article: 0.0%Eva Roytburg: 0.7%Fortune: 0.2%Red Herring0.0%This article: 7.2%Eva Roytburg: 0.8%Fortune: 0.5%Bandwagon7.2%This article: 12.6%Eva Roytburg: 6.2%Fortune: 3.0%Appeal to Emotion12.6%This article: 0.0%Eva Roytburg: 0.7%Fortune: 1.2%Begging the Question0.0%This article: 10.5%Eva Roytburg: 3.2%Fortune: 3.9%Post Hoc (False Cause)10.5%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.1%Tu Quoque0.0%This article: 7.8%Eva Roytburg: 0.9%Fortune: 0.3%Burden of Proof7.8%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.2%Appeal to Nature0.0%This article: 0.0%Eva Roytburg: 2.1%Fortune: 0.4%Composition/Division0.0%This article: 10.5%Eva Roytburg: 1.7%Fortune: 2.4%Anecdotal10.5%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.2%No True Scotsman0.0%This article: 10.5%Eva Roytburg: 5.1%Fortune: 2.3%Ambiguity (Equivocation)10.5%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.2%Middle Ground0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.0%Personal Incredulity0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.1%Special Pleading0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.2%Genetic Fallacy0.0%This article: 0.0%Eva Roytburg: 1.4%Fortune: 1.5%Unattributed Quote0.0%This article: 6.9%Eva Roytburg: 2.7%Fortune: 1.3%Quote-first Misdirection6.9%This article: 32.6%Eva Roytburg: 20.9%Fortune: 4.4%Biased Writer Voice32.6%This article: 0.0%Eva Roytburg: 0.0%Fortune: 1.2%Indoctrination0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.3%Politically Left Leaning Bias0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 0.3%Politically Right Leaning Bias0.0%This article: 0.0%Eva Roytburg: 0.0%Fortune: 1.2%Attempt to Sell a Product or S…0.0%

334 words analyzed.

Speakers

1speaker53%attributed speech157writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 13 words • 0.0% coverageWriter's voice • 49 words • 100.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageBloomberg • 37 words • 100.0% coverageBloomberg • 23 words • 100.0% coverageBloomberg • 26 words • 0.0% coverageBloomberg • 11 words • 0.0% coverageBloomberg • 35 words • 0.0% coverageBloomberg • 26 words • 0.0% coverageBloomberg • 19 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverage
Selected voice

Bloomberg

100%flagged-word coverage
177 attributed words100% of attributed speech96% writer coverage
0%25.0%50.0%Biased Writer Voice-25.0 ptsWriter: 45.9%Bloomberg: 20.9%20.9%Quote-first Misdirection+13.0 ptsWriter: 0.0%Bloomberg: 13.0%13.0%

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.