BS Summary: This article contains 21 faulty reasoning types, including Politically Left Leaning Bias, Negativity Bias, and Hasty Generalization, with Biased Writer Voice as the most egregious example at 53.7% saturation with 298 hits. Analysis detected 1,760 faulty-reasoning hits from 555 analyzed words, generating a BS Score of 69.8% and a BS Rank of 84% (4,453 of 27,714 articles). This article is worse (more manipulative) than 83.90% of the article peer group.

The US economy grew at a sluggish annual pace of 1.5 percent in the second quarter (against inflation more than twice as high), and it would have been much worse if it weren’t for massive investments in artificial intelligence (AI), which may have disastrous consequences down the road, and “resilient consumer spending.” 
In a nutshell, the economy is being propped up by data center investments and Americans buying stuff. 
But which Americans, and what stuff? 
Regular people are already racking up record credit card debts to deal with Trumpflation, i.e., the higher cost of products affected by the president’s tariffs and the war with Iran. 
And many of them are forced to tighten their belts and make painful choices regarding what kind of things they can afford. 
In other words, they are either consuming less or going into more debt. 
So, how come that consumer spending is “resilient?” 
Because the uber-wealthy elites keep getting richer so fast that they don’t even know what to do with all of that money (apart from buying elections, of course). 
Take billionaire Kevin O’Leary. 
Here he is talking about a $1.8 million watch he bought and how he wept when he got it. 
Kevin O’Leary says he begged Rolex for a mythical $1.8 million watch, then cried when the box opened 
“It is the grail piece of all watches. 
It is the white gold, ruby and diamond Daytona. 
Grown men weep just looking at pictures of this mystical beast” 
“I got on my knees and… pic.twitter.com/zoszEUqNp4 
- Yonan (@yonann) July 28, 2026 
O’Leary recently made news when he falsely claimed that anti-data center activists in Utah were funded by the Chinese government and then had to acknowledge that he had no evidence for those smears. 
He and Fox News (which has apologized on the air for its part in this defamation campaign) are still getting sued, and we hope that they will have to pay the people they defamed. 
A verdict for the plaintiffs would have the added benefit of actually spurring the economy by putting money in the pockets of regular Americans. 
But that’s not the point here. 
What is, however, is that his Rolex brag serves as the perfect illustration that it is the uber-wealthy who are keeping the US out of a recession by buying obscenely expensive luxury items. 
In this case, for example, he spent as much on a watch as would feed nearly 1,800 families of four for an entire month. 
And while those 7,100 people have to eat, nobody needs a white gold, diamond, and ruby watch just to prove how rich he is. 
Let’s also not forget that it’s fat cats like O’Leary who are railing against lawmakers who want all Americans to have health insurance and food security and for the ultra-rich to pay their fair share. 
Oh, and they are doing it on the networks that their billionaire buddies own. 
The point is that reports on “resilient consumer spending” obscure the reality that this spending is not necessarily being done by middle-class families; they mean that a very few people at the top have unlimited money to spend on diamond-studded watches, yachts, and political action committees. 
The Rolex Economy Is Humming, the Timex Economy Is Not originally appeared on WhoWhatWhy 
Article reasoning-pattern comparisonThis article: 14.2%Klaus Marre: 10.2%WhoWhatWhy: 6.2%Confirmation Bias14.2%This article: 0.0%Klaus Marre: 0.7%WhoWhatWhy: 0.6%Anchoring Bias0.0%This article: 7.7%Klaus Marre: 2.7%WhoWhatWhy: 2.6%Availability Heuristic7.7%This article: 0.0%Klaus Marre: 0.8%WhoWhatWhy: 0.9%Representativeness Heuristic0.0%This article: 0.0%Klaus Marre: 1.2%WhoWhatWhy: 1.4%Hindsight Bias0.0%This article: 0.0%Klaus Marre: 1.7%WhoWhatWhy: 1.1%Overconfidence Bias0.0%This article: 5.4%Klaus Marre: 7.8%WhoWhatWhy: 5.0%Framing Effect5.4%This article: 0.0%Klaus Marre: 0.4%WhoWhatWhy: 0.3%Loss Aversion0.0%This article: 0.0%Klaus Marre: 0.9%WhoWhatWhy: 0.6%Status Quo Bias0.0%This article: 0.0%Klaus Marre: 0.0%WhoWhatWhy: 0.3%Sunk Cost Effect0.0%This article: 4.3%Klaus Marre: 0.9%WhoWhatWhy: 2.3%Optimism Bias4.3%This article: 19.5%Klaus Marre: 3.7%WhoWhatWhy: 2.9%Pessimism Bias19.5%This article: 35.0%Klaus Marre: 22.5%WhoWhatWhy: 13.9%Negativity Bias35.0%This article: 0.0%Klaus Marre: 1.4%WhoWhatWhy: 1.3%Self-Serving Bias0.0%This article: 0.0%Klaus Marre: 4.6%WhoWhatWhy: 2.3%Fundamental Attribution Error0.0%This article: 0.0%Klaus Marre: 0.0%WhoWhatWhy: 0.0%Actor-Observer Bias0.0%This article: 11.4%Klaus Marre: 2.0%WhoWhatWhy: 1.6%In-Group Bias11.4%This article: 0.0%Klaus Marre: 2.9%WhoWhatWhy: 1.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Klaus Marre: 0.3%WhoWhatWhy: 0.5%Halo Effect0.0%This article: 0.0%Klaus Marre: 1.4%WhoWhatWhy: 0.5%Horn Effect0.0%This article: 0.0%Klaus Marre: 0.0%WhoWhatWhy: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Klaus Marre: 1.1%WhoWhatWhy: 0.9%Recency Bias0.0%This article: 0.0%Klaus Marre: 0.5%WhoWhatWhy: 0.4%Primacy Effect0.0%This article: 0.0%Klaus Marre: 0.1%WhoWhatWhy: 0.0%Blind-Spot Bias0.0%This article: 18.4%Klaus Marre: 10.7%WhoWhatWhy: 5.2%Ad Hominem18.4%This article: 0.0%Klaus Marre: 1.2%WhoWhatWhy: 0.7%Straw Man0.0%This article: 0.0%Klaus Marre: 1.8%WhoWhatWhy: 2.8%Appeal to Authority0.0%This article: 2.3%Klaus Marre: 2.9%WhoWhatWhy: 2.2%False Dilemma2.3%This article: 0.0%Klaus Marre: 4.5%WhoWhatWhy: 2.1%Slippery Slope0.0%This article: 0.0%Klaus Marre: 0.3%WhoWhatWhy: 0.2%Circular Reasoning0.0%This article: 28.6%Klaus Marre: 16.1%WhoWhatWhy: 9.6%Hasty Generalization28.6%This article: 8.3%Klaus Marre: 0.2%WhoWhatWhy: 0.2%Red Herring8.3%This article: 0.0%Klaus Marre: 0.9%WhoWhatWhy: 0.7%Bandwagon0.0%This article: 12.6%Klaus Marre: 9.4%WhoWhatWhy: 6.0%Appeal to Emotion12.6%This article: 0.0%Klaus Marre: 3.6%WhoWhatWhy: 1.5%Begging the Question0.0%This article: 19.1%Klaus Marre: 2.2%WhoWhatWhy: 1.6%Post Hoc (False Cause)19.1%This article: 0.0%Klaus Marre: 0.2%WhoWhatWhy: 0.1%Tu Quoque0.0%This article: 0.0%Klaus Marre: 1.5%WhoWhatWhy: 1.0%Burden of Proof0.0%This article: 0.0%Klaus Marre: 0.0%WhoWhatWhy: 0.2%Appeal to Nature0.0%This article: 6.5%Klaus Marre: 0.5%WhoWhatWhy: 0.2%Composition/Division6.5%This article: 12.6%Klaus Marre: 2.5%WhoWhatWhy: 2.9%Anecdotal12.6%This article: 0.0%Klaus Marre: 0.2%WhoWhatWhy: 0.2%No True Scotsman0.0%This article: 4.3%Klaus Marre: 1.0%WhoWhatWhy: 0.7%Ambiguity (Equivocation)4.3%This article: 0.0%Klaus Marre: 0.0%WhoWhatWhy: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Klaus Marre: 0.4%WhoWhatWhy: 0.2%Middle Ground0.0%This article: 0.0%Klaus Marre: 0.4%WhoWhatWhy: 0.3%Personal Incredulity0.0%This article: 4.3%Klaus Marre: 1.2%WhoWhatWhy: 0.4%Special Pleading4.3%This article: 0.0%Klaus Marre: 0.2%WhoWhatWhy: 0.1%Genetic Fallacy0.0%This article: 0.0%Klaus Marre: 2.1%WhoWhatWhy: 2.4%Unattributed Quote0.0%This article: 3.4%Klaus Marre: 1.3%WhoWhatWhy: 1.0%Quote-first Misdirection3.4%This article: 53.7%Klaus Marre: 36.7%WhoWhatWhy: 17.3%Biased Writer Voice53.7%This article: 8.3%Klaus Marre: 4.3%WhoWhatWhy: 2.8%Indoctrination8.3%This article: 37.1%Klaus Marre: 23.1%WhoWhatWhy: 9.7%Politically Left Leaning Bias37.1%This article: 0.0%Klaus Marre: 0.3%WhoWhatWhy: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%Klaus Marre: 0.6%WhoWhatWhy: 0.6%Attempt to Sell a Product or S…0.0%

555 words analyzed.

Speakers

2speakers11%attributed speech496writer words
Selected voice

Kevin O’Leary

68%flagged-word coverage
53 attributed words90% of attributed speech90% writer coverage
0%32.5%65.0%Biased Writer Voice-60.1 ptsWriter: 60.1%Kevin O’Leary: 0.0%0.0%Politically Left Leaning B-41.5 ptsWriter: 41.5%Kevin O’Leary: 0.0%0.0%Indoctrination-9.3 ptsWriter: 9.3%Kevin O’Leary: 0.0%0.0%Quote-first Misdirection-3.8 ptsWriter: 3.8%Kevin O’Leary: 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.