What the Box Elder County Data Center could mean for Utah 84%

5/5/2026, 8:17:18 PM

BS Summary: This article contains 4 faulty reasoning types, including Negativity Bias, Halo Effect, and Appeal to Authority, with Framing Effect as the most egregious example at 27% saturation with 38 hits. Analysis detected 138 faulty-reasoning hits from 141 analyzed words, generating a BS Score of 75.9% and a BS Rank of 84% (3,510 of 21,887 articles). This article is worse (more manipulative) than 84.00% of the article peer group.

Dubbed the Stratos Project, the data center is the brainchild of Kevin O'Leary, a Canadian businessman and former "Shark Tank" star, who says the facility will rely on the "best technology." 
When brought fully online, the data center is projected to generate and use nearly double the amount of power already consumed by the entire state of Utah. 
It will also require enough water to support 20,000 local homes. 
Salt Lake Tribune reporter Samantha Moilanen and Atlantic staff writer Matteo Wong will join us to talk about the controversy surrounding the data center and what it means for local communities when hyperscale data centers come to town. 
GUESTS  
Samantha Moilanen | reporter for The Salt Lake Tribune 
Matteo Wong | Staff writer for The Atlantic 
Airdate: May 7, 2026 
Article reasoning-pattern comparisonThis article: 0.0%KUER: 2.8%Confirmation Bias0.0%This article: 0.0%KUER: 1.3%Anchoring Bias0.0%This article: 0.0%KUER: 3.4%Availability Heuristic0.0%This article: 0.0%KUER: 1.2%Representativeness Heuristic0.0%This article: 0.0%KUER: 0.5%Hindsight Bias0.0%This article: 0.0%KUER: 1.9%Overconfidence Bias0.0%This article: 27.0%KUER: 7.4%Framing Effect27.0%This article: 0.0%KUER: 1.3%Loss Aversion0.0%This article: 0.0%KUER: 1.2%Status Quo Bias0.0%This article: 0.0%KUER: 0.3%Sunk Cost Effect0.0%This article: 0.0%KUER: 4.4%Optimism Bias0.0%This article: 0.0%KUER: 2.4%Pessimism Bias0.0%This article: 27.0%KUER: 6.3%Negativity Bias27.0%This article: 0.0%KUER: 2.2%Self-Serving Bias0.0%This article: 0.0%KUER: 0.9%Fundamental Attribution Error0.0%This article: 0.0%KUER: 0.2%Actor-Observer Bias0.0%This article: 0.0%KUER: 1.9%In-Group Bias0.0%This article: 0.0%KUER: 0.6%Out-Group Homogeneity Bias0.0%This article: 22.0%KUER: 2.3%Halo Effect22.0%This article: 0.0%KUER: 0.1%Horn Effect0.0%This article: 0.0%KUER: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%KUER: 1.2%Recency Bias0.0%This article: 0.0%KUER: 0.3%Primacy Effect0.0%This article: 0.0%KUER: 0.1%Blind-Spot Bias0.0%This article: 0.0%KUER: 0.6%Ad Hominem0.0%This article: 0.0%KUER: 0.4%Straw Man0.0%This article: 22.0%KUER: 4.7%Appeal to Authority22.0%This article: 0.0%KUER: 1.7%False Dilemma0.0%This article: 0.0%KUER: 1.1%Slippery Slope0.0%This article: 0.0%KUER: 0.2%Circular Reasoning0.0%This article: 0.0%KUER: 4.1%Hasty Generalization0.0%This article: 0.0%KUER: 0.2%Red Herring0.0%This article: 0.0%KUER: 0.7%Bandwagon0.0%This article: 0.0%KUER: 5.6%Appeal to Emotion0.0%This article: 0.0%KUER: 0.7%Begging the Question0.0%This article: 0.0%KUER: 2.4%Post Hoc (False Cause)0.0%This article: 0.0%KUER: 0.1%Tu Quoque0.0%This article: 0.0%KUER: 0.4%Burden of Proof0.0%This article: 0.0%KUER: 0.2%Appeal to Nature0.0%This article: 0.0%KUER: 0.3%Composition/Division0.0%This article: 0.0%KUER: 3.1%Anecdotal0.0%This article: 0.0%KUER: 0.1%No True Scotsman0.0%This article: 0.0%KUER: 1.5%Ambiguity (Equivocation)0.0%This article: 0.0%KUER: 0.0%Gambler’s Fallacy0.0%This article: 0.0%KUER: 0.2%Middle Ground0.0%This article: 0.0%KUER: 0.1%Personal Incredulity0.0%This article: 0.0%KUER: 0.1%Special Pleading0.0%This article: 0.0%KUER: 0.2%Genetic Fallacy0.0%This article: 0.0%KUER: 0.8%Unattributed Quote0.0%This article: 0.0%KUER: 0.7%Quote-first Misdirection0.0%This article: 0.0%KUER: 2.2%Biased Writer Voice0.0%This article: 0.0%KUER: 1.6%Indoctrination0.0%This article: 0.0%KUER: 0.8%Politically Left Leaning Bias0.0%This article: 0.0%KUER: 0.3%Politically Right Leaning Bias0.0%This article: 0.0%KUER: 1.0%Attempt to Sell a Product or S…0.0%

141 words analyzed.

Speakers

No attributed speakers were identified in this analysis.

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Analysis

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