One fallen power line exposed a growing AI data center problem. Here's how to fix it. 65%

By Tim De Chant42%

7/25/2026, 6:05:00 AM

BS Summary: This article contains 21 faulty reasoning types, including Pessimism Bias, Slippery Slope, and Availability Heuristic, with Post Hoc (False Cause) as the most egregious example at 21.5% saturation with 81 hits. Analysis detected 592 faulty-reasoning hits from 376 analyzed words, generating a BS Score of 59.1% and a BS Rank of 65% (7,770 of 21,887 articles). This article is worse (more manipulative) than 64.50% of the article peer group.

A power line went down outside of Washington, DC, this week. 
Normally, the grid would only need a few seconds to recover from such an event. 
But this one took more than 10 minutes because more than 3 gigawatts of data centers stopped drawing power nearly simultaneously. 
The event caused voltage across the PJM grid to spike from Northern Virginia to Chicago, according to data collected by Ting Labs, a startup that runs an IoT sensor network out of people’s electrical sockets. 
The event didn’t cause a blackout, but it did cause lights across the region to flicker. 
The incident demonstrated the effect that data centers can have on the grid  an outcome that experts believe will become more frequent. 
Northern Virginia, which is in PJM’s territory, is home to the highest concentration of data centers in the world. 
“It’s the canary in the coal mine,” Ricardo de Azevedo, CTO at ON.Energy, told TechCrunch. 
These sorts of events involving large loads like data centers are “happening more and more,” he added. 
The event echoes one that happened two years ago, also on PJM’s grid, and it could foreshadow larger events if data centers aren’t built to more elegantly handle disruptions to power supplies. 
The PJM Interconnection manages grids from New Jersey to Illinois and serves 67 million customers, making it the largest grid operator in the United States. 
When the power line went down this week, it triggered data centers to switch to backup power, which removed their load from the grid. 
As more data centers made the switch, they removed greater amounts of load from the grid. 
What started as a relatively small drop in supply became an even larger drop in demand, sending supply surging and causing light bulbs to flicker. 
The mass disconnection this week was twice as large as a similar event in 2024, when 60 data centers simultaneously disconnected, pulling 1.5 gigawatts of load from the grid. 
Back then, data centers accounted for about 6% of PJM’s load, according to Synapse Energy Economics. 
By 2040, they are expected to make up 24%. 
If the problem isn’t addressed soon, things could get a lot worse. 
Article reasoning-pattern comparisonThis article: 4.5%Tim De Chant: 3.3%TechCrunch: 3.0%Confirmation Bias4.5%This article: 2.4%Tim De Chant: 2.2%TechCrunch: 1.4%Anchoring Bias2.4%This article: 17.0%Tim De Chant: 3.1%TechCrunch: 3.5%Availability Heuristic17.0%This article: 0.0%Tim De Chant: 0.6%TechCrunch: 1.1%Representativeness Heuristic0.0%This article: 8.5%Tim De Chant: 0.7%TechCrunch: 0.6%Hindsight Bias8.5%This article: 0.0%Tim De Chant: 2.4%TechCrunch: 2.5%Overconfidence Bias0.0%This article: 1.3%Tim De Chant: 4.3%TechCrunch: 4.8%Framing Effect1.3%This article: 3.2%Tim De Chant: 0.1%TechCrunch: 0.6%Loss Aversion3.2%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.6%Status Quo Bias0.0%This article: 0.0%Tim De Chant: 0.2%TechCrunch: 0.2%Sunk Cost Effect0.0%This article: 2.4%Tim De Chant: 3.0%TechCrunch: 4.9%Optimism Bias2.4%This article: 17.8%Tim De Chant: 5.0%TechCrunch: 1.3%Pessimism Bias17.8%This article: 4.0%Tim De Chant: 8.3%TechCrunch: 5.0%Negativity Bias4.0%This article: 0.0%Tim De Chant: 0.7%TechCrunch: 2.1%Self-Serving Bias0.0%This article: 0.0%Tim De Chant: 1.0%TechCrunch: 0.5%Fundamental Attribution Error0.0%This article: 0.0%Tim De Chant: 0.2%TechCrunch: 0.1%Actor-Observer Bias0.0%This article: 0.0%Tim De Chant: 0.1%TechCrunch: 0.6%In-Group Bias0.0%This article: 0.0%Tim De Chant: 0.3%TechCrunch: 0.3%Out-Group Homogeneity Bias0.0%This article: 6.6%Tim De Chant: 2.4%TechCrunch: 3.5%Halo Effect6.6%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.1%Horn Effect0.0%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.0%Dunning-Kruger Effect0.0%This article: 4.5%Tim De Chant: 1.7%TechCrunch: 2.3%Recency Bias4.5%This article: 0.0%Tim De Chant: 0.2%TechCrunch: 0.3%Primacy Effect0.0%This article: 0.0%Tim De Chant: 0.4%TechCrunch: 0.1%Blind-Spot Bias0.0%This article: 0.0%Tim De Chant: 1.0%TechCrunch: 0.3%Ad Hominem0.0%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.6%Straw Man0.0%This article: 6.6%Tim De Chant: 3.3%TechCrunch: 4.4%Appeal to Authority6.6%This article: 0.0%Tim De Chant: 1.6%TechCrunch: 1.7%False Dilemma0.0%This article: 17.8%Tim De Chant: 2.7%TechCrunch: 0.7%Slippery Slope17.8%This article: 4.3%Tim De Chant: 0.5%TechCrunch: 0.2%Circular Reasoning4.3%This article: 12.2%Tim De Chant: 7.4%TechCrunch: 6.0%Hasty Generalization12.2%This article: 0.0%Tim De Chant: 0.5%TechCrunch: 0.2%Red Herring0.0%This article: 0.0%Tim De Chant: 0.2%TechCrunch: 1.1%Bandwagon0.0%This article: 3.2%Tim De Chant: 2.8%TechCrunch: 2.2%Appeal to Emotion3.2%This article: 0.0%Tim De Chant: 0.3%TechCrunch: 0.6%Begging the Question0.0%This article: 21.5%Tim De Chant: 6.3%TechCrunch: 2.9%Post Hoc (False Cause)21.5%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.1%Tu Quoque0.0%This article: 0.0%Tim De Chant: 0.5%TechCrunch: 0.5%Burden of Proof0.0%This article: 0.0%Tim De Chant: 0.4%TechCrunch: 0.2%Appeal to Nature0.0%This article: 5.1%Tim De Chant: 0.8%TechCrunch: 0.3%Composition/Division5.1%This article: 0.0%Tim De Chant: 2.4%TechCrunch: 2.4%Anecdotal0.0%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.1%No True Scotsman0.0%This article: 0.0%Tim De Chant: 2.5%TechCrunch: 2.0%Ambiguity (Equivocation)0.0%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Tim De Chant: 0.2%TechCrunch: 0.2%Middle Ground0.0%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.0%Personal Incredulity0.0%This article: 0.0%Tim De Chant: 0.2%TechCrunch: 0.1%Special Pleading0.0%This article: 0.0%Tim De Chant: 0.5%TechCrunch: 0.1%Genetic Fallacy0.0%This article: 4.0%Tim De Chant: 0.5%TechCrunch: 2.0%Unattributed Quote4.0%This article: 0.0%Tim De Chant: 0.6%TechCrunch: 0.7%Quote-first Misdirection0.0%This article: 6.1%Tim De Chant: 7.9%TechCrunch: 4.6%Biased Writer Voice6.1%This article: 0.0%Tim De Chant: 0.5%TechCrunch: 0.8%Indoctrination0.0%This article: 0.0%Tim De Chant: 0.0%TechCrunch: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Tim De Chant: 0.5%TechCrunch: 0.1%Politically Right Leaning Bias0.0%This article: 4.3%Tim De Chant: 1.0%TechCrunch: 4.9%Attempt to Sell a Product or S…4.3%

376 words analyzed.

Speakers

1speaker8.5%attributed speech344writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 11 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 35 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 19 words • 0.0% coverageRicardo de Azevedo • 15 words • 100.0% coverageRicardo de Azevedo • 17 words • 0.0% coverageWriter's voice • 32 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverage
Selected voice

Ricardo de Azevedo

100%flagged-word coverage
32 attributed words100% of attributed speech78% writer coverage
0%25.0%50.0%Unattributed Quote+46.9 ptsWriter: 0.0%Ricardo de Azevedo: 46.9%46.9%Biased Writer Voice-6.7 ptsWriter: 6.7%Ricardo de Azevedo: 0.0%0.0%Attempt to Sell a Product -4.7 ptsWriter: 4.7%Ricardo de Azevedo: 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.