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, 1:05:00 PM

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% (7,769 of 21,886 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. 
Confirmation Bias
4.5%
Anchoring Bias
2.4%
Availability Heuristic
17%
Representativeness Heuristic
0%
Hindsight Bias
8.5%
Overconfidence Bias
0%
Framing Effect
1.3%
Loss Aversion
3.2%
Status Quo Bias
0%
Sunk Cost Effect
0%
Optimism Bias
2.4%
Pessimism Bias
17.8%
Negativity Bias
4%
Self-Serving Bias
0%
Fundamental Attribution Error
0%
Actor-Observer Bias
0%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
6.6%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
4.5%
Primacy Effect
0%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
6.6%
False Dilemma
0%
Slippery Slope
17.8%
Circular Reasoning
4.3%
Hasty Generalization
12.2%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
3.2%
Begging the Question
0%
Post Hoc (False Cause)
21.5%
Tu Quoque
0%
Burden of Proof
0%
Appeal to Nature
0%
Composition/Division
5.1%
Anecdotal
0%
No True Scotsman
0%
Ambiguity (Equivocation)
0%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
4%
Quote-first Misdirection
0%
Biased Writer Voice
6.1%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
4.3%

376 words analyzed.

Analysis

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