Power companies can seize private land to make way for new AI data center transmission lines, report says — takeovers could be implemented using eminent domain law when private citizens refuse to sell land ⁠40%

By Etiido Uko⁠32%

7/20/2026, 1:00:47 PM

BS Summary: This article contains 22 faulty reasoning types, including Negativity Bias, Framing Effect, and Appeal to Authority, with Unattributed Quote as the most egregious example at 19% saturation with 92 hits. Analysis detected 800 faulty-reasoning hits from 483 analyzed words, generating a BS Score of 45.1% and a BS Rank of ⁠40% (13,193 of 21,887 articles). This article is better (less manipulative) than 60.30% of the article peer group.

A report by The Conversation has claimed that power companies can seize private land to make way for new transmission lines needed to meet the surging electricity demand of data centers. 
According to the July 16 report by Aaron Walayat, Assistant Professor of Law at the University of Dayton, power companies can use eminent domain — the legal authority that grants the government the power to take private property and convert it to public use in exchange for compensation — to implement the takeovers. 
(Image credit: Microsoft) Photonics and high-speed data movement is the next big AI bottleneck 
The data center cooling state of play 
Massive AI data center buildouts are squeezing energy supplies 
Ultra Ethernet: The data center interconnection of tomorrow 
The AI boom has led to a surge in data centers in the U.S., with thousands already operational and several more planned or under construction. 
While the massive superclusters are necessary for the technological revolution AI has brought about, there's growing opposition to their construction over several concerns. 
Among them are land use, noise pollution, water usage, and the impact of immense electricity consumption , issues that have reportedly made 70% of Americans opposed to building data centers nearby . 
In many instances, data centers draw the required electricity from the grid. 
As the industry enters the gigawatt era, utility companies are under pressure to increase supply to meet surging demand. 
This requires building new power infrastructure, such as transmission lines, which often have to cross private land. 
When this happens, the power companies try to buy the land. 
Should the owner refuse, the government can force a sale through the eminent domain law. 
The law grants the government the power to take private land, regardless of the owner's consent, provided that the land is for public use and the owner receives just compensation. 
The government can also delegate the power to “private entities or common carriers,” such as utility companies. 
It is this legal authority that power companies can enact to implement the takeovers. 
According to the report, the law does not automatically grant infallible authority. 
The company must prove that the infrastructure will be for public use. 
Several states also reserve the right to interpret eminent domain laws according to their own constitutions. 
The report highlights another layer of legalities amid ongoing data center tensions. 
Opponents have successfully blocked 75 planned data center projects in the first quarter of 2026 , including the 2,100-acre Digital Gateway project, eventually canceled over a newspaper-notice technicality . 
On the other hand, several other projects have gone ahead, often with community support. 
Meta recently announced plans to expand its Hyperion AI supercluster from 2 GW to 5 GW . 
Article reasoning-pattern comparisonThis article: 0.0%Etiido Uko: 2.4%Tom's Hardware: 3.8%Confirmation Bias0.0%This article: 0.0%Etiido Uko: 2.0%Tom's Hardware: 2.3%Anchoring Bias0.0%This article: 11.8%Etiido Uko: 2.9%Tom's Hardware: 3.5%Availability Heuristic11.8%This article: 1.7%Etiido Uko: 0.8%Tom's Hardware: 1.1%Representativeness Heuristic1.7%This article: 0.0%Etiido Uko: 0.1%Tom's Hardware: 0.5%Hindsight Bias0.0%This article: 0.0%Etiido Uko: 1.2%Tom's Hardware: 3.5%Overconfidence Bias0.0%This article: 14.7%Etiido Uko: 9.2%Tom's Hardware: 9.2%Framing Effect14.7%This article: 0.0%Etiido Uko: 0.1%Tom's Hardware: 0.9%Loss Aversion0.0%This article: 3.1%Etiido Uko: 0.6%Tom's Hardware: 0.7%Status Quo Bias3.1%This article: 0.0%Etiido Uko: 0.2%Tom's Hardware: 0.3%Sunk Cost Effect0.0%This article: 1.7%Etiido Uko: 6.5%Tom's Hardware: 6.0%Optimism Bias1.7%This article: 11.6%Etiido Uko: 1.4%Tom's Hardware: 2.0%Pessimism Bias11.6%This article: 17.4%Etiido Uko: 5.1%Tom's Hardware: 6.5%Negativity Bias17.4%This article: 2.3%Etiido Uko: 1.8%Tom's Hardware: 1.3%Self-Serving Bias2.3%This article: 0.0%Etiido Uko: 0.3%Tom's Hardware: 0.6%Fundamental Attribution Error0.0%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.2%Actor-Observer Bias0.0%This article: 0.0%Etiido Uko: 0.2%Tom's Hardware: 0.6%In-Group Bias0.0%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.3%Out-Group Homogeneity Bias0.0%This article: 0.0%Etiido Uko: 1.1%Tom's Hardware: 2.8%Halo Effect0.0%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.0%Horn Effect0.0%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.0%Dunning-Kruger Effect0.0%This article: 9.5%Etiido Uko: 1.0%Tom's Hardware: 2.0%Recency Bias9.5%This article: 0.0%Etiido Uko: 1.1%Tom's Hardware: 0.6%Primacy Effect0.0%This article: 0.0%Etiido Uko: 0.1%Tom's Hardware: 0.1%Blind-Spot Bias0.0%This article: 0.0%Etiido Uko: 0.5%Tom's Hardware: 0.2%Ad Hominem0.0%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.2%Straw Man0.0%This article: 13.5%Etiido Uko: 4.5%Tom's Hardware: 5.4%Appeal to Authority13.5%This article: 7.0%Etiido Uko: 1.2%Tom's Hardware: 2.0%False Dilemma7.0%This article: 0.0%Etiido Uko: 0.7%Tom's Hardware: 1.0%Slippery Slope0.0%This article: 3.5%Etiido Uko: 0.1%Tom's Hardware: 0.1%Circular Reasoning3.5%This article: 1.9%Etiido Uko: 3.8%Tom's Hardware: 6.1%Hasty Generalization1.9%This article: 2.5%Etiido Uko: 0.3%Tom's Hardware: 0.3%Red Herring2.5%This article: 6.6%Etiido Uko: 0.8%Tom's Hardware: 1.1%Bandwagon6.6%This article: 0.0%Etiido Uko: 2.5%Tom's Hardware: 3.0%Appeal to Emotion0.0%This article: 0.0%Etiido Uko: 0.5%Tom's Hardware: 0.8%Begging the Question0.0%This article: 5.2%Etiido Uko: 2.5%Tom's Hardware: 3.5%Post Hoc (False Cause)5.2%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.1%Tu Quoque0.0%This article: 2.5%Etiido Uko: 0.5%Tom's Hardware: 0.8%Burden of Proof2.5%This article: 0.0%Etiido Uko: 0.3%Tom's Hardware: 0.3%Appeal to Nature0.0%This article: 0.0%Etiido Uko: 0.7%Tom's Hardware: 0.6%Composition/Division0.0%This article: 12.6%Etiido Uko: 1.6%Tom's Hardware: 1.6%Anecdotal12.6%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.0%No True Scotsman0.0%This article: 5.8%Etiido Uko: 2.8%Tom's Hardware: 3.4%Ambiguity (Equivocation)5.8%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.0%Gambler’s Fallacy0.0%This article: 4.8%Etiido Uko: 0.1%Tom's Hardware: 0.2%Middle Ground4.8%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.0%Personal Incredulity0.0%This article: 0.0%Etiido Uko: 0.4%Tom's Hardware: 0.2%Special Pleading0.0%This article: 0.0%Etiido Uko: 0.1%Tom's Hardware: 0.1%Genetic Fallacy0.0%This article: 19.0%Etiido Uko: 1.7%Tom's Hardware: 2.4%Unattributed Quote19.0%This article: 7.0%Etiido Uko: 0.7%Tom's Hardware: 0.9%Quote-first Misdirection7.0%This article: 0.0%Etiido Uko: 3.3%Tom's Hardware: 7.1%Biased Writer Voice0.0%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 1.3%Indoctrination0.0%This article: 0.0%Etiido Uko: 0.1%Tom's Hardware: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Etiido Uko: 0.0%Tom's Hardware: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Etiido Uko: 0.5%Tom's Hardware: 3.3%Attempt to Sell a Product or S…0.0%

483 words analyzed.

Speakers

3speakers17%attributed speech399writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 34 words • 100.0% coverageWriter's voice • 31 words • 100.0% coverageAaron Walayat • 53 words • 0.0% coverageMicrosoft • 14 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 32 words • 100.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 29 words • 100.0% coverageWriter's voice • 14 words • 0.0% coverageMeta • 17 words • 0.0% coverage
Selected voice

Microsoft

100%flagged-word coverage
14 attributed words17% of attributed speech76% writer coverage
0%12.5%25.0%Unattributed Quote-23.1 ptsWriter: 23.1%Microsoft: 0.0%0.0%Quote-first Misdirection-8.5 ptsWriter: 8.5%Microsoft: 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.