Truthout74%

New York Issues US’s First Statewide Moratorium on New Hyperscale Data Centers 25%

By Amy Green33% Dan Gearino25% Ajani Stella25%

7/15/2026, 1:41:03 PM

BS Summary: This article contains 27 faulty reasoning types, including Pessimism Bias, Post Hoc (False Cause), and Negativity Bias, with Appeal to Emotion as the most egregious example at 18.4% saturation with 178 hits. Analysis detected 1,684 faulty-reasoning hits from 968 analyzed words, generating a BS Score of 37.2% and a BS Rank of 25% (16,540 of 21,887 articles). This article is better (less manipulative) than 75.60% of the article peer group.

New York Gov. 
Kathy Hochul signed an executive order Tuesday making the state the first in the nation to implement a moratorium on new hyperscale data centers. 
The Democratic governor said she would pause environmental permits while the state researches and develops a regulatory framework to protect ratepayers, the environment, the energy grid and communities. 
Four hyperscale data centers are already operating in the state, and applications are pending for 39 more. 
The facilities have sparked concerns over their potential energy and water consumption at a time when there is overwhelming scientific consensus about the need to conserve energy and stem the fossil fuel emissions warming the global climate and intensifying disasters. 
“This pause will remain in place for up to one year while New York establishes the strongest possible framework to protect our communities, guardrails to reduce the risk to our energy grid, minimize land disruption, noise pollution and protect our natural resources, especially our water supply,” Hochul said in remarks accompanying the executive order. 
The New York Legislature approved a broader moratorium in June, although there were doubts over whether Hochul, who is up for re-election this year, would sign the measure, as she had said the issue should be left to municipalities. 
Tuesday’s order represents a good first step but does not go as far as the earlier legislation, said Eric Wood, senior environmental program coordinator at the New York Public Interest Research Group, a nonprofit organization. 
Kate Boicourt, the Environmental Defense Fund’s New York state director, said the executive order is the first step to building a “clear set of rules” standardized across the state. 
“There’s things that need to be statewide standards,” Boicourt said. 
“Otherwise, if you’re having specific municipality-by-municipality rules, you are potentially shifting what’s allowed in one area and not being allowed in the other. 
There’s a lot of the clean energy standards that add up to New York’s climate goals that seem to be critical to cross those boundaries that are within the purview of the state.” 
Some business and trade groups decried the moratorium as bad for business. 
“A shortsighted moratorium only accomplishes one thing: It kills good-paying union jobs,” said Mark McManus, general president of the United Association, a labor union for plumbers and pipefitters that has advocated for data center construction. 
The state was one of about a dozen with legislative proposals this year to pause or ban data centers. 
In April, the Maine legislature became the first in the nation to approve a moratorium, but Gov. 
Janet Mills vetoed the measure. 
The effort in New York is important because it is a “trendsetter state,” said Darrell West, a Brookings Institution senior fellow who researches AI and technology policy. 
“What happens there often spreads to other areas. 
So the fact that New York has adopted a one-year moratorium suggests there may be others that follow, and that’s a very big deal for the future of data centers and AI in general,” he said. 
“The public opposition to data centers is widespread across the country. 
It’s not limited to Democratic or Republican areas, urban or rural areas. 
The public worries are broad-based and across the political spectrum, so there could be lots of states that move in this direction.” 
Cushman & Wakefield, the commercial real estate services company, ranked the New York-New Jersey data center market near the bottom of the country’s top dozen markets, with 657 megawatts of projects in operation at the end of 2025. 
For context, the largest market, Virginia, had 11,275 megawatts in operation. 
A moratorium in New York is significant, but much less so than if it had been in one of the bigger markets, which include Portland, Oregon; Columbus, Ohio; and Phoenix. 
Mitch Jones, managing director of policy and litigation for the national advocacy group Food & Water Watch, welcomed the moratorium, saying data centers threaten electricity bills, water supply and air quality. 
“We’re just glad that New Yorkers are going to have a pause to the building of hyperscale data centers in the state, so that communities can better educate themselves about the dangers posed by the data center buildout, and continue to then educate their elected officials about why permanent protections need to be put in place,” Jones said. 
Jones described data centers as a “cross-cutting issue” that unites Democratic and Republican opposition, and said he hopes Hochul’s actions can set a national precedent. 
A Gallup poll published in May showed that nearly three-fourths of Americans oppose construction of data centers in their localities, including over 60 percent of Republicans. 
“It’s going to put further pressure on legislators to actually pass moratorium bills that are being introduced in their state, and it’s going to put pressure on governors to act on their own and to issue executive orders similar to  but maybe a little more aggressive than  the one signed by Governor Hochul today,” Jones said. 
Cole Jermyn, an energy transition attorney with the Environmental Defense Fund, said the next step for New York is for regulatory agencies to debate the details of long-term data center policy. 
“This is something where details really matter, and executive orders aren’t usually the place where you’re trying to do detailed utility regulatory policy,” Jermyn said. 
“The impact of this executive order will depend on that work,” he added. 
Jones said he hopes Hochul’s executive order will prompt New York to extend its pause on data centers by close to the three years Food & Water Watch originally proposed. 
“What we need to do is take this pause, take the studies included in this pause, but we need to go further and we need to go deeper, and that’s probably going to require taking even a longer moratorium,” Jones said. 
Article reasoning-pattern comparisonThis article: 4.2%Amy Green: 1.3%Truthout: 5.8%Confirmation Bias4.2%This article: 0.0%Amy Green: 0.0%Truthout: 0.8%Anchoring Bias0.0%This article: 8.8%Amy Green: 3.0%Truthout: 3.4%Availability Heuristic8.8%This article: 2.8%Amy Green: 0.4%Truthout: 0.9%Representativeness Heuristic2.8%This article: 0.0%Amy Green: 0.0%Truthout: 0.4%Hindsight Bias0.0%This article: 2.6%Amy Green: 2.1%Truthout: 1.3%Overconfidence Bias2.6%This article: 3.6%Amy Green: 8.5%Truthout: 10.0%Framing Effect3.6%This article: 0.0%Amy Green: 0.0%Truthout: 0.5%Loss Aversion0.0%This article: 3.6%Amy Green: 0.5%Truthout: 0.4%Status Quo Bias3.6%This article: 3.1%Amy Green: 0.4%Truthout: 0.2%Sunk Cost Effect3.1%This article: 9.7%Amy Green: 1.4%Truthout: 1.0%Optimism Bias9.7%This article: 15.8%Amy Green: 3.2%Truthout: 2.3%Pessimism Bias15.8%This article: 12.2%Amy Green: 4.7%Truthout: 12.2%Negativity Bias12.2%This article: 6.7%Amy Green: 1.3%Truthout: 0.9%Self-Serving Bias6.7%This article: 4.0%Amy Green: 1.1%Truthout: 1.4%Fundamental Attribution Error4.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.2%Actor-Observer Bias0.0%This article: 2.6%Amy Green: 0.5%Truthout: 1.9%In-Group Bias2.6%This article: 0.0%Amy Green: 0.0%Truthout: 0.7%Out-Group Homogeneity Bias0.0%This article: 3.0%Amy Green: 0.7%Truthout: 1.0%Halo Effect3.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.3%Horn Effect0.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Amy Green: 0.3%Truthout: 1.2%Recency Bias0.0%This article: 4.2%Amy Green: 0.7%Truthout: 0.3%Primacy Effect4.2%This article: 0.0%Amy Green: 0.4%Truthout: 0.0%Blind-Spot Bias0.0%This article: 4.0%Amy Green: 0.6%Truthout: 1.6%Ad Hominem4.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.5%Straw Man0.0%This article: 9.7%Amy Green: 2.6%Truthout: 3.7%Appeal to Authority9.7%This article: 6.0%Amy Green: 1.5%Truthout: 1.9%False Dilemma6.0%This article: 8.0%Amy Green: 1.1%Truthout: 1.5%Slippery Slope8.0%This article: 0.0%Amy Green: 0.2%Truthout: 0.3%Circular Reasoning0.0%This article: 7.9%Amy Green: 8.3%Truthout: 7.7%Hasty Generalization7.9%This article: 0.0%Amy Green: 0.3%Truthout: 0.3%Red Herring0.0%This article: 4.2%Amy Green: 0.6%Truthout: 0.6%Bandwagon4.2%This article: 18.4%Amy Green: 8.2%Truthout: 8.8%Appeal to Emotion18.4%This article: 0.0%Amy Green: 1.2%Truthout: 1.7%Begging the Question0.0%This article: 12.5%Amy Green: 2.5%Truthout: 3.0%Post Hoc (False Cause)12.5%This article: 0.0%Amy Green: 0.0%Truthout: 0.2%Tu Quoque0.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.8%Burden of Proof0.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.1%Appeal to Nature0.0%This article: 0.0%Amy Green: 0.4%Truthout: 0.4%Composition/Division0.0%This article: 0.0%Amy Green: 6.7%Truthout: 2.7%Anecdotal0.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.1%No True Scotsman0.0%This article: 3.2%Amy Green: 1.2%Truthout: 1.5%Ambiguity (Equivocation)3.2%This article: 0.0%Amy Green: 0.0%Truthout: 0.0%Gambler’s Fallacy0.0%This article: 3.1%Amy Green: 0.4%Truthout: 0.1%Middle Ground3.1%This article: 0.0%Amy Green: 0.0%Truthout: 0.1%Personal Incredulity0.0%This article: 0.0%Amy Green: 0.2%Truthout: 0.1%Special Pleading0.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.3%Genetic Fallacy0.0%This article: 0.0%Amy Green: 0.2%Truthout: 1.5%Unattributed Quote0.0%This article: 0.0%Amy Green: 0.1%Truthout: 1.6%Quote-first Misdirection0.0%This article: 1.2%Amy Green: 0.9%Truthout: 9.5%Biased Writer Voice1.2%This article: 8.8%Amy Green: 2.8%Truthout: 2.9%Indoctrination8.8%This article: 0.0%Amy Green: 0.0%Truthout: 7.2%Politically Left Leaning Bias0.0%This article: 0.0%Amy Green: 0.0%Truthout: 0.3%Politically Right Leaning Bias0.0%This article: 0.0%Amy Green: 0.0%Truthout: 1.3%Attempt to Sell a Product or S…0.0%

968 words analyzed.

Speakers

7speakers70%attributed speech293writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageKathy Hochul • 28 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 40 words • 0.0% coverageKathy Hochul • 54 words • 0.0% coverageWriter's voice • 39 words • 0.0% coverageEric Wood • 35 words • 0.0% coverageKate Boicourt • 29 words • 0.0% coverageKate Boicourt • 10 words • 0.0% coverageKate Boicourt • 23 words • 0.0% coverageKate Boicourt • 33 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageMark McManus • 35 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageDarrell West • 27 words • 100.0% coverageDarrell West • 8 words • 0.0% coverageDarrell West • 36 words • 0.0% coverageDarrell West • 11 words • 0.0% coverageDarrell West • 12 words • 0.0% coverageDarrell West • 22 words • 0.0% coverageWriter's voice • 38 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageMitch Jones • 31 words • 0.0% coverageMitch Jones • 58 words • 100.0% coverageMitch Jones • 25 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageMitch Jones • 58 words • 0.0% coverageCole Jermyn • 31 words • 0.0% coverageCole Jermyn • 25 words • 0.0% coverageCole Jermyn • 13 words • 0.0% coverageMitch Jones • 30 words • 0.0% coverageMitch Jones • 41 words • 0.0% coverage
Selected voice

Mark McManus

100%flagged-word coverage
35 attributed words5.2% of attributed speech75% writer coverage
0%2.5%5.0%Biased Writer Voice-4.1 ptsWriter: 4.1%Mark McManus: 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.