New York’s Ban on the Future ⁠95%

By Josh Wolfe⁠0%

7/15/2026, 5:35:24 PM

BS Summary: This article contains 22 faulty reasoning types, including Framing Effect, Negativity Bias, and Post Hoc (False Cause), with Biased Writer Voice as the most egregious example at 73.6% saturation with 128 hits. Analysis detected 835 faulty-reasoning hits from 174 analyzed words, generating a BS Score of 90.8% and a BS Rank of ⁠95% (1,264 of 21,886 articles). This article is worse (more manipulative) than 94.20% of the article peer group.

New York, birthplace of the power grid, the transistor’s commercial triumph, and the modern corporation, just became the first state in America to ban the future for at least a year. 
This week, Governor Kathy Hochul signed an executive order imposing a moratorium on new data centers. 
She has sold the policy as a prudent pause to protect electricity bills, water, and the grid. 
“As data-center development threatens to hike up utility bills, deplete our natural resources, and create uncertainty for New Yorkers, it’s my responsibility to take action and lead,” she said Tuesday. 
But strip away the press-release piety and you find something simpler, sadder, and short-sighted: pure political posturing. 
Why sign this order now? 
Because the political winds shifted and Albany licked its finger. 
A recent Siena poll found that 46 percent of voters, squeezed by electric bills up nearly 68 percent since 2019, support a moratorium on data-center construction, and Hochul, facing a reelection battle this year, clearly thinks her anti-data-center stance is good politics. 
Article reasoning-pattern comparisonThis article: 19.5%Josh Wolfe: 25.4%The FP: 5.8%Confirmation Bias19.5%This article: 0.0%Josh Wolfe: 4.5%The FP: 0.9%Anchoring Bias0.0%This article: 24.1%Josh Wolfe: 6.0%The FP: 4.1%Availability Heuristic24.1%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.8%Representativeness Heuristic0.0%This article: 5.7%Josh Wolfe: 1.4%The FP: 1.5%Hindsight Bias5.7%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.5%Overconfidence Bias0.0%This article: 38.5%Josh Wolfe: 32.0%The FP: 9.5%Framing Effect38.5%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.5%Loss Aversion0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.5%Status Quo Bias0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.1%Sunk Cost Effect0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.3%Optimism Bias0.0%This article: 27.6%Josh Wolfe: 6.9%The FP: 1.6%Pessimism Bias27.6%This article: 37.4%Josh Wolfe: 23.9%The FP: 10.8%Negativity Bias37.4%This article: 24.1%Josh Wolfe: 6.0%The FP: 1.4%Self-Serving Bias24.1%This article: 9.8%Josh Wolfe: 23.3%The FP: 1.3%Fundamental Attribution Error9.8%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.1%Actor-Observer Bias0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.9%In-Group Bias0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.2%Out-Group Homogeneity Bias0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.9%Halo Effect0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.4%Horn Effect0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.0%Dunning-Kruger Effect0.0%This article: 24.1%Josh Wolfe: 6.0%The FP: 2.1%Recency Bias24.1%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.1%Primacy Effect0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.1%Blind-Spot Bias0.0%This article: 19.5%Josh Wolfe: 13.6%The FP: 2.3%Ad Hominem19.5%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.0%Straw Man0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 3.2%Appeal to Authority0.0%This article: 9.8%Josh Wolfe: 2.4%The FP: 2.5%False Dilemma9.8%This article: 0.0%Josh Wolfe: 0.0%The FP: 1.1%Slippery Slope0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.2%Circular Reasoning0.0%This article: 0.0%Josh Wolfe: 1.4%The FP: 8.9%Hasty Generalization0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.3%Red Herring0.0%This article: 24.1%Josh Wolfe: 12.1%The FP: 1.2%Bandwagon24.1%This article: 17.2%Josh Wolfe: 12.9%The FP: 5.8%Appeal to Emotion17.2%This article: 17.2%Josh Wolfe: 6.8%The FP: 1.5%Begging the Question17.2%This article: 29.9%Josh Wolfe: 13.5%The FP: 2.7%Post Hoc (False Cause)29.9%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.2%Tu Quoque0.0%This article: 2.9%Josh Wolfe: 0.7%The FP: 0.6%Burden of Proof2.9%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.1%Appeal to Nature0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.4%Composition/Division0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 3.2%Anecdotal0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.1%No True Scotsman0.0%This article: 21.3%Josh Wolfe: 5.3%The FP: 2.1%Ambiguity (Equivocation)21.3%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.2%Middle Ground0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.0%Personal Incredulity0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.2%Special Pleading0.0%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.3%Genetic Fallacy0.0%This article: 17.2%Josh Wolfe: 8.6%The FP: 2.5%Unattributed Quote17.2%This article: 17.2%Josh Wolfe: 4.3%The FP: 1.9%Quote-first Misdirection17.2%This article: 73.6%Josh Wolfe: 64.9%The FP: 15.0%Biased Writer Voice73.6%This article: 9.8%Josh Wolfe: 2.4%The FP: 2.8%Indoctrination9.8%This article: 0.0%Josh Wolfe: 0.0%The FP: 0.5%Politically Left Leaning Bias0.0%This article: 0.0%Josh Wolfe: 2.4%The FP: 3.0%Politically Right Leaning Bias0.0%This article: 9.2%Josh Wolfe: 2.3%The FP: 4.6%Attempt to Sell a Product or S…9.2%

174 words analyzed.

Speakers

2speakers51%attributed speech86writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 6 words • 100.0% coverageWriter's voice • 31 words • 100.0% coverageKathy Hochul • 16 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageKathy Hochul • 30 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 5 words • 100.0% coverageWriter's voice • 10 words • 100.0% coverageSiena poll • 42 words • 100.0% coverage
Selected voice

Siena poll

100%flagged-word coverage
42 attributed words48% of attributed speech100% writer coverage
0%50.0%100.0%Biased Writer Voice+0.0 ptsWriter: 100.0%Siena poll: 100.0%100.0%Indoctrination-19.8 ptsWriter: 19.8%Siena poll: 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.