BS Summary: This article contains 31 faulty reasoning types, including Hasty Generalization, Negativity Bias, and False Dilemma, with Biased Writer Voice as the most egregious example at 35.4% saturation with 286 hits. Analysis detected 2,410 faulty-reasoning hits from 808 analyzed words, generating a BS Score of 79.1% and a BS Rank of 86% (2,850 of 20,407 articles). This article is worse (more manipulative) than 86.00% of the article peer group.

“You don’t have to be a weatherman to know which way the wind is blowing,” Bob Dylan wrote in 1965. 
For election season 2026, artificial intelligence (AI) is blowing at gale force. 
The flashpoint has been data centers, the multi-football field-sized computing facilities that power AI. 
Fundamentally, this is a fight about power and whether it will be exercised by democratic institutions or those that control the infrastructure of AI. 
Local citizen outrage has taken its toll. 
The first three months of 2026 saw local data center opposition block or delay 75 projects worth $130 billion in planned construction, according to Data Center Watch. 
This was roughly the same number of projects affected as in all 12 months of 2025. 
AI mega centers have become the symbol of citizen frustration about AI. 
As the most visible manifestation of AI, they have become the proxy for citizen feedback on AI itself. 
The debate over land use also represents the crystallization of broader public concern about AI’s effect on American lives and livelihood. 
“Concerns over data centers relate to broader worries that the rapid ​expansion of AI could upend the labor market,” Reuters reported. 
“Americans don’t know how to fight AI. 
So they’re fighting data centers,” a Vox headline explained. 
As AI leaps from technology to politics, the central question becomes who is in charge: democratic structures or autocratic executives. 
The first decades of the digital era saw a small handful of executives make decisions that affected the rest of us. 
Those same companies are the primary movers making the rules for the AI era as well. 
Long before the public was introduced to large language models and chatbots, early machine intelligence algorithms manipulated online services to optimize for engagement. 
The result harvested unprecedented amounts of personal information, amplified misinformation, and concentrated decisionmaking power in the hands of a few. 
These companies became pseudo-governments to make their own rules in their own self-interest. 
Many of those whose decisions shaped the online experience and social media now seek to make the decisions for computerized cognition. 
As a New York Times commentary observed, “Social media was the first contact between A.I. and humanity, and humanity lost.” 
The AI era is too important to all of us to allow such non-democratic decisionmaking to continue. 
Of course, the United States should lead in AI. 
The issue is whether that leadership will be accountable to democratic institutions or concentrated in the hands of a few private actors. 
AI has thus leapt from a technology issue to a political issue. 
It is now a question of power and who will control whether the infrastructure of the 21st century serves the public interest or the interests of the tech oligarchs and their investors. 
Fully aware of this challenge and that the local data center movement could metastasize to shape national AI policy, those financing and directing the development of AI have been loosening their purse strings to fund political activity. 
One of those, Leading the Future, a super PAC, was launched by industry luminaries, reportedly with $50 million from AI investor Andreessen Horowitz and $50 million from OpenAI’s president Greg Brockman. 
Thanks to deep pockets such as these, the PAC began with $140 million in its coffers for the purpose of “identifying, maintaining, and growing pro-AI candidates.” 
Many of those working for the Silicon Valley powerhouses have pushed back, but their wallets are significantly smaller. 
The Guardrails Alliance, organized by rank-and-file employees of the dominant AI companies, has been collecting small-dollar donations. 
“AI billionaires are buying our elections. 
We’re fighting back,” they proclaim. 
An antidote to the proposition that AI should be largely free of oversight, the group advocates for establishing guardrails for the development and implementation of AI rather than relying on the decisions of the industry. 
The political issues are bipartisan. 
Republican Sen. 
Josh Hawley (R-Mo.) worries, “We are watching a handful of companies assemble a concentration of capital, information, and political power without precedent in the American experience.” 
Democratic Sen. 
Elizabeth Warren (D-Mass.) warns, “Today’s big tech companies have too much power over our economy, our society, and our democracy. 
They’ve bulldozed competition, used our private information for profit, and tilted the playing field against everyone else. 
And in the process, they have hurt small businesses and stifled innovation.” 
Arriving from opposite ends of the political spectrum, both senators identify the emerging political question for the election and beyond: How much economic, informational, and political power should be concentrated in a small number of technology firms? 
As we enter the heart of the political season, the Economist distilled the issue into a single question: “Five men control AI. 
Who controls them?” 
That is a question that will now be put to the people. 
The debate over AI has become a referendum on democratic accountability itself. 
Article reasoning-pattern comparisonThis article: 3.2%Tom Wheeler: 4.3%Brookings: 4.2%Confirmation Bias3.2%This article: 2.0%Tom Wheeler: 3.1%Brookings: 0.8%Anchoring Bias2.0%This article: 6.7%Tom Wheeler: 3.7%Brookings: 2.6%Availability Heuristic6.7%This article: 4.1%Tom Wheeler: 3.1%Brookings: 0.8%Representativeness Heuristic4.1%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.7%Hindsight Bias0.0%This article: 7.8%Tom Wheeler: 2.6%Brookings: 2.6%Overconfidence Bias7.8%This article: 15.1%Tom Wheeler: 10.4%Brookings: 5.2%Framing Effect15.1%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.4%Loss Aversion0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.6%Status Quo Bias0.0%This article: 3.2%Tom Wheeler: 1.1%Brookings: 0.1%Sunk Cost Effect3.2%This article: 1.5%Tom Wheeler: 0.5%Brookings: 3.0%Optimism Bias1.5%This article: 8.9%Tom Wheeler: 3.8%Brookings: 1.8%Pessimism Bias8.9%This article: 23.8%Tom Wheeler: 13.7%Brookings: 5.5%Negativity Bias23.8%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.7%Self-Serving Bias0.0%This article: 1.6%Tom Wheeler: 0.5%Brookings: 0.7%Fundamental Attribution Error1.6%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.2%Actor-Observer Bias0.0%This article: 3.1%Tom Wheeler: 1.4%Brookings: 0.7%In-Group Bias3.1%This article: 2.6%Tom Wheeler: 0.9%Brookings: 0.4%Out-Group Homogeneity Bias2.6%This article: 0.0%Tom Wheeler: 0.0%Brookings: 1.3%Halo Effect0.0%This article: 0.0%Tom Wheeler: 1.9%Brookings: 0.0%Horn Effect0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.0%Dunning-Kruger Effect0.0%This article: 2.0%Tom Wheeler: 1.3%Brookings: 1.2%Recency Bias2.0%This article: 4.6%Tom Wheeler: 1.5%Brookings: 0.3%Primacy Effect4.6%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.1%Blind-Spot Bias0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.2%Ad Hominem0.0%This article: 0.0%Tom Wheeler: 1.4%Brookings: 0.2%Straw Man0.0%This article: 22.8%Tom Wheeler: 8.5%Brookings: 3.9%Appeal to Authority22.8%This article: 23.1%Tom Wheeler: 14.5%Brookings: 1.8%False Dilemma23.1%This article: 0.0%Tom Wheeler: 2.4%Brookings: 1.4%Slippery Slope0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.2%Circular Reasoning0.0%This article: 25.6%Tom Wheeler: 22.0%Brookings: 5.3%Hasty Generalization25.6%This article: 2.7%Tom Wheeler: 0.9%Brookings: 0.1%Red Herring2.7%This article: 0.6%Tom Wheeler: 0.4%Brookings: 0.3%Bandwagon0.6%This article: 20.0%Tom Wheeler: 11.1%Brookings: 2.2%Appeal to Emotion20.0%This article: 3.0%Tom Wheeler: 2.1%Brookings: 0.8%Begging the Question3.0%This article: 12.5%Tom Wheeler: 5.0%Brookings: 3.8%Post Hoc (False Cause)12.5%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.0%Tu Quoque0.0%This article: 1.5%Tom Wheeler: 0.5%Brookings: 0.2%Burden of Proof1.5%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.2%Appeal to Nature0.0%This article: 2.2%Tom Wheeler: 1.6%Brookings: 0.3%Composition/Division2.2%This article: 0.0%Tom Wheeler: 0.0%Brookings: 1.5%Anecdotal0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.1%No True Scotsman0.0%This article: 9.5%Tom Wheeler: 3.2%Brookings: 1.7%Ambiguity (Equivocation)9.5%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.1%Middle Ground0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.0%Personal Incredulity0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.1%Special Pleading0.0%This article: 0.0%Tom Wheeler: 0.0%Brookings: 0.0%Genetic Fallacy0.0%This article: 20.0%Tom Wheeler: 6.7%Brookings: 1.1%Unattributed Quote20.0%This article: 3.8%Tom Wheeler: 3.8%Brookings: 0.3%Quote-first Misdirection3.8%This article: 35.4%Tom Wheeler: 18.6%Brookings: 2.4%Biased Writer Voice35.4%This article: 18.7%Tom Wheeler: 8.5%Brookings: 2.4%Indoctrination18.7%This article: 0.0%Tom Wheeler: 2.1%Brookings: 1.2%Politically Left Leaning Bias0.0%This article: 0.0%Tom Wheeler: 1.1%Brookings: 0.2%Politically Right Leaning Bias0.0%This article: 6.6%Tom Wheeler: 2.2%Brookings: 0.8%Attempt to Sell a Product or S…6.6%

808 words analyzed.

Speakers

10speakers38%attributed speech505writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 100.0% coverageBob Dylan • 20 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 24 words • 100.0% coverageWriter's voice • 7 words • 100.0% coverageData Center Watch • 27 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 21 words • 100.0% coverageReuters • 21 words • 100.0% coverageWriter's voice • 7 words • 100.0% coverageVox • 9 words • 100.0% coverageWriter's voice • 20 words • 100.0% coverageWriter's voice • 21 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 20 words • 100.0% coverageWriter's voice • 13 words • 100.0% coverageWriter's voice • 21 words • 100.0% coverageNew York Times • 20 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 9 words • 100.0% coverageWriter's voice • 22 words • 100.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 32 words • 100.0% coverageWriter's voice • 37 words • 100.0% coverageLeading the Future • 31 words • 100.0% coverageLeading the Future • 26 words • 100.0% coverageWriter's voice • 18 words • 100.0% coverageGuardrails Alliance • 17 words • 0.0% coverageWriter's voice • 6 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageGuardrails Alliance • 35 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageJosh Hawley • 26 words • 100.0% coverageWriter's voice • 2 words • 0.0% coverageElizabeth Warren • 20 words • 100.0% coverageElizabeth Warren • 17 words • 100.0% coverageElizabeth Warren • 12 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageThe Economist • 22 words • 100.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverage
Selected voice

Josh Hawley

100%flagged-word coverage
26 attributed words8.6% of attributed speech99% writer coverage
0%50.0%100.0%Unattributed Quote+97.4 ptsWriter: 2.6%Josh Hawley: 100.0%100.0%Biased Writer Voice-53.3 ptsWriter: 53.3%Josh Hawley: 0.0%0.0%Indoctrination-23.0 ptsWriter: 23.0%Josh Hawley: 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.