WAMU15%

Cyber Monday: Regulating facial recognition 39%

7/13/2026, 12:58:11 PM

BS Summary: This article contains 15 faulty reasoning types, including Framing Effect, Biased Writer Voice, and False Dilemma, with Negativity Bias as the most egregious example at 55.8% saturation with 72 hits. Analysis detected 431 faulty-reasoning hits from 129 analyzed words, generating a BS Score of 44.6% and a BS Rank of 39% (13,387 of 21,887 articles). This article is better (less manipulative) than 61.20% of the article peer group.

For most of human history, you could be seen without being known. 
You could walk through a train station, or sit in a crowded restaurant, or pass a stranger on the street. 
Facial recognition technology is combing billions of photographs across databases. 
Across the internet. 
It's being deployed by local police, by immigration agents, and by governments at a speed that regulation hasn’t kept up with. 
And it raises a question that goes beyond technology: What does it mean to move through public life when your face can be identified, stored, and searched at any moment? 
That can be frightening if you don’t want to be found. 
But what if you do? 
Our Cyber Monday series is returns to try and find an answer. 
Article reasoning-pattern comparisonThis article: 0.0%WAMU: 2.2%Confirmation Bias0.0%This article: 0.0%WAMU: 1.1%Anchoring Bias0.0%This article: 24.8%WAMU: 2.9%Availability Heuristic24.8%This article: 9.3%WAMU: 1.3%Representativeness Heuristic9.3%This article: 0.0%WAMU: 0.4%Hindsight Bias0.0%This article: 0.0%WAMU: 0.9%Overconfidence Bias0.0%This article: 41.1%WAMU: 5.2%Framing Effect41.1%This article: 0.0%WAMU: 1.4%Loss Aversion0.0%This article: 0.0%WAMU: 0.7%Status Quo Bias0.0%This article: 9.3%WAMU: 0.2%Sunk Cost Effect9.3%This article: 9.3%WAMU: 1.5%Optimism Bias9.3%This article: 24.8%WAMU: 2.3%Pessimism Bias24.8%This article: 55.8%WAMU: 7.4%Negativity Bias55.8%This article: 0.0%WAMU: 1.1%Self-Serving Bias0.0%This article: 0.0%WAMU: 0.5%Fundamental Attribution Error0.0%This article: 0.0%WAMU: 0.1%Actor-Observer Bias0.0%This article: 0.0%WAMU: 0.7%In-Group Bias0.0%This article: 0.0%WAMU: 0.5%Out-Group Homogeneity Bias0.0%This article: 0.0%WAMU: 0.6%Halo Effect0.0%This article: 0.0%WAMU: 0.0%Horn Effect0.0%This article: 0.0%WAMU: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%WAMU: 1.3%Recency Bias0.0%This article: 15.5%WAMU: 0.4%Primacy Effect15.5%This article: 0.0%WAMU: 0.0%Blind-Spot Bias0.0%This article: 0.0%WAMU: 0.7%Ad Hominem0.0%This article: 0.0%WAMU: 0.1%Straw Man0.0%This article: 0.0%WAMU: 2.8%Appeal to Authority0.0%This article: 27.1%WAMU: 0.8%False Dilemma27.1%This article: 0.0%WAMU: 1.5%Slippery Slope0.0%This article: 0.0%WAMU: 0.1%Circular Reasoning0.0%This article: 9.3%WAMU: 4.5%Hasty Generalization9.3%This article: 0.0%WAMU: 0.1%Red Herring0.0%This article: 0.0%WAMU: 0.4%Bandwagon0.0%This article: 24.8%WAMU: 4.6%Appeal to Emotion24.8%This article: 0.0%WAMU: 0.6%Begging the Question0.0%This article: 0.0%WAMU: 1.9%Post Hoc (False Cause)0.0%This article: 0.0%WAMU: 0.1%Tu Quoque0.0%This article: 0.0%WAMU: 0.9%Burden of Proof0.0%This article: 0.0%WAMU: 0.1%Appeal to Nature0.0%This article: 0.0%WAMU: 0.3%Composition/Division0.0%This article: 0.0%WAMU: 2.5%Anecdotal0.0%This article: 0.0%WAMU: 0.0%No True Scotsman0.0%This article: 26.4%WAMU: 1.4%Ambiguity (Equivocation)26.4%This article: 0.0%WAMU: 0.0%Gambler’s Fallacy0.0%This article: 0.0%WAMU: 0.3%Middle Ground0.0%This article: 0.0%WAMU: 0.2%Personal Incredulity0.0%This article: 0.0%WAMU: 0.1%Special Pleading0.0%This article: 0.0%WAMU: 0.2%Genetic Fallacy0.0%This article: 0.0%WAMU: 1.2%Unattributed Quote0.0%This article: 0.0%WAMU: 0.9%Quote-first Misdirection0.0%This article: 31.0%WAMU: 2.7%Biased Writer Voice31.0%This article: 0.0%WAMU: 1.0%Indoctrination0.0%This article: 16.3%WAMU: 0.4%Politically Left Leaning Bias16.3%This article: 0.0%WAMU: 0.2%Politically Right Leaning Bias0.0%This article: 9.3%WAMU: 0.7%Attempt to Sell a Product or S…9.3%

129 words analyzed.

Speakers

No attributed speakers were identified in this analysis.

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Analysis

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