WSHU34%

Flock cameras are causing an uproar in CT  and everywhere else 22%

By Davis Dunavin37% WSHU37% Ava Keogh37%

8/7/2026, 8:28:57 AM

BS Summary: This article contains 21 faulty reasoning types, including Framing Effect, Appeal to Authority, and Negativity Bias, with Burden of Proof as the most egregious example at 12.9% saturation with 67 hits. Analysis detected 541 faulty-reasoning hits from 518 analyzed words, generating a BS Score of 28.1% and a BS Rank of 22% (24,108 of 30,584 articles). This article is better (less manipulative) than 78.80% of the article peer group.

A Flock Safety license plate reader is seen along a public road, Thursday, Oct. 16, 2025, in Houston. 
They’re meant to see everything. 
But in the past few weeks, Flock cameras have been seen seemingly everywhere, and not for good reason. 
A Florida man staged a solo protest by blocking one camera with a pool skimmer. 
In one Minnesota town, someone cut down every Flock camera overnight. 
And comedian John Oliver devoted his show this week to privacy and civil rights concerns around the cameras. 
The cameras are motion-activated and use AI to log license plates and other vehicle identifiers. 
Supporters say they crack down on stolen vehicles and investigate crimes. 
Opponents say they’re a violation of privacy and civil rights  and that there’s no way to know who’s watching or why. 
Now the town of Milford, Connecticut has become a front line for opposition to the cameras after a raucous town meeting. 
“All these Flock cameras have nothing to do with safety! 
They have to do with control!” 
said resident Tony de Blasio, who said he was a former Marine, at the meeting. 
“This isn’t a partisan issue. 
I don’t care who’s in this room. 
There are Democrats and Republicans. 
We all want this done.” 
The list of speakers that night bore him out. 
Local candidates from both major parties spoke against the cameras. 
“Benjamin Franklin once said those who would give up essential liberty to purchase a temporary safety deserve neither liberty nor safety,” Democrat Andrew Rice said. 
“If you want safety, then give the people resources that they need to live decent lives.” 
Republican Chris Lancia, who spoke immediately after Rice, said he’s worked in telecommunications for decades building cameras like Flock. 
“What can’t a police officer do that these cameras don’t?” 
Lancia said. 
“You want the speeding to stop? 
Put a police cruiser there. 
Let our officers do their job. 
Stop being soft on crime. 
These cameras need to go.” 
Milford police chief Keith Mello’s the one who proposed them in the first place. 
He said he still thinks they’re a good idea, especially because he doesn’t have enough cops as it is. 
“I’ll say now, if you don’t trust police or you don’t trust the government, you don’t trust big business, there’s probably not a lot that I can do to convince you other than tell you this is the best information that we have,” Mello said. 
Milford officials voted to consider a moratorium on the cameras next month. 
But in the meantime, state leaders  including Milford’s own representative in Hartford  are already speaking out. 
Senate Majority Leader Bob Duff and State Senator James Maroney of Milford said the cameras are an invasive technology. 
They said residents have a right to be concerned, and deserve answers about who’s watching and why. 
The state of Connecticut will conduct a survey on the number of cameras and how they are used to strengthen protection acts and technology regulations in 2027. 
This story was first published Aug. 7, 2026 by WSHU. 
Article reasoning-pattern comparisonThis article: 8.7%Davis Dunavin: 0.0%CTMirror: 2.0%Confirmation Bias8.7%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.5%Anchoring Bias0.0%This article: 3.5%Davis Dunavin: 1.7%CTMirror: 2.1%Availability Heuristic3.5%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.7%Representativeness Heuristic0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.3%Hindsight Bias0.0%This article: 1.0%Davis Dunavin: 0.0%CTMirror: 1.0%Overconfidence Bias1.0%This article: 12.5%Davis Dunavin: 3.7%CTMirror: 3.7%Framing Effect12.5%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.5%Loss Aversion0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.5%Status Quo Bias0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.2%Sunk Cost Effect0.0%This article: 1.0%Davis Dunavin: 0.0%CTMirror: 2.5%Optimism Bias1.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 1.4%Pessimism Bias0.0%This article: 10.8%Davis Dunavin: 5.2%CTMirror: 4.7%Negativity Bias10.8%This article: 5.0%Davis Dunavin: 0.0%CTMirror: 1.6%Self-Serving Bias5.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.5%Fundamental Attribution Error0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%Actor-Observer Bias0.0%This article: 1.0%Davis Dunavin: 3.5%CTMirror: 0.9%In-Group Bias1.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.2%Out-Group Homogeneity Bias0.0%This article: 3.7%Davis Dunavin: 0.0%CTMirror: 1.0%Halo Effect3.7%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.0%Horn Effect0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.0%Dunning-Kruger Effect0.0%This article: 6.9%Davis Dunavin: 0.0%CTMirror: 0.6%Recency Bias6.9%This article: 1.9%Davis Dunavin: 0.0%CTMirror: 0.3%Primacy Effect1.9%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%Blind-Spot Bias0.0%This article: 1.0%Davis Dunavin: 2.9%CTMirror: 0.8%Ad Hominem1.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.2%Straw Man0.0%This article: 12.0%Davis Dunavin: 7.3%CTMirror: 2.2%Appeal to Authority12.0%This article: 6.2%Davis Dunavin: 5.6%CTMirror: 1.2%False Dilemma6.2%This article: 1.0%Davis Dunavin: 0.0%CTMirror: 0.6%Slippery Slope1.0%This article: 1.7%Davis Dunavin: 0.0%CTMirror: 0.1%Circular Reasoning1.7%This article: 3.5%Davis Dunavin: 2.1%CTMirror: 3.1%Hasty Generalization3.5%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%Red Herring0.0%This article: 1.0%Davis Dunavin: 1.4%CTMirror: 0.5%Bandwagon1.0%This article: 0.0%Davis Dunavin: 2.8%CTMirror: 3.6%Appeal to Emotion0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.5%Begging the Question0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 1.9%Post Hoc (False Cause)0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%Tu Quoque0.0%This article: 12.9%Davis Dunavin: 2.9%CTMirror: 0.5%Burden of Proof12.9%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%Appeal to Nature0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.2%Composition/Division0.0%This article: 5.0%Davis Dunavin: 1.7%CTMirror: 1.9%Anecdotal5.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%No True Scotsman0.0%This article: 4.2%Davis Dunavin: 0.0%CTMirror: 1.1%Ambiguity (Equivocation)4.2%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%Middle Ground0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.0%Personal Incredulity0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.1%Special Pleading0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.2%Genetic Fallacy0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.6%Unattributed Quote0.0%This article: 0.0%Davis Dunavin: 1.7%CTMirror: 0.8%Quote-first Misdirection0.0%This article: 0.0%Davis Dunavin: 1.9%CTMirror: 2.0%Biased Writer Voice0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 2.0%Indoctrination0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.6%Politically Left Leaning Bias0.0%This article: 0.0%Davis Dunavin: 1.7%CTMirror: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Davis Dunavin: 0.0%CTMirror: 0.4%Attempt to Sell a Product or S…0.0%

518 words analyzed.

Speakers

6speakers51%attributed speech255writer words
Selected voice

Keith Mello

100%flagged-word coverage
64 attributed words24% of attributed speech69% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

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.