KQED61%

San Francisco Resident’s Tour of Surveillance Infrastructure Shows System ‘Greater Than Sum of Its Parts’ 47%

By Samantha Kennedy26%

6/21/2026, 5:36:20 PM

BS Summary: This article contains 31 faulty reasoning types, including Appeal to Emotion, Post Hoc (False Cause), and Ambiguity (Equivocation), with Negativity Bias as the most egregious example at 33.3% saturation with 267 hits. Analysis detected 1,802 faulty-reasoning hits from 802 analyzed words, generating a BS Score of 48.5% and a BS Rank of 47% (11,699 of 21,887 articles). This article is better (less manipulative) than 53.40% of the article peer group.

Larry Kubin wonders if San Francisco might look like something out of a sci-fi show soon. 
Humanoid robots and things like that. 
“It’s just where trends are heading, and thinking about where to draw the line on what makes people safe versus where it starts to get a little invasive,” said Kubin, who decided to investigate. 
Kubin, toured the city in search of surveillance infrastructure technology that has sparked a surge in criticism over privacy concerns. 
He published his findings in The Fogline, an independent site he runs with his wife. 
He found around 700 San Francisco Police Department drone flights in February alone, a rundown of city-owned tech, separate private cameras and a push for even more surveillance. 
Among the tech are around 400 Flock Safety automated license plate readers used by SFPD. 
Police Chief Derrick Lew said this week that out-of-state and federal law enforcement agencies had “improperly” accessed the data, after the Northern California Regional Intelligence Center queried the system hundreds of times. 
The incident prompted SFPD to stop sharing Flock data with NCRIC and another agency, the Western States Information Network. 
It wasn’t the first of the city’s problems with Flock. 
In 2025, an investigation by The San Francisco Standard revealed that SFPD had allowed out-of-state agencies to search its system 1.6 million times, a possible violation of state law. 
Some SFPD personnel also appeared to make searches on behalf of federal agencies. 
The Bay Area cities of Santa Cruz, Mountain View, El Cerrito and the town of Los Altos Hills have canceled Flock contracts over worries of improper data sharing, all of which learned their own data had been searched in similar ways. 
Santa Clara County also iced the company out, and Berkeley council members last month approved a contract extension but not an expansion. 
Flock’s attention in the media, plus a 2019 look at Seattle’s surveillance infrastructure, was part of Kubin’s inspiration for the tour. 
“I wanted to look more into that because my initial reaction was, like, ‘Oh, reading a license plate, that’s not so bad,’” Kubin said. 
But then he started spotting cameras in “postcard views” of the city and places where people chill. 
He said it feels like a much different world than when he was growing up. 
“We shouldn’t have to need this much technology. 
We shouldn’t need a police surveillance technology inventory that’s continuing to expand,” Kubin added. 
For that, he in part blames the city’s voter-approved Proposition E. 
The 2024 ballot measure allows SFPD to roll out new surveillance technology for a full year without an official policy. 
“I’m just picturing where we are now and whether it can become like a sci-fi TV show, right? 
They’re not doing this now, but you can see with these new powers of things like Proposition E,” Kubin said. 
“The checks and balances are a bit looser.” 
Proponents of the measure have defended it, with a former spokesperson for the Yes on E campaign saying officers are “highly trained and should be trusted to make smart decisions” about the use of drones in high-speed chases. 
SFPD’s surveillance network has increased in recent years. 
The Department opened its fully operational Real Time Investigation Center at its headquarters last year. 
Mayor Daniel Lurie touted it as an important resource in his efforts to keep the city safe and clean. 
The center houses a central hub that synthesizes real-time data from Flock cameras, drones and other public safety cameras. 
As of the reopening, the center helped make at least 800 arrests, according to ABC7. 
But the San Francisco-based Electronic Frontier Foundation is a critic of the center and how it came to be. 
EFF said that these centers, which other cities like San Jose have too, are “basically control rooms that pull together all feeds from a vast warrantless digital dragnet.” 
SFPD’s center was funded partly through Prop. 
E, with later additional backing from crypto billionaire and Ripple CEO Chris Larsen. 
Larsen, through Ripple and his nonprofit San Francisco Police Community Foundation, gifted $9.4 million to the new headquarters. 
Larsen’s support was another inspiration for Kubin’s deep-dive into surveillance. 
He said that, while Larsen’s “crypto billionaire” title was not enough for him to be upset, his name had come up a lot in funding increasing police technology. 
Kubin said that the introduction of each surveillance tool in isolation  Flock automated license plate reader cameras, drones, ShotSpotter technology and so on  might’ve made sense at the time for safety. 
But he worries that it soon evolves into something else. 
“The fact that all those different modalities are coming together into this Real-Time Investigation Center  the whole of that is now greater than the sum of its parts,” Kubin said. 
Article reasoning-pattern comparisonThis article: 10.1%Samantha Kennedy: 1.1%CalMatters: 1.9%Confirmation Bias10.1%This article: 0.0%Samantha Kennedy: 1.3%CalMatters: 0.9%Anchoring Bias0.0%This article: 13.8%Samantha Kennedy: 2.7%CalMatters: 3.0%Availability Heuristic13.8%This article: 0.0%Samantha Kennedy: 0.9%CalMatters: 1.0%Representativeness Heuristic0.0%This article: 2.5%Samantha Kennedy: 0.3%CalMatters: 0.5%Hindsight Bias2.5%This article: 0.0%Samantha Kennedy: 1.1%CalMatters: 1.2%Overconfidence Bias0.0%This article: 3.9%Samantha Kennedy: 4.3%CalMatters: 6.3%Framing Effect3.9%This article: 0.0%Samantha Kennedy: 0.6%CalMatters: 1.0%Loss Aversion0.0%This article: 1.0%Samantha Kennedy: 0.9%CalMatters: 0.7%Status Quo Bias1.0%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.2%Sunk Cost Effect0.0%This article: 3.0%Samantha Kennedy: 4.2%CalMatters: 3.5%Optimism Bias3.0%This article: 8.2%Samantha Kennedy: 1.3%CalMatters: 1.4%Pessimism Bias8.2%This article: 33.3%Samantha Kennedy: 6.7%CalMatters: 6.4%Negativity Bias33.3%This article: 1.9%Samantha Kennedy: 1.2%CalMatters: 1.7%Self-Serving Bias1.9%This article: 1.4%Samantha Kennedy: 0.7%CalMatters: 0.7%Fundamental Attribution Error1.4%This article: 0.0%Samantha Kennedy: 0.2%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 0.0%Samantha Kennedy: 2.4%CalMatters: 1.7%In-Group Bias0.0%This article: 5.1%Samantha Kennedy: 0.4%CalMatters: 0.4%Out-Group Homogeneity Bias5.1%This article: 4.0%Samantha Kennedy: 1.0%CalMatters: 2.7%Halo Effect4.0%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.1%Horn Effect0.0%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.0%Dunning-Kruger Effect0.0%This article: 5.2%Samantha Kennedy: 1.3%CalMatters: 0.9%Recency Bias5.2%This article: 5.4%Samantha Kennedy: 0.2%CalMatters: 0.3%Primacy Effect5.4%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 2.4%Samantha Kennedy: 0.6%CalMatters: 0.6%Ad Hominem2.4%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.2%Straw Man0.0%This article: 12.6%Samantha Kennedy: 2.5%CalMatters: 3.1%Appeal to Authority12.6%This article: 6.7%Samantha Kennedy: 0.9%CalMatters: 1.1%False Dilemma6.7%This article: 3.7%Samantha Kennedy: 1.3%CalMatters: 0.8%Slippery Slope3.7%This article: 0.0%Samantha Kennedy: 0.2%CalMatters: 0.1%Circular Reasoning0.0%This article: 5.4%Samantha Kennedy: 3.5%CalMatters: 3.6%Hasty Generalization5.4%This article: 0.0%Samantha Kennedy: 0.2%CalMatters: 0.2%Red Herring0.0%This article: 5.1%Samantha Kennedy: 0.6%CalMatters: 0.7%Bandwagon5.1%This article: 20.6%Samantha Kennedy: 4.7%CalMatters: 5.3%Appeal to Emotion20.6%This article: 2.7%Samantha Kennedy: 0.5%CalMatters: 0.6%Begging the Question2.7%This article: 20.2%Samantha Kennedy: 2.5%CalMatters: 2.0%Post Hoc (False Cause)20.2%This article: 0.0%Samantha Kennedy: 0.1%CalMatters: 0.1%Tu Quoque0.0%This article: 0.0%Samantha Kennedy: 0.6%CalMatters: 0.3%Burden of Proof0.0%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.2%Appeal to Nature0.0%This article: 3.9%Samantha Kennedy: 0.7%CalMatters: 0.2%Composition/Division3.9%This article: 9.1%Samantha Kennedy: 2.4%CalMatters: 3.1%Anecdotal9.1%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 16.2%Samantha Kennedy: 1.5%CalMatters: 1.2%Ambiguity (Equivocation)16.2%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 4.1%Samantha Kennedy: 0.1%CalMatters: 0.1%Middle Ground4.1%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.1%Personal Incredulity0.0%This article: 0.0%Samantha Kennedy: 0.1%CalMatters: 0.1%Special Pleading0.0%This article: 5.1%Samantha Kennedy: 0.3%CalMatters: 0.1%Genetic Fallacy5.1%This article: 0.0%Samantha Kennedy: 1.1%CalMatters: 0.8%Unattributed Quote0.0%This article: 3.5%Samantha Kennedy: 1.1%CalMatters: 0.7%Quote-first Misdirection3.5%This article: 1.9%Samantha Kennedy: 1.7%CalMatters: 3.1%Biased Writer Voice1.9%This article: 2.7%Samantha Kennedy: 2.3%CalMatters: 1.9%Indoctrination2.7%This article: 0.0%Samantha Kennedy: 1.4%CalMatters: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Samantha Kennedy: 0.0%CalMatters: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Samantha Kennedy: 0.2%CalMatters: 1.2%Attempt to Sell a Product or S…0.0%

802 words analyzed.

Speakers

9speakers59%attributed speech332writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 15 words • 0.0% coverageLarry Kubin • 16 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageLarry Kubin • 34 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 15 words • 100.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageDerrick Lew • 32 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageThe San Francisco Standard • 29 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 41 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageLarry Kubin • 24 words • 0.0% coverageLarry Kubin • 17 words • 0.0% coverageLarry Kubin • 15 words • 0.0% coverageLarry Kubin • 8 words • 100.0% coverageLarry Kubin • 14 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageLarry Kubin • 18 words • 0.0% coverageLarry Kubin • 20 words • 0.0% coverageLarry Kubin • 8 words • 0.0% coverageYes on E campaign • 38 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageSFPD • 15 words • 0.0% coverageDaniel Lurie • 19 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageABC7 • 15 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageElectronic Frontier Foundation (EFF) • 28 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageChris Larsen • 18 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageLarry Kubin • 28 words • 0.0% coverageLarry Kubin • 33 words • 0.0% coverageLarry Kubin • 10 words • 0.0% coverageLarry Kubin • 31 words • 0.0% coverage
100%flagged-word coverage
28 attributed words6.0% of attributed speech81% writer coverage
0%50.0%100.0%Quote-first Misdirection+100.0 ptsWriter: 0.0%Electronic Frontier Foundation (EFF): 100.0%100.0%Biased Writer Voice-4.5 ptsWriter: 4.5%Electronic Frontier Foundation (EFF): 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.