MinnPost17%

In Minneapolis’ search for crime deterrents, drones fly into a wall 26%

By Trevor Mitchell13%

7/22/2026, 3:18:33 PM

BS Summary: This article contains 33 faulty reasoning types, including Loss Aversion, Pessimism Bias, and Self-Serving Bias, with Negativity Bias as the most egregious example at 6.3% saturation with 88 hits. Analysis detected 1,388 faulty-reasoning hits from 1,402 analyzed words, generating a BS Score of 37.8% and a BS Rank of 26% (16,301 of 21,886 articles). This article is better (less manipulative) than 74.50% of the article peer group.

In mid-May, I sat in the Minneapolis City Council’s chambers as police pitched the idea of a “Drones as First Responders” pilot program. 
Based on Council members’ responses then, it wasn’t hard to imagine a future where drones zipped through city skies responding to 911 calls ahead of police. 
Members of the Council’s Public Health, Safety and Equity Committee expressed tentative interest in the idea of an eye in the sky able to inform an officer that a suspect had fled, for example, or that the situation had shifted, or maybe never existed in the first place. 
Even some of the Council’s progressives noted potential benefits, though not without some skepticism around privacy concerns and the federal government’s access to the data. 
Completely unmentioned in that meeting was the use of Skydio drones by Israel in the Israel-Hamas war, which has come to drive a sizable portion of the opposition over the past two months and swing a key Council member to kill the pilot program in a 6-6 vote. 
Related: Public safety or Orwellian trap? 
Minneapolis opens conversation on drones as first responders 
To LaTrisha Vetaw  the Council member from Ward 4 who said two and a half years of work went into the planning of the pilot program  the July 16 ‘no’ vote was frustrating. 
What she saw as a potential boon to her constituents, she said, was voted down because a country on the other side of the world had purchased the same equipment. 
But to local activists, dozens of whom attended a Council hearing on the matter earlier this month, the vote offered reassurance that they could raise concerns and be heard. 
What remains to be seen is whether there will be another push for the program, perhaps with another company. 
After two mass shootings in the city over the weekend, Mayor Jacob Frey made public pitches for the concept, saying “we need to embrace proven technology, from drones to ShotSpotter, that helps officers do their jobs more effectively.” 
Critics pounced, taking to social media to criticize the mayor’s approach as misguided at best. 
‘Another solution out the window’ 
“Of course I experienced disappointment,” Vetaw said in an interview with MinnPost, who said that the idea for the drones originally came as a response to illegal dumping, a problem she said is rampant in her ward. 
Research on that issue led her to realize that the drones could be used for much more than identifying someone who’s leaving a couch on a front lawn or disposing of oil down a storm drain. 
One of the stories that stays with Vetaw is that of a grandmother she said was carjacked while she was driving her grandchildren. 
It was people like her, and others who’d had similar experiences with crime, who had been contacting Vetaw’s office in support of the pilot program, she said. 
“In a minute, that drone could have been to Annie and her grandkids,” she said. 
Heather Hinkel, a resident of neighboring Ward 5, says she understands the program’s good intentions and believes there may be a way for police to use drones in a responsible way. 
But she thinks many of the arguments in favor of drones are “meritless.” 
The police already know where open-air drug markets are, she said. 
What good does it do to bring a drone? 
Higher among her concerns is “how Skydio makes money,” she said. 
She mentioned the company’s ties not only to Israel, but since at least 2021 , to U.S. 
Immigration and Customs Enforcement. 
Council members Jason Chavez (Ward 8) and Aurin Chowdhury (Ward 12) made clear Skydio’s ICE contracts were a factor in their votes against the program. 
“I think some of us kind of feel helpless about some of the global stuff that’s happening,” Hinkel said. 
To speak out against the partnership with Skydio, she said, felt productive. 
Julia Brysky, a real-time operations analyst with the Drones as First Responders program, monitors 911 calls at the Brooklyn Park Police Department on Wednesday, May 20, 2026, in Brooklyn Park, Minn. 
The program rapidly deploys drones to 911 calls, relaying information before officers arrive. 
Credit: Ellen Schmidt/MinnPost/CatchLight Local/Report for America 
Vetaw said she understands the concerns of critics around Skydio’s connections to ICE and agrees with some of the skepticism. 
And that’s the reason she repeated over and over that what they were voting on was a free pilot program that would last 75 days, so they could learn about the program’s strengths, weaknesses and whether it could help the city. 
“We’re not saying we will do it,” Vetaw said. 
“We’re saying let’s try.” 
But when it comes to the issue of the company’s work with Israel, Vetaw said the issue isn’t at the top of her list. 
“This is why I chose municipal government,” she said. 
“So I don’t have to work on international affairs.” 
If working with Israel crosses a line in the sand, she said, “I don’t know what we’re going to be giving up.” 
Related: Are we doomed to disagree? 
Not if we truly value diverse opinions 
Much of the Council’s discussion around drones involved how the machines could work with the city’s existing Axon technologies. 
Axon invented the Taser used by the Minneapolis Police Department and supplies them, along with body cameras and the Fusus mapping system . 
The company is also on the widely-used BDS divestment short list for its ties to Israel regarding some of those same products. 
U.S. 
Customs and Immigration Enforcement has purchased Axon products, as well. 
Vetaw knows for some people, the connection trumps the possible public safety benefits. 
“That is their perspective,” she said. 
“That is not the perspective of the person whose car was stolen while they were eating dinner. 
They want to hear solutions,” she said. 
Lucio Rubio, a Ward 4 resident and the treasurer of the Folwell Neighborhood Association, is certainly looking for solutions. 
When he heard about the idea of using drones to stop dumping or car thefts, he thought it was interesting. 
But he didn’t really think about it too hard until he wondered if it could help with an open-air drug market in his neighborhood, one that he said has led to a number of gunshots. 
“I was low-key rooting for this thing to happen,” he said. 
But then there was Skydio and their connections to Israel and ICE. 
“It was concerning for sure,” he said, “especially as a Mexican who was an immigrant, now a naturalized citizen.” 
Rubio was, and still is, torn about the idea. 
“When it got voted down,” he said, “it did kind of bum me out a bit because that’s another solution out the window that’s not going to help my block.” 
But what he felt was more important was that the community had come together and pushed to make their voices heard. 
And he wonders if maybe a process where that same community had been brought in on the drone discussion earlier could have had a different result. 
“The reason why this got shot down was because Vetaw went about it the wrong way,” he said. 
Maybe. 
But it’s clear that some Council members, like Jamal Osman, were not going to be convinced. 
Does the perfect drone company exist? 
“I support exploring technology that can help, including drones, in our first response,” Osman said at the Council meeting where the vote failed. 
“But only with a vendor that has no contract with militaries that are killing other people.” 
Adam Schwartz, the privacy litigation director for the Electronic Frontier Federation, said a quickly growing number of companies sell drones. 
It’s hard to tell, he said, whether any of them would limit their business model to sell only to local law enforcement. 
“Even if one did pick this narrow business model at a particular time,” he said, “that company could easily shift to a broader business model at a later time.” 
And even that narrowly focused company could still see data shared with ICE or other agencies, depending on local and state laws. 
“The only solid way to ensure that personal data collected by a city does not make its way to a federal agency,” Schwartz said, “is to not collect that data in the first place.” 
The post In Minneapolis’ search for crime deterrents, drones fly into a wall appeared first on MinnPost . 
Article reasoning-pattern comparisonThis article: 4.3%Trevor Mitchell: 1.1%MinnPost: 2.0%Confirmation Bias4.3%This article: 0.0%Trevor Mitchell: 1.1%MinnPost: 0.6%Anchoring Bias0.0%This article: 5.0%Trevor Mitchell: 3.0%MinnPost: 2.7%Availability Heuristic5.0%This article: 0.0%Trevor Mitchell: 0.6%MinnPost: 0.9%Representativeness Heuristic0.0%This article: 2.9%Trevor Mitchell: 1.4%MinnPost: 0.5%Hindsight Bias2.9%This article: 4.9%Trevor Mitchell: 1.3%MinnPost: 1.6%Overconfidence Bias4.9%This article: 2.9%Trevor Mitchell: 2.8%MinnPost: 5.3%Framing Effect2.9%This article: 6.2%Trevor Mitchell: 1.9%MinnPost: 0.6%Loss Aversion6.2%This article: 4.4%Trevor Mitchell: 1.2%MinnPost: 0.7%Status Quo Bias4.4%This article: 2.9%Trevor Mitchell: 1.6%MinnPost: 0.4%Sunk Cost Effect2.9%This article: 3.9%Trevor Mitchell: 2.5%MinnPost: 3.3%Optimism Bias3.9%This article: 5.2%Trevor Mitchell: 1.4%MinnPost: 1.3%Pessimism Bias5.2%This article: 6.3%Trevor Mitchell: 5.0%MinnPost: 6.3%Negativity Bias6.3%This article: 5.1%Trevor Mitchell: 1.3%MinnPost: 1.4%Self-Serving Bias5.1%This article: 3.9%Trevor Mitchell: 1.0%MinnPost: 0.6%Fundamental Attribution Error3.9%This article: 0.6%Trevor Mitchell: 0.1%MinnPost: 0.2%Actor-Observer Bias0.6%This article: 0.0%Trevor Mitchell: 0.6%MinnPost: 1.1%In-Group Bias0.0%This article: 0.9%Trevor Mitchell: 0.1%MinnPost: 0.3%Out-Group Homogeneity Bias0.9%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 2.6%Halo Effect0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.0%Horn Effect0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.0%Dunning-Kruger Effect0.0%This article: 3.4%Trevor Mitchell: 1.5%MinnPost: 1.0%Recency Bias3.4%This article: 0.5%Trevor Mitchell: 0.1%MinnPost: 0.3%Primacy Effect0.5%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.0%Blind-Spot Bias0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.3%Ad Hominem0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.3%Straw Man0.0%This article: 4.4%Trevor Mitchell: 3.2%MinnPost: 4.0%Appeal to Authority4.4%This article: 3.6%Trevor Mitchell: 1.7%MinnPost: 1.4%False Dilemma3.6%This article: 2.1%Trevor Mitchell: 0.9%MinnPost: 0.7%Slippery Slope2.1%This article: 0.0%Trevor Mitchell: 0.5%MinnPost: 0.2%Circular Reasoning0.0%This article: 1.6%Trevor Mitchell: 1.4%MinnPost: 4.1%Hasty Generalization1.6%This article: 3.4%Trevor Mitchell: 1.0%MinnPost: 0.4%Red Herring3.4%This article: 1.1%Trevor Mitchell: 0.2%MinnPost: 0.5%Bandwagon1.1%This article: 2.5%Trevor Mitchell: 2.9%MinnPost: 4.3%Appeal to Emotion2.5%This article: 0.6%Trevor Mitchell: 0.1%MinnPost: 0.6%Begging the Question0.6%This article: 1.9%Trevor Mitchell: 0.6%MinnPost: 2.5%Post Hoc (False Cause)1.9%This article: 0.0%Trevor Mitchell: 0.2%MinnPost: 0.1%Tu Quoque0.0%This article: 0.0%Trevor Mitchell: 0.2%MinnPost: 0.5%Burden of Proof0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.1%Appeal to Nature0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.4%Composition/Division0.0%This article: 4.7%Trevor Mitchell: 2.3%MinnPost: 2.4%Anecdotal4.7%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.1%No True Scotsman0.0%This article: 2.5%Trevor Mitchell: 1.7%MinnPost: 1.1%Ambiguity (Equivocation)2.5%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.0%Gambler’s Fallacy0.0%This article: 0.5%Trevor Mitchell: 0.1%MinnPost: 0.1%Middle Ground0.5%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.0%Personal Incredulity0.0%This article: 0.0%Trevor Mitchell: 0.5%MinnPost: 0.1%Special Pleading0.0%This article: 1.6%Trevor Mitchell: 0.2%MinnPost: 0.1%Genetic Fallacy1.6%This article: 2.6%Trevor Mitchell: 0.5%MinnPost: 1.0%Unattributed Quote2.6%This article: 0.0%Trevor Mitchell: 1.0%MinnPost: 0.8%Quote-first Misdirection0.0%This article: 1.2%Trevor Mitchell: 1.0%MinnPost: 4.1%Biased Writer Voice1.2%This article: 0.0%Trevor Mitchell: 0.1%MinnPost: 1.7%Indoctrination0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.7%Politically Left Leaning Bias0.0%This article: 0.0%Trevor Mitchell: 0.0%MinnPost: 0.3%Politically Right Leaning Bias0.0%This article: 1.4%Trevor Mitchell: 0.3%MinnPost: 1.1%Attempt to Sell a Product or S…1.4%

1402 words analyzed.

Speakers

6speakers58%attributed speech592writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 11 words • 100.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 48 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 48 words • 0.0% coverageWriter's voice • 6 words • 100.0% coverageWriter's voice • 8 words • 0.0% coverageLaTrisha Vetaw • 35 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageMayor Jacob Frey • 38 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageLaTrisha Vetaw • 37 words • 100.0% coverageWriter's voice • 36 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageLaTrisha Vetaw • 27 words • 0.0% coverageLaTrisha Vetaw • 15 words • 0.0% coverageHeather Hinkel • 31 words • 0.0% coverageHeather Hinkel • 13 words • 0.0% coverageHeather Hinkel • 11 words • 0.0% coverageHeather Hinkel • 9 words • 0.0% coverageHeather Hinkel • 11 words • 0.0% coverageHeather Hinkel • 17 words • 0.0% coverageHeather Hinkel • 4 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageHeather Hinkel • 19 words • 0.0% coverageHeather Hinkel • 12 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageLaTrisha Vetaw • 20 words • 0.0% coverageLaTrisha Vetaw • 41 words • 0.0% coverageLaTrisha Vetaw • 9 words • 0.0% coverageLaTrisha Vetaw • 4 words • 0.0% coverageLaTrisha Vetaw • 24 words • 0.0% coverageLaTrisha Vetaw • 9 words • 0.0% coverageLaTrisha Vetaw • 9 words • 0.0% coverageLaTrisha Vetaw • 22 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageLaTrisha Vetaw • 6 words • 0.0% coverageLaTrisha Vetaw • 17 words • 0.0% coverageLaTrisha Vetaw • 7 words • 0.0% coverageLaTrisha Vetaw • 19 words • 0.0% coverageLucio Rubio • 20 words • 0.0% coverageLucio Rubio • 35 words • 0.0% coverageLucio Rubio • 11 words • 0.0% coverageLucio Rubio • 12 words • 0.0% coverageLucio Rubio • 19 words • 0.0% coverageLucio Rubio • 9 words • 0.0% coverageLucio Rubio • 30 words • 0.0% coverageLucio Rubio • 21 words • 0.0% coverageLucio Rubio • 26 words • 0.0% coverageLucio Rubio • 18 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageJamal Osman • 16 words • 0.0% coverageAdam Schwartz • 20 words • 100.0% coverageAdam Schwartz • 22 words • 0.0% coverageAdam Schwartz • 29 words • 0.0% coverageAdam Schwartz • 22 words • 0.0% coverageAdam Schwartz • 34 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverage
Selected voice

Mayor Jacob Frey

100%flagged-word coverage
38 attributed words4.7% of attributed speech55% writer coverage
0%2.5%5.0%Biased Writer Voice-2.9 ptsWriter: 2.9%Mayor Jacob Frey: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Loading…
Loading…
Loading…

Analysis

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