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Video · 2026-08-18 · 56m · 6 moments

Mass Surveillance, Police Misuse, and Who Controls Your Flock Cameras with Flock CEO, Garret Langley

✦ AI generated

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01
Fact

Flock Safety has helped solve over a million crimes and find thousands of missing people by providing license plate reading and vehicle description technology.

Garrett Langley highlights the significant impact of Flock Safety's technology, noting it has assisted in solving over a million crimes and finding more than 10,000 missing individuals, including children and the elderly.

transcript

Garrett Langley: north of a million crimes solved using Flock. North of 10,000 people found who were missing. And that's everything from our grandparents with dementia to our children. Like just last week in Atlanta, there was a stolen car that happened to have a 2-year-old in the back seat. And thankfully, because of very hard work by Atlanta Police Department and our cameras, that little kid was safely returned within the hour. I don't know what that would have happened if without Flock.

02
Mechanism

Communities should decide how long Flock's data is stored, but the company provides default settings (currently 7 days) to balance privacy and efficacy.

Garrett explains that Flock allows local city councils to determine data retention periods, having recently reduced the default setting to 7 days to better balance privacy concerns with the needs of law enforcement.

transcript

Garrett Langley: And so for the longest time, 30 days was our default. We've recently shifted that down to 7 days. Um we think that's a reasonable trade-off, but we still think cities should should decide um or states for that matter. But someone who is democratically elected should have the final decision of how this technology works in their community.

03
Mechanism

Flock's 'audit assistance' tool detects and flags abnormal usage patterns, such as an officer repeatedly searching for the same license plate without a legitimate reason, to identify potential misconduct.

Garrett details a new 'audit assistance' tool that helps identify police misconduct by flagging abnormal usage patterns, such as an officer repeatedly searching for a specific license plate without adding it to a 'hot list' for the entire department.

transcript

Garrett Langley: So here's a good example. Um, this is the easiest one. Let's say you're an officer and you'll say you're trying to stalk me. You would look for me. You'd say, 'I'm looking for Garrett's car. It's ABC124.' And you'd search for it and kind of figure out where it is. And then the next day, you'd search for me again. And then the next day, you'd search for me again. That's very abnormal. If you were truly trying to find me because I committed a crime, you would have put my tag on the hot list so that anyone else in the police department would have been also notified because you might be asleep, you might be off shift because I'm a criminal.

04
Claim

AI should be used cautiously in law enforcement with third-party validation to ensure it works as expected and is objective, rather than rushing to deploy untested features.

Garrett advocates for a deliberate and cautious approach to integrating AI into law enforcement, emphasizing the necessity of third-party validation to ensure the technology is objective and effective before widespread deployment.

transcript

Garrett Langley: You have to deploy this with third party proper attestation that it's that it's working as expected. It shouldn't be up to me. It shouldn't be up to my customers. Someone who actually doesn't want this to work should come in and say, 'Well, guess what? It it does actually like this is actually really good and it's making officers more effective. It's making officers more objective, less subjective.' Like that should be our end goal is that AI is used in a way that increases the number of crimes they can solve and decreases the likelihood if they get the wrong person.

supports · 1

05
Context

People with private security are often more opposed to surveillance technologies like Flock, while those in less affluent areas who lack such protections are more supportive because they don't feel safe.

The discussion highlights a perceived hypocrisy where wealthy individuals with private security are often more opposed to public surveillance systems, while those in less affluent communities, who lack such protections, are often more supportive of them.

transcript

Jason: And for those who have a gate and have a guard and have cameras and have a security system and they have Jaime's incredible doorbell camera, right, and they have all these products and these services, they're like, 'Why does why does anyone need to feel any safer?' It's like, 'Because most people don't have any of this stuff and they don't feel safe when they go to bed.'

06
Example

Drones can be sent to 911 calls before officers, providing a 40x optical zoom to assess threats and de-escalate situations that might otherwise lead to violence.

Garrett shares an example of how drones can be dispatched to 911 calls to provide immediate visual assessment, potentially de-escalating a dangerous situation before a police officer arrives on the scene.

transcript

Garrett Langley: Instead, they launch the drone. The drone's at 400 feet, flying 60 miles an hour, so it gets there in under a minute as the crow flies. Yep. And it's got a 40x optical zoom, so it zooms all the way in. It's not a gun. It's a lighter. It's one of those toy like lighter things. That call the woman back and say, 'Hey, ma'am, it's just a lighter. You're okay.'

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