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What's Going On With Flock Cameras We Did A Deep Dive · The Matt Walsh Show

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  Speaker 1: Maybe you've heard of the horseshoe theory, which was coined,
• 0:03
  Speaker 1: I think, back in the dark ages by a wise
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  Speaker 1: man who realized that all of his podcasts were starting to.
• 0:09
  Speaker 2: Sound the same.
• 0:10
  Speaker 1: And the idea is that at the extreme ends of
• 0:12
  Speaker 1: the spectrum, the right and the left are pretty much indistinguishable.
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  Speaker 1: That's the idea of the horseshoe. And under this theory,
• 0:19
  Speaker 1: whether they're on the right or the left, political activists, quote,
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  Speaker 1: have a tendency to see politics in unambiguous terms, distrust
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  Speaker 1: authorities and elites, and have intense hostility towards those who
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  Speaker 1: hold other views. Now, whatever you make of the theory itself,
• 0:32
  Speaker 1: there's no question that the left and the right are
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  Speaker 1: now finding a lot more common ground than usual. And
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  Speaker 1: that's notable because, as they've openly admitted many times, the
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  Speaker 1: left is committed to the destruction of Western civilization and
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  Speaker 1: the rule of law. I mean, you'd think it would
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  Speaker 1: be very difficult for anyone to find agreement with these people.
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  Speaker 1: But increasingly, that's not the case. Communists have found very
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  Speaker 1: unlikely allies in the conservative movement. on a handful of issues,
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  Speaker 1: on an increasing number of issues. First, of course, there
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  Speaker 1: was the AI data center debate, which we've discussed before.
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  Speaker 1: On both the right and the left, there's a consensus
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  Speaker 1: that these data centers are going to poison the water,
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  Speaker 1: prevent anyone from sleeping, usher in the apocalypse, and take
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  Speaker 1: everybody's job, among other things. And while there are very
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  Speaker 1: real issues with data centers, which we've talked about, the
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  Speaker 1: debate surrounding the issue has become a complete mess. It's
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  Speaker 1: descended into hysteria. Whenever there's a bipartisan consensus, that's the
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  Speaker 1: typical result. People tend to work themselves into hysterics when
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  Speaker 1: they're in echo chamber because they just keep ratcheting up
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  Speaker 1: the paranoia and the panic. The end result is that
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  Speaker 1: nobody can have a serious discussion. Anyone who tries to
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  Speaker 1: provide a dissenting opinion gets shouted down, and ultimately, perversely,
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  Speaker 1: that works for the benefit of the bad guys or
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  Speaker 1: alleged bad guys. If you're running a data center and
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  Speaker 1: you want to do something nefarious with it, It's very
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  Speaker 1: good news if all your critics start sounding like lunatics.
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  Speaker 1: People who sound crazy are easy to discredit and dismiss.
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  Speaker 1: We're seeing a similar trajectory play out with the debate
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  Speaker 1: over flock cameras, which at this point you've probably heard about.
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  Speaker 1: People are talking about flock cameras on podcasts and local
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  Speaker 1: news reports and cable news and social media. They're talking
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  Speaker 1: about flock cameras on next door podcasts. And in case
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  Speaker 1: you haven't heard about them, though, flat cameras are, just
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  Speaker 1: to basically summarize, are AI-enabled surveillance cameras that scan license
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  Speaker 1: plates and log other information about vehicles, which are then
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  Speaker 1: used by law enforcement to track people with outstanding warrants,
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  Speaker 1: or they're used in the case of Amber Alerts or
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  Speaker 1: a missing person, and so on. And there are now
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  Speaker 1: tens of thousands of these cameras all over the country.
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  Speaker 1: Soon there will be hundreds of thousands if there aren't already.
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  Speaker 1: And no matter who you ask about this, you'll hear
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  Speaker 1: the same thing, that these cameras are supposedly making 1984 real.
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  Speaker 1: They're ushering in a vast surveillance state in which no
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  Speaker 1: human connection or interaction is possible and in which innocent
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  Speaker 1: people are stalked and harassed everywhere they go. And most
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  Speaker 1: of the people making this argument are using their cell
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  Speaker 1: phones to do so without a hint of irony. I mean,
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  Speaker 1: they're logging on to social media platforms which exist to
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  Speaker 1: sell your personal information and complaining about the surveillance state.
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  Speaker 1: They're using cellular networks that are constantly surveilled by a
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  Speaker 1: major corporation as well as the NSA. And after telling
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  Speaker 1: the NSA exactly where they are, and after informing Facebook
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  Speaker 1: and Nextdoor and Instagram of all their personal information, these
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  Speaker 1: people are alerting the public to the danger of the
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  Speaker 1: surveillance state, and specifically the danger that's posed by flock cameras. Now,
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  Speaker 1: before we begin, I am not a supporter of mass
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  Speaker 1: surveillance in general, obviously. Flock, as we will discuss, has
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  Speaker 1: a lot of problems. But These problems are not a
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  Speaker 1: license to lie about Flock or about any other issue.
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  Speaker 1: They're not an excuse to spread false information or make
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  Speaker 1: posts that are deliberately misleading.
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  Speaker 2: And that's what we're seeing.
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  Speaker 1: You know, it's gone on far too long and it
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  Speaker 1: needs to end. For example, here's a report from the
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  Speaker 1: official news channel of the Democrat Party, MS Now, where
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  Speaker 1: every anchor is apparently contractually obligated to look as much
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  Speaker 1: like Rachel Maddow as possible.
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  Speaker 3: Watch.
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  Speaker 4: So I hate to tell you, but you might be
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  Speaker 4: getting flocked, as in F-L-O-C-K-E-D, flocked. Across the country, there
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  Speaker 4: is a new kind of surveillance taking place. It is
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  Speaker 4: an estimated 100,000 cameras recording cars, where they go, what
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  Speaker 4: they look like, when they pass by. All of this
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  Speaker 4: is creating searchable records of everyday Americans' movements. It is
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  Speaker 4: what happens when you get flocked. It is a reference
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  Speaker 4: to Flock Safety, the largest provider of automatic license plate
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  Speaker 4: readers in the United States. These plate readers are pretty unassuming.
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  Speaker 4: They're often attached to utility poles like that and streetlights
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  Speaker 4: that line highways and neighborhoods and parking lots. And supporters
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  Speaker 4: say that those plate readers help solve crimes by giving
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  Speaker 4: investigators leads they might not otherwise have. But you don't
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  Speaker 4: have to be suspected of a crime or really do
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  Speaker 4: anything at all to end up being in the database.
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  Speaker 4: You simply just drive by it. And as you might imagine,
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  Speaker 4: concerns about privacy and whether flock cameras actually work are
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  Speaker 4: starting to pile up.
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  Speaker 5: Can anybody in this room tell me, do flock cameras
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  Speaker 5: stop crime?
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  Speaker 6: Okay?
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  Speaker 2: Y'all wasting money, man. A million dollars on that?
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  Speaker 5: That's trash.
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  Speaker 2: I trust our police.
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  Speaker 1: I don't trust Locke.
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  Speaker 5: No more automated license plate readers of any brand.
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  Speaker 4: This technology is anti-democratic.
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  Speaker 7: Just so you all know, I am a right-wing MAGA
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  Speaker 7: Republican voter. I'm telling you all this so you all
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  Speaker 7: grasp how this issue spans across this political spectrum. An
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  Speaker 7: AI surveillance apparatus goes against the very essence of freedom
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  Speaker 7: and the core values of our country.
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  Speaker 8: We didn't vote for.
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  Speaker 7: This, and we sure as hell don't want it, so
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  Speaker 7: do us a favor and get the flock out of here.
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  Speaker 1: That anchor was so impressed with himself for that flock pun.
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  Speaker 1: He was so impressed, even though he didn't even write it.
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  Speaker 2: Hate to tell you, but you're getting flocked.
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  Speaker 9: Get it?
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  Speaker 1: No, you thought I said the F word, but I
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  Speaker 1: said flock. F-L-O-C-K. You get the joke, do you? Now,
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  Speaker 1: no matter what you think about flock cameras, even if
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  Speaker 1: you think they should all be banned immediately, there's something
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  Speaker 1: you need to know and notice about segments like this.
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  Speaker 1: Every single investigative segment into flock cameras does the same thing.
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  Speaker 1: They all brush past the idea of that these cameras
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  Speaker 1: could possibly be useful in solving crime. As you just heard,
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  Speaker 1: the guy in the town hall meeting implies that these
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  Speaker 1: cameras don't stop crime at all. And the anchor barely
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  Speaker 1: mentions the idea that cameras could be useful. He simply
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  Speaker 1: said that supporters say they solve crime before immediately talking
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  Speaker 1: about the privacy issue. That's a pretty obvious sign that
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  Speaker 1: you're being manipulated. If we're going to talk about the
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  Speaker 1: issues with flock cameras, and we should talk about them,
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  Speaker 1: and we will, We have to tell the whole story, not.
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  Speaker 2: Just part of it. Again, this is.
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  Speaker 1: Not going to be a pro-flock monologue exactly, but it's
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  Speaker 1: also not going to be the same slop that insults
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  Speaker 1: your intelligence, which you've probably heard dozens of times now.
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  Speaker 1: So let's begin with a few real-life cases in which
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  Speaker 1: flock cameras have been directly involved in criminal investigations. There's
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  Speaker 1: no better way to learn what these cameras are capable
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  Speaker 1: of and how they're useful or not useful, as the
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  Speaker 1: case may be. Because as in fact, they are used
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  Speaker 1: to solve crimes. That's a real thing. So you can't
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  Speaker 1: just you can't just stand there and say, well, well,
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  Speaker 1: you think that these are used to solve crimes?
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  Speaker 2: Ridiculous.
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  Speaker 1: Waving your hand at it doesn't like, of course, they're
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  Speaker 1: used to solve crimes.
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  Speaker 2: It's a real thing.
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  Speaker 1: So we'll start with a murder that took place on
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  Speaker 1: April 13th, 2024 at Wilbur Young Park in Blue Springs, Missouri.
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  Speaker 1: There was a fistfight and then a shooting around 10.30 p.m.
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  Speaker 1: Dozens of shell cases were discovered at the scene, and
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  Speaker 1: authorities determined that at least three people had fired shots.
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  Speaker 1: Three people were hit and two were killed. The first
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  Speaker 1: thing the police did was check the city-owned cameras that
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  Speaker 1: were nearby. These are dumb cameras that are not connected
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  Speaker 1: to flock system. The cameras revealed that a man, later
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  Speaker 1: identified as Marquise Earl Lee Savannah, raced to a car
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  Speaker 1: shortly after the shooting. But the footage was grainy. It
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  Speaker 1: didn't capture the license plate of the car. All the
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  Speaker 1: camera showed was that the car was a Chevy Cruze
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  Speaker 1: with a specific color and configuration. And that information ordinarily
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  Speaker 1: would not narrow down the search very much. Then the
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  Speaker 1: authorities turned to the city's flock cameras, which work differently.
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  Speaker 1: They aren't simply license plate readers. Flock cameras track dozens
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  Speaker 1: of individual characteristics of cars from color to bumper stickers
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  Speaker 1: to dents. And this is one of the core features
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  Speaker 1: of the product, which they call Freeform. A police officer
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  Speaker 1: can type in the Flock system that he's looking for
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  Speaker 1: a gray pickup truck with tinted windows and a bumper
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  Speaker 1: sticker that says no border wall, and the system will
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  Speaker 1: find it. They can use AI in ways that would
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  Speaker 1: have been unthinkable just 10 years ago, even five years ago,
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  Speaker 1: to sift through thousands of videos and identify a precise match. Now,
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  Speaker 1: Flock's relevant patent specifically covers a, quote, system and method
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  Speaker 1: for object-based query of video content captured by a dynamic
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  Speaker 1: surveillance network, which allows them to parse videos for content,
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  Speaker 1: and keep it in a database in connection with data
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  Speaker 1: that identifies the content, object class, aspects of the object,
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  Speaker 1: confidence scores, timing, location data, et cetera. As reported by
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  Speaker 1: Footnote 4A, quote, the patent family extends to neural networks
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  Speaker 1: trained to identify clothing, estimate height and weight, and classify
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  Speaker 1: other physical characteristics of individuals stored by design in searchable databases.
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  Speaker 1: That is, an index is being built continuously by design
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  Speaker 1: and is queryable by any user Flock decides gets a
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  Speaker 1: search box. Now, all this to say, even without a
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  Speaker 1: license plate, flock cameras can track down a specific Chevy Cruze,
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  Speaker 1: and that's exactly what happened in this case. This is
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  Speaker 1: from the local Fox affiliate quote. According to court documents,
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  Speaker 1: a sergeant used the flock camera system to identify the sedan,
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  Speaker 1: shown on the park camera as a specific color, year, make,
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  Speaker 1: and model bearing a specific license plate. Two days later,
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  Speaker 1: another sergeant received a flock hit on the Chevy Cruze.
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  Speaker 1: The patrol sergeant then responded to the area to look
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  Speaker 1: for it, spotted it at a car wash nearby, and
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  Speaker 1: took the driver into custody. Flowers said the department has
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  Speaker 1: had the network for about a year.
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  Speaker 2: Super helpful.
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  Speaker 1: We use it constantly during our investigations, Flowers said. Investigators
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  Speaker 1: could track a vehicle back in time for up to
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  Speaker 1: 30 days with a hotspot map showing areas where it
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  Speaker 1: appears frequently. Authorities said this can be used to determine
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  Speaker 1: where a suspect may live.
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  Speaker 2: Now, this kind of investigation happens all the time with Flock.
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  Speaker 2: Here's another example.
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  Speaker 1: In the summer of 2024, at the Cherry Creek Shopping
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  Speaker 1: Center in Denver, a gang of South American thieves stole
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  Speaker 1: more than $ 12 million in jewelry. And according to authorities,
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  Speaker 1: four people traveled from California to Denver in a dark-colored
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  Speaker 1: pickup truck without any license plates. They were dressed like
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  Speaker 1: construction workers. They had hard hats, masks, gloves, reflexive vests,
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  Speaker 1: as you can see here. They arrived at the mall
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  Speaker 1: around 8 p.m., at which point they began cutting through
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  Speaker 1: a wall from a shop next to the jewelry store
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  Speaker 1: before breaking into display cases.
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  Speaker 2: And store safes.
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  Speaker 1: They were in the store for a total of eight hours,
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  Speaker 1: and about three hours into the theft, they tripped an alarm.
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  Speaker 1: But when mall security cameras arrived, You know, security looked
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  Speaker 1: at the cameras. They assumed that it was related to
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  Speaker 1: a construction job. And so the gang went all over
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  Speaker 1: the country in this way, carrying out similar heists as
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  Speaker 1: far away as New Jersey. They were proving extremely difficult
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  Speaker 1: to catch because, again, their truck didn't have a license
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  Speaker 1: plate and the criminals were all wearing masks. Once they
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  Speaker 1: were gone, police had no description to work with. The
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  Speaker 1: investigation only turned a corner once the authorities began using
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  Speaker 1: flock cameras. This is from CBS News, quote, Shortly after
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  Speaker 1: the Denver heist, investigators fed information about the truck into
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  Speaker 1: a database belonging to Flock Systems, the company that has
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  Speaker 1: installed license plate reader cameras in Colorado and across the country.
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  Speaker 1: As it turns out, the system does more than help
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  Speaker 1: track vehicles through their license plates. It's essentially machine learning technology,
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  Speaker 1: a kind of artificial intelligence, said Holly Balin, a spokesperson
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  Speaker 1: for Flock Safety. By inputting the type of vehicle, body style, color,
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  Speaker 1: and number of other characteristics of the truck into the
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  Speaker 1: flock system, it told investigators that the precise truck had
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  Speaker 1: been seen by another camera on Interstate 70 in Glenwood Springs,
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  Speaker 1: headed toward Denver before the heist. At that time, the
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  Speaker 1: truck displayed California license plates. So that was a major
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  Speaker 1: break in the case. The flock cameras tracked the pickup
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  Speaker 1: truck a long way back based on its physical characteristics.
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  Speaker 1: And with the help of Flock's patented AI, in this case,
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  Speaker 1: the authorities learned that the truck involved in the jewelry
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  Speaker 1: heist was displaying a California plate at one point along
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  Speaker 1: Interstate 70. And meanwhile, the authorities obtained a search warrant
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  Speaker 1: for the cell phone tower at the shopping center. They
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  Speaker 1: found that a phone belonging to an illegal alien named
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  Speaker 1: Gustavo Salas Ortega was active at the mall during the heist.
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  Speaker 1: And by itself, that's not a smoking gun because there's
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  Speaker 1: plenty of reasons.
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  Speaker 2: Why somebody might be around the mall. late at night, arguably.
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  Speaker 1: But in this case, the information was damning because the
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  Speaker 1: same cell phone also pinged the tower along Interstate 70
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  Speaker 1: at the precise moment the flock cameras were capturing the
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  Speaker 1: pickup truck. So in other words, because of the flock
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  Speaker 1: cameras in conjunction with cell phone data, authorities developed probable
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  Speaker 1: cause that Gustavo Salas Ortega was involved in the robbery.
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  Speaker 1: He wasn't simply at the mall during the robbery. He
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  Speaker 1: was also driving a truck that arrived right before the
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  Speaker 1: robbery carrying construction workers and left once the robbery was concluded. Again,
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  Speaker 1: Whenever you think of flock cameras or the privacy implications
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  Speaker 1: in these cases, the flock cameras were clearly useful. Not
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  Speaker 1: just useful, they were pivotal in solving a serious crime.
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  Speaker 1: There's no getting around that. It is a good thing, unambiguously,
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  Speaker 1: for murderers and illegal alien jewelry.
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  Speaker 2: Thieves to be in prison.
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  Speaker 1: We need to remove these people from society and the
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  Speaker 1: cameras allow the authorities to do that.
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  Speaker 2: So it can't be as simple.
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  Speaker 1: If we have technology that would help us solve crimes
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  Speaker 1: like this, it cannot be as simple as just to say, well,
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  Speaker 1: we just.
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  Speaker 2: Shouldn't use it. We should be more sporting. We should
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  Speaker 2: be good sports.
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  Speaker 1: Yeah, we could solve these crimes, but it'd be better
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  Speaker 1: to have these murderers running free. That seems like a
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  Speaker 1: wildly overly simplistic take on this issue. And there's a
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  Speaker 1: reason that no one at MSNOW or on your favorite
• 14:25
  Speaker 1: conspiracy podcast wants to talk about these cases. It's a
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  Speaker 1: lot easier to get clicks by telling people that Big
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  Speaker 1: Brother is watching.
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  Speaker 2: Them and that they need to panic and riot in.
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  Speaker 1: The streets about it. But the reality is just a
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  Speaker 1: lot more complicated. And there are plenty of other cases
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  Speaker 1: I could talk about. Just a couple of weeks ago
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  Speaker 1: in Porter County, Indiana, a flock camera alerted police to
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  Speaker 1: a stolen U-Haul on the highway. They pulled it over,
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  Speaker 1: arrested the driver and returned the vehicle. Again, it's clearly
• 14:51
  Speaker 1: a positive outcome. Last year, flock cameras tracked down a
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  Speaker 1: man who shot a police officer in Oklahoma. The cameras
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  Speaker 1: traced his vehicle to New Mexico. The cameras identified his
• 15:00
  Speaker 1: license plate in a Walmart parking lot. Police swarmed the area.
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  Speaker 1: The guy then shot himself. This is clearly a violent
• 15:06
  Speaker 1: and dangerous person. And because of these cameras, the police
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  Speaker 1: got to him before he could shoot anyone else except himself, which,
• 15:12
  Speaker 1: you know, well, that's his choice.
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  Speaker 2: Makes things easier in a lot of ways.
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  Speaker 1: Then there was the carjacking that took place a couple
• 15:18
  Speaker 1: of months ago in Oakland County, Michigan, in which a
• 15:21
  Speaker 1: man shot a woman in a mall parking lot and
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  Speaker 1: took her car. The police department used flock cameras to
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  Speaker 1: find the car and arrest the carjacker in.
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  Speaker 2: A little over an hour.
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  Speaker 1: There was also the 60-year-old man in Indiana who was
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  Speaker 1: arrested near a park for sexual battery on a juvenile
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  Speaker 1: after flock cameras found his car. That seems like a
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  Speaker 1: positive outcome. And here's another example from Iowa a few
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  Speaker 1: months ago.
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  Speaker 7: Last Tuesday, one person was shot and another assaulted here
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  Speaker 7: at Nicholson Ford Park.
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  Speaker 8: Marshalltown police were later able to arrest a suspect thanks
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  Speaker 8: to a piece of technology.
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  Speaker 9: The technology is extremely beneficial for us.
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  Speaker 8: The two victims who were at Nicholson Ford Park, along
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  Speaker 8: with witnesses, gave authorities a description of the vehicle.
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  Speaker 9: We really didn't have a whole lot to go off
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  Speaker 9: right away, short of a vehicle description. So we were
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  Speaker 9: able to use our flock cameras.
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  Speaker 8: Captain Kyle Stevenson with Marshalltown Police says one of the
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  Speaker 8: flock cameras helped authorities zero in on a vehicle the
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  Speaker 8: day of the incident.
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  Speaker 9: It was kind of a unique vehicle description, and we
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  Speaker 9: were able to use the cameras to find that vehicle
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  Speaker 9: and identify the vehicle and then ultimately the occupants of
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  Speaker 9: the vehicle.
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  Speaker 2: And here's one more.
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  Speaker 1: This is from the Brown University mass shooting that you
• 16:30
  Speaker 1: probably remember from the end of last year. A random
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  Speaker 1: homeless guy reported a suspicious vehicle on Reddit. and told
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  Speaker 1: police that it was probably related to the shooting. They
• 16:38
  Speaker 1: tracked the car retroactively and learned that it had been
• 16:41
  Speaker 1: spotted 14 times by flock cameras in the two weeks
• 16:44
  Speaker 1: before the shooting.
• 16:45
  Speaker 2: Watch.
• 16:46
  Speaker 5: Now, a case that gripped the nation can be seen
• 16:49
  Speaker 5: as the latest success story for flock cameras. Much of
• 16:52
  Speaker 5: the Northeast was on edge after two people died and
• 16:55
  Speaker 5: many others were injured in a mass shooting at Brown University.
• 16:59
  Speaker 5: Police then connected the gunman on the loose to the
• 17:01
  Speaker 5: murder of an MIT professor. more fear and concern out
• 17:05
  Speaker 5: in the community. After several days, investigators got their breakthrough tip,
• 17:09
  Speaker 5: a lead on the car driven by the gunman. According
• 17:13
  Speaker 5: to an Associated Press report, police used the 70 flock
• 17:16
  Speaker 5: cameras in Providence, Rhode Island, to retroactively track the movement
• 17:20
  Speaker 5: of the suspect's Nissan sedan. That trail helped lead them
• 17:24
  Speaker 5: to a storage facility in New Hampshire, where police found
• 17:27
  Speaker 5: the suspect dead.
• 17:29
  Speaker 2: His motive? Still unknown.
• 17:33
  Speaker 1: Now, we can spend the next few weeks talking about
• 17:35
  Speaker 1: cases like this, but you get the point.
• 17:37
  Speaker 2: These are verifiable.
• 17:39
  Speaker 1: These are true stories in which flock cameras clearly assisted
• 17:41
  Speaker 1: the authorities in tracking some very dangerous people. These cameras
• 17:45
  Speaker 1: have saved lives as a result. There's no question about it.
• 17:48
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  Speaker 1: By itself, of course, that doesn't mean the campaign are
• 19:50
  Speaker 1: automatically a net positive. It's a good point in their favor.
• 19:55
  Speaker 1: It doesn't automatically mean it. It doesn't mean we shouldn't
• 19:57
  Speaker 1: talk about the privacy implications. But if we're going to
• 19:59
  Speaker 1: have an honest discussion about these cameras, we have to
• 20:01
  Speaker 1: talk about the benefits that are clearly being realized because
• 20:06
  Speaker 1: of the cameras. You can't weigh the pros and cons
• 20:08
  Speaker 1: of the cameras And you can't talk about the trade-offs
• 20:11
  Speaker 1: if you simply refuse to discuss stories like this. Now,
• 20:15
  Speaker 1: if you ignore all this evidence and simply conclude that
• 20:18
  Speaker 1: anybody who supports flock cameras must be a corporate shill
• 20:21
  Speaker 1: or a fed or whatever retarded nonsense, then you're not
• 20:25
  Speaker 1: worth taking seriously. I mean, I could just as easily
• 20:27
  Speaker 1: say that you're on the side of the foreign invaders
• 20:29
  Speaker 1: and the leftist NGO allies who despise flock cameras because
• 20:32
  Speaker 1: they're being used to enforce immigration law. Which, by the way,
• 20:36
  Speaker 1: is one of the main reasons why the left doesn't
• 20:37
  Speaker 1: like them. That's what they're really upset about. if we're
• 20:40
  Speaker 1: actually being honest. People who enforce COVID lockdowns don't actually
• 20:44
  Speaker 1: care about your privacy. Their sole objective for some time
• 20:48
  Speaker 1: now has been to flood this country with criminals, particularly
• 20:50
  Speaker 1: foreign criminals, but really any criminal that they can take,
• 20:53
  Speaker 1: they'll take them all, in order to enact demographic replacement.
• 20:57
  Speaker 1: They've turned California into a colony of Mexico that will
• 21:00
  Speaker 1: never again elect another Republican, and they want to do
• 21:02
  Speaker 1: the same thing to the rest of the country. Flock
• 21:04
  Speaker 1: cameras stand in the way, which is why they oppose them.
• 21:08
  Speaker 2: It's that simple.
• 21:10
  Speaker 1: Let's go back to that MSNOW segment to give you
• 21:12
  Speaker 1: an idea. So don't take it from me. Listen to
• 21:16
  Speaker 1: their objections.
• 21:19
  Speaker 4: And now the fight over flock has moved on to
• 21:21
  Speaker 4: college campuses. At least 75 campuses have these cameras. Places
• 21:27
  Speaker 4: that my next guest, Bulwark journalist Adrian Carrasquillo says are
• 21:31
  Speaker 4: the next frontier of the deportation wars.
• 21:33
  Speaker 2: But there are students who are pushing back.
• 21:35
  Speaker 4: The Bulwark reports that groups are organizing against the use
• 21:38
  Speaker 4: of plate readers with the goal to, quote, see flock
• 21:41
  Speaker 4: no longer deployed on campuses at all. And joining me
• 21:44
  Speaker 4: now to discuss it all is Adrian Carrasquillo, national immigration
• 21:48
  Speaker 4: correspondent at The Bulwark, and Tobias Halpern, student at California
• 21:51
  Speaker 4: Polytechnic State University and founder of DFLOC, S-L-O, a.k.a.
• 21:55
  Speaker 2: SLO.
• 21:56
  Speaker 4: Tobias, let me start with you. Thanks to both of
• 21:58
  Speaker 4: you for being here. Tell me more about what you
• 22:00
  Speaker 4: guys are doing at DFLOC, SLO, and, you know, why
• 22:04
  Speaker 4: of all the issues on a college campus is this
• 22:06
  Speaker 4: so important to you?
• 22:08
  Speaker 10: Yeah i mean so we we're in a unique unique
• 22:11
  Speaker 10: institution where san luis obispo and cal poly claims to
• 22:15
  Speaker 10: be a hispanic serving institution and as you started to
• 22:19
  Speaker 10: bring up the ice connection was uh just too big
• 22:22
  Speaker 10: to ignore when you opt into flock when you buy
• 22:26
  Speaker 10: a flock camera like cal poly did you don't just
• 22:29
  Speaker 10: buy a surveillance camera you're buying access and participation into
• 22:33
  Speaker 10: this network And so I think that's what really bothers people,
• 22:37
  Speaker 10: and that's what really bothers students, and that's what bothered
• 22:39
  Speaker 10: us at Cal Poly, is that as a Hispanic-serving institution,
• 22:44
  Speaker 10: they are going out and entering this network that has
• 22:47
  Speaker 10: time and time again aided ICE in illegal deportations and
• 22:51
  Speaker 10: just created this surveillance dragnet that is really uncomfortable to
• 22:55
  Speaker 10: anyone when you think about it.
• 22:57
  Speaker 1: So MSNOW brings on two guests, both of them opposed
• 23:00
  Speaker 1: to FLOC, and both of them spend the entire time
• 23:02
  Speaker 1: talking about ICE and immigration enforcement. And one of them
• 23:05
  Speaker 1: is literally an immigration reporter. The other is some kid
• 23:08
  Speaker 1: who's concerned about illegal deportations, by which he means deportations.
• 23:11
  Speaker 1: Of course, all deportations are illegal to these people.
• 23:14
  Speaker 2: This is not an accident. This is their entire focus.
• 23:17
  Speaker 1: The kid's not worried about flock cameras somehow being used
• 23:19
  Speaker 1: to frame him for a crime or record him in
• 23:21
  Speaker 1: his home or any of the horror stories you might
• 23:23
  Speaker 1: hear about. He's concerned that flock cameras will be used
• 23:25
  Speaker 1: to identify and deport Democrat Party voters. That's where the
• 23:28
  Speaker 1: left's opposition to flock cameras comes from. similar to why
• 23:32
  Speaker 1: they hate ring cameras. It's why they elect DAs who
• 23:35
  Speaker 1: open the prisons. They want criminals to get away with crimes.
• 23:37
  Speaker 1: I mean, it's really no more complicated than that. So
• 23:40
  Speaker 1: if you're on the right, if you want to preserve
• 23:42
  Speaker 1: Western civilization, which means preserving law and order and national identity,
• 23:47
  Speaker 1: you're making common cause with these people. It doesn't necessarily
• 23:50
  Speaker 1: mean you're wrong, but it should give you some pause.
• 23:53
  Speaker 1: It should make you scrutinize very carefully why you oppose
• 23:56
  Speaker 1: plot cameras.
• 23:57
  Speaker 2: And what you know about them. So let's do that.
• 24:00
  Speaker 1: Now, the arguments against flock cameras break down into two categories,
• 24:03
  Speaker 1: hypothetical problems and actual problems, meaning cases where flock has
• 24:07
  Speaker 1: been misused beyond any doubt. Professor Wilford Riley offers this
• 24:11
  Speaker 1: example of a hypothetical problem with flock cameras. He says, quote,
• 24:14
  Speaker 1: it just objectively is bad if you scuffle with a
• 24:17
  Speaker 1: bum for 45 seconds to protect your girl, make out
• 24:19
  Speaker 1: with that same lady against the wall outside a nightclub,
• 24:22
  Speaker 1: or drive 25 miles over the speed limit anywhere a
• 24:25
  Speaker 1: robot can fly to your house and charge you with
• 24:27
  Speaker 1: 2A misdemeanors. This is especially the case given that one,
• 24:31
  Speaker 1: only taxpayers with addresses can get targeted in this fashion,
• 24:34
  Speaker 1: and two, this will immediately get political in both directions. Now,
• 24:39
  Speaker 1: this is a scenario that we should say, for the record,
• 24:42
  Speaker 1: has never taken place. As far as I know, nothing
• 24:44
  Speaker 1: like this has actually ever occurred. And for good measure,
• 24:47
  Speaker 1: we'll include Peter Hassan's reply.
• 24:49
  Speaker 2: To that post. He's at the Free Beacon.
• 24:51
  Speaker 1: He says, quote, I'm sorry, but the flock discussions are
• 24:53
  Speaker 1: so deranged. Flock is basically a tool to make it
• 24:55
  Speaker 1: easier to catch gangbangers after drive-by shootings, which is why
• 24:58
  Speaker 1: libs hate it. And you have people on the right
• 25:00
  Speaker 1: making up fake scenarios and then getting mad about them.
• 25:03
  Speaker 2: Very stupid own goals.
• 25:05
  Speaker 1: Now, as you'd imagine, Peter was dogpiled for that post,
• 25:09
  Speaker 1: including by people on the right.
• 25:11
  Speaker 2: It's not an easy position to stake out.
• 25:12
  Speaker 1: A lot of people replied to him by making the
• 25:14
  Speaker 1: argument that under a future Democrat administration, you could imagine
• 25:17
  Speaker 1: Riley scenario happening for real. During the next fake pandemic,
• 25:21
  Speaker 1: you could easily picture Gavin Newsom's administration shutting down the
• 25:24
  Speaker 1: roads and arresting any homeowner in a right-wing neighborhood who
• 25:26
  Speaker 1: ventures outside. And just as easily, you could imagine Gavin
• 25:29
  Speaker 1: Newsom's administration allowing foreigners and felons like George Floyd to
• 25:33
  Speaker 1: roam the streets with total impunity. This is the anarcho-tyranny
• 25:37
  Speaker 1: objection to flock cameras, which Mike Cernovich has made very forcefully.
• 25:40
  Speaker 1: The idea is that if the rule of law existed
• 25:43
  Speaker 1: in this country, then flock cameras would be fine. But
• 25:46
  Speaker 1: we all saw how the FBI ruthlessly hunted down January
• 25:49
  Speaker 1: 6th grandmothers, while at the same time they ignored BLM
• 25:52
  Speaker 1: rioters who committed murder and destroyed small businesses all over
• 25:55
  Speaker 1: the country. We all saw how we saw how the
• 25:57
  Speaker 1: public health experts so-called said we couldn't protest the lockdowns
• 26:00
  Speaker 1: because it was too dangerous. But at the same time,
• 26:02
  Speaker 1: BLM had every right to terrorize entire neighborhoods because white
• 26:06
  Speaker 1: supremacy was supposedly an even bigger problem than COVID. So
• 26:09
  Speaker 1: what guarantees do we have that flock cameras won't be
• 26:12
  Speaker 1: used in the exact same way to punish the enemies
• 26:14
  Speaker 1: of the Democrat Party? Well, the answer, of course, is
• 26:17
  Speaker 1: that we have no guarantees whatsoever. I mean, it's conceivable
• 26:21
  Speaker 1: that if communists take control of the government, again, they'll
• 26:24
  Speaker 1: use these cameras to crack down on free expression. They'll
• 26:27
  Speaker 1: track us everywhere we go. They'll make sure we aren't
• 26:29
  Speaker 1: going to go to any unapproved gatherings or visit any
• 26:33
  Speaker 1: enemies of the state. They'll make 1984 real, and we'll
• 26:36
  Speaker 1: have to endure another 50 years of listening to cliched
• 26:40
  Speaker 1: references to that particular book. And as alarming as that
• 26:44
  Speaker 1: hypothetical is, We have to keep a few things in mind.
• 26:47
  Speaker 1: First of all, AI-powered devices are already tracking us everywhere
• 26:51
  Speaker 1: we go. They're called cell phones. And unlike flock cameras,
• 26:55
  Speaker 1: which mainly track vehicles, cell phones are usually in your pocket.
• 27:01
  Speaker 1: They log every single one of your movements going back years.
• 27:04
  Speaker 1: I'm not just talking about Google services like Google Maps,
• 27:07
  Speaker 1: which record your location in the background. I'm talking about
• 27:09
  Speaker 1: the cell phone signal itself, even when you're not using
• 27:12
  Speaker 1: the phone. Just to give you an idea of how
• 27:15
  Speaker 1: precise this tracking is, remember the lunatic who ambushed those
• 27:19
  Speaker 1: firefighters in Idaho last summer? He lit a brush fire
• 27:22
  Speaker 1: on the west slope of Canfield Mountain, and then when
• 27:24
  Speaker 1: the firefighters showed up, he retreated to the woods and
• 27:26
  Speaker 1: opened fire. Now, the SWAT team had no idea where
• 27:30
  Speaker 1: the shooter was, so they spent several hours slowly driving
• 27:33
  Speaker 1: up to the scene of the shooting in an armored Bearcat,
• 27:36
  Speaker 1: trying to find where the sniper had gone. They didn't
• 27:38
  Speaker 1: want to get out and look because they were worried
• 27:40
  Speaker 1: they'd get shot. And they sent up thermal drones, but
• 27:43
  Speaker 1: they weren't returning any heat signatures.
• 27:45
  Speaker 2: So what did they do?
• 27:46
  Speaker 1: Well, they got a court order requiring a cell phone
• 27:49
  Speaker 1: company to provide information about any cell phones in the area.
• 27:53
  Speaker 1: And while they had a tentative match with somebody in
• 27:55
  Speaker 1: the woods, the data wasn't specific enough to pinpoint the
• 27:57
  Speaker 1: suspect's exact location. So the FBI flew a helicopter overhead
• 28:01
  Speaker 1: equipped with digital receiver technology, which is basically a cell
• 28:04
  Speaker 1: site simulator. It mimics a cell tower and cell phones
• 28:07
  Speaker 1: automatically attempt to connect to it. That's how they located
• 28:10
  Speaker 1: the precise location of the shooter within a margin of inches.
• 28:14
  Speaker 2: Okay.
• 28:15
  Speaker 1: So in other words, if you have a cell phone,
• 28:18
  Speaker 1: then you can't hide from anyone. If you have a
• 28:20
  Speaker 1: cell phone, then the scenario you're worried about with flock
• 28:23
  Speaker 1: cameras is already happening. Google, Apple, and the cell phone
• 28:28
  Speaker 1: carriers already know everything about you, including where you are
• 28:32
  Speaker 1: every second of the day. They're all selling that information.
• 28:35
  Speaker 1: And even if they weren't, the FBI has equipment that
• 28:37
  Speaker 1: can locate precisely where your cell phone is at any
• 28:40
  Speaker 1: moment in time. So if you're opposed to flock cameras,
• 28:44
  Speaker 1: then it doesn't make any sense to also have no
• 28:47
  Speaker 1: problem with the cell phone.
• 28:48
  Speaker 2: There's no getting around it.
• 28:50
  Speaker 1: But even if you successfully lobby to get flock cameras
• 28:53
  Speaker 1: banned nationwide, and even if you throw away your phone,
• 28:56
  Speaker 1: you're still going to be tracked by cameras 99% of
• 28:59
  Speaker 1: the time. First of all, pretty much every residential neighborhood
• 29:03
  Speaker 1: is now flooded with ring cameras. If you go for
• 29:05
  Speaker 1: a walk in a typical suburb, there's a very good
• 29:08
  Speaker 1: chance that ring cameras can easily piece together your entire
• 29:11
  Speaker 1: route and listen to your conversations. Many of these cameras
• 29:15
  Speaker 1: have enough range to see the street, so they can
• 29:18
  Speaker 1: track vehicles also. Now, it's true that Ring cameras are
• 29:21
  Speaker 1: technically more decentralized than Flock cameras, since Flock cameras are
• 29:24
  Speaker 1: leased to law enforcement agencies, but owned and maintained by Flock,
• 29:28
  Speaker 1: while Ring cameras are owned by millions of individuals, homeowners.
• 29:31
  Speaker 2: And business owners.
• 29:32
  Speaker 1: But in practice, it's not much of a distinction. Ring,
• 29:35
  Speaker 1: like Flock, maintains all the footage on its servers. During
• 29:39
  Speaker 1: an investigation, police can easily obtain a search warrant for
• 29:42
  Speaker 1: all of that footage without asking individual homeowners for permission.
• 29:46
  Speaker 1: So if you want to ban Flock cameras, then to
• 29:50
  Speaker 1: achieve any kind of meaningful result, you really have to
• 29:52
  Speaker 1: ban Ring cameras too.
• 29:54
  Speaker 2: And that would obviously be a disaster for about a
• 29:56
  Speaker 2: dozen reasons.
• 29:57
  Speaker 1: First of all, people have the right to install cameras
• 29:59
  Speaker 1: on their own property if they want to.
• 30:02
  Speaker 2: That's their right.
• 30:02
  Speaker 1: Secondly, Ring cameras capture all kinds of criminal activity every
• 30:05
  Speaker 1: single day. If you've ever used the Ring app, you
• 30:09
  Speaker 1: know that people are constantly posting videos of crimes. They're
• 30:11
  Speaker 1: also posting thousands of comments about missing dogs and lost mail,
• 30:14
  Speaker 1: which you need to filter out before you go insane.
• 30:17
  Speaker 1: But third, as a journalist Cam Higbee pointed out, once
• 30:19
  Speaker 1: you start banning private people from using cameras, you're basically
• 30:22
  Speaker 1: making it illegal to be a journalist. a real journalist anyway.
• 30:26
  Speaker 1: Cam Higbee has shot some extremely important footage over the
• 30:28
  Speaker 1: past few years. We feature his coverage on the show
• 30:30
  Speaker 1: many times. He's one of the few people who's willing
• 30:33
  Speaker 1: to risk his life to cover Antifa violence, for example.
• 30:35
  Speaker 1: But if we're going to ban private surveillance, then we
• 30:38
  Speaker 1: have to ban journalists like Cam Higbee too. Now, of course,
• 30:42
  Speaker 1: none of the opponents of Flock will go that far.
• 30:44
  Speaker 1: When you drill down, they'll say that they're really opposed
• 30:47
  Speaker 1: to Flock because there are specific concrete issues with this
• 30:50
  Speaker 1: specific surveillance system, not cameras in general.
• 30:54
  Speaker 2: That's where the actual debate lies. At least that's.
• 30:55
  Speaker 1: What the rational critics will say. So let's focus on
• 30:59
  Speaker 1: that debate, on the rational debate, as opposed to the
• 31:03
  Speaker 1: hypotheticals and the grand sweeping paranoia about a surveillance state
• 31:07
  Speaker 1: that has already been in place for a really long
• 31:09
  Speaker 1: time and you're already participating in every single day when you.
• 31:11
  Speaker 2: Walk around with your cell phone.
• 31:14
  Speaker 1: The first substantive argument against Flock, one you may have seen,
• 31:18
  Speaker 1: is that they supposedly spied on children. So here's one
• 31:20
  Speaker 1: viral post, for example, that has millions of views. Quote,
• 31:23
  Speaker 1: a flock vice president logged into the Dunwoody PD's flock
• 31:27
  Speaker 1: system and looked at a camera in the children's gymnastics
• 31:29
  Speaker 1: room of a private community center here in Dunwoody. He
• 31:32
  Speaker 1: did not look at any other cameras in the entire
• 31:34
  Speaker 1: 400 camera network that day. Now, the way that's written,
• 31:38
  Speaker 1: it obviously sounds like the flock vice president is a
• 31:41
  Speaker 1: pervert who belongs in prison. And indeed, you'll find thousands
• 31:44
  Speaker 1: of comments accusing the VP by name of being a pedophile. Now,
• 31:49
  Speaker 1: what this post omits is that, according to Flock, their
• 31:51
  Speaker 1: vice president was running a sales demo of the system
• 31:54
  Speaker 1: when he pulled up to feed. He wasn't specifically trying
• 31:56
  Speaker 1: to pull up the gymnastics center for the purpose of
• 31:58
  Speaker 1: looking at children. Instead, they say he was trying to
• 32:01
  Speaker 1: demonstrate how the system safeguards work. So, for example, if
• 32:04
  Speaker 1: you try to search for Star of David so that
• 32:06
  Speaker 1: you can round up all the Jews, it will deny
• 32:08
  Speaker 1: the request. Now, if you try to enter someone's specific name,
• 32:11
  Speaker 1: it will deny the request. It's only supposed to pull
• 32:14
  Speaker 1: up videos that match general descriptions like black pickup truck,
• 32:17
  Speaker 1: you know, or something like that.
• 32:19
  Speaker 2: Now, is Floch's story excuse true?
• 32:23
  Speaker 1: We don't know, but it's also true that we have
• 32:26
  Speaker 1: no actual evidence that Floch's VP is a pedophile. The
• 32:29
  Speaker 1: VP knows that all of these searches are stored, which
• 32:32
  Speaker 1: is how they were eventually released to the public, so
• 32:34
  Speaker 1: it certainly would be odd for him to pull up
• 32:36
  Speaker 1: this footage one day knowing that anyone could submit a
• 32:39
  Speaker 1: records request and discover the search. If you're going to
• 32:42
  Speaker 1: accuse a man of one of the most serious crimes imaginable,
• 32:46
  Speaker 1: you need some evidence.
• 32:48
  Speaker 2: There's none here at all.
• 32:50
  Speaker 1: But even assuming their story is true, does that mean
• 32:55
  Speaker 1: that Flock bears no responsibility here?
• 32:56
  Speaker 2: Well, of course not.
• 32:57
  Speaker 1: They've admitted this was wrong and that Flock cameras that
• 32:59
  Speaker 1: are installed in sensitive locations shouldn't be a part of
• 33:02
  Speaker 1: any sales demo. The only reason Flock should have been
• 33:04
  Speaker 1: looking at this gymnastics center is if there was an
• 33:06
  Speaker 1: emergency and somebody was trying to harm these children, like
• 33:09
  Speaker 1: what happened at that Taylor Swift dance studio in the
• 33:11
  Speaker 1: UK when the foreigner who's family was imported from Rwanda,
• 33:14
  Speaker 1: massacred several children. So for example, that would be a
• 33:17
  Speaker 1: valid occasion to use the cameras. And you can see
• 33:22
  Speaker 1: the mugshot of that guy here, by the way, the
• 33:23
  Speaker 1: guy who looks like he's been struck by lightning every
• 33:25
  Speaker 1: day of his life. These people exist and Flock is
• 33:29
  Speaker 1: supposed to assist in tracking them. That was their deal
• 33:32
  Speaker 1: with the gymnastic center when they installed the equipment and
• 33:35
  Speaker 1: they broke the deal by accessing the footage for no reason.
• 33:38
  Speaker 1: But this is the perfect illustration of what I'm talking
• 33:41
  Speaker 1: about by making this about pedophilia and Critics of Flock
• 33:44
  Speaker 1: are discrediting themselves for no reason. There's no evidence that
• 33:46
  Speaker 1: Flock's vice president is a pervert. But that's the claim
• 33:50
  Speaker 1: Flock's detractors are making with total confidence. Instead of focusing
• 33:53
  Speaker 1: on the actual issue, which there is one, they're just
• 33:56
  Speaker 1: making something up. It's counterproductive. It's also extremely dumb. And
• 34:00
  Speaker 1: we see it all the time. Now, another argument you'll hear,
• 34:03
  Speaker 1: which is a better argument, is that Flock's tracking is
• 34:06
  Speaker 1: so pervasive and so extensive that it's the equivalent of
• 34:08
  Speaker 1: a specific police officer following.
• 34:10
  Speaker 2: You around all day when you're in your car.
• 34:13
  Speaker 1: Is the kind of surveillance that under our existing law
• 34:15
  Speaker 1: may be a violation of your Fourth Amendment rights. It's
• 34:17
  Speaker 1: true that anybody, including police officers, has the constitutional right
• 34:21
  Speaker 1: to observe you in public. You don't have any expectation
• 34:24
  Speaker 1: of privacy when you're driving in your car. People are
• 34:26
  Speaker 1: free to observe you on the road. But it's also
• 34:28
  Speaker 1: true that if somebody follows you around all the time,
• 34:31
  Speaker 1: everywhere you go, then they're crossing a line into stalking
• 34:33
  Speaker 1: and harassment. And the argument is that by tracking people
• 34:36
  Speaker 1: for hundreds of miles, flock cameras are basically acting as stalkers.
• 34:39
  Speaker 1: They're the equivalent of police officers who are harassing you,
• 34:42
  Speaker 1: following you around. Now, you can think of a few
• 34:46
  Speaker 1: ways to address this concern. One solution would be to
• 34:47
  Speaker 1: prevent anyone at Flock or a local police department from
• 34:50
  Speaker 1: viewing any footage without explicit authorization from a court. That's
• 34:54
  Speaker 1: already the expectation, but it's often violated. Flock footage is
• 34:58
  Speaker 1: routinely being accessed without any justification.
• 35:01
  Speaker 7: Watch.
• 35:03
  Speaker 3: A police officer who used license plate reader cameras to
• 35:06
  Speaker 3: track down a woman and wrongly accused her of theft
• 35:09
  Speaker 3: will be disciplined. This story has been spreading online over
• 35:12
  Speaker 3: the last month. Sergeant Jamie Milliman with the Columbine Valley
• 35:15
  Speaker 3: Police Department showed up to a woman's home and claimed
• 35:19
  Speaker 3: he had video evidence proving she stole a package. Milliman
• 35:22
  Speaker 3: used the flock safety cameras to track her down. Turns
• 35:25
  Speaker 3: out the allegation was wrong. The woman ended up proving
• 35:28
  Speaker 3: she wasn't the theft. The thief, in providing her own
• 35:32
  Speaker 3: video evidence, the town administrator with Columbine Valley, wrote that
• 35:35
  Speaker 3: Officer Milliman will be disciplined, but won't elaborate beyond that.
• 35:40
  Speaker 11: And now former Georgia Sheriff's employees facing charges accused of
• 35:44
  Speaker 11: using license plate data to stalk two people. And the
• 35:47
  Speaker 11: GBI is now investigating. Investigators say Ana Altabello, a secretary
• 35:52
  Speaker 11: at the Eccles County Sheriff's Office, searched the flock safety
• 35:56
  Speaker 11: system on multiple occasions for two people she knew personally.
• 36:00
  Speaker 11: The GBI says the searches were unrelated to any law
• 36:03
  Speaker 11: enforcement activity. And unfortunately, this isn't the first time that
• 36:07
  Speaker 11: law enforcement has been accused of misusing flock safety data.
• 36:11
  Speaker 11: Back in October, Sandy Springs Police said that they had
• 36:13
  Speaker 11: to fire a reserve officer for refusing to cooperate in
• 36:17
  Speaker 11: an investigation into possible misconduct related to the system.
• 36:22
  Speaker 1: These are cases you'll hear about a lot when you're
• 36:24
  Speaker 1: listening to the anti-flock side of the argument. They'll point
• 36:26
  Speaker 1: to the fact that technology has been abused. And there
• 36:29
  Speaker 1: are many more cases like this. Here's CBS Atlanta with
• 36:32
  Speaker 1: a recap. Cherokee County, three sheriff's employees, including a lieutenant
• 36:35
  Speaker 1: and sergeant, were arrested after investigators alleged they improperly searched
• 36:38
  Speaker 1: the county's License plate, reader database, Albany. Five former Albany
• 36:43
  Speaker 1: police officers were arrested after a Georgia Bureau investigation probe
• 36:47
  Speaker 1: found they allegedly used flock data for unauthorized purposes following
• 36:50
  Speaker 1: an internal audit. Green County Sheriff's deputy was arrested and
• 36:53
  Speaker 1: fired after investigators said an audit showed she used the
• 36:56
  Speaker 1: flock system for personal reasons. Fayetteville, three police officers were
• 37:00
  Speaker 1: fired this week after investigators say they searched license plates
• 37:02
  Speaker 1: belonging to themselves, family members, and acquaintances without a legitimate
• 37:05
  Speaker 1: law enforcement purpose. Meanwhile, Reason put out this video where
• 37:10
  Speaker 1: a sassy reporter outlines a few more egregious cases.
• 37:13
  Speaker 2: Watch.
• 37:13
  Speaker 6: 20 times in one month. Then there's the Arkansas couple
• 37:17
  Speaker 6: that had a flock camera pointed right at their house,
• 37:19
  Speaker 6: putting them and their guests under constant warrantless surveillance. And
• 37:24
  Speaker 6: not to perpetuate stereotypes, but multiple cops and police chiefs
• 37:27
  Speaker 6: have accessed flock hundreds of times to stalk their exes
• 37:31
  Speaker 6: and current partners. But don't worry, you can stalk people too,
• 37:34
  Speaker 6: because flock cameras are hackable in under 30 seconds. They
• 37:37
  Speaker 6: can be turned into a personal spy device, run on
• 37:39
  Speaker 6: an Android operating system discontinued in 2021, and didn't even
• 37:42
  Speaker 6: have two-factor authentication until it recently came out that they didn't.
• 37:46
  Speaker 6: YouTuber Ben Jordan even found 51 vulnerabilities with Flock and
• 37:49
  Speaker 6: said accessing them is so easy, 12-year-olds could do it.
• 37:53
  Speaker 6: We don't condone the destruction of Flock cameras, but we're
• 37:55
  Speaker 6: also not surprised the public has reached their boiling point.
• 37:58
  Speaker 6: One Virginia man now faces 19 felonies and six misdemeanors
• 38:02
  Speaker 6: for destroying 13 cameras over six months.
• 38:09
  Speaker 1: I hate the editing on these. I hate the way
• 38:11
  Speaker 1: these videos are edited now. Every video now, in particular,
• 38:15
  Speaker 1: any video where it's a woman talking to a camera now,
• 38:21
  Speaker 1: it's like, it's all, the tone, the attitude, the like,
• 38:27
  Speaker 1: I gotta have 50 different poses.
• 38:29
  Speaker 2: It's a 30 second video.
• 38:31
  Speaker 1: You have important information about a serious topic and you
• 38:35
  Speaker 1: need 50 poses? You're looking this way. You're up this way.
• 38:40
  Speaker 1: You're sitting down. You're on top of the light post.
• 38:42
  Speaker 1: You're doing pull-ups. And what is with everyone now, every video,
• 38:48
  Speaker 1: especially on TikTok, people have the cadence of like a
• 38:50
  Speaker 1: cartoon character. Yeah, that's like a cartoon character. Yeah, it's
• 38:54
  Speaker 1: like a cartoon character, cadence and tone and facial expressions
• 38:58
  Speaker 1: and like.
• 38:59
  Speaker 2: Moving around all the time.
• 39:00
  Speaker 1: Why is everyone talking like cartoon character? Just give the information.
• 39:05
  Speaker 2: That's all we need.
• 39:08
  Speaker 1: Does that, does anyone, do you absorb the information better
• 39:12
  Speaker 1: when they cut it together that way with 50 different
• 39:14
  Speaker 1: poses and the attitude and the tone and the cartoon character,
• 39:19
  Speaker 1: you know, cadence?
• 39:20
  Speaker 2: Does that help anybody?
• 39:21
  Speaker 1: Anyway. We needed flock cameras to track every single person
• 39:30
  Speaker 1: who makes videos like that.
• 39:32
  Speaker 2: Round them all up and deport them to the surface
• 39:36
  Speaker 2: of the sun.
• 39:39
  Speaker 1: Anyway, these are all legitimate examples of problems with the
• 39:42
  Speaker 1: implementation of flock cameras. Some cops are misusing them for
• 39:45
  Speaker 1: personal reasons. The cameras also apparently have some technical vulnerabilities.
• 39:49
  Speaker 1: although it's worth pointing out that no one has actually
• 39:51
  Speaker 1: hacked these cameras in real life, as far as we know,
• 39:53
  Speaker 1: outside of these proof-of-concept tests. There have been situations where
• 39:57
  Speaker 1: police departments' passwords have been compromised or where camera feeds
• 40:00
  Speaker 1: have been broadcast online by mistake, but it looks like
• 40:04
  Speaker 1: those issues were patched. In any event, it's true that
• 40:06
  Speaker 1: flat cameras have been.
• 40:07
  Speaker 2: Abused, which is a problem. The problem is.
• 40:10
  Speaker 1: If you banned every technology that was abused, you wouldn't
• 40:13
  Speaker 1: have any technology left.
• 40:14
  Speaker 2: I mean, there have been.
• 40:16
  Speaker 1: Cases where bad actors purchased data from wireless carriers, which
• 40:19
  Speaker 1: they obtained via web portals operated by third-party brokers that
• 40:23
  Speaker 1: didn't run any legal checks. That doesn't mean that we
• 40:25
  Speaker 1: should ban cell phones. It means we should punish the
• 40:28
  Speaker 1: brokers who are selling the data. Along the same lines,
• 40:30
  Speaker 1: when Edward Snowden revealed that the NSA was secretly collecting
• 40:33
  Speaker 1: phone data from millions of Verizon users with secret warrants,
• 40:37
  Speaker 1: nobody suggested that we should ban Verizon or cell phones,
• 40:40
  Speaker 1: and for good reason. For all my critiques of modern technology,
• 40:46
  Speaker 1: and there are many, cell phones are ultimately do more
• 40:51
  Speaker 1: good than harm. The fact that bad actors can hijack
• 40:55
  Speaker 1: our cell phone data doesn't mean that we should revert
• 40:57
  Speaker 1: to the Stone Age. It means that to the best
• 40:58
  Speaker 1: of our ability, we need to recognize that some degree
• 41:01
  Speaker 1: of surveillance is an inevitable byproduct.
• 41:04
  Speaker 2: Of the age that we're living in. It's just the reality.
• 41:07
  Speaker 1: The only practical safeguard against the abuse of that surveillance,
• 41:11
  Speaker 1: aside from the things we've already talked about, putting systems
• 41:15
  Speaker 1: and policies and laws in place, governing when this kind
• 41:18
  Speaker 1: of stuff can be accessed and.
• 41:19
  Speaker 2: By who, which we should do.
• 41:23
  Speaker 1: But that all requires that we elect people who will
• 41:27
  Speaker 1: not abuse the technology and punish those.
• 41:31
  Speaker 2: Who do abuse it or will.
• 41:34
  Speaker 1: End the anarcho-tyranny. Now, that's not the most dramatic or
• 41:39
  Speaker 1: compelling solution. It's not a perfect solution. But it's the
• 41:44
  Speaker 1: only one with any chance of success. It's the only
• 41:47
  Speaker 1: choice we have. We can't align with communists for any
• 41:51
  Speaker 1: reason on any issue. We can't repeat the talking points
• 41:53
  Speaker 1: from activists on MSNOW who are lying to your face
• 41:56
  Speaker 1: in order to subvert ICE and assist illegal aliens in
• 41:59
  Speaker 1: avoiding detection. I mean, as unpopular as it may be
• 42:02
  Speaker 1: to say, with or without Flock, mass surveillance is already here.
• 42:06
  Speaker 1: It's been here for a long time. You've already made
• 42:10
  Speaker 1: yourself 100% trackable and traceable with the cell phone you're
• 42:15
  Speaker 1: using to listen to me right now. And while that
• 42:18
  Speaker 1: may sound ominous, and it is, the truth is there
• 42:22
  Speaker 1: are a few things even worse than mass surveillance. Mass
• 42:27
  Speaker 1: demographic replacement is one of those things. So don't let
• 42:31
  Speaker 1: your concerns about mass surveillance, which are totally legitimate, turn
• 42:36
  Speaker 1: you into an unwitting supporter of mass demographic replacement. That's
• 42:40
  Speaker 1: where the flock debate is heading. Whether or not you're
• 42:43
  Speaker 1: a fan of flock cameras, that's the unavoidable reality of
• 42:48
  Speaker 1: the current debate. Now, yes, if you say that out loud,
• 42:51
  Speaker 1: you'll be called a shill and a fed and a fascist.
• 42:54
  Speaker 1: But one thing you won't be is an accomplice to
• 42:56
  Speaker 1: the largest foreign invasion this country has ever seen. You'll
• 43:00
  Speaker 1: be one of the few people who's not giving the
• 43:02
  Speaker 1: communists exactly what they want right now. And whether you
• 43:06
  Speaker 1: support flock or not, that's a pretty good place to be.
• 43:11
  Speaker 2: That'll do it for the show today. Thanks for watching.
• 43:12
  Speaker 2: Thanks for listening. Talk to you tomorrow. Have a great day. Godspeed.
• 43:22
  Speaker 1: Once upon a time, there was a country.
• 43:25
  Speaker 2: Not just a country, but a big one, an empire.
• 43:28
  Speaker 1: And in that empire, there was an upper middle class
• 43:30
  Speaker 1: family where two boys were raised by their mother, loved books,
• 43:35
  Speaker 1: Uncle Tom's cabin, and the Bible. Their father admired the
• 43:38
  Speaker 1: country's leaders. were patriotic and happy. Both sons went to
• 43:43
  Speaker 1: universities where they were radicalized. One of the brothers read
• 43:46
  Speaker 1: a book and convinced him to try to shoot the
• 43:48
  Speaker 1: country's leader.
• 43:49
  Speaker 2: He was hanged.
• 43:51
  Speaker 1: The other brother read the same books but decided to
• 43:54
  Speaker 1: lead a movement. First they came from the universities and
• 43:57
  Speaker 1: no one.
• 43:57
  Speaker 2: Seemed to care. Then they took over the unions and again,
• 44:00
  Speaker 2: no one seemed to care.
• 44:01
  Speaker 1: Then they created their own media organizations and took over
• 44:04
  Speaker 1: the cities.
• 44:05
  Speaker 2: And again, most people just ignored it. Change, after all,
• 44:08
  Speaker 2: was something they could believe in. until it was too late.
• 44:12
  Speaker 2: Sound familiar? This is the real history of communism, the
• 44:16
  Speaker 2: Russian Revolution.