Speaker 1: Brought to you by Toyota. Let's go places. Welcome to
Speaker 1: Forward Thinking. Hi there, everyone, and welcome to Forward Thinking,
Speaker 1: the podcast that looks at the future and says, someone
Speaker 1: left the cake out in the rain. I'm Jonathan Strickland,
Speaker 1: I'm Lauren voc Obama, and I'm Joe McCormick. And we'll
Speaker 1: never have that recipe again. All right, So today we
Speaker 1: wanted to talk about the fact that we have a
Speaker 1: proliferation of cameras all around us these days. There seems
Speaker 1: to always be a camera somewhere, whether it's in the
Speaker 1: hands of a person, or on on a street corner,
Speaker 1: or in a corner store, or on someone's face. There
Speaker 1: there seem to be just about everywhere, now right, Yeah,
Speaker 1: this has gone from science fiction to reality in our lifetimes. Yeah, yeah,
Speaker 1: right right, yeah. When when Well, i mean not that
Speaker 1: any of us were around in uh came out, but
Speaker 1: you just blew my mind. Yeah when Orwell published nineteen
Speaker 1: eighty four, which came out in nineteen forty nine, and
Speaker 1: that really did presage this era of surveillance where in
Speaker 1: that case, a very uh totalitarian and oppressive government was
Speaker 1: using surveillance to keep the population cowed and under control. Right,
Speaker 1: There was a sense that you never knew when someone
Speaker 1: was watching you, so you so there had to be
Speaker 1: on good behavior continually because yeah, you had to operate
Speaker 1: under the assumption that you were being watched and that
Speaker 1: someone was going to punish you if you didn't anything wrong.
Speaker 1: That's kind of interesting considering that when when that book
Speaker 1: came out in nineteen forty nine, that actually predates the
Speaker 1: uh the deployment of a lot of CCTV technology, which
Speaker 1: followed a few years later. But the earliest I could
Speaker 1: find of any sort of use of closed circuit television
Speaker 1: cameras dates back to nineteen forty two, and that was
Speaker 1: in World War Two Germany. They were using that not
Speaker 1: to keep an eye on citizens or try and report
Speaker 1: people or anything along those lines. They were using it
Speaker 1: because they needed a way to observe V two rocket
Speaker 1: launches without getting fried when something would go wrong. So
Speaker 1: losing a camera is better than losing a scientist with
Speaker 1: a clipboard who was standing there a second ago. And
Speaker 1: now there's just a pair of smoking shoes for MythBusters.
Speaker 1: Yeah right, Well, um, it looks like CCTV cameras first
Speaker 1: became popular or widespread in the seventies and eighties. Yeah,
Speaker 1: there was some there's some precedent for cameras in the
Speaker 1: UK before that, but it was all it wasn't necessarily
Speaker 1: close circuit television cameras. But back in nineteen sixty there
Speaker 1: were a couple of times when police in the UK
Speaker 1: installed cameras in Trafalgar Square. Once but when the tai
Speaker 1: royal family was visiting and they just wanted to make
Speaker 1: sure that they were able to keep an eye on
Speaker 1: crowd control. Uh. And then the other time was during
Speaker 1: well the fifth of November, which of course is Guy
Speaker 1: Fox Day. Remember remember I remember, do you the Gunpowder
Speaker 1: treason and plot? Wait, you're not saying they had sec
Speaker 1: TV camera when he tried to blow up Parliament. No,
Speaker 1: this was nineteen sixty on the anniversary of that. Actually
Speaker 1: was on the anniversary of him being captured. To be fair,
Speaker 1: Guy Fox Day is to celebrate the fact that the
Speaker 1: government captured Guy Fox, not the fact that a man
Speaker 1: tried to blow up Parliament, right, never know that from
Speaker 1: that movie and all the people who wear the masks. Yeah, no,
Speaker 1: that's true. I did a full podcast about Guy Fox
Speaker 1: Day on a on a completely separate channel where I
Speaker 1: talked about what Guy fox Day is all about and
Speaker 1: how the the modern misconception and particularly in America, casts
Speaker 1: it as sort of an anti hero. But really Guy
Speaker 1: fox Day was all about hey we stopped Yeah anyway,
Speaker 1: but that that was Those were two incidents where the
Speaker 1: London police installed some cameras. In both of those cases,
Speaker 1: those cameras were meant to just be temporary. They set
Speaker 1: him up in order to kind of give themselves a
Speaker 1: little extra manpower. Well, they thought it was such a
Speaker 1: great idea that they would just go ahead and deploy
Speaker 1: those suckers all over the place, although it did take
Speaker 1: them a few decades. Yeah, I saw something about I
Speaker 1: think the so there were some cameras like up in
Speaker 1: Times Square in the nineteen seventies and stuff like that,
Speaker 1: but um, this really got big in the eighties. I
Speaker 1: think between A figure I saw was that between nineteen
Speaker 1: eighty and two thousand, CCTV sales jumped seven Yeah, that's
Speaker 1: when the explosion. The early days were in the sixties
Speaker 1: and seventies where they were usually being laid out along
Speaker 1: roadways things like that in order to just keep an
Speaker 1: eye on how things were flowing through London. Mainly London
Speaker 1: was the big city where this was happening. You did
Speaker 1: have it in some other cities. New York had some
Speaker 1: in Times Square like you mentioned, but uh, and then
Speaker 1: you had some private companies or retail organizations that were
Speaker 1: installing them as a mean to try and counteract any
Speaker 1: sort of shoplifting activity. So but those were really the
Speaker 1: the main uses until the nineteen eighties. That's when it
Speaker 1: really started to quote unquote exclude well. Actually, uh, one
Speaker 1: thing that we one misconception we might want to clear
Speaker 1: up is this idea that most of these uh CCTV
Speaker 1: cameras are public. The majority, the vast majority, are still private. Um.
Speaker 1: So when when you've heard about how many times you
Speaker 1: might be photographed or video recorded going about your business
Speaker 1: throughout the day, most of those images are going to
Speaker 1: happen at you know, the shop, you go into, the
Speaker 1: place where you work, the public exactly. Yeah, um yeah, there,
Speaker 1: I mean, there there are plenty of official public cameras,
Speaker 1: public meaning that they're owned by the government as opposed
Speaker 1: to private companies. But they do have that. I mean,
Speaker 1: it's just a fraction of all the cameras that are
Speaker 1: out there, right, although it should be noted that according
Speaker 1: to the Electronic Can Occasions Privacy Act of nine, police
Speaker 1: can legally use footage from private cameras pursue any kind
Speaker 1: of Yeah. Yeah, and they do all the time, of course. Yeah. Um. Well,
Speaker 1: so one interesting question that people started worrying about, especially
Speaker 1: in the in the post nine eleven era, when they're
Speaker 1: started to be increasing awareness that maybe we should really
Speaker 1: worry about privacy and recording. Um, people started to say,
Speaker 1: how many cameras are there and how much of our
Speaker 1: lives are being recorded? Yeah, because there was no way
Speaker 1: of really knowing this. Uh, I would argue, there's still
Speaker 1: no way. Well, yeah, just essentially, if you have if
Speaker 1: you have a cell phone that was manufactured in the
Speaker 1: last you know, five years, you probably have you have
Speaker 1: at least a still camera, if not a full digital
Speaker 1: video camera that can upload uh footage directly to the
Speaker 1: internet or at least save it on the phone and
Speaker 1: then transferred. I'm just talking about cct not even when
Speaker 1: we we'll get to personal devices, and so even even
Speaker 1: answering the question about CCTV is deaf, That's all I'm
Speaker 1: talking about. Yeah, people who have cameras and and they're
Speaker 1: they're rolling. Yeah, you can count on it. UM. So
Speaker 1: there are a few different numbers. One number that you
Speaker 1: might have seen bouncing around a lot um is an
Speaker 1: estimate that comes from the UK, and the UK is
Speaker 1: famous for this because it's often said that it's the
Speaker 1: most surveiled place in the world. Right, they've got cameras everywhere,
Speaker 1: by the way, set in London in oceanny all right, yeah, yeah,
Speaker 1: airstrip one okay, UM, So the figure is four point
Speaker 1: two million. Now I'll revise this in a second, but
Speaker 1: this has been for years. People have bandied this about
Speaker 1: four point two million cameras in the UK and that
Speaker 1: works out to one camera for every fourteen people that
Speaker 1: takes I mean, and so you see this sited a
Speaker 1: lot of times by privacy advocates in the UK and stuff. Um.
Speaker 1: But it turns out that this is probably not the
Speaker 1: most accurate estimate UM. In fact, it's probably very high.
Speaker 1: Because the way they got this estimate um is that
Speaker 1: there was a paper that basically they looked at a
Speaker 1: couple of streets, um, and they were like, well, how
Speaker 1: many cameras are are on these streets, combining public cameras
Speaker 1: and cameras and you know, privately owned businesses and and
Speaker 1: all that, um. And then they extrapolated that out um
Speaker 1: and and got this really high number. UM. So in
Speaker 1: the county Cheshire in England. UM, they had police community
Speaker 1: support officers go through and physically count all of the
Speaker 1: cameras to see, well, exactly how many are there really?
Speaker 1: Um And then they use some statistical models to um say, well,
Speaker 1: you know, compared to the urban density and and stuff
Speaker 1: and other areas, UM, what we can say that the
Speaker 1: UK more likely has one point eight five million cameras,
Speaker 1: about significantly fewer than four points less than half of
Speaker 1: the original estimate. It's still a bunch. Yeah, well there
Speaker 1: are a few the funny things here. Either way, that's
Speaker 1: a huge amount of cameras. Number two, it's just kind
Speaker 1: of creepy that people have no idea their their estimates
Speaker 1: are differing by the millions. Well yeah, yeah, well when
Speaker 1: you get to when you get to big numbers, people
Speaker 1: are really bad about estimating that anyway. Right, This this
Speaker 1: goes beyond just cameras. This goes to just how how
Speaker 1: humans work in general. Like, once we get beyond a
Speaker 1: certain point, estimations no longer really work out in our favor.
Speaker 1: We're really bad with big numbers. It's also why you
Speaker 1: get things like, hey, let's play the lottery. Look how
Speaker 1: much money it is. What are the odds of winning?
Speaker 1: And you just you know, the odds are so astronomical
Speaker 1: that you would, uh, your eyes glaze over. You're just like,
Speaker 1: well that's big. You're like someone has to win, right
Speaker 1: and so. But if you really think about the odds,
Speaker 1: you just think, well, really buying a lottery ticket and
Speaker 1: throwing a dollar away, there's not a whole lot of
Speaker 1: difference there. Yeah, you have a chance of winning, but
Speaker 1: it's so tiny, and you're probably supporting your local schools,
Speaker 1: but well, supporting some school. Yeah, the the if my
Speaker 1: money goes to Georgia Tech, you're gonna know, you know,
Speaker 1: I'm gonna be upset. Um. But at any rate, the
Speaker 1: point is that we're really bad at that sort of thing,
Speaker 1: So it doesn't really surprise me, you know, to go
Speaker 1: one point eight million versus four point two million, because
Speaker 1: once you get over a certain number that you might
Speaker 1: as well just say lots there are. The point is
Speaker 1: either way, it's it's one of the most surveilled places
Speaker 1: in the world, if not the most, and it's it's
Speaker 1: incredibly dense surveillance. Oh yeah, and and this plays a
Speaker 1: role in in television and movies and absolutely like you know,
Speaker 1: like Torchwood. And there's the moment where Watson is uh
Speaker 1: is called. He's answering the phone in a a phone booth,
Speaker 1: which apparently they still exist, I guess, but he's answering
Speaker 1: a phone and then the voice on the other line
Speaker 1: tells him to look up at the various corners, and
Speaker 1: you can see that there are the cameras that are
Speaker 1: mounted on the outside of buildings, and the cameras very
Speaker 1: specifically look away from his um phone booth for showing
Speaker 1: that the conversation is going to be private and not
Speaker 1: displayed on any kind of uh uh closed circuit television technology.
Speaker 1: So it's it's a part of life over there in
Speaker 1: the United States. It's still something that we would consider
Speaker 1: very unusual, right. I would actually argue, though, going back
Speaker 1: to a slightly earlier point, that it doesn't matter technically
Speaker 1: how many there are there due to principles that were
Speaker 1: talked about by A. Jeremy Bentham in the in the
Speaker 1: seventeen eighties about the pinopticon, which which which was the
Speaker 1: concept of this prison that had this a circular tower
Speaker 1: in the kind of a ring of a prison with
Speaker 1: a circular tower, whereas the cells are on the outside,
Speaker 1: the cells are on the outside, and the guards are
Speaker 1: on the inside, and the prisoners don't know when they're
Speaker 1: being watched, that they have to operate under the assumption
Speaker 1: that they're always being watched. Like we were talking about earlier,
Speaker 1: and this this concept got a big reprise for pries
Speaker 1: in the seventies when for co Is starting to talk
Speaker 1: about it as as a metaphor for the way that
Speaker 1: all of these cameras around us and and the watchfulness
Speaker 1: of society was operating. Yeah. Well, um, part of that
Speaker 1: comes into Uh, we'll come in when we want to
Speaker 1: say what is the effect these cameras have and we
Speaker 1: can get to that in a minute. One another thing
Speaker 1: I wanted to bring up though about this, uh more
Speaker 1: recent account of the cameras in the UK is earlier
Speaker 1: when we were saying that most of the cameras are private.
Speaker 1: This was definitely the case here. You know, they counted
Speaker 1: in County Cheshire more than twelve thousand cameras and only
Speaker 1: about five hundreds of them were public. Wow. Okay, so
Speaker 1: most of these like we were saying, they're in parking lots,
Speaker 1: you know, shops, the places that are privately and people
Speaker 1: trying to protect their stuff. Right, Well, they're recording you
Speaker 1: either way, so that that's still something that again is
Speaker 1: is fairly alien to two people. In the United States,
Speaker 1: we don't have as many camera the now. The retails
Speaker 1: shops definitely do, but not as many cameras that are
Speaker 1: just mounted on the side of buildings as you would
Speaker 1: see in London. Right, we don't have as many, but
Speaker 1: some places in the United States are getting there. Um well,
Speaker 1: a lot of big cities in the United States now
Speaker 1: have pretty serious CCTV infrastructure. Um. For example, they think
Speaker 1: that probably Chicago is the most surveilled city in America.
Speaker 1: And uh, an often cited figure is that there are
Speaker 1: ten thousand CCTV cameras in Chicago. I don't know if
Speaker 1: that is confirmed. That just that number shows up a lot.
Speaker 1: I'm sure most of them are pointed at cemeteries to
Speaker 1: make sure the dead stopped rising from the grave to
Speaker 1: vote in every election. Well, that's possible. Um, No, I
Speaker 1: was being too generous. I don't think that's what they're doing. Um,
Speaker 1: that's a that's a corruption in Chicago joke. Yeah, it
Speaker 1: is here in Atlanta. Supposedly, the city, over the course
Speaker 1: of a year grew from seventeen police cameras to more
Speaker 1: than that's a pretty explosive growth. Yeah, And one of
Speaker 1: the big questions is are we getting our money's worth?
Speaker 1: Are these cameras here in Atlanta? Are these cameras actually
Speaker 1: uh correlated with preventing crime? Yeah? And uh turns out
Speaker 1: the answer is by no means unanimous. And it's really
Speaker 1: hard to get the statistics to agree on this. From
Speaker 1: Some studies seem to show that it does help a lot,
Speaker 1: Some studies show very little help, Some show almost no
Speaker 1: help at all. Well, it's definitely a very complicated thing.
Speaker 1: I mean, I guess the only thing, the only way
Speaker 1: you could say it's it wouldn't be complicated is if
Speaker 1: you were to look at crime rates in a neighborhood
Speaker 1: before there were ever any cameras there versus crime rates
Speaker 1: there once the cameras are put in there, and ignoring
Speaker 1: the fact of things like population changes, nothing else has changed.
Speaker 1: Of course, life is complex. You can do that, I mean,
Speaker 1: you can compare neighborhoods statistics, but a lot of times Um,
Speaker 1: what it seems like often happens is that when you
Speaker 1: implement these cameras, they seem to coincide with other new policies,
Speaker 1: like we also added more patrol cars, um so so
Speaker 1: so can you can't be absolutely certain that it was
Speaker 1: the cameras that had any sort of measurable impact. It
Speaker 1: may be one of these other other UH initiatives that
Speaker 1: are enacted around the same time. Yeah, Like, for example,
Speaker 1: one thing I saw is that when they added a
Speaker 1: whole bunch of CCTV cameras to the to the trains
Speaker 1: in Chicago, they said crime jumped. Um. Now that doesn't
Speaker 1: mean there were more murders. They actually saw a decrease
Speaker 1: in violent crime, but there was an increase in recorded
Speaker 1: fair skipping or fair evasion and other stuff like that.
Speaker 1: So really it just meant that the police were able
Speaker 1: to observe. Well, I don't know if that was the reason,
Speaker 1: but that that could be it. I'm not saying it's
Speaker 1: the reason. I'm saying that they were able to observe
Speaker 1: a lot more like it may not have been that
Speaker 1: there was a rise in incidents. It was just there
Speaker 1: was a rise and awareness. I don't say, yeah, I
Speaker 1: see what you're saying. I don't know that that's the case,
Speaker 1: but that that could be. Um. But yeah, I mean
Speaker 1: one often cited again statistic by privacy advocates in the
Speaker 1: UK is that there's really only been about one UK
Speaker 1: crime solved for every thousand cameras. I mean, whether whether
Speaker 1: we give that credence or not, um, but there's clearly
Speaker 1: a discrepancy about the value these things have. The people
Speaker 1: who seem most in favor of them are law enforcement
Speaker 1: like officers themselves, and some of the discrepancy comes in
Speaker 1: the question of whether these actually prevent crime or whether
Speaker 1: they just make it easier to prosecute crime once it's
Speaker 1: been committed. Got So it may be that it's not
Speaker 1: so much a deterrent as it is just an effective
Speaker 1: means of if you need evidence for prosecution. One thing
Speaker 1: I saw is that in one environment they seem to
Speaker 1: suggest that putting cameras out along with signs that say
Speaker 1: you know, there's a camera recording what you're doing right now,
Speaker 1: actually was more preventative than just having the cameras. You
Speaker 1: might guess that makes sense, yeah, which which is why
Speaker 1: the usually when they put these cameras out there. Um,
Speaker 1: you know, in in this whole kitten comboot of a
Speaker 1: giant box with these you know, very big, very obvious
Speaker 1: sorts of things, because yeah, yeah, they do more good
Speaker 1: by telling you that it's there that hypothetically you could
Speaker 1: you could even have a camera, like an inactive camera
Speaker 1: saying on the side of a building and if you
Speaker 1: have a sign there, then it may have it may
Speaker 1: be a deterrent. But even if it's not active, well, uh,
Speaker 1: that actually may be the case in a lot like that.
Speaker 1: There is clearly a lot of public skepticism about whether
Speaker 1: anybody's actually watching these cameras. And it's not entirely unfounded. Um,
Speaker 1: because as much as it costs to install a camera,
Speaker 1: it costs that much more to pay somebody to pay
Speaker 1: attention to it in real time. Yeah that makes sense. Yeah,
Speaker 1: this is I was looking at um cameras used in
Speaker 1: in traffic situations, traffic monitoring, red light camera stuff like that,
Speaker 1: and um uh and and yeah. There were similar discrepancies
Speaker 1: in the statistics that people found about whether they were
Speaker 1: useful or not. And one said he found that there
Speaker 1: was a significant increase in crashes and especially crashes with
Speaker 1: injuries in Florida with red light cameras, possibly because people
Speaker 1: were slamming on their brakes in order to avoid getting
Speaker 1: a ticket at a red light rather than just going
Speaker 1: through it when perhaps it would have been more safe
Speaker 1: at right when when the light is amber and uh,
Speaker 1: and it is no longer safe for you to actually stop,
Speaker 1: rather it's safer for you to go through. Then that's
Speaker 1: what you're supposed to do. The problem is that a
Speaker 1: lot of people don't really seem to, at least in Atlanta.
Speaker 1: From my own this is anecdotal, obviously, but for my
Speaker 1: own experience of riding around in cars in Atlanta, it
Speaker 1: seems that no one's really concerned about hitting on the
Speaker 1: brakes until the light is red. And even then you
Speaker 1: probably got about two or three cars that go through first.
Speaker 1: Oh yeah, as my wife wants said, in Atlanta, red
Speaker 1: light means okay, only five more cars, right. But that
Speaker 1: we do have some some intersections here in Atlanta that
Speaker 1: do have these these cameras that are located on them
Speaker 1: that that are supposed to take picture ars of cars
Speaker 1: after they pass through a red light. Right, And these
Speaker 1: are these cameras are usually still cameras. They're usually tripped
Speaker 1: by sensors um they might be video or radar, um
Speaker 1: or electromagnetic sensors that are that are done through wires
Speaker 1: that are placed in the asphalt. And these cameras are
Speaker 1: in addition to other kinds of traffic cameras, speed cameras, UM,
Speaker 1: cameras that are involved in police cars themselves that scan
Speaker 1: license plates, cameras that are starting to be installed on
Speaker 1: on officers themselves. UM, there's there's some of that gonna
Speaker 1: gonna happen in Seattle, UM. Five and eighty two American
Speaker 1: communities alone have some kind of traffic cameras in place. Uh.
Speaker 1: Several states prohibit the use of them. Several states have
Speaker 1: legislature going in right now in and and and and
Speaker 1: it's it's it's a really contentious subject because yeah, because
Speaker 1: because again you have a lot of people saying like, well,
Speaker 1: what how much good do they do? How much privacy
Speaker 1: do we need? And and you know, municipalities have some
Speaker 1: of these trait cameras up online, the video ones you
Speaker 1: can go check. There's entire databases of these things that
Speaker 1: you can access. And there are very real reasons why
Speaker 1: that's very helpful. Um, you know, they could help first
Speaker 1: responders arrive on scene. With an idea of what the
Speaker 1: situation is, and in case of a terrible accident or
Speaker 1: or in case of a national emergency, you're not even
Speaker 1: national emergency, in case of some kind of weather emergency
Speaker 1: or or something like happened in Boston, you can you
Speaker 1: can let people know what's going on on the ground.
Speaker 1: It also means that someone who would normally be taking
Speaker 1: that route might be able to see that there's something
Speaker 1: serious going on and they know too reroute, which ultimately
Speaker 1: helps those first responders who are trying to get at
Speaker 1: the scene and take care of anyone who might be
Speaker 1: injured or whatever the situation is. So, you know, to
Speaker 1: to an individual, it may seem like, oh, well, this way,
Speaker 1: my commute is not going to be three hours long.
Speaker 1: But if you step out of that and you look
Speaker 1: at the big scheme of things, it also means that
Speaker 1: that the people who are there to help in an
Speaker 1: emergency can actually do their job. Yeah. Of course this
Speaker 1: would tie into, as we've talked about before, the idea
Speaker 1: of a smart traffic grid. I mean, if you're going
Speaker 1: to have such a thing in the future, like autonomous
Speaker 1: cars responding and and doing traffic the smart way, you'd
Speaker 1: essentially have to have traffic cameras right right, Yeah, and
Speaker 1: computers could be watching them and help you reroute to
Speaker 1: make sure that you get there as fast as possible. Exactly.
Speaker 1: So well, here's a question, though, I wonder that maybe
Speaker 1: one difference between the idea of say, cameras in a
Speaker 1: shop or on a street corner looking at the sidewalk
Speaker 1: or a park versus traffic cameras at red lights. When
Speaker 1: do you have the expectation of privacy and when should
Speaker 1: you be able to feel like I shouldn't have to
Speaker 1: expect somebody's watching me. Well, according to Cats Versus the
Speaker 1: United States, as of nineteen sixty seven, people in public
Speaker 1: areas cannot expect privacy since they are knowingly exposing themselves.
Speaker 1: The same thing is true in the United Kingdom, where
Speaker 1: if you are in any sort of public area, then
Speaker 1: you by law have no expectation of privacy as far
Speaker 1: as being caught on camera or anything along those lines.
Speaker 1: As Second U s Circuit Court of Appeals said that
Speaker 1: just recording people in a public place is totally fine. Um,
Speaker 1: it's it's recording with an intent to commit some further crime.
Speaker 1: That is a criminal behavior. So I see, so if
Speaker 1: you're if you're just you know, out and about and
Speaker 1: you've got a camera going in a public place and
Speaker 1: it's just because you think it's a nice day and
Speaker 1: you want to record that. There's that's perfectly fine. Uh,
Speaker 1: that there may be people who take issue with that,
Speaker 1: and they may make that known to you. Yeah, the
Speaker 1: specific case was was in in a private residences as
Speaker 1: well um private spaces that the case surrounded this um
Speaker 1: woman who's I think a woman had passed away and
Speaker 1: without a will, and her son recorded a family conversation
Speaker 1: unbeknownst to the rest of the members of the family,
Speaker 1: and the court said that was totally fine and that
Speaker 1: that he could in fact submit that video is evidence. Interesting. Yeah,
Speaker 1: that's something one of those things where you never know
Speaker 1: if if it were to go further, if that would
Speaker 1: hold up or not. It's I mean, that's of course
Speaker 1: the way law works in the United States, right You
Speaker 1: you challenge the law, or someone someone can challenge a law,
Speaker 1: and then it goes up the court system until ultimately
Speaker 1: the Supreme Court could make a decision. Sometimes they decide
Speaker 1: not to decide, uh, and then that sort of answers
Speaker 1: the question, at least in that particular case. But yeah,
Speaker 1: I mean there there are other, uh incidents of cameras
Speaker 1: that I wanted to talk about. Joe what Well, I
Speaker 1: thought there was one funny thing I read when looking
Speaker 1: at CCTV cameras in the UK, in conjunction with the
Speaker 1: traffic cameras, they've actually even got mobile CCTV cameras, mean
Speaker 1: that they've got surveillance cars. These are like mobile units
Speaker 1: that drive around and record what's going on in traffic.
Speaker 1: That's well, that kind of ties into what I was
Speaker 1: going to talk about, which are the ashcams that you
Speaker 1: find in uh in Russia? You did? You did? You know?
Speaker 1: The more we talk about, the less subtle it is.
Speaker 1: But that that smooth segue allows me to talk about
Speaker 1: Russian dash cams. Uh. And of course a lot of
Speaker 1: people who are on the internet, I mean they're familiar
Speaker 1: with this because the videos from these have popped up
Speaker 1: all over the place. I mean, YouTube's got entire channels
Speaker 1: devoted to Russian dash camp village tell us all about
Speaker 1: it for those of us who lag behind. So uh,
Speaker 1: it's what it sounds like. It's a camera that a
Speaker 1: driver would mount to their car in such a way
Speaker 1: as to record what's going on, like the forward view
Speaker 1: of what that they would see when they're behind the wheel.
Speaker 1: Often it's not mounted directly on the dashboard. It's actually
Speaker 1: the ones I saw were more frequently mounted on the mirror,
Speaker 1: the rear view mirror, and would would hang either next
Speaker 1: to it or underneath that and and be up against
Speaker 1: the windshield. But the idea is that in Russia there's
Speaker 1: a deep distrust in government and in the police, and
Speaker 1: and there's a a very deep belief that corruption uh
Speaker 1: completely permeates those institutions, and so there are a lot
Speaker 1: of Russian drivers. In fact, Al Jazeera in November two
Speaker 1: thousand and twelve said that it estimated there were about
Speaker 1: one million people in Russia have installed these dashboard camps.
Speaker 1: And the whole point is so that they can have
Speaker 1: a record of anything that happens while they are operating
Speaker 1: their vehicle, so that they can use that in any
Speaker 1: case that would go to court that they would be
Speaker 1: involved in. For example, if you're driving down highway in
Speaker 1: Russia and an official government car cuts you off or
Speaker 1: bumps into you, you would want to have footage of
Speaker 1: that so that if you were brought to court by
Speaker 1: this official. You could say I'm not guilty of this,
Speaker 1: this car ran into me, and in fact i've seen
Speaker 1: footage of that, of that kind of instance. But they've
Speaker 1: also used it for other reasons too, because it's not
Speaker 1: just the government that tends to get up to a
Speaker 1: little shady stuff in Russia. There are people who will
Speaker 1: attempt to fake getting hit by a car so that
Speaker 1: they can uh then sue someone and try and essentially
Speaker 1: they're trying to extort you for money. It's not even
Speaker 1: to get to the point where they're trying to get insurance.
Speaker 1: They're just trying to extort money from you. There's a
Speaker 1: video that I plan on on linking to on the
Speaker 1: forward thinking Facebook and Twitter feeds, so be on the
Speaker 1: lookout for it. There's a video of this car where
Speaker 1: there's a man standing in the road. The guy driving
Speaker 1: the car comes to a complete stop and he's stopped
Speaker 1: in front of the guy who's just standing there. The
Speaker 1: guy who is staying there looks at the car, then
Speaker 1: slowly leans over and essentially lays on the hood of
Speaker 1: the car for a second, then slowly lowers himself to
Speaker 1: the ground and then limps off, claiming that he was
Speaker 1: hit by the car it was. I mean, it's so
Speaker 1: obviously not a guy getting by a car. It is.
Speaker 1: It is. I mean, it's comical. It's so badly done.
Speaker 1: And the fact that the guy caught the whole thing
Speaker 1: on camera shows that he could, you know, dispute this
Speaker 1: entirely saying I didn't if anything, I can sue this
Speaker 1: guy for running into my car because my car was
Speaker 1: at a complete stop when he laid on my my car. Yeah. Well,
Speaker 1: I mean this is clearly a good idea, even in
Speaker 1: a place where if you totally trust the government and
Speaker 1: don't fear corruption at all, it would just help settle
Speaker 1: private traffic disputes. You know, you get into a wreck
Speaker 1: with somebody else and it's you're both saying I wasn't
Speaker 1: at fault. Well, if you have it on tape, and
Speaker 1: it's easier to say, well, you know, then according to
Speaker 1: this footage, you know this car or this party was
Speaker 1: at fault. Uh Yeah, And and that is used quite
Speaker 1: a bit in Russia. They also use it because, uh,
Speaker 1: they're often very treacherous driving conditions in Russia in parts
Speaker 1: where uh you know, in the winter, where the roads
Speaker 1: get really icy, they need to be able to if
Speaker 1: there's an accident, show what exactly happened, so that way,
Speaker 1: you know, when it comes to insurance, you can claim
Speaker 1: the right thing. Also, they use it because insurance companies
Speaker 1: can sometimes withhold payments uh and say that, oh no,
Speaker 1: that that didn't happen the way you said it. And
Speaker 1: when you have a record of it, then you can
Speaker 1: say no, you owe me money because based upon my policy,
Speaker 1: this is all covered. Uh. That's also to capture events
Speaker 1: on like road rage things like that, um, all drunk
Speaker 1: driving accidents. I mean, it's it's pretty dark stuff. Now
Speaker 1: that there are some great dash cam videos that are
Speaker 1: out there that capture really wonderful, little sweet moments. I'm
Speaker 1: not you know, so it's nice that we can see
Speaker 1: some stuff outher that's not just the nastiest part of
Speaker 1: humanity right there. There are a lot of videos. I
Speaker 1: saw one that was just a montage of them, and
Speaker 1: I'd say about half of all the videos where cars
Speaker 1: that would stop in the middle of the road turn
Speaker 1: on the emergency blinkers so the driver could get out
Speaker 1: and help an elderly person cross the street because they
Speaker 1: were they couldn't move they because the traffic was so strong,
Speaker 1: and they would get out and put themselves at risk
Speaker 1: to help someone get across the street, and then they
Speaker 1: get back in their car and drive off. So they're
Speaker 1: about half the videos were of that. So and then
Speaker 1: there's some once in a lifetime events that we would
Speaker 1: not have seen if it weren't for the fact that
Speaker 1: there were Russian dash camps capturing it. Are you talking
Speaker 1: about something falling out of the sky, I'm talking about
Speaker 1: the chelia Bensk media. Is that what you're talking about. Yeah,
Speaker 1: so this was a meteor that was it was spectacular.
Speaker 1: You know the videos of this meteor that that the
Speaker 1: videos were fake? Yeah, sure, yeah, well it looked like
Speaker 1: a science fiction film. So yeah, yeah, this fireball flying
Speaker 1: over Russia. Uh. And there were videos taken not just
Speaker 1: from dash camps but also from mobile devices as well.
Speaker 1: But the meteor flew over Russia and exploded over the
Speaker 1: Cheliabinsk Oblast, which caused a massive shock wave that spread
Speaker 1: out so far that building in six different surrounding cities
Speaker 1: suffered damage. Seven thousand two buildings in total were damaged
Speaker 1: by that shock wave. Mostly it was stuff like windows
Speaker 1: shattering because the shock wave was so so powerful, But
Speaker 1: we would not have seen nearly as much footage of
Speaker 1: that if it weren't for the fact that these dash
Speaker 1: cams exist in that people upload the video footage to YouTube.
Speaker 1: I foresee that things like this will become popular in
Speaker 1: places other than Russia. I mean, it's such a good idea.
Speaker 1: I can't imagine why you wouldn't want to do that.
Speaker 1: In the United States, you occasionally encounter some law enforcement
Speaker 1: officials who are not so keen on the idea of
Speaker 1: video cameras being turned on them. That's a very that's
Speaker 1: a very general way of saying that there are there's
Speaker 1: a a great deal of resistance in some communities among
Speaker 1: some law enforcement officials from the thought of citizens being
Speaker 1: able to shoot video of anything that's going on. The
Speaker 1: eVols police that that Seattle project that I had mentioned
Speaker 1: a minute ago, this is going to equip at least
Speaker 1: a dozen officers with a wearable camera for a year
Speaker 1: long trial and uh. And the reason is that the
Speaker 1: Seattle Police Department has gotten complaints of brutality recently and
Speaker 1: of other wrongdoings and um, and they decided as as
Speaker 1: a protective measure, to put these cameras on their officers
Speaker 1: and send them out into the world so that they
Speaker 1: could say, no, really, I was doing my job. This
Speaker 1: is the job that I was doing. And hopefully, if
Speaker 1: you know, should anything terrible happen, it will work the
Speaker 1: other way as well. But right, right, so, I agree.
Speaker 1: I think that the dash cam is a good idea
Speaker 1: in the sense that it will cut down on a
Speaker 1: lot of the shenanigans that happen, or at least will
Speaker 1: allow a wronged party the chance to prove that they
Speaker 1: in fact were the wronged party. Uh. It may not
Speaker 1: prevent those incidents, but if it helps a person get
Speaker 1: insurance or prove that they were not at fault in
Speaker 1: a particular situation, I think that's a great thing. Um.
Speaker 1: I think that it's going to you know, in America,
Speaker 1: I think it's tricky. We've got this this sense that
Speaker 1: uh we have. It's this this individuality, independence, privacy thing
Speaker 1: that's all wrapped up together in a sense of what
Speaker 1: it is to be American, and the idea of having
Speaker 1: cameras all around tends to make at least a certain
Speaker 1: segment of the population uneasy. Yeah. Well, they may have
Speaker 1: a point, um, because we're I can only imagine that
Speaker 1: this is going to increase I mean, I I don't
Speaker 1: see anything that's telling me, well, but within five years
Speaker 1: we'll have fewer cameras were a back off. I mean,
Speaker 1: this is going to increase in every direction from everything
Speaker 1: I can tell. Both more people are going to be having,
Speaker 1: you know, recording ready personal devices, but we're all these
Speaker 1: cities are adding more CCTV cameras. I was reading about, Um,
Speaker 1: the CCTV industry is preparing for a big boom in
Speaker 1: the wake of the Boston bombings because they were so
Speaker 1: instrumental in helping catch the right well both were in
Speaker 1: in the Boston Marathon bombings. Both public CCTV cameras and
Speaker 1: private recording devices were huge in catching the guys who
Speaker 1: did it, Like you saw, within just a few days
Speaker 1: those images came out, and I remember thinking at the time, like, wow,
Speaker 1: I mean there's just so much being recorded that, like
Speaker 1: we randomly got images of these guys. Nobody was trying
Speaker 1: to record them, right, these huge sweeping crowd shots and
Speaker 1: just and we were like, oh no, that dude, Yeah yeah, yeah, yeah,
Speaker 1: And uh, I mean, not only are we going to
Speaker 1: see a lot more cameras deployed. And I agree with you, Joe,
Speaker 1: that that trend is not going to slow down. It's,
Speaker 1: if anything, it's going to increase quite a bit. But
Speaker 1: we also have the technology now, the facial recognition technology.
Speaker 1: These are algorithms, software algorithms that are built sometimes firmware
Speaker 1: algorithms that are built directly into cameras. More frequently it's
Speaker 1: built into the back end. But it can be in
Speaker 1: either case. It can be in the device itself, or
Speaker 1: it can be in whatever is processing the video feed
Speaker 1: that can go in and start to identify individuals. Now
Speaker 1: you have to create a database for that to work. Obviously,
Speaker 1: you can't just point a camera that's you know, at
Speaker 1: someone's face and then they automatically the camera somehow knows
Speaker 1: who that person is. But you could develop a database
Speaker 1: of people and uh and the way the camera does
Speaker 1: this essentially divides your face into quadrants and it starts
Speaker 1: to look for points of similarity between your face and
Speaker 1: whatever faces are in the database, and if it matches
Speaker 1: a certain percentage of a certainty, it will go ahead
Speaker 1: and at least suggest an identity. If not, just go
Speaker 1: ahead and a sign and identity of that face. So,
Speaker 1: like like a visual fingerprint, you know something that you
Speaker 1: don't have to you don't have to have touched anything.
Speaker 1: You could have been wearing your fancy fancy robber gloves
Speaker 1: and still get caught, right, because it's it's mostly looking
Speaker 1: at things like the distance of your you know, your
Speaker 1: eyes from other parts of your face, or how your
Speaker 1: chin is shaped, that kind of stuff, and it's designed
Speaker 1: to be able to extrapolate that information based upon whichever
Speaker 1: direction your face is facing. So even if you're not
Speaker 1: looking head on into the camera, a good facial recognition
Speaker 1: algorithm can at least come up with suggestions of who
Speaker 1: that person might be, assuming that again, that the person
Speaker 1: is in the database. We see this all the time
Speaker 1: on social media sites like Facebook and Google Plus. They
Speaker 1: have that that face tagging technology in there, to the
Speaker 1: point where it'll start suggesting people like you you want
Speaker 1: to tag a picture, and often the very first name
Speaker 1: that pops up is the person that you wanted to tag,
Speaker 1: because it's comparing that face against all the other tags
Speaker 1: that you have made that appear in your friends list,
Speaker 1: and then starts to extrapolate from that, and you know,
Speaker 1: if it's not that person, you just type in whoever
Speaker 1: it is, and then that gets added to the database. Sure, well,
Speaker 1: you can you can. You can opt out of this
Speaker 1: on Facebook and Google Plus for now anyway and tell
Speaker 1: it not to create that that algorithm, that specific number
Speaker 1: for you that says, you know, this is this is
Speaker 1: how my face looks? Is your face? Man? Yeah? Yeah.
Speaker 1: When I see these technologies, I wonder exactly how good
Speaker 1: are they? I mean, can they tell the difference between
Speaker 1: Mick Jagger and Don k Nots. Have you ever noticed
Speaker 1: how similar they look whenever they when prancing on stage?
Speaker 1: They were almost identical? Or or or can they tell
Speaker 1: the difference between Natalie Portman and Kira Knightley. Uh yeah,
Speaker 1: I can't. I don't which which one, Which one was
Speaker 1: in which one was in parts of the Caribbean. I
Speaker 1: don't know. Okay, but those are the two that look
Speaker 1: really similar, right, I didn't make that up? Maybe maybe
Speaker 1: to you they're they're they're both a little bit elfin.
Speaker 1: It's like sure, but there Don Knots and Mick Jagger
Speaker 1: definitely you know, separated birth. But you know, you don't
Speaker 1: believe me, Go look this up after the podcast. There
Speaker 1: there are there are a lot of instances of people
Speaker 1: who look similar. But the thing about the computer algorithm
Speaker 1: is it can get really really specific, like looking at
Speaker 1: the position of your ears on your head, and you
Speaker 1: you know, things that are going to remain the same
Speaker 1: unless you had some sort of you know, you could
Speaker 1: have plastic surgery that alters the way you look and
Speaker 1: that would mess up the algorithm. Ort least algorithm possibly
Speaker 1: wouldn't recognize you based upon whatever you had done. And
Speaker 1: when it comes down to things like you know, identical twins,
Speaker 1: can it can it tell one twin apart from the other?
Speaker 1: Probably not, I mean unless there are enough subtle differences
Speaker 1: for the computer to be able to pick up on it.
Speaker 1: Keeping in mind, the resolution on these cameras isn't always
Speaker 1: that incredibly sharp. You know, facial recognition software is getting
Speaker 1: better and better, but you still need a high resolution
Speaker 1: camera to really take advantage of it. Well, the resolution
Speaker 1: on the cameras plays a role even if you're not
Speaker 1: using facial recation, if you're just looking at it. Lots
Speaker 1: of the cameras that are deployed right now are not
Speaker 1: HD cameras, and they, uh, they might play some sort
Speaker 1: of deterrent role. But the problem is once you get
Speaker 1: your hands on the footage, a lot of times it's like,
Speaker 1: well it's a guy with a hat on, which again
Speaker 1: is one of those things like if you've got someone
Speaker 1: who's watching the footage live, then they can respond to
Speaker 1: it in real time, which you know, that's one deterrent.
Speaker 1: But if you're talking about using it as a means
Speaker 1: to pursue someone legally, then obviously the resolution it plays
Speaker 1: a huge role. And and not only that, but the
Speaker 1: camera angle and the duration and all that kind of
Speaker 1: because we can't we can't zoom in and turn it
Speaker 1: around the way that they can on police procedurals, right right, No, yeah,
Speaker 1: zoom and enhanced. Zoom and enhanced does not work. Yeah,
Speaker 1: well the old every procedural ever since. Um. But anyway,
Speaker 1: the the big fear I think that that folks who
Speaker 1: are really concerned with this trend, the big fear they
Speaker 1: have is that we're going to have this huge amount
Speaker 1: of this huge number of cameras out there, even more
Speaker 1: than we already do, and it's going to be a
Speaker 1: combination of the ones that are mounted on the side
Speaker 1: of buildings, the ones that are inside businesses, the ones
Speaker 1: that are on dashboards, the ones that cops are wearing,
Speaker 1: and all the ones that we have at our disposal.
Speaker 1: The phones and the Google Glass and all the other
Speaker 1: kind of stuff, and and in traffic, and all of
Speaker 1: these cameras could be streaming or uploading video to some
Speaker 1: sort of Internet server. We're looking ahead in the future here.
Speaker 1: This is the dark version, right. So you've got all
Speaker 1: this video going into a server. It's more video than
Speaker 1: any person could ever watch because you're you're getting so
Speaker 1: many different streams, all in real time. Obviously, no one
Speaker 1: could keep an eye on all of this. But if
Speaker 1: you designed really really powerful algorithms that could identify people
Speaker 1: and only that, but also get triggered for certain instances,
Speaker 1: things that when this sort of situation happens, log it,
Speaker 1: or when this person shows up, log it right then
Speaker 1: now if if they're a registered sex offender for example, Yeah,
Speaker 1: so then you've got this global always on I that's
Speaker 1: watching everything and logging anything of note. Uh And and
Speaker 1: who decides what is of note versus what isn't. That's
Speaker 1: a big question. That's the big fear. And the thing
Speaker 1: is is that the technology that we've got is heading
Speaker 1: in such a direction that that sort of future is possible.
Speaker 1: Not necessarily that it's going to happen, but that assuming
Speaker 1: that we are able to keep up with the trends
Speaker 1: that we have now, assuming we're able to continue improving
Speaker 1: the algorithms and the equipment and deployment and somehow have
Speaker 1: the capacity to handle that's this much data. That's a
Speaker 1: big question. Well, I mean it seems to me, and
Speaker 1: you feel free to disagree. The question is not whether
Speaker 1: we can do it, it's just whether we're going to
Speaker 1: exactly That's that's where the real question comes in. The
Speaker 1: technology is going to can be done right, It's happening
Speaker 1: right now. The nice thing is that being aware of
Speaker 1: that means that you can be part of the conversation
Speaker 1: and talk about what are the benefits, what are the
Speaker 1: the things that are are detrimental to society in general
Speaker 1: and your peace of mind in particular, That those are
Speaker 1: important conversations. Yeah, it's interesting because when the idea of
Speaker 1: surveillance comes up, I feel this tug from both sides.
Speaker 1: I don't want to be paranoid, but I don't want
Speaker 1: to be naive, and I don't know how to feel
Speaker 1: about things like this. On one hand, I'm like, I mean,
Speaker 1: come on, I mean, the government is not actually like
Speaker 1: trying to track me and stuff like that. They they're
Speaker 1: they're bigger fish. Yeah, like why are there trying to
Speaker 1: see me undressed or something like who cares? Why would they?
Speaker 1: I just don't see that happening. But on the other hand,
Speaker 1: and again, you know, I don't want to be a sucker,
Speaker 1: like you should be cautious. And there are there are
Speaker 1: probably some people who might have really legitimate fears like um, well,
Speaker 1: like like activists if you're if you're protesting something and
Speaker 1: your government doesn't really appreciate you doing that, and and
Speaker 1: you might think that the protest is important. Well, a
Speaker 1: lot of it. It depends on the orientation of the government, right,
Speaker 1: Like I mean, are you scared of this government now? Well,
Speaker 1: I mean the same infrastructure will be there with whatever
Speaker 1: government exists in forty years. Just that is that government
Speaker 1: something we shouldn't worry about. And there there there are,
Speaker 1: um there are suits in progress that are discussing this
Speaker 1: kind of data and and this kind of information. The
Speaker 1: a C. L u As of Maden got involved in
Speaker 1: a lawsuit in California about those automatic license plate recognition
Speaker 1: scanners that are are in some some police cruisers that
Speaker 1: can scan you know, hundreds of license plates per minute
Speaker 1: going at pretty high speeds through a parking lot um
Speaker 1: and there was concerned that some of the data was
Speaker 1: being kept for too long or um or that it
Speaker 1: could it could hypothetically be used to create these records
Speaker 1: of what normal citizens with no records of wrong wrongdoing
Speaker 1: or doing and where they're going well, And you know,
Speaker 1: I think it's important for us just to remember that
Speaker 1: that while we're painting this sort of Orwellian future that's
Speaker 1: very frightening, obviously, that's not it's not a foregone conclusion
Speaker 1: that that's going to be what the future is, and
Speaker 1: that if we do pay very close attention and we're careful,
Speaker 1: we can have all the benefits of this technology without
Speaker 1: the you know, the the scary, dark science fiction dystopia
Speaker 1: version as well. Lots of people don't like to mention
Speaker 1: the benefits because I don't know, I mean, there's a
Speaker 1: cynical tendency we have to to play up, you know.
Speaker 1: But I mean they do actually solve crimes. It's debatable
Speaker 1: to what extent, but I mean they helped surveillance help
Speaker 1: to catch the Boston bombers. So I mean, clearly there
Speaker 1: are a lot of sides to this issue. It's very
Speaker 1: complex and We don't mean to suggest that it's it's
Speaker 1: at all something you can boil down and solve in
Speaker 1: a in a simple podcast, but these are are good
Speaker 1: questions to ask. It's good to think about as we
Speaker 1: move towards the future and make sure that we have
Speaker 1: the best possible positioning for everything from our rights of
Speaker 1: privacy UH to our our personal safety, and to make
Speaker 1: sure that we have those checks and balances in place.
Speaker 1: These are all things that we need to think about.
Speaker 1: So it's good to have this discussion. And guys, if
Speaker 1: you have any suggestions for future episodes of forward Thinking,
Speaker 1: please right in let us know. You can send us
Speaker 1: an email. Our address is fub thinking at discovery dot
Speaker 1: com or go to fw thinking dot com. That's our
Speaker 1: website where we have all the videos, the blogs, the podcasts.
Speaker 1: We've got links to our social media stuff there. So
Speaker 1: come visit us, be part of the conversation. Tell us
Speaker 1: what you're excited about, tell us what you want to
Speaker 1: know more about. We definitely want to hear from you,
Speaker 1: and we will talk to you again really soon. For
Speaker 1: more on this topic and the future of technology, visit
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