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Speaker 1: Okay, all right, let's set the stage for this evening's

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Speaker 1: classic episode. Fellow conspiracy realists, cast your memory back to

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Speaker 1: twenty nineteen. Nobody was really sure what would happen. Alexander

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Speaker 1: Dugan had some ideas, he had some wishes on his

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Speaker 1: wish list, and we got we got very We finally

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Speaker 1: did an episode on something we had been talking about

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Speaker 1: for gosh, more than a decade at this point, the

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Speaker 1: idea of smart devices and surveillance. And I think this

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Speaker 1: might have been the one that radicalized us a little bit.

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Speaker 2: Maybe a bit tiny bit, because this is definitely a

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Speaker 2: moment in time when, in real time, we realized just

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Speaker 2: how much mass data collection was happening within our phones,

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Speaker 2: not by necessarily the government, but by individual third party

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Speaker 2: companies that we all say yes to when we down

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Speaker 2: load their applications or we use their services.

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Speaker 1: Who reads the terms and conditions right? Who reads down

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Speaker 1: to paragraph seventeen of the agreement, especially when you're scrolling

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Speaker 1: on a phone and you're in a hurry because you

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Speaker 1: got to get the app dude.

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Speaker 2: Well, then, but then when you combine that with companies

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Speaker 2: potentially giving that information to governmental entities, and you combine

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Speaker 2: that with actual governmental entities that have stated before or

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Speaker 2: it's been leaked before stellar wind that communications on individual

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Speaker 2: phones are being picked up, and even communications through the

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Speaker 2: massive pipelines that go underneath the oceans.

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Speaker 3: Mm hmm.

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Speaker 1: Yeah, it's a prism of conspiracy and it probably takes

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Speaker 1: five eyes to see oo in full right. This is

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Speaker 1: also this is also shot up for anybody who ever thought, oh,

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Speaker 1: my phone is listening to me, the speakers take it

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Speaker 1: up something, it's so much deeper.

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Speaker 2: Oh my gosh, Ben, I'm gonna say this so I

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Speaker 2: say it on record. That is happening so much to

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Speaker 2: me recently where it's that echo on the telephone. It's

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Speaker 2: that thing where you're getting feedback when you're talking to

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Speaker 2: one other person when you don't have the speakerphone on,

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Speaker 2: or when you're using a Bluetooth headset that's got a

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Speaker 2: microphone that's close to it, when you're talking on PlayStation.

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Speaker 1: Oh buddy, oh man, Well, Matt, I'm with you there.

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Speaker 1: If this is the year we get hauled off to

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Speaker 1: the crazy house, that I think we'll be in the

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Speaker 1: same uber because we're not paying for the ambulance.

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Speaker 2: Is the joke anyway?

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Speaker 1: Anyway, this is our classic episode twenty nineteen smart devices

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Speaker 1: and surveillance.

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Speaker 4: From UFOs to psychic powers and government conspiracies. History is

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Speaker 4: riddled with unexplained events. Turn back now or learn this

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Speaker 4: stuff they don't want you to know. A production of

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Speaker 4: iHeart Radios How Stuff Works.

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Speaker 2: Welcome back to the show. My name is Matt.

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Speaker 3: My name is no.

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Speaker 1: They call me Ben. We are joined as always with

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Speaker 1: our super producer Paul, mission control deck and in spirit

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Speaker 1: because today we have our returning super producer Seth Johnson.

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Speaker 1: Everybody give him a hand. Most importantly, you are you.

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Speaker 1: You are here, and that makes this stuff they don't

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Speaker 1: want you to know. I was thinking about this. How

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Speaker 1: many people, on average do you think are listening today's

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Speaker 1: show on a cell phone or maybe on a laptop

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Speaker 1: with another electronic device on in the background.

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Speaker 3: M I would say many, if not most.

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Speaker 2: I see. I'm thinking a lot of people probably have

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Speaker 2: their phone in their pocket or on one of those

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Speaker 2: cool little armbands when they're just yeah, oh yeah, dude.

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Speaker 1: Runners or people who want to look like they have

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Speaker 1: ran or will run somewhere in the future.

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Speaker 3: Yeah, there's so I should chase those people. Is that

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Speaker 3: what you're saying? OK?

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Speaker 1: Yeah, yeah, give them, give them some steaks, you know

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Speaker 1: what I mean. I think that's what's missing for joggers.

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Speaker 3: I feel like that, you know. I feel like jogging

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Speaker 3: is just practice for you know, running away from something,

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Speaker 3: you know. I feel like these people are very paranoid.

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Speaker 1: One of my this might be a hot take, but

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Speaker 1: one of my very old and dear friends years back,

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Speaker 1: you guys know him, he told me. He told me

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Speaker 1: that one of the first signs of gentrification in a

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Speaker 1: neighborhood was people running when no one's chasing them.

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Speaker 3: Brilliant.

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Speaker 1: He's a weird guy, but I thought it was a

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Speaker 1: good point.

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Speaker 3: I think so too so so.

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Speaker 2: But the reason that we're even mentioning this, like multiple

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Speaker 2: devices going on in the same audio space, is because

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Speaker 2: that's one of the main things we're going to be

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Speaker 2: talking about today, our devices and potentially monitoring them.

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Speaker 1: So, right, are you addicted to your phone, your television,

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Speaker 1: or your tablet? Are you one of the people, like

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Speaker 1: many of us, who can't really hold a conversation without

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Speaker 1: at least checking in on this thing. I'm guilty of that.

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Speaker 3: He's literally doing it right now.

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Speaker 1: Yeah, well, I'm kind of waving it around, do you

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Speaker 1: find yourself tuning out, you know, when when the conversation

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Speaker 1: is taking its course, and then finding yourself tuning into

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Speaker 1: the closest device whatever that is, what like right exactly, So,

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Speaker 1: just for the lay of the land, here, we have

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Speaker 1: three laptops out open right now. We all have our

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Speaker 1: phone somewhere near our person, and we have you know,

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Speaker 1: a bevy of av equipment that is probably the most

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Speaker 1: innocent of the contraptions here right in this room. And

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Speaker 1: if you are one of those people who constantly finds

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Speaker 1: yourself clicking in or dropping out of conversation, tuning into

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Speaker 1: something else, you are not alone. Let's reiterate that, because

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Speaker 1: at first it sounds kind of nice, right, it sounds

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Speaker 1: kind of like ah, warm, fuzzy huggy time. No, no, no,

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Speaker 1: think about it. You are not alone in multiple senses

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Speaker 1: of the phrase. Here are the facts.

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Speaker 2: Smartphones, smart devices, smart everything. Really it's everywhere, and you're

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Speaker 2: probably working with one right now just because you need

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Speaker 2: the technology to listen to this today. Let's look at

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Speaker 2: the Pew Research organization. There, they've done you know, they

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Speaker 2: do statistics like nobody else. It is estimated they say

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Speaker 2: that more than five billion people have mobile devices, and

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Speaker 2: over half of these connections are smartphones, so they're doing

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Speaker 2: more than just making a connection via satellite to another

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Speaker 2: phone somewhere or from you know, it's not a landline anymore.

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Speaker 2: It is it's a phone. It's an encyclopedia. It's absolutely

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Speaker 2: everything you could possibly do.

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Speaker 3: It's like Ziggy from Quantum Leap. Yes, no, literally have

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Speaker 3: that in our hands now. It doesn't quite predict the future,

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Speaker 3: but it comes damn close.

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Speaker 1: Yeah. And this is that's a global number, yes, throughout

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Speaker 1: the world numbers. So more than half of the people

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Speaker 1: alive today have one of these things. It's I'm holding

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Speaker 1: up the phone again like a prop. It's one of

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Speaker 1: technology's biggest breakthrough success stories of recent decades because just

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Speaker 1: a few decades ago, no one had him.

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Speaker 2: Exactly.

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Speaker 1: Now five billion people have these, so get this.

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Speaker 3: In the US specifically, we've got nine to ten or

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Speaker 3: more Americans aged thirty four and under who have had

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Speaker 3: a smartphone since twenty fifteen, while the ownership rate among

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Speaker 3: the fifty and older age group has raisen from fifty

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Speaker 3: three percent to sixty seven percent over the same period.

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Speaker 3: One of my dearest oldest friends, who is in his

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Speaker 3: early fifties very purposefully still has a dumb phone. Oh, Harry, Harry, Yeah, yeah,

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Speaker 3: very much on purpose. He just like he is old

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Speaker 3: school in that way where he rejects a lot of

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Speaker 3: this like over connectedness, and consequently he's a much more.

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Speaker 2: Thoughtful person than a lot of people that I know

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Speaker 2: you well. After this episode, most of us are going

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Speaker 2: to want to switch back. I know, I know Verizon

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Speaker 2: where I am offers a flip phone.

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Speaker 1: Option, so Nokia's never break too Well, there you go.

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Speaker 2: It seems more and more like a good option. We'll

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Speaker 2: get into it.

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Speaker 1: Though, because it doesn't just stop with smartphones. We also

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Speaker 1: are talking about smart TVs, and yes, Matt, you're absolutely right.

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Speaker 1: This may well ruin some some people's day, but this

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Speaker 1: is important to know. So we checked out STATISTICA when

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Speaker 1: we wanted to find some more stats and specs on

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Speaker 1: smart TVs. The global TV set unit sales are projected

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Speaker 1: to increase from two hundred and twenty nine million units

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Speaker 1: in twenty sixteen to two hundred and fifty nine million

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Speaker 1: by twenty twenty. That's pretty nuts, because you know, televisions

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Speaker 1: shouldn't be this sort of disposable resource. They never were, right,

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Speaker 1: but now more and more people are buying TVs more

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Speaker 1: and more frequently.

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Speaker 3: I mean, I have a smart TV that is made

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Speaker 3: by Amazon. I'm sure it's made by some third party

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Speaker 3: manufacturer overseas.

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Speaker 2: It is Amazon.

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Speaker 3: You know why though, you guys, because it was dirt

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Speaker 3: cheap and it's it works great, and I likely interconnectedness

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Speaker 3: of it. But we'll get into some of the features

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Speaker 3: that this well you call it a feature, it's really

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Speaker 3: more like a bug. No, literally a listening surveillance feature,

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Speaker 3: but just not for you.

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Speaker 1: Yeah, feature bug is in the eye of the beholder.

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Speaker 3: That's absolutely right, And in this case, the eye of

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Speaker 3: the beholder is big data.

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Speaker 1: Yeah. As of twenty eighteen, seventy percent of the television's

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Speaker 1: being sold across the planet are smart TVs. And a

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Speaker 1: smart TV at the most basic explanatory level, is a

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Speaker 1: television that combines a lot of features one would associate

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Speaker 1: with a computer. Right, So, if you like no own

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Speaker 1: a smart TV, you can watch your favorite shows, but

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Speaker 1: you don't have to just watch them when they're on.

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Speaker 1: You can also you know, dial it up on demand

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Speaker 1: for instance. You can connect it with your phone.

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Speaker 3: Not to mention, you can it's very customizable. You can

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Speaker 3: combine all of the different services into one kind of

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Speaker 3: widget box, let's call it. Where you have your Netflix,

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Speaker 3: you got your Hulu, you got your Amazon, which obviously,

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Speaker 3: my Amazon TV leans pretty heavily on the global search

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Speaker 3: on My Amazon TV searches like all of Amazon, and

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Speaker 3: it gives you products, it gives you TV shows, it

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Speaker 3: gives you other stuff that's in your set of apps

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Speaker 3: or subscriptions, but very much leaning toward the Amazon side

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Speaker 3: of things.

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Speaker 2: Yeah, the most important thing about a smart TV, when

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Speaker 2: we call it that, is that it's able to communicate

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Speaker 2: with your network or the network that it's attached to,

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Speaker 2: and could possibly see all of the other devices that

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Speaker 2: are attached to that network.

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Speaker 1: Could possibly sure this is This is true though, so

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Speaker 1: Android is probably the most widely used operating system among

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Speaker 1: smart TVs, but that by no means should be taken

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Speaker 1: to indicate that other oss aren't in there. iPhones are

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Speaker 1: in there as well. Apple has a hand in this.

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Speaker 1: And while smart device addiction is real, especially when we

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Speaker 1: talk about mobile devices, it's I think we should bracket

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Speaker 1: that as the subject of its own episode in the future,

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Speaker 1: assuming we don't get black backed or disappeared there's more

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Speaker 1: to the story behind the purposefully addictive technology. Here. You see,

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Speaker 1: while we stare into that electronic abyss, even though we

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Speaker 1: might not know it, sometimes things in that abyss, in

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Speaker 1: this sort of black mirror, are staring back at you.

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Speaker 2: And we'll get into that right after a quick word

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Speaker 2: from our sponsor.

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Speaker 1: Here's where it gets crazy. So we talked about smart devices.

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Speaker 1: They're popular. Everybody loves them. They're the hottest thing since

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Speaker 1: fresh baked sliced bread. Whatever.

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Speaker 2: Yeah, they do all the stuff we need, they do.

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Speaker 1: All the stuff we want too writ But with smart

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Speaker 1: devices comes the concept of surveillance. And we've talked about

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Speaker 1: this a little bit before at our previous episodes on

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Speaker 1: big data, big data, whatever your preference may be.

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Speaker 2: Oh yeah, and if you're worried about you know your

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Speaker 2: smart device is tracking you or anything, and you still

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Speaker 2: have one of these Amazon echoes or maybe a Google

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Speaker 2: personal assistant like a home or something plugged in and

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Speaker 2: turned on, you can stop worrying. They've already got you.

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Speaker 2: It's over. It's just too late. Yeah, we're having a

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Speaker 2: little bit of fun. There's that's not fully true. You

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Speaker 2: think that's fun, Matt, But there is some sand to

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Speaker 2: this idea, and we're gonna get into it a little

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Speaker 2: bit later.

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Speaker 3: Remember back when PDA's were a thing. Sure, personal digital assistance. Yeah,

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Speaker 3: now we have robot overlords that are like doing our bidding?

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Speaker 3: But are they really? Are we not really just doing

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Speaker 3: their bidding?

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Speaker 2: Oh? God?

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Speaker 1: Right, it's like the old oh Man. There's so many

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Speaker 1: weird ways to go with this. But we should talk

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Speaker 1: about the nuts and bolts too, right, because we know

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Speaker 1: our smart devices have to keep track of the user.

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Speaker 1: You have GPS, you have the ways app or something

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Speaker 1: you're driving, you have Lyft, you have Uber, what have you?

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Speaker 3: You know, all things that make the stuff function and

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Speaker 3: make it convenient for you.

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Speaker 1: And then there are also a lot of apps that say, hey,

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Speaker 1: we want permission to access your microphone or your location,

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Speaker 1: and you're like, wow, Candy Crush, this is getting serious.

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Speaker 1: You know, I'm picking that as an example that's not one. Okay, great, Well,

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Speaker 1: at least we have candy Crush to remain as a

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Speaker 1: sacrosanct example of good programming. But when our smart devices

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Speaker 1: are keeping track of us, the kind of surveillance that

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Speaker 1: they have is, as we can tell, squarely aimed at

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Speaker 1: tracking our preferences. Let me figure out what you like

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Speaker 1: says your mobile device such that I can give you

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Speaker 1: better offers make it easier for you to say yes

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Speaker 1: to things in the future. And that's why if you

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Speaker 1: were on our Facebook group, here's where it gets crazy.

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Speaker 1: You'll see You'll see all the strange, insidious examples ranging

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Speaker 1: from hilarious to disquieting about how just how these algorithms

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Speaker 1: can hone in. I think, Noel, you posted a meme

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Speaker 1: recently that was Facebook related.

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Speaker 2: Yeah, I did.

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Speaker 3: It was one of these great Simpsons memes where it

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Speaker 3: was just an image of like Bart Simpson in bed

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Speaker 3: and Homer leaning in really creepily like eyeball to eyeball,

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Speaker 3: and it was I think Homer was labeled as Facebook

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Speaker 3: ads and Bart was labeled as things I said out

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Speaker 3: loud but never actually Google searched or whatever.

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Speaker 1: Or some people even say I was just thinking about this.

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Speaker 3: It definitely started a conversation of people giving examples of

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Speaker 3: these things. And I've experienced it too. We have a

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Speaker 3: lot of advertisers that like vet stuff through us, and

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Speaker 3: sometimes I feel like I just say it or like

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Speaker 3: I'm talking to you guys about it, and I've never

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Speaker 3: even like read copy or seen an email or gone

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Speaker 3: to the site. Next thing, you know, Facebook's serving me

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Speaker 3: up you know, tushy or whatever. That bad example. But

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Speaker 3: like you know, you know I'm talking about You've seen it,

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Speaker 3: have them?

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Speaker 2: Sure? No, there's a reason for that. So, you know,

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Speaker 2: we get into why what are the motives behind all

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Speaker 2: of this surveillance. We kind of talked about a little

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Speaker 2: bit tracking our preferences and everything, but honestly, like what

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Speaker 2: are you going to do with all of that? If

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Speaker 2: you if you start to really think about and understand

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Speaker 2: what the economic model is behind all this stuff, you

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Speaker 2: realize that it's because we, you, me, each of us,

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Speaker 2: We are the batteries of the economic system, its products.

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Speaker 2: It's literally the matrix. We are living in the matrix everybody.

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Speaker 2: We are inside our pods. Our pods consist of your

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Speaker 2: smartphone and your smart TV and all the things you

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Speaker 2: interact with your laptop. That is us. We are the

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Speaker 2: byproducts of a lifestyle obsession, a fight club.

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Speaker 3: No, and here's the thing too, we mentioned I mentioned

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Speaker 3: this off air. I got that Amazon TV because it

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Speaker 3: had a lot of features, It had really high resolution,

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Speaker 3: and it was dirt cheap and TV prices way down,

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Speaker 3: and as we saw at the beginning of the show,

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Speaker 3: TV sales way up. And I think you can't ignore

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Speaker 3: that there's an exchange going on there with like we're

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Speaker 3: giving up this part of ourselves in exchange for cheaper

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Speaker 3: and better, more efficient technology.

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Speaker 1: Well, one must ask at a certain point, one must

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Speaker 1: ask where the income for where the company is actually

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Speaker 1: arriving from. We've mentioned before one of my favorite examples,

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Speaker 1: and I won't go into it now because longtime listeners

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Speaker 1: have already heard this for a time. Target the corporation,

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Speaker 1: the retail store was not making most of its money

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Speaker 1: off of selling people baby toys and trousers. Do people

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Speaker 1: still say trus trousers? Okay, sure, knickerbockers whatever. They were

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Speaker 1: making the bulk of their income, a huge proportion of

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Speaker 1: it from selling their security system infrastructure to other companies,

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Speaker 1: kind of like the way McDonald's makes most of its

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Speaker 1: money through real estate. So it's okay to sell a

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Speaker 1: television at a phenomenal loss, right when you know you're

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Speaker 1: going to recoup that money and then some on something else.

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Speaker 1: And I think that's what's happening at the televisions. Would

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Speaker 1: you agree?

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Speaker 3: I mean, It sure seems like that to me.

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Speaker 1: So we know, we know that no matter who you are,

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Speaker 1: no matter where you are in this wide world or

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Speaker 1: just orbiting yourround it, you have something that really wants

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Speaker 1: to be your friend, wants to be your best friend,

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Speaker 1: your teacher, your mother, your secret lover, to quote Homer Simpson.

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Speaker 1: And this thing that can't wait to be your best

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Speaker 1: friend is called the advertising industry. It's had its eye

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Speaker 1: on you for a while. It already knows a lot

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Speaker 1: about you, right Matt.

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Speaker 2: Oh, yeah, it knows a great deal about you. But

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Speaker 2: it wants to go deeper. It wants to go a

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Speaker 2: therapist style on you. He wants to know what you love,

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Speaker 2: what do you hate, who do you trust? And also

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Speaker 2: how much liquid cash can you get your hands on

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Speaker 2: in the short term. Now, okay, again we're joking a

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Speaker 2: little bit, but you get the point. For real. They

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Speaker 2: want to know how much you can spend and what

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Speaker 2: you would want to spend it on if you absolutely could,

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Speaker 2: right now, if somebody just popped something in front of

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Speaker 2: your face, right now, what is the number one thing

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Speaker 2: you would buy? Because we'll find it and we will

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Speaker 2: show it to you and you will buy it.

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Speaker 3: Yeah, and companies just gobble up all of this data

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Speaker 3: because the level of technology that we're at right now

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Speaker 3: isn't quite as sophisticated as they would like. We're getting there,

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Speaker 3: they're certainly pushing it every day, but right now it's

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Speaker 3: just kind of like a throwing everything at the wall

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Speaker 3: and seeing what sticks approach.

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Speaker 2: You know.

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Speaker 1: Artificial intelligence, it turns out, in this regard at least,

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Speaker 1: is not that intelligent and it needs a ton of help.

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Speaker 2: So it's efficient as all hell, but it is not.

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Speaker 2: It cannot make the connections a lot of times unless

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Speaker 2: it is helped out by a human user.

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Speaker 1: Still a black box, though great example works.

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Speaker 3: I often get served ads for things that I've already bought.

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Speaker 1: That's yeah, I was gonna say too. That's like it's

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Speaker 1: we're at the stage where in the Terminator franchise, the

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Speaker 1: original cyborgs were easily discernible from organic humans, right because

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Speaker 1: it's a bit ridiculous. There's not any human advertiser who

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Speaker 1: would say, well, this person just bought a toilet, so

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Speaker 1: you know what, they need five more toilets.

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Speaker 2: You know.

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Speaker 1: That's like, like, what's gonna happen? Are you gonna are

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Speaker 1: you gonna just bought a toilet. You'll see an ad

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Speaker 1: for it, and then you'll go, no, I don't know,

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Speaker 1: Maybe I'll just treat myself. It's it's bizarre.

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Speaker 2: Well, maybe you're a contractor. Maybe it thinks we're all

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Speaker 2: contractors and we're all building out bathroom fair points.

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Speaker 1: Yeah, and we know that, we know that companies have

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Speaker 1: a lot they want to do with this data, even

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Speaker 1: if they can't entirely get the rubber to meet the

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Speaker 1: road and practice. And we'll we'll expand that picture in

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Speaker 1: a frightening way a little bit later, but for now,

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Speaker 1: let's think of it this way. Companies give all the

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Speaker 1: data they can get their hands on, even the stuff

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Speaker 1: you would think is unimportant. They give all of that

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Speaker 1: equal weighting. When it comes to picking it up. There's

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Speaker 1: nothing that gets ignored if it's able to be monitored

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Speaker 1: and captured. And that's because AI programs, as we said,

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Speaker 1: just aren't that intelligent yet. They are efficient, mat but

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Speaker 1: they're not that intelligent. Like think about home surveillance systems.

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Speaker 1: You have a you know, Noel, You and I probably

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Speaker 1: have Amazon Echoes, yes, yeah, and you have a Google

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Speaker 1: Home or something like that.

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Speaker 2: Correct.

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Speaker 1: Okay, so these home surveillance systems, which is the correct

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Speaker 1: term for them. These home surveillance systems have these uh,

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Speaker 1: these assistants, these programs that will guess at what they

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Speaker 1: think you said, but they still frequently missed the mark.

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Speaker 1: You know what I mean, right, But they.

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Speaker 3: Also aren't listening and I think in theory and unless

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Speaker 3: you say that wake word right, whatever that might be.

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Speaker 2: No, they are always listening. Oh hey, the because they

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Speaker 2: have to hear the wake word.

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Speaker 1: I love doing this. Let's prank someone who's listening to

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Speaker 1: one of those in their house right now. Alexa no play,

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Speaker 1: Alexa play, don't please? Don't the remix are the origin

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Speaker 1: We're kidding, We're kidding. I hope we're all still friends

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Speaker 1: with our with our various devices. But but we say

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Speaker 1: this to point out that these things are far from perfect.

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Speaker 1: And there are a lot of people employed by these companies,

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Speaker 1: human listeners, right, just like many of us listening today,

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Speaker 1: who are tasked with going through these things and seeing

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Speaker 1: listening to the recording that someone said and then seeing

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Speaker 1: what the assistant thought they said, and then reconciling the

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Speaker 1: two to build a better mouse trap for your personal information.

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Speaker 2: Yes, and that is where we get into the Amazon

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Speaker 2: Echo story out of Bloomberg that we were going to

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Speaker 2: talk about, and that is the fact that there are

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Speaker 2: thousands of Amazon employees and contractors who, like Ben said,

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Speaker 2: are tasked with literally listening to what the microphone recorded

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Speaker 2: in your living room. So if so, you're asking Noel

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Speaker 2: about is is it always listening? Yes, the microphone is

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Speaker 2: always turned on. As long as you've got your Alexa

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Speaker 2: plugged in or your Google Home plugged in, that mic

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Speaker 2: is on and it is listening. It doesn't record anything

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Speaker 2: until you say Alexa or computer or Echo or whatever.

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Speaker 3: The key, right is the wavecord? Yeah, sure, But which

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Speaker 3: is a creepy phrase in and of itself if you

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Speaker 3: ask me.

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Speaker 2: But that is literally an open mic sitting in your house.

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Speaker 2: It's a hot mic, and that is where it gets

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Speaker 2: really creepy. But it also gets really creepy. Like, Okay,

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Speaker 2: on the surface, it makes complete sense. It's what Ben

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Speaker 2: was saying. It's quality assurance, right, it's trying to make

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Speaker 2: that AI better. It's an educational thing for the system.

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Speaker 2: But below the surface, like if you really break it

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Speaker 2: down and you take away some of the words that

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Speaker 2: are in there that make it feel like a fun

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Speaker 2: and exciting new thing. There is this mic in your room.

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Speaker 2: It's recording information things that you're saying in your private home,

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Speaker 2: and it's sending it to some person that you've never met.

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Speaker 2: And then this stranger is going to transcribe exactly what

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Speaker 2: you said in your living room. Then it's going to

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Speaker 2: feed it back in that system, so that when that

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Speaker 2: mic here's you talk again, it knows exactly what you said.

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Speaker 3: But again, it's only after you've said the wakeword. It's

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Speaker 3: not They're not transcribing all your conversations in your living room.

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00:22:55,040 --> 00:22:58,000
Speaker 3: It's all in theory stuff that you are attempting to

437
00:22:58,040 --> 00:23:01,160
Speaker 3: communicate to the device of Otherwise it wouldn't be any

438
00:23:01,240 --> 00:23:03,080
Speaker 3: use to them, it wouldn't help them improve the algorithm

439
00:23:03,119 --> 00:23:03,400
Speaker 3: at all.

440
00:23:03,560 --> 00:23:06,640
Speaker 2: But my point here is that that is how it functions,

441
00:23:07,080 --> 00:23:10,199
Speaker 2: according to the way the creators want it to function

442
00:23:10,280 --> 00:23:14,359
Speaker 2: right now. Made this device on. Yes, that is the

443
00:23:14,480 --> 00:23:17,480
Speaker 2: forward facing thing. And I'm not saying Amazon is doing

444
00:23:17,520 --> 00:23:21,040
Speaker 2: anything illegal or you know, scary like that, but there

445
00:23:21,200 --> 00:23:24,840
Speaker 2: is there is an easy route there to exploit that

446
00:23:24,960 --> 00:23:26,400
Speaker 2: microphone that's in your living room.

447
00:23:26,440 --> 00:23:30,000
Speaker 3: That's sure. So you're saying, maybe if someone a bad

448
00:23:30,040 --> 00:23:32,119
Speaker 3: actor let's say, got a hold of this, or do

449
00:23:32,119 --> 00:23:34,000
Speaker 3: you think Amazon could potentially be the bad.

450
00:23:33,840 --> 00:23:39,040
Speaker 1: Actor Amazon's partners. Let's let's say, let's foreshadow it that way,

451
00:23:39,119 --> 00:23:43,160
Speaker 1: Amazon's Amazon's buddies, the folks in bed with it. But Matt,

452
00:23:43,200 --> 00:23:45,280
Speaker 1: what's interesting to me about this is that you are

453
00:23:45,320 --> 00:23:50,280
Speaker 1: talking in terms of an above the surface level. Yes,

454
00:23:50,520 --> 00:23:53,440
Speaker 1: my spider sense tells me you've got to below the surface.

455
00:23:53,480 --> 00:23:58,600
Speaker 2: Take, No, well below the surface. Take is just in

456
00:23:58,640 --> 00:24:01,720
Speaker 2: my mind, the reality of the situation of We've talked

457
00:24:01,720 --> 00:24:03,480
Speaker 2: about it before on here. We kind of hit it

458
00:24:03,480 --> 00:24:05,840
Speaker 2: a couple times in this episode already, just that we

459
00:24:05,880 --> 00:24:09,359
Speaker 2: are literally bugging ourselves. And you know, and you think,

460
00:24:09,600 --> 00:24:13,280
Speaker 2: when you think about a world in which perhaps the

461
00:24:13,320 --> 00:24:17,359
Speaker 2: powers that be end up ruling, Let's just say this

462
00:24:17,560 --> 00:24:20,280
Speaker 2: United States that we live in. Let's say that some

463
00:24:20,440 --> 00:24:22,800
Speaker 2: group comes along and takes over. And now it is

464
00:24:22,880 --> 00:24:25,560
Speaker 2: illegal in this land to do X. And let's say

465
00:24:25,600 --> 00:24:29,320
Speaker 2: your family or your living situation is X. Now there

466
00:24:29,359 --> 00:24:31,840
Speaker 2: is a microphone in your living room or your kitchen

467
00:24:31,880 --> 00:24:34,479
Speaker 2: or wherever it is, and if you're just having a

468
00:24:34,560 --> 00:24:37,600
Speaker 2: regular conversation about what your life is and what you

469
00:24:37,640 --> 00:24:40,000
Speaker 2: are doing, but it is illegal in this land, and

470
00:24:40,000 --> 00:24:43,520
Speaker 2: there's a mic in there, right, there's potential that there

471
00:24:44,240 --> 00:24:48,080
Speaker 2: you could be abused in some way or persecuted.

472
00:24:48,160 --> 00:24:51,359
Speaker 3: That's all reminds me of the telescreens in nineteen eighty four,

473
00:24:51,920 --> 00:24:54,359
Speaker 3: which were like on this on one level, seen as

474
00:24:54,440 --> 00:24:56,879
Speaker 3: like a luxury and as like a really cool technological

475
00:24:56,920 --> 00:24:59,760
Speaker 3: gadget where you could watch all of these whatever entertainment

476
00:25:00,080 --> 00:25:02,080
Speaker 3: so wished. But it was a two way thing. It

477
00:25:02,119 --> 00:25:06,199
Speaker 3: was monitoring you. But there's a certain acceptance of it,

478
00:25:06,359 --> 00:25:08,920
Speaker 3: you know, like it's not secret monitoring. Everyone knows they're

479
00:25:08,960 --> 00:25:11,440
Speaker 3: being monitored. They just know to stay in line and

480
00:25:11,440 --> 00:25:14,760
Speaker 3: not fall outside of the party, you know, doctrine or whatever.

481
00:25:15,000 --> 00:25:17,040
Speaker 3: And we've kind of found ourselves in a very similar

482
00:25:17,080 --> 00:25:20,920
Speaker 3: situation where like complicit in our own surveillance.

483
00:25:20,560 --> 00:25:24,240
Speaker 1: Or well was nothing if not prescient in that regard.

484
00:25:24,560 --> 00:25:28,320
Speaker 1: There's a there's here's a real life example or something

485
00:25:28,359 --> 00:25:30,960
Speaker 1: that could play out plausibly. And this is heavy stuff.

486
00:25:31,240 --> 00:25:35,479
Speaker 1: So imagine that you live in a country that is

487
00:25:36,640 --> 00:25:41,320
Speaker 1: least economic developed country economically developed country, and that country

488
00:25:41,440 --> 00:25:45,280
Speaker 1: has an authoritarian government and they have strict religious laws

489
00:25:45,320 --> 00:25:49,159
Speaker 1: of one sort or another. Let's say that for a

490
00:25:49,280 --> 00:25:52,280
Speaker 1: time there was a different regime, and you were maybe

491
00:25:52,320 --> 00:25:55,400
Speaker 1: in a same sex relationship, and you and your partner

492
00:25:55,840 --> 00:25:59,280
Speaker 1: lived lived your normal, everyday life. Right. You just happen

493
00:25:59,320 --> 00:26:01,440
Speaker 1: to have your device because you like to hear music

494
00:26:01,440 --> 00:26:04,040
Speaker 1: when you cook. Who doesn't like that? But then the

495
00:26:04,080 --> 00:26:10,080
Speaker 1: regime changes, and now again same sex relationships are forbidden

496
00:26:10,200 --> 00:26:13,560
Speaker 1: or haram or whatever. And now that stuff that you

497
00:26:13,800 --> 00:26:18,800
Speaker 1: said that got hoovered up into the cloud, now it

498
00:26:18,840 --> 00:26:21,959
Speaker 1: makes you complicit in what that government sees as a crime.

499
00:26:22,080 --> 00:26:26,000
Speaker 1: And that means that, according to that government, the stuff

500
00:26:26,000 --> 00:26:28,879
Speaker 1: that you did, which was perfectly fine, your relationship was

501
00:26:28,960 --> 00:26:33,320
Speaker 1: perfectly fine until someone retroactively decided it wasn't. And now

502
00:26:34,000 --> 00:26:39,159
Speaker 1: because you wanted to hear the remakes to ignition, now

503
00:26:39,200 --> 00:26:42,160
Speaker 1: just because of the conversation that occurred around that time,

504
00:26:42,480 --> 00:26:46,040
Speaker 1: now you are in hot water and there's not a

505
00:26:46,119 --> 00:26:50,040
Speaker 1: recourse to help you. That's a terrifying possibility. Matt. You

506
00:26:50,080 --> 00:26:54,280
Speaker 1: were telling us off air that at least some companies

507
00:26:54,520 --> 00:27:00,000
Speaker 1: like Amazon attempt to quell those fears by publicly stated

508
00:27:00,160 --> 00:27:03,800
Speaker 1: there are hard constraints on how long an echo can

509
00:27:03,840 --> 00:27:04,360
Speaker 1: record something.

510
00:27:04,359 --> 00:27:08,200
Speaker 2: Oh yeah, absolutely, And again to Amazon's defense, I am

511
00:27:08,240 --> 00:27:12,680
Speaker 2: being completely conspiratorial in this and it's just one of

512
00:27:12,760 --> 00:27:14,639
Speaker 2: those weird foresight things that both men and I were

513
00:27:14,640 --> 00:27:18,040
Speaker 2: talking about there. But Amazon has stated that only a

514
00:27:18,080 --> 00:27:22,560
Speaker 2: fraction of one percent of interactions with their devices actually

515
00:27:23,080 --> 00:27:25,840
Speaker 2: gets transcribed in this way by a human, by a

516
00:27:25,920 --> 00:27:28,200
Speaker 2: human where it gets sent off. They transcribe at the

517
00:27:28,240 --> 00:27:31,239
Speaker 2: center back in since the beginning of twenty nineteen, and

518
00:27:31,280 --> 00:27:33,480
Speaker 2: this is by the way, from August of twenty nineteen

519
00:27:33,520 --> 00:27:38,440
Speaker 2: from the ambient, so eight months of transcribing had had

520
00:27:38,480 --> 00:27:41,240
Speaker 2: gone through and only point two percent of all requests

521
00:27:41,240 --> 00:27:45,000
Speaker 2: to Alexa had actually been transcribed. So that's very a

522
00:27:45,160 --> 00:27:48,200
Speaker 2: very very small number of conversations that actually get listened

523
00:27:48,240 --> 00:27:49,119
Speaker 2: to and transcribed.

524
00:27:49,280 --> 00:27:52,399
Speaker 1: Interesting how they put it in percentage though, because putting

525
00:27:52,440 --> 00:27:56,000
Speaker 1: it in percentage can make something something seems smaller than

526
00:27:56,000 --> 00:27:57,040
Speaker 1: it is in reality.

527
00:27:57,200 --> 00:28:02,560
Speaker 3: Right, it's a massive sample size, right, That small percentage

528
00:28:02,880 --> 00:28:04,080
Speaker 3: is actually a massive.

529
00:28:03,840 --> 00:28:07,359
Speaker 1: Number, right, Right, It just sounds a little more reasonable.

530
00:28:07,520 --> 00:28:07,760
Speaker 3: Right.

531
00:28:07,880 --> 00:28:12,680
Speaker 2: Well, here's the great thing. When you say, hey, whatever,

532
00:28:13,080 --> 00:28:15,720
Speaker 2: Alexa gonna do it, You're gonna do it. Spread it

533
00:28:15,760 --> 00:28:18,320
Speaker 2: out enough. But when you do that, generally you ask

534
00:28:18,359 --> 00:28:21,359
Speaker 2: a very short request or a very short question or

535
00:28:21,400 --> 00:28:22,600
Speaker 2: something to that effect, and then.

536
00:28:22,520 --> 00:28:24,520
Speaker 3: It does the thing and then like that window of

537
00:28:25,040 --> 00:28:26,400
Speaker 3: monitoring is over kind of.

538
00:28:26,400 --> 00:28:29,240
Speaker 2: Right, generally, yeah, it lasts for about two seconds, that's

539
00:28:29,280 --> 00:28:33,000
Speaker 2: the average. So when somebody is transcribing, that's literally all

540
00:28:33,320 --> 00:28:33,960
Speaker 2: all it says.

541
00:28:34,119 --> 00:28:35,800
Speaker 3: You can they make good money doing that?

542
00:28:35,920 --> 00:28:38,160
Speaker 1: Or is it like they know it's Amazon, They're not

543
00:28:38,200 --> 00:28:39,520
Speaker 1: getting paid very well at all?

544
00:28:39,640 --> 00:28:41,480
Speaker 3: Is it sort of like we as a company, we

545
00:28:42,120 --> 00:28:44,479
Speaker 3: do a lot of transcribing interviews and stuff. You think

546
00:28:44,480 --> 00:28:46,360
Speaker 3: it's very similar to that. You think even outsource it.

547
00:28:46,400 --> 00:28:46,840
Speaker 3: They couldn't.

548
00:28:46,880 --> 00:28:47,680
Speaker 2: It is contractors.

549
00:28:47,760 --> 00:28:48,480
Speaker 3: It is contractors.

550
00:28:48,560 --> 00:28:50,600
Speaker 2: Some of its contractors, some of its employees got it.

551
00:28:50,760 --> 00:28:55,920
Speaker 1: And this practice has no currently has no real legal

552
00:28:56,040 --> 00:29:01,160
Speaker 1: constraints because, as we know, technology always outpaces legislation tale

553
00:29:01,160 --> 00:29:04,800
Speaker 1: as old as time. However, I get the feeling that

554
00:29:04,920 --> 00:29:08,000
Speaker 1: a lot of us were sort of aware that something's

555
00:29:08,040 --> 00:29:10,360
Speaker 1: off with these home assistants, or that there is some

556
00:29:10,480 --> 00:29:13,640
Speaker 1: kind of transaction at play. If it's not terrible, if

557
00:29:13,680 --> 00:29:16,560
Speaker 1: it's something we're okay with, we knew there was still something.

558
00:29:16,840 --> 00:29:19,160
Speaker 1: And you can hear, you know, when things go wrong

559
00:29:19,240 --> 00:29:21,840
Speaker 1: in nine one one calls and all these other spooky

560
00:29:21,880 --> 00:29:26,280
Speaker 1: stories about things going south with Google or Amazon. But

561
00:29:26,520 --> 00:29:30,320
Speaker 1: what about the other devices. We have some news for

562
00:29:30,360 --> 00:29:34,000
Speaker 1: you about smart TVs. Look around your room or wherever

563
00:29:34,040 --> 00:29:36,520
Speaker 1: you happen to find yourself, is there a TV in there?

564
00:29:36,800 --> 00:29:39,440
Speaker 1: Things are about to get very interesting for you. After

565
00:29:39,480 --> 00:29:45,360
Speaker 1: a word from our sponsors.

566
00:29:45,760 --> 00:29:49,200
Speaker 2: All right, we're back. Let's jump in to something we

567
00:29:49,360 --> 00:29:52,400
Speaker 2: learned about thanks to New York Times in a twenty

568
00:29:52,560 --> 00:29:57,440
Speaker 2: eighteen article about filing. New York Times, they are not failing.

569
00:29:57,480 --> 00:30:00,600
Speaker 1: I don't believe, I mean not after this bump. I

570
00:30:00,640 --> 00:30:04,400
Speaker 1: mentioned this article in the gang Stalking episode. So you're welcome,

571
00:30:04,480 --> 00:30:04,880
Speaker 1: New York.

572
00:30:05,080 --> 00:30:08,600
Speaker 2: Yes you did, Ben. Ben did bring this up, and

573
00:30:08,680 --> 00:30:10,320
Speaker 2: we decided we were going to look into it, and

574
00:30:10,520 --> 00:30:13,760
Speaker 2: we did, and now we can't look away forever. So

575
00:30:14,000 --> 00:30:18,400
Speaker 2: it's a thing called Samba TV. That sounds fun Samba TV, it.

576
00:30:18,360 --> 00:30:20,320
Speaker 3: Sounds really funny. Know what else sounds finn I'm gonna

577
00:30:20,320 --> 00:30:22,640
Speaker 3: skip down just just a tad. How does this sound

578
00:30:22,680 --> 00:30:22,880
Speaker 3: to you?

579
00:30:22,920 --> 00:30:24,200
Speaker 1: Guys? Hey?

580
00:30:24,280 --> 00:30:26,400
Speaker 3: How about you want to interact with your favorite shows,

581
00:30:26,560 --> 00:30:30,520
Speaker 3: get recommendations based on the content you love, connect your

582
00:30:30,560 --> 00:30:35,600
Speaker 3: devices for exclusive content and special offers. How about Samba

583
00:30:35,600 --> 00:30:39,360
Speaker 3: Interactive TV lets you engage with your TV in a

584
00:30:39,400 --> 00:30:42,200
Speaker 3: whole new way. That sounds great sounds.

585
00:30:42,280 --> 00:30:42,800
Speaker 2: Damn good.

586
00:30:42,800 --> 00:30:43,360
Speaker 3: I'm into that.

587
00:30:43,880 --> 00:30:45,320
Speaker 2: So what is Samba TV?

588
00:30:45,640 --> 00:30:45,800
Speaker 3: Oh?

589
00:30:45,840 --> 00:30:47,040
Speaker 1: Hey man, what's Samba TV?

590
00:30:47,840 --> 00:30:51,560
Speaker 2: Okay, I'll tell you. It is a software, a piece

591
00:30:51,600 --> 00:30:55,160
Speaker 2: of software that is present in a lot of television models,

592
00:30:55,160 --> 00:30:58,560
Speaker 2: some models from nearly a dozen smart TV brands. And

593
00:30:58,600 --> 00:31:02,640
Speaker 2: again this is as of late twenty eighteen. That has changed.

594
00:31:03,240 --> 00:31:06,960
Speaker 2: There are more included now, but it is Sony Sharp Phillips,

595
00:31:07,560 --> 00:31:09,280
Speaker 2: a lot of that, all the hits, all the head

596
00:31:09,320 --> 00:31:13,120
Speaker 2: ones in this software. In particular, it identifies what is

597
00:31:13,160 --> 00:31:17,880
Speaker 2: being watched on the monitor the television by literally analyzing

598
00:31:17,920 --> 00:31:21,320
Speaker 2: the pixels displayed and then comparing that data to a

599
00:31:21,360 --> 00:31:23,520
Speaker 2: set of known media that exists out there.

600
00:31:23,560 --> 00:31:25,920
Speaker 3: It's a similar way like audio things or even YouTube

601
00:31:25,920 --> 00:31:28,120
Speaker 3: things are flagged for copyright violations.

602
00:31:28,360 --> 00:31:31,040
Speaker 2: Yes, but in this case it is the end user

603
00:31:31,560 --> 00:31:35,640
Speaker 2: that is the actual piece of hardware that is being monitored.

604
00:31:35,720 --> 00:31:39,240
Speaker 1: Right, And this was always coming Nielsen ratings, like the

605
00:31:39,320 --> 00:31:41,520
Speaker 1: Nielsen Institution wanted this.

606
00:31:41,920 --> 00:31:45,000
Speaker 2: Yes, there needed to be a way to find out

607
00:31:45,000 --> 00:31:49,360
Speaker 2: who was watching what when, and in particular, when you're

608
00:31:49,360 --> 00:31:53,320
Speaker 2: saying about who, it means everybody who is around, not

609
00:31:53,480 --> 00:31:58,200
Speaker 2: just that this household is watching something. But here's the

610
00:31:58,280 --> 00:32:02,280
Speaker 2: idea you're viewing history is then in part used to suggest,

611
00:32:02,520 --> 00:32:05,520
Speaker 2: as Noel was saying, as the flowery language there that's

612
00:32:05,560 --> 00:32:07,840
Speaker 2: actually present in the PR from Samba TV.

613
00:32:07,920 --> 00:32:09,200
Speaker 1: Oh yeah, they wrote that copy.

614
00:32:09,080 --> 00:32:10,720
Speaker 3: Of Well it's not only the PR, it's the opt

615
00:32:10,800 --> 00:32:11,440
Speaker 3: in message.

616
00:32:11,520 --> 00:32:15,200
Speaker 2: Yes, yes, it's used to suggest the next content that

617
00:32:15,400 --> 00:32:19,880
Speaker 2: Samba TV believes you will yourself enjoy. But that is

618
00:32:19,920 --> 00:32:23,600
Speaker 2: not all that Samba TV does. It also identifies all

619
00:32:23,640 --> 00:32:26,440
Speaker 2: the other devices that are connected to the same network

620
00:32:26,720 --> 00:32:29,200
Speaker 2: through which it is accessing the internet.

621
00:32:29,400 --> 00:32:32,360
Speaker 1: So your friend comes over, they have a phone with

622
00:32:32,480 --> 00:32:35,400
Speaker 1: Wi Fi. Now they're in the loop as well.

623
00:32:35,520 --> 00:32:38,160
Speaker 2: Yes, if you are Netflix and chilling or whatever the

624
00:32:38,240 --> 00:32:41,000
Speaker 2: kids call it these days at somebody else's house or

625
00:32:41,040 --> 00:32:44,360
Speaker 2: apartment and Samba TV is there, it knows that you're

626
00:32:44,400 --> 00:32:46,920
Speaker 2: there because it can identify your device and the Mac

627
00:32:46,960 --> 00:32:47,960
Speaker 2: address and all those things.

628
00:32:48,000 --> 00:32:50,960
Speaker 3: And here's the thing. This company claims that it is

629
00:32:51,040 --> 00:32:54,760
Speaker 3: adhering very closely to privacy guidelines set forth by the

630
00:32:54,960 --> 00:32:58,400
Speaker 3: Federal Trade Commission, that it does not directly sell any

631
00:32:58,440 --> 00:33:01,440
Speaker 3: of this data. Instead, at tizers can pay the company

632
00:33:01,720 --> 00:33:05,120
Speaker 3: to kind of guide the hand of the ads in

633
00:33:05,200 --> 00:33:08,840
Speaker 3: the placement, which which makes sense. Doesn't sound too insidious, right.

634
00:33:09,200 --> 00:33:13,320
Speaker 2: Well, it's directing ads to the other devices that are

635
00:33:13,400 --> 00:33:17,560
Speaker 2: present who they believe are watching the television program right.

636
00:33:17,520 --> 00:33:20,720
Speaker 1: Right, right, And so your opt in stuff happens at

637
00:33:20,720 --> 00:33:23,920
Speaker 1: the television right at the TV, but it doesn't happen

638
00:33:23,960 --> 00:33:27,480
Speaker 1: at your smartphone necessarily if you walk into someone else's house.

639
00:33:28,560 --> 00:33:31,040
Speaker 3: And so, how do they get around the legality of

640
00:33:31,280 --> 00:33:34,600
Speaker 3: other people? Like, are they automatically part of your opt

641
00:33:34,640 --> 00:33:38,560
Speaker 3: in when they's.

642
00:33:37,040 --> 00:33:39,720
Speaker 1: That's what I'm saying, there's not informed consents. Interesting and

643
00:33:39,760 --> 00:33:42,800
Speaker 1: also think about this, this technology is amazing. If our

644
00:33:42,920 --> 00:33:46,920
Speaker 1: species was less of a garbage fire, we could use

645
00:33:46,960 --> 00:33:50,160
Speaker 1: this to do wonderful things for you know, say someone's

646
00:33:50,200 --> 00:33:53,080
Speaker 1: mental health, right, and someone's like, okay, I see you've

647
00:33:53,120 --> 00:33:56,080
Speaker 1: watched Faces of Death four nine times in a row.

648
00:33:56,280 --> 00:33:58,880
Speaker 1: I'd like to recommend the Great British Bacon Show. Do

649
00:33:58,920 --> 00:33:59,560
Speaker 1: you know what I mean?

650
00:34:00,560 --> 00:34:03,040
Speaker 3: You do a better job with your content consumption? No,

651
00:34:03,160 --> 00:34:07,120
Speaker 3: it's totally true. And when you let's say you plug

652
00:34:07,160 --> 00:34:11,600
Speaker 3: in your new smart TV and it has Samba on it,

653
00:34:11,600 --> 00:34:15,000
Speaker 3: it will present you with that very flowery language that's

654
00:34:15,040 --> 00:34:18,520
Speaker 3: the opt in message. There is a giant terms of

655
00:34:18,560 --> 00:34:22,000
Speaker 3: service and privacy policy. You know page that you can

656
00:34:22,239 --> 00:34:25,440
Speaker 3: peruse if you wish. I believe it's sixty five hundred

657
00:34:25,440 --> 00:34:27,960
Speaker 3: words for the terms of service and four thousand words

658
00:34:27,960 --> 00:34:30,160
Speaker 3: for the privacy policy. But why would you even bother

659
00:34:30,280 --> 00:34:33,000
Speaker 3: doing that when you can interact with your favorite shows,

660
00:34:33,160 --> 00:34:36,200
Speaker 3: get recommendations based on the content that you love.

661
00:34:36,600 --> 00:34:38,840
Speaker 1: That terms of service is a real page turner.

662
00:34:38,880 --> 00:34:41,399
Speaker 3: Oh yeah, yeah, But why would you want to do

663
00:34:41,480 --> 00:34:44,399
Speaker 3: that when this seems so innocuous and you just want

664
00:34:44,400 --> 00:34:46,080
Speaker 3: to start playing your Fallout four?

665
00:34:46,320 --> 00:34:49,399
Speaker 2: Yeah, well, to see, that's not the real insidious thing

666
00:34:49,520 --> 00:34:53,080
Speaker 2: here is that Let's put yourself in the position of

667
00:34:53,200 --> 00:34:55,720
Speaker 2: you've spent let's say the last couple of months saving

668
00:34:55,800 --> 00:34:57,840
Speaker 2: up money because you really, you know, you need to

669
00:34:57,840 --> 00:35:00,839
Speaker 2: get this new TV. You're really excited about it. You

670
00:35:00,920 --> 00:35:04,719
Speaker 2: finally get it right, and you're installing it your you know,

671
00:35:04,880 --> 00:35:06,960
Speaker 2: your hands are all sweaty because you know Fallout four,

672
00:35:07,080 --> 00:35:09,040
Speaker 2: the next playthrough is about to happen. You're like, oh

673
00:35:09,040 --> 00:35:11,680
Speaker 2: my god, this is I'm so excited. You plug this

674
00:35:11,760 --> 00:35:15,000
Speaker 2: thing in, you start going through the initialization process, the

675
00:35:15,080 --> 00:35:18,560
Speaker 2: Samba thing pops up, and you know you can you

676
00:35:18,640 --> 00:35:20,839
Speaker 2: literally have to decide if you're going to spend an

677
00:35:20,880 --> 00:35:24,239
Speaker 2: hour parsing through all of that legal ease or if

678
00:35:24,280 --> 00:35:26,440
Speaker 2: you're gonna get to whatever it is you're you wanted

679
00:35:26,440 --> 00:35:31,120
Speaker 2: to get to, and most people just click enable and

680
00:35:31,160 --> 00:35:33,440
Speaker 2: move forward. It has nothing to do with the flowery

681
00:35:33,520 --> 00:35:36,640
Speaker 2: language or anything like that. It says enable, Okay, yes,

682
00:35:36,760 --> 00:35:39,000
Speaker 2: this gets me to the next thing. Just click and enable,

683
00:35:39,239 --> 00:35:41,279
Speaker 2: And that is exactly what most people do.

684
00:35:41,840 --> 00:35:46,120
Speaker 1: Right on the order of an estimated ninety percent, A

685
00:35:46,200 --> 00:35:50,000
Speaker 1: vast majority of people do click enable. And once this

686
00:35:50,040 --> 00:35:53,200
Speaker 1: stuff is up and running, it's a katie bar the

687
00:35:53,280 --> 00:35:56,360
Speaker 1: doors they used to say in Days of your Samba

688
00:35:56,400 --> 00:36:00,880
Speaker 1: sees everything that is displayed on the monitor, regardless of

689
00:36:00,920 --> 00:36:04,400
Speaker 1: what you're watching or playing or how you're displaying it.

690
00:36:04,400 --> 00:36:08,279
Speaker 1: It doesn't matter if you're watching TV. It doesn't matter

691
00:36:08,320 --> 00:36:10,600
Speaker 1: if you're watching a film. It doesn't matter if you're

692
00:36:10,640 --> 00:36:12,760
Speaker 1: broadcasting a home video.

693
00:36:12,920 --> 00:36:15,759
Speaker 2: Right yeah, it could be literally anything, you know, if

694
00:36:15,800 --> 00:36:18,360
Speaker 2: you are broadcasting a home video of something that you

695
00:36:18,400 --> 00:36:22,520
Speaker 2: wouldn't want anyone else to see, Samba TV is analyzing it.

696
00:36:22,520 --> 00:36:25,560
Speaker 2: It isn't necessarily matching up with any known media. Sure,

697
00:36:25,600 --> 00:36:27,920
Speaker 2: but if you broadcast the same kind of home videos,

698
00:36:28,000 --> 00:36:31,239
Speaker 2: Let's say I your kids, maybe a romantic video you

699
00:36:31,280 --> 00:36:36,120
Speaker 2: made with your partner. I mean, honestly, who knows. That's

700
00:36:36,160 --> 00:36:38,919
Speaker 2: again taking a little bit further than the known technology

701
00:36:39,000 --> 00:36:41,400
Speaker 2: or the known reasons for using it. But it could

702
00:36:41,440 --> 00:36:46,000
Speaker 2: be used in the future by someone to figure out

703
00:36:46,960 --> 00:36:49,120
Speaker 2: very personal, intimate things about you. But it's sort of like.

704
00:36:49,120 --> 00:36:51,000
Speaker 3: When we read about the NSA and the way the

705
00:36:51,080 --> 00:36:53,840
Speaker 3: NSA was monitoring people's phone calls. They weren't recording the

706
00:36:53,880 --> 00:36:57,400
Speaker 3: actual audio. They were just capturing the metadata so they

707
00:36:57,440 --> 00:36:59,360
Speaker 3: knew how long a call lasted, or like you know

708
00:36:59,360 --> 00:37:03,160
Speaker 3: who this web of interconnectedness or whatever, it's similar with this.

709
00:37:03,280 --> 00:37:07,719
Speaker 3: It's not like they're recording actually what you're streaming. They're

710
00:37:07,760 --> 00:37:10,600
Speaker 3: just capturing the data of what it is, how long

711
00:37:10,600 --> 00:37:12,840
Speaker 3: you watched it for, et cetera, of the pixels of

712
00:37:12,880 --> 00:37:13,440
Speaker 3: the pixels.

713
00:37:13,800 --> 00:37:19,799
Speaker 1: Right, So this, okay, this is true. Even if we

714
00:37:19,960 --> 00:37:24,040
Speaker 1: want to be as skeptical or I should say, as

715
00:37:24,120 --> 00:37:27,680
Speaker 1: credulous as we can, and if we take those pieces

716
00:37:27,719 --> 00:37:31,600
Speaker 1: of State of pr copy at their word, this still

717
00:37:31,719 --> 00:37:37,080
Speaker 1: has a ton of hilarious, cartoonish vulnerabilities. You can learn

718
00:37:37,120 --> 00:37:40,000
Speaker 1: too much about people and there's no way for the

719
00:37:40,120 --> 00:37:43,040
Speaker 1: end user to stop it. Other than try to opt out.

720
00:37:43,040 --> 00:37:45,000
Speaker 1: But opting out it doesn't delete all the stuff that

721
00:37:45,040 --> 00:37:49,080
Speaker 1: has already learned about you. Are we being paranoid perhaps,

722
00:37:49,520 --> 00:37:57,480
Speaker 1: or perhaps we should introduce you to Alfonso. Oh God,

723
00:37:57,600 --> 00:37:59,040
Speaker 1: I love that Alfonso.

724
00:37:59,280 --> 00:38:02,440
Speaker 2: Okay, So to break this down thus far, we've got

725
00:38:02,520 --> 00:38:08,759
Speaker 2: our personal assistance that always are on Slicious no matter

726
00:38:08,760 --> 00:38:10,879
Speaker 2: if we're saying the keywords or not. They have their

727
00:38:10,920 --> 00:38:13,920
Speaker 2: microphone on and they are listening. They aren't necessarily recording

728
00:38:13,960 --> 00:38:16,040
Speaker 2: all the time, but they are. Now you have your

729
00:38:16,040 --> 00:38:20,200
Speaker 2: smartphone over there that is literally watching what you're watching too,

730
00:38:20,360 --> 00:38:23,760
Speaker 2: and it is making informed decisions about what you watch

731
00:38:23,840 --> 00:38:27,360
Speaker 2: and sending ads to all the devices in your house. Now,

732
00:38:27,600 --> 00:38:30,520
Speaker 2: let's say you're on one of those devices. Let's say

733
00:38:30,680 --> 00:38:33,239
Speaker 2: it's an Android device. Let's say you went to the

734
00:38:33,280 --> 00:38:37,439
Speaker 2: Google Play whatever it is app store thing, and you've

735
00:38:37,440 --> 00:38:40,680
Speaker 2: downloaded some apps and some games. Well a lot of

736
00:38:40,719 --> 00:38:43,480
Speaker 2: these apps and games, not all of them, but a

737
00:38:43,480 --> 00:38:47,759
Speaker 2: lot of them have partnered with this thing called Alphonso.

738
00:38:47,960 --> 00:38:58,360
Speaker 2: So this is a really interesting little piece of software

739
00:38:58,400 --> 00:39:00,960
Speaker 2: that's attached to these apps, and what it will do

740
00:39:01,480 --> 00:39:06,160
Speaker 2: is prompt you to enable the use of your microphone.

741
00:39:06,400 --> 00:39:10,160
Speaker 1: Right and these would be things that do not ostensibly

742
00:39:10,239 --> 00:39:12,839
Speaker 1: need that kind of access. Pull three D beer pong,

743
00:39:12,920 --> 00:39:16,239
Speaker 1: trick shot, real bowling, strike ten pen, you know these

744
00:39:16,320 --> 00:39:20,560
Speaker 1: kind of word salady names, little fun waste of time apps.

745
00:39:20,680 --> 00:39:24,080
Speaker 2: Well, and not just those some anti spying software. There's

746
00:39:24,200 --> 00:39:25,800
Speaker 2: a ton of apps out.

747
00:39:25,680 --> 00:39:30,920
Speaker 1: There right because it's it's this Alphonso is app agnostic. Yes,

748
00:39:31,239 --> 00:39:35,520
Speaker 1: So here's what happens. Here's why they want that microphone access.

749
00:39:36,040 --> 00:39:38,520
Speaker 1: Because when you're using this app, or when you grant

750
00:39:38,560 --> 00:39:43,480
Speaker 1: this app microphone access, Alfonso can figure out what you

751
00:39:43,640 --> 00:39:48,320
Speaker 1: happen to watch by identifying audio signals and television ads

752
00:39:48,360 --> 00:39:51,680
Speaker 1: and shows and even matching that information with the places

753
00:39:51,760 --> 00:39:55,600
Speaker 1: people visit and the movies they see really quickly. Here

754
00:39:55,680 --> 00:39:58,839
Speaker 1: is how it works. So we're all hanging out, we're

755
00:39:58,960 --> 00:40:03,040
Speaker 1: watching some television show that we're into. Let's go with lost,

756
00:40:03,160 --> 00:40:06,520
Speaker 1: something with commercials. So when the show switches to commercial,

757
00:40:06,840 --> 00:40:12,040
Speaker 1: there is a pitch an audio signal that goes out

758
00:40:12,239 --> 00:40:15,400
Speaker 1: to the room. You cannot hear it, your pets cannot

759
00:40:15,440 --> 00:40:18,640
Speaker 1: hear it, your kids cannot hear it. No one can

760
00:40:18,680 --> 00:40:21,000
Speaker 1: hear it, and no one is supposed to hear it.

761
00:40:21,000 --> 00:40:24,680
Speaker 1: It's only for your phone's and that's what they do.

762
00:40:24,719 --> 00:40:28,360
Speaker 1: They communicate with your phone, and then the phone will

763
00:40:28,719 --> 00:40:36,719
Speaker 1: also let people know via Alfonso. The phone will let

764
00:40:36,760 --> 00:40:40,400
Speaker 1: the users of the app, the real app. The users

765
00:40:40,400 --> 00:40:44,880
Speaker 1: of Alfonso understand who is in that room, where they

766
00:40:44,920 --> 00:40:48,080
Speaker 1: came from, maybe where they're going, and what they would

767
00:40:48,160 --> 00:40:50,400
Speaker 1: like to buy. That's not what you sign up for

768
00:40:50,520 --> 00:40:52,560
Speaker 1: when you walk. You know, you go to a potluck

769
00:40:52,600 --> 00:40:55,080
Speaker 1: at your friend's house to watch some kind of film. Right,

770
00:40:55,680 --> 00:40:57,919
Speaker 1: and how many apps are we talking here?

771
00:40:58,040 --> 00:41:00,000
Speaker 2: Well, okay, so according to the New York Times, there

772
00:41:00,040 --> 00:41:02,240
Speaker 2: were over two hundred and fifty apps on the Google

773
00:41:02,239 --> 00:41:06,399
Speaker 2: Play Store with this feature. Right, And if you want,

774
00:41:06,440 --> 00:41:08,359
Speaker 2: if you head over to the Google Play Store and

775
00:41:08,440 --> 00:41:12,960
Speaker 2: you type in quotations Alfonso Automated. That's A L P

776
00:41:13,200 --> 00:41:15,640
Speaker 2: H O N S O A U T O M

777
00:41:15,680 --> 00:41:18,319
Speaker 2: A T E D, and you will find all of

778
00:41:18,320 --> 00:41:20,719
Speaker 2: the various apps that have this thing installed. But then

779
00:41:20,760 --> 00:41:22,759
Speaker 2: if you if you look at an interview with some

780
00:41:22,840 --> 00:41:28,280
Speaker 2: Alfonso people, they said that there are thousands of apps

781
00:41:28,360 --> 00:41:30,640
Speaker 2: that they've partnered with and they didn't want to disclose

782
00:41:30,680 --> 00:41:33,760
Speaker 2: all of them because they have competitors who are trying

783
00:41:33,760 --> 00:41:37,880
Speaker 2: to basically get in on their territory. Yeah, approach their territory.

784
00:41:37,880 --> 00:41:40,640
Speaker 3: Remember when spyware was a big concern. This is like

785
00:41:40,680 --> 00:41:42,160
Speaker 3: some next level spyware.

786
00:41:42,400 --> 00:41:43,200
Speaker 1: This is spyware.

787
00:41:43,280 --> 00:41:45,320
Speaker 3: Yeah, but it's like different, right, It's like it literally

788
00:41:45,560 --> 00:41:48,160
Speaker 3: is opt in, right, it's spying on you.

789
00:41:48,600 --> 00:41:50,799
Speaker 2: Yeah, it's crazy, and now we know it's cyclical. So

790
00:41:50,960 --> 00:41:55,200
Speaker 2: it's all of the devices functioning together in this web

791
00:41:55,440 --> 00:41:57,800
Speaker 2: of trying to figure out what you want the most

792
00:41:57,880 --> 00:42:00,960
Speaker 2: and how to display that thing to you most effectively.

793
00:42:01,080 --> 00:42:05,320
Speaker 1: I guess Staltz effect. Yeah. This also, this problem becomes

794
00:42:06,160 --> 00:42:12,400
Speaker 1: complicated even further when we realize that private entity institutions

795
00:42:12,440 --> 00:42:15,440
Speaker 1: are not the only actors in this sphere. Indeed, they

796
00:42:15,560 --> 00:42:19,279
Speaker 1: may be some of the more innocuous. I love that

797
00:42:19,320 --> 00:42:22,480
Speaker 1: you mentioned spywaar or NOL, because the best spywear right

798
00:42:22,560 --> 00:42:25,960
Speaker 1: now is being built not by private industry but by

799
00:42:26,080 --> 00:42:31,959
Speaker 1: state actors. We mentioned Amazon's partners, right, Amazon's partners using

800
00:42:32,000 --> 00:42:37,319
Speaker 1: the data. Amazon's partners are alphabet soup intelligence agencies or

801
00:42:38,000 --> 00:42:41,200
Speaker 1: strongly thought to be so, especially.

802
00:42:40,880 --> 00:42:43,760
Speaker 2: Legedly, especially thanks to that early cash injection.

803
00:42:44,200 --> 00:42:47,759
Speaker 1: Right, exactly so. According to a Washington Post article from

804
00:42:47,800 --> 00:42:51,600
Speaker 1: twenty seventeen, the United States government has already turned theoretical

805
00:42:51,640 --> 00:42:55,440
Speaker 1: exploits and vulnerabilities in this kind of stuff into functioning

806
00:42:55,520 --> 00:43:00,600
Speaker 1: attack tools. One of these goes by the objectively badass

807
00:43:00,680 --> 00:43:05,560
Speaker 1: name Weeping Angel. Weeping Angel is specifically meant to target

808
00:43:05,680 --> 00:43:09,880
Speaker 1: Samsung TVs. This is just a small, microcosmic example, and

809
00:43:09,920 --> 00:43:12,120
Speaker 1: this is at least what it was doing two years ago,

810
00:43:12,640 --> 00:43:18,000
Speaker 1: according to WikiLeaks after infestation, Weeping Angel places a target

811
00:43:18,040 --> 00:43:21,240
Speaker 1: TV in a fake off mode so that the owner

812
00:43:21,360 --> 00:43:24,480
Speaker 1: believes the TV's off when it's still on. And then

813
00:43:24,680 --> 00:43:27,800
Speaker 1: in this fake off mode, the TV operates as a bug,

814
00:43:28,120 --> 00:43:31,359
Speaker 1: recording conversations in the room and then sending them over

815
00:43:31,400 --> 00:43:35,520
Speaker 1: the cloud to a covert CIA server. This sounds bonkers.

816
00:43:35,560 --> 00:43:37,560
Speaker 1: This sounds bananas. I can't believe it's real.

817
00:43:37,920 --> 00:43:41,799
Speaker 2: Why would anybody ever be paranoid? Right?

818
00:43:42,680 --> 00:43:43,359
Speaker 1: Why would they?

819
00:43:43,480 --> 00:43:44,320
Speaker 2: That's crazy?

820
00:43:45,480 --> 00:43:48,279
Speaker 1: And I hope whomever is listening to this around a

821
00:43:48,320 --> 00:43:52,000
Speaker 1: smart television has unplugged their headphones and is listening on speaker.

822
00:43:53,520 --> 00:43:57,239
Speaker 2: You know, Okay, look everything, I just have to say this,

823
00:43:57,320 --> 00:44:00,400
Speaker 2: everything we've been discussing today, If if you are of

824
00:44:00,440 --> 00:44:04,560
Speaker 2: a certain mind, perhaps like myself quite a lot, quite frequently,

825
00:44:05,440 --> 00:44:08,560
Speaker 2: it could lead you down a dark pathway where it

826
00:44:08,640 --> 00:44:13,160
Speaker 2: feels as though there's surveillance everywhere and you're being targeted

827
00:44:13,560 --> 00:44:16,680
Speaker 2: in some way. We can assure you this is not

828
00:44:16,920 --> 00:44:20,680
Speaker 2: just about you, no matter what you may think or

829
00:44:20,960 --> 00:44:25,239
Speaker 2: no matter what you may believe. Sure it is, it's

830
00:44:25,360 --> 00:44:30,000
Speaker 2: mass it's everybody, and again it is not necessarily nefarious.

831
00:44:31,560 --> 00:44:32,240
Speaker 2: But it's real.

832
00:44:33,000 --> 00:44:36,200
Speaker 1: I that's a matter of perspective. There is a certain

833
00:44:36,920 --> 00:44:40,960
Speaker 1: self importance or self aggrandizing that occurs when people are

834
00:44:41,000 --> 00:44:47,239
Speaker 1: suffering from paranoid delusions. Right, But being paranoid about this

835
00:44:47,320 --> 00:44:50,680
Speaker 1: sort of stuff does not make you delusional. It means

836
00:44:50,719 --> 00:44:54,480
Speaker 1: that you have unfortunately turned over the rock and you've

837
00:44:54,520 --> 00:44:57,640
Speaker 1: seen the thing squirming in the darkness beneath. This is

838
00:44:57,840 --> 00:44:58,800
Speaker 1: very real stuff.

839
00:44:59,400 --> 00:45:02,359
Speaker 2: I love that, and I also am terrified by it.

840
00:45:03,320 --> 00:45:06,799
Speaker 3: But you know, it's not all bad. I mean, there

841
00:45:06,840 --> 00:45:11,080
Speaker 3: are ways of kind of at least stemming some of

842
00:45:11,080 --> 00:45:13,920
Speaker 3: this stuff a little bit. Right, Yeah, So, how to

843
00:45:14,040 --> 00:45:16,080
Speaker 3: Geek actually has an easy to follow a guide on

844
00:45:16,120 --> 00:45:19,080
Speaker 3: how to stop Google Home from recording you all the time.

845
00:45:19,120 --> 00:45:21,719
Speaker 3: Google Home has a thing where it actually saves your

846
00:45:21,800 --> 00:45:24,200
Speaker 3: voice memos. You can check that out. You have to

847
00:45:24,239 --> 00:45:28,000
Speaker 3: opt in for constant recording allegedly, while you can if

848
00:45:28,040 --> 00:45:29,480
Speaker 3: you're an existing user opt out.

849
00:45:29,920 --> 00:45:32,600
Speaker 2: Yeah, that's the that's the whole thing. They've updated their

850
00:45:32,680 --> 00:45:36,760
Speaker 2: terms of service basically Google Home has right and actually

851
00:45:37,400 --> 00:45:39,799
Speaker 2: Amazon has done something similar there where you have more

852
00:45:39,880 --> 00:45:42,719
Speaker 2: choices now. But if you're an A I think, if

853
00:45:42,719 --> 00:45:45,480
Speaker 2: you're a legacy user, you actually can't get out of

854
00:45:45,480 --> 00:45:50,280
Speaker 2: some of the agreements you already signed into. Yeah, somebody

855
00:45:50,360 --> 00:45:52,360
Speaker 2: fact checked me on that, but I recall reading that

856
00:45:52,440 --> 00:45:56,160
Speaker 2: this morning. Here's the good thing. Remember Samba TV we

857
00:45:56,160 --> 00:45:59,000
Speaker 2: were talking about it felt so creepy. Literally, all you

858
00:45:59,080 --> 00:46:01,520
Speaker 2: have to do is say disable when you get to

859
00:46:01,560 --> 00:46:04,239
Speaker 2: that screen and you're installing your TV. That's all you

860
00:46:04,320 --> 00:46:05,600
Speaker 2: have to do and you're done.

861
00:46:05,640 --> 00:46:07,440
Speaker 3: Do you really not think it has something like why

862
00:46:07,480 --> 00:46:09,239
Speaker 3: do you think people are so prone? Ninety percent? Is

863
00:46:09,280 --> 00:46:11,920
Speaker 3: such a massive like amount? Like, are so prone to

864
00:46:12,040 --> 00:46:13,160
Speaker 3: click enable.

865
00:46:12,920 --> 00:46:16,320
Speaker 1: Because you've got a new toy and you want to

866
00:46:16,360 --> 00:46:19,839
Speaker 1: take full advantage because it's presented, like I said, as

867
00:46:19,880 --> 00:46:23,319
Speaker 1: this lovely way of like making this a better experience

868
00:46:23,400 --> 00:46:24,200
Speaker 1: for you the user.

869
00:46:24,520 --> 00:46:25,600
Speaker 3: Why wouldn't I want that?

870
00:46:25,719 --> 00:46:25,879
Speaker 1: Well?

871
00:46:25,920 --> 00:46:28,200
Speaker 2: And it's a menu that you have to click through, right,

872
00:46:28,280 --> 00:46:31,240
Speaker 2: So think about it this way. If it's on enable,

873
00:46:31,360 --> 00:46:33,680
Speaker 2: so you your cursor is on enable. When the screen

874
00:46:33,760 --> 00:46:36,720
Speaker 2: pops up, you'd have to go down to terms of service,

875
00:46:36,800 --> 00:46:39,839
Speaker 2: down to privacy policy, down to learn more, down one

876
00:46:39,880 --> 00:46:44,120
Speaker 2: more to disable the clicks. The as stupid as that sounds,

877
00:46:44,680 --> 00:46:48,520
Speaker 2: and you know, benign as five clicks or four clicks,

878
00:46:49,200 --> 00:46:53,000
Speaker 2: people will take the easier route and just say, okay, fine.

879
00:46:52,840 --> 00:46:55,520
Speaker 1: Enable, I'm in a hurry. I can't do I got

880
00:46:55,640 --> 00:46:57,399
Speaker 1: MF places to be, you know what I mean.

881
00:46:57,640 --> 00:46:58,240
Speaker 2: It's true.

882
00:46:58,480 --> 00:47:02,440
Speaker 1: So it's it is true, and it's an exploit not

883
00:47:02,520 --> 00:47:07,120
Speaker 1: just of technology, but an exploit of our own hardwired physiology.

884
00:47:07,760 --> 00:47:12,239
Speaker 1: Our brains are built to function this way, right, and

885
00:47:12,600 --> 00:47:16,839
Speaker 1: this leads us to some conclusions in what is very

886
00:47:16,920 --> 00:47:20,600
Speaker 1: much an ongoing events right. The first conclusion is that

887
00:47:20,920 --> 00:47:23,960
Speaker 1: there are some issues remaining. There's a lack of accountability.

888
00:47:24,280 --> 00:47:28,000
Speaker 1: One of the primary issues in this conversation is the

889
00:47:28,200 --> 00:47:31,640
Speaker 1: utter lack of accountability on the part of private institutions

890
00:47:31,880 --> 00:47:36,040
Speaker 1: as well as government agencies. It is not difficult to

891
00:47:36,120 --> 00:47:42,719
Speaker 1: imagine these companies cooperating with intelligence agencies, further exacerbating the

892
00:47:42,760 --> 00:47:46,960
Speaker 1: legal pitfalls involved. And again it's important to point out

893
00:47:47,400 --> 00:47:49,640
Speaker 1: just as a cheap skate. It's important to point out

894
00:47:49,960 --> 00:47:53,680
Speaker 1: that the people getting their data gathered are not paid

895
00:47:53,680 --> 00:47:56,520
Speaker 1: for that information, quite the opposite it used to be.

896
00:47:56,920 --> 00:47:58,960
Speaker 1: You know, what's that old adage. We always said, if

897
00:47:58,960 --> 00:48:01,360
Speaker 1: you're not paying for it, you are not the customer,

898
00:48:01,480 --> 00:48:06,160
Speaker 1: you're the product. Yes, right, But now the pendulum swings

899
00:48:06,360 --> 00:48:09,200
Speaker 1: a little bit further in the wrong direction in my opinion,

900
00:48:09,360 --> 00:48:13,840
Speaker 1: because we are paying for these services. We are paying Amazon,

901
00:48:13,920 --> 00:48:18,080
Speaker 1: we're paying Google to spy on us to whatever end,

902
00:48:18,120 --> 00:48:20,839
Speaker 1: and we are we are not accounting not only for this,

903
00:48:21,000 --> 00:48:24,520
Speaker 1: we're not accounting for the larger problem, which is that

904
00:48:24,840 --> 00:48:31,200
Speaker 1: insurance companies aggregate this information, your financial institutions aggregate this information,

905
00:48:31,719 --> 00:48:35,920
Speaker 1: and there is nothing that stops them from cooperating together

906
00:48:36,120 --> 00:48:40,680
Speaker 1: to build a footprint of you close enough. The idea

907
00:48:40,880 --> 00:48:45,279
Speaker 1: is that this footprint, this digital impression of you, will

908
00:48:45,320 --> 00:48:48,920
Speaker 1: one day have the fidelity such that it can predict

909
00:48:49,040 --> 00:48:50,680
Speaker 1: future actions you will take.

910
00:48:50,800 --> 00:48:53,720
Speaker 3: So you're saying that it could in theory be used

911
00:48:53,840 --> 00:48:55,520
Speaker 3: against you, Yes, very much.

912
00:48:55,600 --> 00:48:58,120
Speaker 2: So we're saying they're going to make Android versions of

913
00:48:58,160 --> 00:48:59,440
Speaker 2: you knowl' I'm cool with that.

914
00:48:59,600 --> 00:49:00,480
Speaker 3: That's what some help.

915
00:49:00,600 --> 00:49:03,319
Speaker 2: Yeah, but it's not gonna be about you anymore. No, No,

916
00:49:03,560 --> 00:49:05,320
Speaker 2: it's gonna be Amazon.

917
00:49:04,880 --> 00:49:10,000
Speaker 1: And and and it's it's fascinating when you think about it,

918
00:49:10,080 --> 00:49:11,759
Speaker 1: because now I know.

919
00:49:11,719 --> 00:49:14,680
Speaker 3: You're not joking. It's it's it's like a shape of

920
00:49:14,719 --> 00:49:17,000
Speaker 3: me that is my data, you know, like it's out

921
00:49:17,040 --> 00:49:20,959
Speaker 3: there in the matrix. It's a null shaped data cluster.

922
00:49:20,840 --> 00:49:23,800
Speaker 1: Or a Matt shaped data cluster, a Seth shaped cluster,

923
00:49:25,000 --> 00:49:26,720
Speaker 1: Seth shaped cluster.

924
00:49:26,840 --> 00:49:27,680
Speaker 2: That sounds like a band.

925
00:49:27,880 --> 00:49:30,000
Speaker 1: Yes, it does like a tasty treat, it does. I

926
00:49:30,000 --> 00:49:32,440
Speaker 1: feel like it's maybe a it's maybe like a hostess thing.

927
00:49:33,040 --> 00:49:38,640
Speaker 1: So we are brilliant ideas for desserts to treat the side.

928
00:49:39,120 --> 00:49:43,000
Speaker 1: We are all in this together. We are looking at

929
00:49:43,040 --> 00:49:45,680
Speaker 1: the end of privacy as we recognize it. And that's

930
00:49:45,680 --> 00:49:48,160
Speaker 1: sort of tricky. That sounds more dramatic than it really is,

931
00:49:48,239 --> 00:49:50,880
Speaker 1: because the concept of privacy as we know and enjoy

932
00:49:50,920 --> 00:49:55,480
Speaker 1: it today is relatively recent. Yes, right, and everything we've

933
00:49:55,600 --> 00:49:59,040
Speaker 1: learned indicates that type of privacy we idealize may end

934
00:49:59,120 --> 00:50:03,880
Speaker 1: up becoming a short lived fat to future historians. We're entering.

935
00:50:04,200 --> 00:50:06,400
Speaker 1: You know, Matt, you and I talked about this a

936
00:50:06,440 --> 00:50:10,040
Speaker 1: long time ago. An inequality of privacy, Right, Privacy is

937
00:50:10,080 --> 00:50:14,960
Speaker 1: a new currency. Some of the world's most influential, powerful,

938
00:50:15,000 --> 00:50:19,240
Speaker 1: successful people still have this kind of privacy, right yeah.

939
00:50:19,680 --> 00:50:22,040
Speaker 2: A weird example is just think about how much it

940
00:50:22,120 --> 00:50:27,359
Speaker 2: costs to get a good tint on your windows. I'm

941
00:50:27,400 --> 00:50:30,960
Speaker 2: not kidding. I'm not kidding. If you see someone drive

942
00:50:31,040 --> 00:50:35,919
Speaker 2: by with perfectly tinted like the darkest windows you've ever seen,

943
00:50:36,200 --> 00:50:41,359
Speaker 2: that is expensive. Well, and that's literally privacy just in

944
00:50:41,400 --> 00:50:42,160
Speaker 2: your car anyway.

945
00:50:42,360 --> 00:50:47,879
Speaker 1: I'm sorry, I feel like something going on is your car, Okay.

946
00:50:47,080 --> 00:50:49,600
Speaker 2: No, no, I'm just saying that that amount of privacy

947
00:50:49,719 --> 00:50:53,759
Speaker 2: just to be on the road driving costs money, right yeah.

948
00:50:53,800 --> 00:50:56,680
Speaker 2: And if you think about really good shutters on a

949
00:50:56,719 --> 00:51:02,160
Speaker 2: home or something like that, in those little examples, it

950
00:51:03,000 --> 00:51:06,880
Speaker 2: takes quite a bit of means to protect yourself just

951
00:51:06,960 --> 00:51:09,719
Speaker 2: from someone viewing with their eyeballs where you are at

952
00:51:09,719 --> 00:51:12,440
Speaker 2: any time. And then if you apply that to the

953
00:51:12,520 --> 00:51:15,759
Speaker 2: digital space, it gets more and more expensive.

954
00:51:15,880 --> 00:51:19,880
Speaker 1: It's creating something very similar in nuts and bolts and

955
00:51:19,920 --> 00:51:23,640
Speaker 1: the mechanics of it to the infamous sesame credit that's

956
00:51:23,640 --> 00:51:26,640
Speaker 1: occurring in the Chinese mainlanes precisely. And I'm not being

957
00:51:26,680 --> 00:51:29,080
Speaker 1: alarmist about this, and I don't you know, I don't

958
00:51:29,080 --> 00:51:33,080
Speaker 1: want people to be any more frightened. That is absolutely appropriate.

959
00:51:33,360 --> 00:51:37,200
Speaker 1: You should be a little We're at the Pandora problem right.

960
00:51:37,400 --> 00:51:41,239
Speaker 1: Once the Pandora's jar is unscrewed, once the lid is off,

961
00:51:41,280 --> 00:51:44,239
Speaker 1: there is no going back. There were some rumblings in

962
00:51:44,280 --> 00:51:48,439
Speaker 1: Congress about investigating what is essentially a smart TV spir ring,

963
00:51:48,760 --> 00:51:51,719
Speaker 1: but the advantages of keeping the technology in play for

964
00:51:51,800 --> 00:51:55,799
Speaker 1: now seem to outweigh the problems of consent and the

965
00:51:55,840 --> 00:51:59,080
Speaker 1: fact that consent is not occurring, and the fact that yes,

966
00:51:59,440 --> 00:52:03,319
Speaker 1: this could and up with your with your information from

967
00:52:03,360 --> 00:52:06,480
Speaker 1: other places, such that it might affect your ability to

968
00:52:06,480 --> 00:52:09,360
Speaker 1: get a car loan, It might affect where you can live.

969
00:52:10,239 --> 00:52:12,360
Speaker 1: This can get very dirty, very quickly.

970
00:52:12,440 --> 00:52:17,239
Speaker 3: It's a slippery slope, and especially once I mean, what if,

971
00:52:17,239 --> 00:52:19,880
Speaker 3: like we can't opt out anymore, you know, if if

972
00:52:19,880 --> 00:52:23,600
Speaker 3: that goes away, Like are we really owed that right

973
00:52:23,680 --> 00:52:25,440
Speaker 3: to opt out? Like it's sort of like almost a

974
00:52:25,480 --> 00:52:28,200
Speaker 3: pr move to allow us to opt out, Like you

975
00:52:28,440 --> 00:52:30,640
Speaker 3: could very easily say, as the manufacture of a product,

976
00:52:30,719 --> 00:52:33,400
Speaker 3: say well, if you don't want us to have your data,

977
00:52:33,440 --> 00:52:36,160
Speaker 3: don't buy the products. Like it's sort of almost a courtesy.

978
00:52:36,200 --> 00:52:37,959
Speaker 3: If you think about it to allow people to opt

979
00:52:37,960 --> 00:52:38,319
Speaker 3: out of this.

980
00:52:38,520 --> 00:52:39,799
Speaker 1: Yeah, but what it could just.

981
00:52:39,719 --> 00:52:41,840
Speaker 3: Are you owed a fancy television?

982
00:52:41,960 --> 00:52:45,240
Speaker 1: But it's no, but are you owed? And are you owed?

983
00:52:45,600 --> 00:52:48,960
Speaker 1: Are you required to participate in some of these systems

984
00:52:48,960 --> 00:52:50,919
Speaker 1: insurance one is required to.

985
00:52:50,840 --> 00:52:52,960
Speaker 3: Do so absolutely, that's different, I think. But I guess

986
00:52:53,000 --> 00:52:55,120
Speaker 3: what I'm saying is, like with the television, all these

987
00:52:55,160 --> 00:52:59,040
Speaker 3: are gadgets that, like you could not necessarily call necessities.

988
00:52:59,480 --> 00:53:04,840
Speaker 2: Well, think about think about most people with a steady job,

989
00:53:05,600 --> 00:53:09,480
Speaker 2: think about email communication nowadays, or an app that's used

990
00:53:09,560 --> 00:53:13,880
Speaker 2: wherever you work or you know there. You have to

991
00:53:13,960 --> 00:53:17,080
Speaker 2: have some kind of connection like that. You really do,

992
00:53:17,560 --> 00:53:20,239
Speaker 2: and with most of these devices, you're going to run

993
00:53:20,239 --> 00:53:21,120
Speaker 2: into these issues.

994
00:53:22,000 --> 00:53:25,840
Speaker 1: Or add to that the compounding complicating factor that for

995
00:53:25,920 --> 00:53:29,840
Speaker 1: the for a huge proportion of people who have mobile phones,

996
00:53:30,040 --> 00:53:34,360
Speaker 1: it's their only way to access not just the Internet,

997
00:53:34,360 --> 00:53:38,200
Speaker 1: but it's their primary tool for any financial dealings like

998
00:53:38,239 --> 00:53:42,200
Speaker 1: people's lives hinge on this thing. Yes, so I see

999
00:53:42,280 --> 00:53:46,040
Speaker 1: both sides of that, But here's what I think we

1000
00:53:46,080 --> 00:53:48,000
Speaker 1: can end with. We can say it's not just the

1001
00:53:48,120 --> 00:53:52,560
Speaker 1: United States. Way back in twenty seventeen, when WikiLeaks released this,

1002
00:53:53,320 --> 00:53:56,719
Speaker 1: they showed that digital spine is going to continue to grow.

1003
00:53:56,719 --> 00:53:57,680
Speaker 1: It's not going to go away.

1004
00:53:57,880 --> 00:53:59,680
Speaker 2: We're talking about the Weeping Angel thing, right right.

1005
00:53:59,600 --> 00:54:02,480
Speaker 1: Weeping Angel and specific which again is just for Samsung

1006
00:54:02,560 --> 00:54:04,680
Speaker 1: TVs and it's relatively low tech. You have to put

1007
00:54:04,680 --> 00:54:08,480
Speaker 1: a USB stick in there, but now you don't. Now

1008
00:54:08,560 --> 00:54:11,840
Speaker 1: it's now it's a whole different thing. You know, anybody

1009
00:54:11,880 --> 00:54:14,960
Speaker 1: got sort of irritated when you bought a new cell

1010
00:54:15,000 --> 00:54:17,560
Speaker 1: phone and it had stuff pre installed that you can't move.

1011
00:54:17,840 --> 00:54:20,799
Speaker 1: Think about this times a thousand. That's what's happening. That's

1012
00:54:20,800 --> 00:54:24,120
Speaker 1: what's going to happen. And it's not just happening in

1013
00:54:24,120 --> 00:54:28,799
Speaker 1: the US. Other advanced nations China, Russia, Britain, Israel and

1014
00:54:28,840 --> 00:54:33,640
Speaker 1: so on are creating newer, more robust, powerful tools to

1015
00:54:33,760 --> 00:54:38,320
Speaker 1: do this, and any any nation that can gain access

1016
00:54:38,320 --> 00:54:41,359
Speaker 1: to this kind of spying technology is going to do so,

1017
00:54:41,680 --> 00:54:43,760
Speaker 1: and they can do it through a web of private industry.

1018
00:54:43,920 --> 00:54:46,879
Speaker 1: There are no laws. This is wild West, and it's

1019
00:54:47,040 --> 00:54:49,759
Speaker 1: very bad. It's very bad for the people who are

1020
00:54:49,760 --> 00:54:51,399
Speaker 1: not at the top of the food chain.

1021
00:54:52,320 --> 00:54:55,719
Speaker 2: And with that, we all threw away our devices. We

1022
00:54:55,920 --> 00:55:00,640
Speaker 2: got out our acoustic guitars or ukuleles and started Kumbaya.

1023
00:55:00,840 --> 00:55:04,720
Speaker 1: I started writing my version of roth Water Emerson's on Nature.

1024
00:55:04,800 --> 00:55:08,719
Speaker 2: Right, that's correct. I got our my Jimbei out and

1025
00:55:08,760 --> 00:55:10,000
Speaker 2: we just started playing.

1026
00:55:09,719 --> 00:55:14,080
Speaker 3: Finger symbols from the Yeah.

1027
00:55:13,120 --> 00:55:15,440
Speaker 2: And we just you know, commune with nature for the

1028
00:55:15,440 --> 00:55:19,480
Speaker 2: rest of our lives and watch the sunset dissipate over

1029
00:55:19,520 --> 00:55:20,000
Speaker 2: the horizon.

1030
00:55:20,040 --> 00:55:21,440
Speaker 3: Had an ashram in Quebec.

1031
00:55:22,440 --> 00:55:24,600
Speaker 2: Yeah, and then we all woke up and went back

1032
00:55:24,600 --> 00:55:24,959
Speaker 2: to work.

1033
00:55:25,040 --> 00:55:27,680
Speaker 3: Yeah, that's true. And hey, listen, I'm just being Devil's

1034
00:55:27,719 --> 00:55:29,880
Speaker 3: aavogaated about like are you owed a smart TV? And

1035
00:55:29,920 --> 00:55:32,839
Speaker 3: I agree it's a great question. Well with the phone though,

1036
00:55:32,880 --> 00:55:36,080
Speaker 3: You're right, the phone is for many an affordable entry

1037
00:55:36,080 --> 00:55:39,200
Speaker 3: point to the Internet because it doubles as a you know,

1038
00:55:39,320 --> 00:55:42,840
Speaker 3: a crucial communication device and a way to access the Internet,

1039
00:55:42,840 --> 00:55:45,279
Speaker 3: which we can all agree is a necessity for things

1040
00:55:45,320 --> 00:55:49,200
Speaker 3: like banking everything, you know, everything starts on the Internet,

1041
00:55:49,440 --> 00:55:54,400
Speaker 3: the Web, of course. But I would argue that for

1042
00:55:54,480 --> 00:55:56,600
Speaker 3: the things like, you know, an Alexa, do we do

1043
00:55:56,640 --> 00:56:00,439
Speaker 3: we need an Alexa? Maybe maybe for accessibility? Maybe maybe

1044
00:56:00,440 --> 00:56:03,320
Speaker 3: that's a thingy for like people with disabilities, and Alexa

1045
00:56:03,360 --> 00:56:08,000
Speaker 3: could be a very important addition to a home for others.

1046
00:56:08,040 --> 00:56:09,520
Speaker 3: I think it's more of a luxury and sort of

1047
00:56:09,520 --> 00:56:10,440
Speaker 3: like a neat little gadget.

1048
00:56:10,520 --> 00:56:12,840
Speaker 2: You know, you're absolutely right, and you all nobody needs

1049
00:56:12,960 --> 00:56:17,640
Speaker 2: a smart television monitor right, But very soon the only

1050
00:56:17,800 --> 00:56:22,360
Speaker 2: available televisions will be smart televisions, at least ones that

1051
00:56:22,400 --> 00:56:23,480
Speaker 2: are easily purchased.

1052
00:56:23,560 --> 00:56:25,160
Speaker 3: I think what I was getting at when Ben talked

1053
00:56:25,160 --> 00:56:27,440
Speaker 3: about the sesame credit and the slippery slope of all

1054
00:56:27,480 --> 00:56:30,399
Speaker 3: this is what if there does come a time where

1055
00:56:30,440 --> 00:56:33,480
Speaker 3: you can't opt out anymore. Just by buying the thing

1056
00:56:33,520 --> 00:56:35,880
Speaker 3: and installing it in your home, you're opting in. The

1057
00:56:35,920 --> 00:56:37,759
Speaker 3: Only way to opt out is to not buy it,

1058
00:56:38,160 --> 00:56:39,279
Speaker 3: or to buy something else.

1059
00:56:39,520 --> 00:56:42,840
Speaker 2: There you go, or live in the woods.

1060
00:56:42,920 --> 00:56:47,520
Speaker 1: And that's our classic episode for this evening. We can't

1061
00:56:47,520 --> 00:56:48,359
Speaker 1: wait to hear your thoughts.

1062
00:56:48,440 --> 00:56:49,759
Speaker 3: It's right let us know what you think. You can

1063
00:56:49,840 --> 00:56:52,359
Speaker 3: reach to the handle Conspiracy Stuff where we exist on

1064
00:56:52,400 --> 00:56:56,800
Speaker 3: Facebook x and YouTube on Instagram and TikTok or Conspiracy

1065
00:56:56,800 --> 00:56:57,319
Speaker 3: Stuff Show.

1066
00:56:57,360 --> 00:56:59,560
Speaker 2: If you want to call us dial one eight three

1067
00:56:59,719 --> 00:57:04,880
Speaker 2: three the STDWYTK that's our voicemail system. You've got three minutes.

1068
00:57:04,920 --> 00:57:07,120
Speaker 2: Give yourself a cool nickname and let us know if

1069
00:57:07,120 --> 00:57:09,200
Speaker 2: we can use your name and message on the air.

1070
00:57:09,560 --> 00:57:11,120
Speaker 2: If you got more to say than can fit in

1071
00:57:11,120 --> 00:57:13,919
Speaker 2: that voicemail, why not instead send us a good old

1072
00:57:13,960 --> 00:57:14,720
Speaker 2: fashioned email.

1073
00:57:14,960 --> 00:57:17,880
Speaker 1: We are the entities to read every single piece of

1074
00:57:17,880 --> 00:57:22,320
Speaker 1: correspondence we receive. Be aware, yet not afraid. Sometimes the

1075
00:57:22,400 --> 00:57:44,919
Speaker 1: void writes back conspiracy at iHeartRadio dot com.

1076
00:57:45,160 --> 00:57:47,200
Speaker 2: Stuff they don't want you to know. Is a production

1077
00:57:47,320 --> 00:57:51,840
Speaker 2: of iHeartRadio. For more podcasts from iHeartRadio, visit the iHeartRadio app,

1078
00:57:51,920 --> 00:57:55,120
Speaker 2: Apple Podcasts, or wherever you listen to your favorite shows.