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Speaker 1: From UFOs to psychic powers and government conspiracies. History is

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Speaker 1: riddled with unexplained events. You can turn back now or

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Speaker 1: learn the stuff they don't want you to know. A

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Speaker 1: production of I Heart Radios How Stuff Works. Welcome back

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Speaker 1: to the show. My name is Matt, my name they

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

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

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

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

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

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Speaker 1: you to know. I was thinking about this. How many people,

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Speaker 1: on average do you think are listening today's show on

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Speaker 1: a cell phone or maybe on a laptop with another

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Speaker 1: electronic device on in the background. I would say many,

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Speaker 1: if not most. I see. I'm thinking a lot of

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Speaker 1: people probably have their phone in their pocket or on

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Speaker 1: one of those cool little arm bands. Yeah yeah, Or

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

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Speaker 1: will run somewhere in the Yeah, there's so I should

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Speaker 1: chase those people. Is that what you're saying? Yeah, give them,

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Speaker 1: give them some steaks, you know what I mean. I

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Speaker 1: think that's what's missing for joggers. I feel like, you know,

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Speaker 1: I feel like jogging is just practice for you know,

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Speaker 1: running away from something. You know. I feel like these

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Speaker 1: people are very paranoid. One of my this might be

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Speaker 1: a hot take, but one of my very old and

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Speaker 1: dear friends years back, you guys know him, he told me.

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Speaker 1: He told me that one of the first signs of

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Speaker 1: gentrification in the neighborhood was people running when no one's

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Speaker 1: chasing them. Brilliant. He's a weird guy, but I thought

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Speaker 1: it was a good point. So so. But the reason

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Speaker 1: we're even mentioning this like multiple devices going on in

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Speaker 1: the same audio spaces, because that's one of the main

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Speaker 1: things we're gonna be talking about today, our devices and

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Speaker 1: potential monitoring themselves. Right. Are you addicted to your phone,

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

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Speaker 1: like many of us, who can't really hold a conversation

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Speaker 1: without at least checking in on this thing. I'm guilty

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Speaker 1: of that, he's right now. Yeah, well, I'm kind of

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Speaker 1: waving it around. Do you find yourself tuning out, you know,

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Speaker 1: when when the conversation is taking its course, and then

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Speaker 1: finding yourself tuning into the closest device, whatever that is.

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Speaker 1: Like right exactly. So just for the lay of the land, here,

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Speaker 1: we have three laptops out open right now, we all

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

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Speaker 1: you know, a bevy of a V equipment that is

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Speaker 1: probably the most innocent of the contraptions here right in

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Speaker 1: this room. And if you are one of those people

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Speaker 1: who constantly finds yourself clicking in or dropping out of

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Speaker 1: conversation tuning into something else, you are not alone. Let's

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Speaker 1: reiterate that, because at first it sounds kind and nice, right,

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Speaker 1: it sounds 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. Smartphones, smart device

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Speaker 1: is smart everything. Really, it's everywhere, and uh, you're probably

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Speaker 1: working with one right now just because you need the

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Speaker 1: technology to listen to this today. Let's let's look at

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Speaker 1: the Pew Research organization there. They've done you know, they

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Speaker 1: do statistics like nobody else. It is estimated they say

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Speaker 1: that more than five billion people have mobile devices, and

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Speaker 1: over half of these connections are smart phones. So they're

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Speaker 1: doing more than just making a connection via satellite to

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Speaker 1: another phone somewhere or from you know, it's it's not

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Speaker 1: a landline anymore. It is. It's a phone, it's an encyclopedia.

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Speaker 1: It's absolutely everything you could possibly do it. It's like

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Speaker 1: Ziggy from Quantum Leap. Yes, no, literally have that in

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Speaker 1: our hands now. Doesn't quite predict the future, but it

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Speaker 1: comes damn close. Yeah. And this is that's a global

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Speaker 1: number throughout the world number. So more than half of

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Speaker 1: the people alive today have one of these things. It's

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Speaker 1: I'm holding up the phone again like a prop. It's

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

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

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Speaker 1: Now five billion people have these. So get this. In

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Speaker 1: the U s specifically, we've got nine and ten or

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Speaker 1: more Americans aged thirty four and under who have had

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Speaker 1: a smartphone since twenty fifteen UM, while the ownership rate

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Speaker 1: among the fifty and older age group has risen sixty

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Speaker 1: seven percent over the same period. One of my dearest

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Speaker 1: oldest friends, who is in his um early fifties, very

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Speaker 1: purposefully still has a dumb phone. Oh, Harry, Harry, Yeah,

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Speaker 1: very much on purpose. He just like he is old

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Speaker 1: school in that way where he rejects a lot of

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Speaker 1: this like over connectedness, and consequently he's a much more

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Speaker 1: thoughtful person than a lot of people that I know. Well,

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Speaker 1: after this episode, most of us are gonna want to

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Speaker 1: switch back. I know, I know Verizon where I am

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Speaker 1: offers a flip phone option, so no kids never break two. Well,

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Speaker 1: there you go. It seems more and more like a

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Speaker 1: good option. We'll get into it though, because it doesn't

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Speaker 1: just stop with smart phones. We also are talking about

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Speaker 1: smart TVs. And yes, Matt, you're absolutely right. This may

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Speaker 1: well ruin some some people's day, but this is important

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Speaker 1: to know. So we checked out Statistic when we wanted

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Speaker 1: to find some more stats and specs on smart TVs.

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Speaker 1: The global TV set unit sales are projected to increase

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Speaker 1: from two nine million units in six to two nine

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

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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: more frequently. I mean, I have a smart TV that

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Speaker 1: is made by Amazon. I'm sure it's made by some

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Speaker 1: third party manufacturer from overseas. To do you know why though,

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Speaker 1: you guys, Because it was dirt cheap, and it's it

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Speaker 1: works great, and I like the interconnectedness of it. But

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Speaker 1: we'll get into some of the features that this uh,

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Speaker 1: well you call it a feature is really more like

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Speaker 1: a bug literally feature, but just not for you. Feature.

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Speaker 1: Bug is in the eye of the behold. That's actually right,

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Speaker 1: and in this case, the eye of the beholder is

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Speaker 1: big data. Yeah. As of of the television is being

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Speaker 1: sold across the planet are smart TVs, and a smart

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

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

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

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

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

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

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Speaker 1: for instance, you can connect it with your phone. Not

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Speaker 1: to mention you can it's very customizable. You can combine

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Speaker 1: all of these different services into one kind of widget box,

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Speaker 1: let's call it. Where you have your Netflix, you got

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Speaker 1: your Hulu, you got your Amazon which obviously, my Amazon

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Speaker 1: TV leans pretty heavily on the global search on my

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Speaker 1: Amazon TV searches like all of Amazon, and it gives

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Speaker 1: you products. It gives you TV shows, it gives you

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Speaker 1: other stuff that's you know, in your set of apps

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Speaker 1: or subscriptions, but very much leaning towards the Amazon side

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Speaker 1: of things. Yeah, the most important thing about a smart TV,

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Speaker 1: when we call it that, is that it's able to

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Speaker 1: communicate with your network or the network that it's attached to,

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Speaker 1: and could possibly see all of the other devices that

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Speaker 1: are attached to that network, could possibly sure this is

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Speaker 1: This is true though, so Android is probably the most

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Speaker 1: widely used operating system among smart TVs, but that by

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Speaker 1: no means should be taken to into that other oss

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Speaker 1: aren't in Their iPhones are in there as well. Apple

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Speaker 1: has a hand in this. And while smart device addiction

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Speaker 1: is real, especially when we talk about mobile devices, it's

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Speaker 1: I think we should brack at that as the subject

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Speaker 1: of its own episode in the future, assuming we don't

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Speaker 1: get black backed or disappeared. There's more to the story

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Speaker 1: behind the purposefully addictive technology here. You see, while we

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Speaker 1: stare into that electronic abyss, even though we might not

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Speaker 1: know it, sometimes things in that abyss, in this sort

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Speaker 1: of black mirror, are staring back at you. And we'll

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Speaker 1: get into that right after a quick word 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, the hottest things since uh

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Speaker 1: fresh baked slice bread whatever. Yeah, they do all the

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Speaker 1: stuff we need, they do all the stuff we want

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Speaker 1: to write. But with smart devices comes the concept of surveillance.

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Speaker 1: And we've talked about this a little bit before it

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Speaker 1: our previous episodes on big data, big data whenever your

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Speaker 1: preference maybe oh yeah, and if you're worried about you know,

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Speaker 1: your smart devices tracking you or anything, and you still

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Speaker 1: have one of these Amazon echoes or maybe a Google

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Speaker 1: personal assistant like a home or something plugged in and

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Speaker 1: turned on, you can stop worrying. They've already got you.

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Speaker 1: It's over. It's just too late. Yeah, we're having a

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Speaker 1: little bit funny there. That's that's not fully true, you

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Speaker 1: think this man. But but there is some sand to

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Speaker 1: this idea, and we're gonna get into it a little

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Speaker 1: bit later. We're back when p d a s were

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Speaker 1: a thing personal digital assistance, And now we have robot

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Speaker 1: overlords that are like doing our bidding? But are they

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Speaker 1: really are we not really just doing their bidding? Oh god? Right,

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Speaker 1: it's like the old oh Man there's so many weird

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Speaker 1: ways to go with this, but we should talk about

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

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

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Speaker 1: have GPS, you have the ways app or something you're driving,

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Speaker 1: you have lift, you have Uber, what have you? You know,

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Speaker 1: all things that make the stuff function and make it

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Speaker 1: convenient for you. And then there are also a lot

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Speaker 1: of apps that say, hey, we want permission to access

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Speaker 1: your microphone or your location, and you're like, wow, Candy Crush,

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Speaker 1: this is getting serious. You know I'm picking that as

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Speaker 1: an example that's not one. Okay, great, Well, at least

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Speaker 1: we have candy Crush to remain as a sacrosanct example

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Speaker 1: of good programming. But when our smart devices are keeping

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Speaker 1: track of us, the kind of surveillance that they have is,

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Speaker 1: as we can tell, uh, squarely aimed at tracking our preferences.

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Speaker 1: Let me figure out what you like, says your mobile device,

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Speaker 1: such that I can give you better offers make it

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Speaker 1: easier for you to say yes to things in the future.

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Speaker 1: And that's why if you were on our Facebook group,

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Speaker 1: here's where it gets crazy. You'll see you'll see all

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Speaker 1: the strange, insidious examples ranging from hilarious to disquieting about

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Speaker 1: how just how these algorithms can hone in. I think, no,

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Speaker 1: you posted a meme recently that was Facebook related. Yeah,

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Speaker 1: I did. It was one of these great Simpsons memes

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Speaker 1: where it was just an image of like Bart Simpson

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Speaker 1: in bed and Homer leaning in really creepily like eyeball

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Speaker 1: to eyeball, and it was I think Homer was labeled

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Speaker 1: as Facebook ads and Bart was labeled as things I

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Speaker 1: said out 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 1: It definitely started a conversation of people giving examples and

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Speaker 1: these things. And I've experienced it too. We have a

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Speaker 1: lot of advertisers that like vet stuff through us, and

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Speaker 1: sometimes I feel like I just say it or like

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Speaker 1: I'm talking to you guys about it, and I've never

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Speaker 1: even like read copy or seen an email or gone

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Speaker 1: to the site. Next thing, you know, Facebook serving me

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Speaker 1: up you know, tushy or whatever. Bad bad example. But

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Speaker 1: like you know, you know I'm talking about you've seen

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Speaker 1: to have them. Sure there's a reason for that. So

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Speaker 1: you know, we get into why, what are the motives

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Speaker 1: behind all of the surveillance. We kind of talked about

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Speaker 1: a little bit tracking our preferences and everything, but honestly, like,

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Speaker 1: what are you gonna do with all of that? If

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Speaker 1: you if you start to really think about and understand

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Speaker 1: what the economic model is behind all this stuff, you

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Speaker 1: realize that it's because we, you, me, each of us,

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Speaker 1: We are the batteries of the economic system products. It's

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Speaker 1: literally the matrix. We are living in the matrix. Everybody

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Speaker 1: we are inside our pods are pods consist of your

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Speaker 1: smartphone and your smart TV and all the things you

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Speaker 1: interact with your laptop. That that is us. We are

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Speaker 1: the byproducts of a lifestyle obsession, a fight clip, no,

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Speaker 1: and and and here's the thing too, we mentioned I

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Speaker 1: mentioned this off air. Um I got that Amazon TV

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Speaker 1: because it had a lot of features, It had really

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Speaker 1: high resolution, and it was dirt cheap, and TV prices

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Speaker 1: way down, and as we saw at the beginning of

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Speaker 1: the show, TV sales way up. And I think that

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Speaker 1: you can't ignore that there's an exchange going on there

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Speaker 1: with like we're giving up this part of ourselves in

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Speaker 1: exchange for cheaper and better, more efficient technology. Well, one

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

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Speaker 1: the income for the company is actually arriving from. Right,

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Speaker 1: We've mentioned before one of my favorite examples, and I

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Speaker 1: won't go into it now because long time listeners have

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

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

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Speaker 1: of selling you know, people baby toys and trousers to

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Speaker 1: people still say trousers, knickerbockers, whatever. They were making the

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Speaker 1: bulk of their income, a huge proportion of it from

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Speaker 1: selling their security system infrastructure to other companies, kind of

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

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Speaker 1: real estate. So it's okay to sell a television at

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Speaker 1: a phenomenal loss, right when you know you're going to

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

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Speaker 1: I think that's what's happening that the televisions. Would you agree?

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Speaker 1: I mean, it sure seems like that to me. So

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Speaker 1: you 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 or begin around it, you have something that really

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

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Speaker 1: your your teacher, your mother, your secret lover to quote

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Speaker 1: Homer Simpson, and this thing that can't wait to be

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Speaker 1: your best friend is called the advertising industry. It's had

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

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Speaker 1: a lot about you right now. Oh yeah, it knows

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Speaker 1: a great deal about you. But it wants to go deeper.

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Speaker 1: It wants to go a therapist style on you. He

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Speaker 1: wants to know what you love, what do you hate,

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Speaker 1: who do you trust? And also how much liquid cash

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Speaker 1: can you get your hands on in the short term. Okay, again,

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Speaker 1: we're joking a little bit, but you get the point. Uh,

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Speaker 1: for real, They want to know how much you can

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Speaker 1: spend and what you would want to spend it on

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Speaker 1: if you absolutely could right now, If somebody just popped

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Speaker 1: something in front of your face right now, what is

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Speaker 1: the number one thing you would buy? Because we'll find

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Speaker 1: it and we will show it to you and you

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Speaker 1: will buy it. Yeah, and companies just bobble up all

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Speaker 1: of this data because, um, the the level of technology

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Speaker 1: that we're at right now isn't quite as sophisticated as

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Speaker 1: they would like. We're getting there, they're certainly pushing it

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Speaker 1: every day, but right now it's just kind of like

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Speaker 1: a throwing everything at the wall and seeing what sticks approach,

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Speaker 1: you know, artificial intelligence, It turns out in this regard

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Speaker 1: at least is not that intelligent and it needs a

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Speaker 1: ton of help. So it's efficient as all hell, but

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Speaker 1: but it is not. It cannot make the connections a

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Speaker 1: lot of times unless it is helped out by a

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Speaker 1: human user. It's still a black box. Though great example works.

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Speaker 1: 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. You know.

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

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Speaker 1: are you gonna just bought a toilet? You'll see an

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Speaker 1: ad for it and then you'll go though, I don't know,

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

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Speaker 1: you're a contractor. Maybe it thinks we're all contractors and

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Speaker 1: we're all building out fair points. Yeah, and we know

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Speaker 1: that we know that companies have a lot they want

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Speaker 1: to do with this data, even if they can't entirely

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Speaker 1: get the rubber to meet the road in practice. And

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Speaker 1: we'll we'll expand that picture in a frightening way a

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Speaker 1: little bit later, but for now, let's think of it

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Speaker 1: this way. Companies give all the data they can get

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Speaker 1: their hands on, even the stuff you would think is unimportant.

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Speaker 1: They give all of that equal waiting when it comes

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Speaker 1: to picking it up. There's nothing that gets ignored if

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Speaker 1: it's able to be monitored and captured. And that's because

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Speaker 1: AI programs, as we said, just aren't that intelligent yet.

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Speaker 1: They are efficient, map, but they're not that intelligent. Like

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Speaker 1: think about home surveillance systems. You have a you know,

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Speaker 1: uh no, you and I probably have Amazon echos. Yeah,

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Speaker 1: and you have a Google Home or something like that. Okay,

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Speaker 1: So these home surveillance systems, which is the correct term

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Speaker 1: for them, these home surveillance systems have these uh these assistance,

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Speaker 1: these programs that will guess at what they think you said,

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Speaker 1: but they still frequently missed the mark, you know what

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Speaker 1: I mean. But they also aren't listening. And I think

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Speaker 1: in theory until unless you say that wake word, right,

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Speaker 1: whatever that might be. They are always listening. Oh, hey,

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Speaker 1: the because they have to hear the wake word. I

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

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Speaker 1: of those in their house, right, Alexa play, Alexa play,

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Speaker 1: don't please? Don't the remix are the origin. We're kidding,

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Speaker 1: We're kidding, Hope. We're all still friends with our with

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Speaker 1: our various devices. But but we say this to point

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Speaker 1: out that these things are far from perfect, and there

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Speaker 1: are a lot of people employed by these companies human listeners, right,

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Speaker 1: just like many of us listening today, who are tasked

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Speaker 1: with going through these things and seeing listening to the

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Speaker 1: recording that someone said, and then seeing what the assistant

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Speaker 1: thought they said, and then reconciling the too to build

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Speaker 1: a better mouse trap for your personal information. Yes, and

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Speaker 1: that is where we get into, uh, the Amazon echo

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Speaker 1: story out of Bloomberg that we were going to talk about,

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Speaker 1: and that is the fact that there are thousands of

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Speaker 1: Amazon employees and contractors who, like Ben said, are tasked

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Speaker 1: with listen, literally listening to what the microphone recorded in

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Speaker 1: your living room. So if so, you're asking Noel about

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Speaker 1: is is it always listening? Yes? The microphone has always

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Speaker 1: turned on. As long as you've got your Alexa plugged

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Speaker 1: in or your Google Home plugged in, that mike is

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Speaker 1: on and it is listening. It doesn't record anything until

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Speaker 1: you say alexa or compute or echo or whatever. The

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Speaker 1: key right is the wake word. But which is a

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Speaker 1: creepy phrase in and of itself if you ask me.

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Speaker 1: But that is literally an open mic sitting in your

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Speaker 1: house and uh that that is where it gets really creepy.

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Speaker 1: But it also gets really creepy. Like, Okay, on the surface,

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Speaker 1: it makes complete sense. It's what Ben was saying. It's

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Speaker 1: quality assurance, right, it's trying to make that AI better.

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Speaker 1: It's an educational thing for the system. But below the surface,

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Speaker 1: like if you really break it down and you take

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Speaker 1: away some of the words that are in there that

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Speaker 1: make it feel like a fun and exciting new thing,

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Speaker 1: there is this mike in your room. It's recording information

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Speaker 1: things that you're saying in your private home, and it's

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Speaker 1: sending it to some person that you've never met, and

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Speaker 1: then this stranger is going to transcribe exactly what you

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Speaker 1: said in your living room. Then it's going to feed

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Speaker 1: it back in that system. So that when that mike

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Speaker 1: here's you talk again. It knows exactly what you said.

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Speaker 1: But again it's only after you've said the wake word.

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Speaker 1: It's it's it's not They're not transcribing your conversations in

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Speaker 1: your living room. It's all in theory stuff that you

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Speaker 1: were attempting to communicate to the device. Otherwise it wouldn't

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Speaker 1: be any use to them, It wouldn't help them improve

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Speaker 1: the algorithm at all. But my point here is that

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Speaker 1: that is how it functions, according to the way the

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Speaker 1: creators wanted to function, right, made this device and the

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Speaker 1: f a Q. Yes, that is the forward facing thing.

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Speaker 1: And I'm not saying Amazon is doing anything illegal or

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Speaker 1: you know, scary like that, but there is there is

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Speaker 1: an easy route there to exploit that microphone that's in

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Speaker 1: your living room. That's all I'm saying. So she's saying,

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Speaker 1: maybe if someone a bad actor, let's say, got ahold

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Speaker 1: of this, or do you think Amazon could potentially be

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Speaker 1: the bad actor Amazon's partners, Let's let's say, let's foreshadow

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Speaker 1: it that way. Amazon's Amazon's buddies, the folks in bed

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Speaker 1: with it. But that what's interesting to me about this

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Speaker 1: is that you are talking in terms of and above

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Speaker 1: the surface level. Yes, my spider sense tells me you've

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Speaker 1: got to the surface. Take. No, well, the surface take

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Speaker 1: is just in my mind, the reality of the situation

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Speaker 1: of We've talked about it before on here. We kind

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Speaker 1: of hit it a couple of times in this episode already,

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Speaker 1: just that we are literally bugging ourselves. And you know,

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Speaker 1: and you think when you think about a world in

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Speaker 1: which perhaps the powers that be end up ruling, Let's

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Speaker 1: just say this United States that we live in. Let's

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Speaker 1: say that some group comes along and takes over, and

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Speaker 1: now it is illegal in this land to do X.

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Speaker 1: And let's say your family or your living situation is X.

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Speaker 1: Now there is a microphone in your living room or

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Speaker 1: your kitchen or wherever it is, and if you're just

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Speaker 1: having a regular conversation about what your life is and

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Speaker 1: what you are doing, but it is illegal in this

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Speaker 1: land and there's a mic in there, there's potential that

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Speaker 1: there you could be abused in some way or persecuted.

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Speaker 1: That's all remind me of the telescreens in nine four,

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Speaker 1: which we're like, on this on one level seen as

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Speaker 1: like a luxury and it's like a really cool technological

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Speaker 1: gadget where you could watch all of these whatever entertainment

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Speaker 1: you so wished, But it was a two way thing.

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Speaker 1: It was monitoring you. But there's a certain acceptance of it,

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Speaker 1: you know, like it's not secret monitoring. Everyone knows they're

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Speaker 1: being monitored. They just know to stay in line and

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Speaker 1: not fall outside of the party, you know, doctrine or whatever.

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Speaker 1: Then we've kind of found ourselves in a very similar

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Speaker 1: situation where like complicit in our own surveillance or well,

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Speaker 1: was nothing if not prescient in that regard. There's a

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Speaker 1: there's here's a real life example or something that could

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Speaker 1: play out plausibly. And this is heavy stuff. So imagine

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Speaker 1: that you live in a country that is of least

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Speaker 1: economic developed country economically developed country, and that country has

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Speaker 1: an authoritarian government and they have strict religious laws of

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Speaker 1: one sort or another. Let's say that for a time

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Speaker 1: there was a different regime and you were maybe in

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Speaker 1: the sane sex relationship, and you and your partner lived

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Speaker 1: lived your normal everyday life. Right, you just happen to

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Speaker 1: have your device on because you like to hear music

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Speaker 1: when you cook. Who doesn't like that? But then the

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Speaker 1: regime changes and now uh, now again, uh, same sex

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Speaker 1: relationships are forbidden or haram or whatever. And now that's

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Speaker 1: stuff that you said that got hoovered up into the cloud.

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Speaker 1: Now it makes you complicit in what that government sees

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Speaker 1: as a crime. And that means that, according to that government, uh,

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Speaker 1: the stuff that you did, which was perfectly fine, your

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Speaker 1: relationship was perfectly fine until someone retroactively decided it wasn't.

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Speaker 1: And now because you wanted to hear uh the remix

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Speaker 1: to ignition, now just because of the you know, conversation

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Speaker 1: that occurred around that time, now you are in hot

427
00:23:51,440 --> 00:23:55,600
Speaker 1: water and there's not a recourse to help you. That's

428
00:23:55,600 --> 00:23:59,000
Speaker 1: a terrifying possibility. Matt. You were telling us off air

429
00:23:59,160 --> 00:24:04,560
Speaker 1: that at least some companies like Amazon attempt to well

430
00:24:04,760 --> 00:24:09,119
Speaker 1: those fears by publicly stating there are hard constraints on

431
00:24:09,240 --> 00:24:12,400
Speaker 1: how long an echo can record someth Oh. Yeah, absolutely,

432
00:24:12,440 --> 00:24:15,800
Speaker 1: And and again to am Amazon's defense, I am being

433
00:24:15,800 --> 00:24:19,920
Speaker 1: completely conspiratorial in this, um and I it's just one

434
00:24:19,920 --> 00:24:21,760
Speaker 1: of those weird foresight things that both men and I

435
00:24:21,800 --> 00:24:24,840
Speaker 1: were talking about there. Um. But Amazon has stated that

436
00:24:24,920 --> 00:24:28,480
Speaker 1: only a fraction of one percent of interactions with their

437
00:24:28,520 --> 00:24:32,800
Speaker 1: devices actually gets transcribed in this way by a human

438
00:24:32,920 --> 00:24:35,400
Speaker 1: by a human where it gets sent off, they transcribe

439
00:24:35,440 --> 00:24:38,520
Speaker 1: the center back in. Since the beginning of twenty and

440
00:24:38,560 --> 00:24:40,800
Speaker 1: this is by the way, from August of twenty nineteen

441
00:24:40,840 --> 00:24:45,720
Speaker 1: from the ambiance, so eight months of transcribing had had

442
00:24:45,800 --> 00:24:48,520
Speaker 1: gone through and only point two percent of all requests

443
00:24:48,520 --> 00:24:52,280
Speaker 1: to Alexa had actually been transcribed. So that's very a

444
00:24:52,400 --> 00:24:55,520
Speaker 1: very very small number of conversations that actually get listened

445
00:24:55,520 --> 00:24:59,000
Speaker 1: to and transcribed. Interesting how they put it in percentage though,

446
00:24:59,040 --> 00:25:02,480
Speaker 1: because putting it in percentage can make something something seems

447
00:25:02,520 --> 00:25:04,960
Speaker 1: smaller than it is in reality. Right, It was a

448
00:25:05,080 --> 00:25:09,920
Speaker 1: massive sample size, right, and so that small percentage um

449
00:25:10,200 --> 00:25:13,040
Speaker 1: is actually a massive number, right, Right, It just sounds

450
00:25:13,359 --> 00:25:16,440
Speaker 1: a little more reasonable. Right. Well, here's the great thing.

451
00:25:16,760 --> 00:25:23,879
Speaker 1: When you say, hey, whatever, spread it out enough. But

452
00:25:23,920 --> 00:25:26,399
Speaker 1: when you do that, generally you ask a very short

453
00:25:26,600 --> 00:25:29,520
Speaker 1: request or a very short question or something to that effect,

454
00:25:29,560 --> 00:25:31,199
Speaker 1: and then it does the thing and then like that

455
00:25:31,280 --> 00:25:34,720
Speaker 1: window of monitoring is over a kind of right generally, Yeah,

456
00:25:34,720 --> 00:25:37,680
Speaker 1: it lasted for about two seconds, that's the average. So

457
00:25:37,880 --> 00:25:41,240
Speaker 1: when somebody is transcribing, that's literally all all it says.

458
00:25:41,400 --> 00:25:43,600
Speaker 1: Can they make good money doing that? Or is it

459
00:25:43,640 --> 00:25:46,280
Speaker 1: like they do? It's Amazon, they're not getting paid very

460
00:25:46,280 --> 00:25:48,159
Speaker 1: well at all. Is it sort of like we as

461
00:25:48,160 --> 00:25:51,240
Speaker 1: a company, we um do a lot of transcribing interviews

462
00:25:51,240 --> 00:25:52,600
Speaker 1: and stuff. You think it's very similar to that. You

463
00:25:52,600 --> 00:25:56,000
Speaker 1: think that even outsources they couldn't it isnt some of

464
00:25:56,040 --> 00:26:00,160
Speaker 1: its contractors, some of his employees. And this practice has

465
00:26:00,280 --> 00:26:05,080
Speaker 1: no currently has no real legal constraints because, as we know,

466
00:26:05,200 --> 00:26:10,280
Speaker 1: technology always outpaces legislation tale as old as time. However,

467
00:26:10,960 --> 00:26:13,640
Speaker 1: I get the feeling that a lot of us were

468
00:26:13,720 --> 00:26:16,679
Speaker 1: sort of aware that something's off with these home assistance

469
00:26:16,840 --> 00:26:19,760
Speaker 1: or that there is some kind of transaction at play.

470
00:26:19,800 --> 00:26:21,919
Speaker 1: If it's not terrible, if it's something we're okay with,

471
00:26:22,200 --> 00:26:24,920
Speaker 1: we knew there was still something. And you can hear,

472
00:26:25,160 --> 00:26:27,400
Speaker 1: you know, when things go wrong and nine one one

473
00:26:27,480 --> 00:26:30,720
Speaker 1: calls and all these other spooky stories about things going

474
00:26:30,760 --> 00:26:36,560
Speaker 1: south with Google or Amazon. But what about the other devices.

475
00:26:36,600 --> 00:26:39,560
Speaker 1: We have some news for you about smart TVs. Look

476
00:26:39,600 --> 00:26:42,359
Speaker 1: around your room or wherever you happen to find yourself,

477
00:26:42,680 --> 00:26:44,800
Speaker 1: is there a TV in there? Things are about to

478
00:26:44,800 --> 00:26:53,000
Speaker 1: get very interesting for you. After a word from our sponsors,

479
00:26:53,040 --> 00:26:56,520
Speaker 1: all right, we're back. Let's jump in to something we

480
00:26:56,640 --> 00:26:59,280
Speaker 1: learned about thanks to new York Times in a two

481
00:26:59,280 --> 00:27:03,320
Speaker 1: thousand eight teen article about ailing New York Times that

482
00:27:03,680 --> 00:27:05,800
Speaker 1: they are not failing. I don't believe, I mean not

483
00:27:05,960 --> 00:27:09,240
Speaker 1: after this bump. I mentioned this article in the Game

484
00:27:09,280 --> 00:27:13,719
Speaker 1: Stalking episode. So you're welcome, New York. Yes you did. Um,

485
00:27:14,119 --> 00:27:16,399
Speaker 1: Then you Ben did bring this up, and we decided

486
00:27:16,440 --> 00:27:18,439
Speaker 1: we're going to look into it, and we did, and

487
00:27:18,520 --> 00:27:21,800
Speaker 1: now we can't look away forever. So it's a thing

488
00:27:21,840 --> 00:27:25,960
Speaker 1: called Samba TV. That sounds fun. Samba TV, it sounds

489
00:27:25,960 --> 00:27:27,840
Speaker 1: really funny. Any what else sounds fun? I'm gonna skip

490
00:27:27,840 --> 00:27:29,880
Speaker 1: down just just a tad um. How does this sound

491
00:27:29,920 --> 00:27:32,600
Speaker 1: to you? Guys? Hey? How about you want to interact

492
00:27:32,680 --> 00:27:35,960
Speaker 1: with your favorite shows, get recommendations based on the content

493
00:27:36,240 --> 00:27:41,400
Speaker 1: you love, connect your devices for exclusive content and special offers.

494
00:27:42,119 --> 00:27:45,360
Speaker 1: How about Samba Interactive TV. Let's you engage with your

495
00:27:45,400 --> 00:27:49,520
Speaker 1: TV in a whole new way. That sounds great, sounds

496
00:27:49,560 --> 00:27:53,439
Speaker 1: damn good? Into that? So, so what is Samba TV? Oh? Hey, man,

497
00:27:53,520 --> 00:27:57,879
Speaker 1: what's Samba TV? Okay, I'll tell you. Um. It is

498
00:27:57,920 --> 00:28:00,720
Speaker 1: a software, piece of software that is president in a

499
00:28:00,840 --> 00:28:04,080
Speaker 1: lot of television models, some models from nearly a dozen

500
00:28:04,160 --> 00:28:08,880
Speaker 1: smart TV brands. And again this is as of late eighteen,

501
00:28:09,080 --> 00:28:12,439
Speaker 1: that has changed. There are more included now, but it

502
00:28:12,560 --> 00:28:16,199
Speaker 1: is Sony Sharp Phillips a lot of that all the all.

503
00:28:17,160 --> 00:28:20,680
Speaker 1: In this software, in particular, it identifies what is being

504
00:28:20,800 --> 00:28:25,280
Speaker 1: watched on the monitor the television by literally analyzing the

505
00:28:25,280 --> 00:28:28,840
Speaker 1: pixels displayed and then comparing that data to a set

506
00:28:28,880 --> 00:28:31,359
Speaker 1: of known media that exists out there. It's a similar

507
00:28:31,359 --> 00:28:34,040
Speaker 1: way like audio things or even YouTube things are flagged

508
00:28:34,040 --> 00:28:37,359
Speaker 1: for copyright violations. Yes, but in this case it is

509
00:28:37,480 --> 00:28:41,120
Speaker 1: the end user, that is the the actual piece of

510
00:28:41,160 --> 00:28:44,400
Speaker 1: hardware that is being monitored. Right, And this was always

511
00:28:44,400 --> 00:28:49,440
Speaker 1: coming Nielsen ratings, like the Nielsen Institution wanted this. Yes,

512
00:28:50,080 --> 00:28:52,200
Speaker 1: there there needed to be a way to find out

513
00:28:52,280 --> 00:28:56,479
Speaker 1: who was watching what when. Um. And in particular, when

514
00:28:56,480 --> 00:28:59,760
Speaker 1: you're talking about who, it means everybody who is is

515
00:28:59,800 --> 00:29:04,480
Speaker 1: a round, not just that this household is watching something. Um.

516
00:29:04,480 --> 00:29:07,200
Speaker 1: But but here's the here's the idea. Your viewing history

517
00:29:07,560 --> 00:29:10,840
Speaker 1: is then, in part used to suggest, as Noel was saying,

518
00:29:10,920 --> 00:29:13,800
Speaker 1: as the flowery language there that's actually present in the

519
00:29:13,840 --> 00:29:16,400
Speaker 1: PR from Samba TV. Oh yeah they wrote that copy.

520
00:29:16,560 --> 00:29:19,280
Speaker 1: It's not only the PR, it's the opt in message. Yes. Yes,

521
00:29:19,400 --> 00:29:23,360
Speaker 1: it's used to suggest the next content that Samba TV

522
00:29:23,480 --> 00:29:27,320
Speaker 1: believes you will yourself enjoy. Um. But that is not

523
00:29:27,360 --> 00:29:31,000
Speaker 1: all that Samba TV does. It also identifies all the

524
00:29:31,080 --> 00:29:34,160
Speaker 1: other devices that are connected to the same network through

525
00:29:34,200 --> 00:29:38,720
Speaker 1: which it is accessing the internet. So your friend comes over,

526
00:29:38,800 --> 00:29:41,680
Speaker 1: they have a phone with WiFi. Now they're in the

527
00:29:41,680 --> 00:29:43,560
Speaker 1: there in the loop as well. Yes, if you are

528
00:29:43,680 --> 00:29:46,239
Speaker 1: Netflix and chilling or whatever the kids call it these

529
00:29:46,320 --> 00:29:50,160
Speaker 1: days at somebody else's house or apartment, uh, and Samba

530
00:29:50,200 --> 00:29:52,560
Speaker 1: TV is there. It knows that you're there because it

531
00:29:52,600 --> 00:29:54,840
Speaker 1: can identify your device and the MAC address and all

532
00:29:54,840 --> 00:29:57,560
Speaker 1: those things. And here's the thing that this company claims

533
00:29:57,760 --> 00:30:01,200
Speaker 1: that it is hearing very closely to privacy guidelines set

534
00:30:01,240 --> 00:30:04,160
Speaker 1: forth by the Federal Trade Commission, that it does not

535
00:30:04,400 --> 00:30:08,120
Speaker 1: directly sell any of this data. Instead, advertisers can pay

536
00:30:08,120 --> 00:30:11,400
Speaker 1: the company to kind of guide the hand of the

537
00:30:11,440 --> 00:30:14,880
Speaker 1: ads in the placement, which, which makes sense, doesn't sound

538
00:30:14,880 --> 00:30:19,000
Speaker 1: too insidious, right, Well, it's directing adds to the other

539
00:30:19,040 --> 00:30:23,120
Speaker 1: devices that are present who they believe are watching the

540
00:30:23,160 --> 00:30:26,880
Speaker 1: television program right right right, And so your opt in

541
00:30:27,000 --> 00:30:30,840
Speaker 1: stuff happens at the television right at the It doesn't

542
00:30:30,880 --> 00:30:34,120
Speaker 1: happen at your smartphone necessarily if you walk into someone

543
00:30:34,160 --> 00:30:37,600
Speaker 1: else's house. So how how do they get around the

544
00:30:37,720 --> 00:30:41,120
Speaker 1: legality of other people? Like? Are they automatically part of

545
00:30:41,160 --> 00:30:45,000
Speaker 1: your opt in when they jo? That's what I'm saying,

546
00:30:45,000 --> 00:30:48,040
Speaker 1: there's not informed consent. Really interesting, And also think about this,

547
00:30:48,040 --> 00:30:52,360
Speaker 1: This technology is amazing. If our species was less of

548
00:30:52,360 --> 00:30:55,560
Speaker 1: a garbage fire, we could use this to do wonderful

549
00:30:55,640 --> 00:30:58,760
Speaker 1: things for you know, say someone's mental health right, and

550
00:30:58,840 --> 00:31:01,640
Speaker 1: someone's like, Okay, I see you've watched Faces of Death

551
00:31:01,720 --> 00:31:04,480
Speaker 1: four nine times in a row. I'd like to recommend

552
00:31:04,560 --> 00:31:06,840
Speaker 1: the Great British Baking Show. Do you know what I mean?

553
00:31:07,800 --> 00:31:10,280
Speaker 1: To do a better job with your content consumption? No,

554
00:31:10,440 --> 00:31:14,080
Speaker 1: it's totally true. UM. And when you let's say you

555
00:31:14,080 --> 00:31:17,600
Speaker 1: plug in your new uh smart TV UM and it

556
00:31:17,680 --> 00:31:20,760
Speaker 1: has Samba on it, it will present you with that

557
00:31:20,960 --> 00:31:23,600
Speaker 1: very flowery language. That's the opt in message. There is

558
00:31:24,000 --> 00:31:28,240
Speaker 1: a giant terms of service and privacy policy you know

559
00:31:28,360 --> 00:31:31,280
Speaker 1: page that you can peruse if you wish. UM. I

560
00:31:31,320 --> 00:31:34,240
Speaker 1: believe it's six words for the terms of service and

561
00:31:34,320 --> 00:31:36,840
Speaker 1: four thousand words for the privacy policy. But why would

562
00:31:36,880 --> 00:31:39,240
Speaker 1: you even bother doing that when you can interact with

563
00:31:39,280 --> 00:31:42,880
Speaker 1: your favorite shows? Get recommendations based on the content that

564
00:31:42,960 --> 00:31:46,120
Speaker 1: you love. Term of service is a real page turner.

565
00:31:46,160 --> 00:31:48,920
Speaker 1: Oh yeah, but why would you want to do that

566
00:31:49,000 --> 00:31:51,760
Speaker 1: when this seems so innocuous and you just want to

567
00:31:51,800 --> 00:31:54,400
Speaker 1: start playing your Fallout four. Yeah, well to see that

568
00:31:54,520 --> 00:31:58,680
Speaker 1: that's not the real insidious thing here is that Let's

569
00:31:58,720 --> 00:32:01,600
Speaker 1: let's put yourself in the vision of you've spent let's

570
00:32:01,600 --> 00:32:03,920
Speaker 1: say the last couple of months saving up money because

571
00:32:03,960 --> 00:32:05,920
Speaker 1: you really, you know, you need to get this new TV.

572
00:32:06,040 --> 00:32:09,280
Speaker 1: You're really excited about it. Uh, you finally get it right,

573
00:32:09,680 --> 00:32:12,760
Speaker 1: and you're installing it your you know, your hands are

574
00:32:12,760 --> 00:32:14,920
Speaker 1: all sweaty because you know Fallout four, the next play

575
00:32:14,920 --> 00:32:16,640
Speaker 1: through is about to happen. You're like, oh my god,

576
00:32:16,680 --> 00:32:19,400
Speaker 1: this is I'm so excited. You plug this thing in,

577
00:32:19,640 --> 00:32:22,920
Speaker 1: you start going through the initialization process, the Samba thing

578
00:32:23,000 --> 00:32:26,320
Speaker 1: pops up, and uh, you know you can you literally

579
00:32:26,360 --> 00:32:28,360
Speaker 1: have to decide if you're going to spend an hour

580
00:32:28,840 --> 00:32:31,720
Speaker 1: parsing through all of that legal ease, or if you're

581
00:32:31,720 --> 00:32:33,800
Speaker 1: gonna get to whatever it is you're you wanted to

582
00:32:33,800 --> 00:32:38,880
Speaker 1: get to. And most people just click enable and move forward.

583
00:32:38,920 --> 00:32:41,160
Speaker 1: And it has nothing to do with the flowery language

584
00:32:41,240 --> 00:32:44,160
Speaker 1: or anything like that. It says enable, Okay, yes, this

585
00:32:44,200 --> 00:32:46,640
Speaker 1: gets me to the next thing. Just click enable, And

586
00:32:46,680 --> 00:32:50,080
Speaker 1: that is exactly what most people do. Right on the

587
00:32:50,240 --> 00:32:55,000
Speaker 1: order of an estimated the vast majority of people do

588
00:32:55,120 --> 00:32:58,880
Speaker 1: click enable. And once this stuff is up and running,

589
00:32:59,240 --> 00:33:01,360
Speaker 1: it's a k de bar the doors they used to

590
00:33:01,400 --> 00:33:05,239
Speaker 1: say in days of your Samba sees everything that is

591
00:33:05,280 --> 00:33:09,400
Speaker 1: displayed on the monitor, regardless of what you're watching or

592
00:33:09,440 --> 00:33:12,720
Speaker 1: playing or how you're displaying it. It doesn't matter if

593
00:33:12,760 --> 00:33:16,200
Speaker 1: you're watching TV. Uh, it doesn't matter if you're watching

594
00:33:16,240 --> 00:33:20,800
Speaker 1: a film. It doesn't matter if you're broadcasting a home video, right, yeah,

595
00:33:20,800 --> 00:33:22,800
Speaker 1: it could be. It could be literally anything. You know,

596
00:33:22,880 --> 00:33:25,479
Speaker 1: if you are broadcasting a home video of something that

597
00:33:25,560 --> 00:33:29,000
Speaker 1: you wouldn't want anyone else to see, Samba TV is

598
00:33:29,040 --> 00:33:32,480
Speaker 1: analyzing it. It isn't necessarily matching up with any known media,

599
00:33:32,880 --> 00:33:35,240
Speaker 1: but if you broadcast the same kind of home videos,

600
00:33:35,280 --> 00:33:38,480
Speaker 1: let's say, if your kids, maybe a romantic video you

601
00:33:38,560 --> 00:33:42,840
Speaker 1: made with your partner. Um, I mean, honestly, who knows.

602
00:33:43,200 --> 00:33:45,480
Speaker 1: That's again taking a little bit further than the known

603
00:33:45,520 --> 00:33:48,320
Speaker 1: technology or the known reasons for using it. But it

604
00:33:48,400 --> 00:33:53,000
Speaker 1: could be used in the future by someone to figure

605
00:33:53,040 --> 00:33:56,200
Speaker 1: out very personal, intimate things about you. But it's sort

606
00:33:56,240 --> 00:33:57,760
Speaker 1: of like when we read about the n s A

607
00:33:57,880 --> 00:33:59,800
Speaker 1: and the way the n s A was monitoring people's

608
00:33:59,800 --> 00:34:02,760
Speaker 1: phone calls. They weren't recording the actual audio. They were

609
00:34:02,800 --> 00:34:05,320
Speaker 1: just capturing the metadata so they knew how long a

610
00:34:05,360 --> 00:34:07,720
Speaker 1: call lasted or like you know who this web of

611
00:34:07,800 --> 00:34:10,440
Speaker 1: like can of interconnectedness or whatever, it's similar with this.

612
00:34:10,560 --> 00:34:15,000
Speaker 1: It's not like they're recording actually what you're streaming. They're

613
00:34:15,040 --> 00:34:17,879
Speaker 1: just capturing the data of what it is, how long

614
00:34:17,880 --> 00:34:20,760
Speaker 1: you watched it for, etcetera, of the pixels of the pixels.

615
00:34:21,360 --> 00:34:25,600
Speaker 1: So so this, okay, this, this is true. Even if

616
00:34:26,160 --> 00:34:30,520
Speaker 1: even if we want to be as skeptical or I

617
00:34:30,520 --> 00:34:34,080
Speaker 1: should say, as credulous as we can, and if we

618
00:34:34,200 --> 00:34:37,480
Speaker 1: take those pieces of stated pr copy at their word,

619
00:34:38,120 --> 00:34:43,840
Speaker 1: this still has a ton of hilarious, cartoonish vulnerabilities. You

620
00:34:43,880 --> 00:34:46,800
Speaker 1: can learn too much about people, and there's no way

621
00:34:46,880 --> 00:34:49,719
Speaker 1: for the end user to stop it other than try

622
00:34:49,760 --> 00:34:51,799
Speaker 1: to opt out. But opting out it doesn't delete all

623
00:34:51,800 --> 00:34:54,319
Speaker 1: the stuff that has already learned about you. Are we

624
00:34:54,440 --> 00:34:59,680
Speaker 1: being paranoid? Perhaps, or perhaps we should introduce you to Alfonso.

625
00:35:04,160 --> 00:35:07,520
Speaker 1: Oh God, I love that Alfonso Okay, so just to

626
00:35:07,560 --> 00:35:11,120
Speaker 1: break this down thus far, we've got our personal assistance

627
00:35:11,239 --> 00:35:16,160
Speaker 1: that always are on listening, no matter, no matter if

628
00:35:16,160 --> 00:35:18,680
Speaker 1: we're saying the keywords or not. They have their microphone

629
00:35:18,680 --> 00:35:21,759
Speaker 1: on and they're listening. They aren't necessarily recording all the time,

630
00:35:22,040 --> 00:35:24,319
Speaker 1: but they are. Now, you have your smartphone over there

631
00:35:24,640 --> 00:35:27,880
Speaker 1: that is literally watching what you're watching, too, and it

632
00:35:28,000 --> 00:35:31,560
Speaker 1: is making informed decisions about what you watch and sending

633
00:35:31,640 --> 00:35:35,120
Speaker 1: ads to all the devices in your house. Now, let's

634
00:35:35,120 --> 00:35:38,160
Speaker 1: say you're on one of those devices. Let's say it's

635
00:35:38,160 --> 00:35:40,920
Speaker 1: an Android device. Let's say you went to the Google

636
00:35:41,000 --> 00:35:45,279
Speaker 1: Play whatever it is app store thing and you've downloaded

637
00:35:45,280 --> 00:35:48,400
Speaker 1: some apps and some games. Well a lot of these

638
00:35:48,600 --> 00:35:50,920
Speaker 1: apps and games, not all of them, but a lot

639
00:35:51,000 --> 00:35:55,960
Speaker 1: of them have partnered with this this thing called Alfonso.

640
00:35:55,239 --> 00:36:05,040
Speaker 1: So this is uh, really interesting little little piece of

641
00:36:05,160 --> 00:36:08,080
Speaker 1: software that's attached to these apps, and what it will

642
00:36:08,120 --> 00:36:13,919
Speaker 1: do is prompt you to enable the use of your microphone. Right,

643
00:36:14,080 --> 00:36:17,680
Speaker 1: and these would be things that do not ostensibly need

644
00:36:17,760 --> 00:36:20,760
Speaker 1: that kind of access. Pool, three D, Beer Pong, trick Shot,

645
00:36:21,000 --> 00:36:23,799
Speaker 1: Real Bowling, Strike ten pen. You know these kind of

646
00:36:23,800 --> 00:36:28,120
Speaker 1: word sality names, little fun waste of time apps. Well,

647
00:36:28,120 --> 00:36:31,399
Speaker 1: and not just those some anti spying software. There's there's

648
00:36:31,440 --> 00:36:34,759
Speaker 1: a ton of apps out there right because it's it's

649
00:36:34,840 --> 00:36:40,120
Speaker 1: this Alfonso is app agnostic. So here's what happens. Here's

650
00:36:40,160 --> 00:36:44,760
Speaker 1: why they want that microphone access, because when you're using

651
00:36:44,760 --> 00:36:47,440
Speaker 1: this app, or when you grant this app microphone access,

652
00:36:47,480 --> 00:36:52,480
Speaker 1: Alfonso can figure out what you happen to watch by

653
00:36:52,520 --> 00:36:56,960
Speaker 1: identifying audio signals and television ads and shows and even

654
00:36:57,040 --> 00:36:59,920
Speaker 1: matching that information with the places people visit and the

655
00:37:00,080 --> 00:37:03,720
Speaker 1: movies they see really quickly. Here is how it works.

656
00:37:04,000 --> 00:37:07,839
Speaker 1: So you're we're all hanging out, we're watching some television

657
00:37:07,840 --> 00:37:11,880
Speaker 1: show that we're into. Let's go with Lost, something with commercials.

658
00:37:11,920 --> 00:37:15,800
Speaker 1: So when the show switches to commercial, there is a

659
00:37:15,840 --> 00:37:20,480
Speaker 1: pitch an audio signal that goes out to the room.

660
00:37:20,600 --> 00:37:23,439
Speaker 1: You cannot hear it, your pets cannot hear it, your

661
00:37:23,560 --> 00:37:26,360
Speaker 1: kids cannot hear it, no one can hear it, and

662
00:37:26,400 --> 00:37:29,400
Speaker 1: no one is supposed to hear it. It's only for

663
00:37:29,480 --> 00:37:32,719
Speaker 1: your phone. That's and that's what they do. They communicate

664
00:37:32,760 --> 00:37:36,839
Speaker 1: with your phone, and then the phone will also let

665
00:37:36,920 --> 00:37:45,000
Speaker 1: people know via Alfonso. The phone will let the the

666
00:37:45,120 --> 00:37:47,759
Speaker 1: users of the app, the real app, the users of

667
00:37:47,760 --> 00:37:53,240
Speaker 1: Alfonso understand who is in that room, where they came from,

668
00:37:53,239 --> 00:37:56,040
Speaker 1: maybe where they're going, and what they would like to buy.

669
00:37:56,440 --> 00:37:58,359
Speaker 1: That's not what you sign up for when you walk.

670
00:37:58,640 --> 00:38:00,120
Speaker 1: You know, you go to a pot luck at your

671
00:38:00,160 --> 00:38:03,239
Speaker 1: friend's house to watch some kind of film. Right, and

672
00:38:03,680 --> 00:38:06,280
Speaker 1: how many apps are we talking here? Okay, So according

673
00:38:06,280 --> 00:38:08,080
Speaker 1: to the New York Times, there were over two d

674
00:38:08,239 --> 00:38:12,960
Speaker 1: fifty apps on the Google Play Store with this feature, right, um,

675
00:38:13,040 --> 00:38:14,600
Speaker 1: And if you want, if you head over to the

676
00:38:14,600 --> 00:38:19,239
Speaker 1: Google Play Store and you type in quotations Alfonso Automated.

677
00:38:19,360 --> 00:38:22,000
Speaker 1: That's A L P H O N S O A

678
00:38:22,160 --> 00:38:24,640
Speaker 1: U T O M A T E D, and you

679
00:38:24,680 --> 00:38:26,840
Speaker 1: will find all of the various apps that have this

680
00:38:26,880 --> 00:38:29,120
Speaker 1: thing installed. But then if you if you look at

681
00:38:29,160 --> 00:38:33,319
Speaker 1: an interview with some Alfonso UM people, they said that

682
00:38:33,360 --> 00:38:36,719
Speaker 1: there are thousands of apps that they've partnered with and

683
00:38:36,760 --> 00:38:38,839
Speaker 1: they didn't want to disclose all of them because they

684
00:38:38,880 --> 00:38:43,279
Speaker 1: have competitors who are trying to basically get in on

685
00:38:43,320 --> 00:38:46,440
Speaker 1: their territory, ye, poach their territory. Remember when spyware was

686
00:38:46,480 --> 00:38:49,440
Speaker 1: a big concern. This is like some next level spyware

687
00:38:50,840 --> 00:38:53,279
Speaker 1: that's like different, Right, It's like it literally is opt

688
00:38:53,360 --> 00:38:56,839
Speaker 1: in right, it's spying on you. It's crazy, and now

689
00:38:56,880 --> 00:38:59,680
Speaker 1: we know it's cyclical. So it's all of the devices

690
00:39:00,120 --> 00:39:03,879
Speaker 1: functioning together in this web of trying to figure out

691
00:39:03,920 --> 00:39:06,520
Speaker 1: what you want the most and how to display that

692
00:39:06,560 --> 00:39:09,839
Speaker 1: thing to you the most effectively. I guess Shelton effect. Yeah.

693
00:39:10,239 --> 00:39:16,000
Speaker 1: This this also, this problem becomes complicated even further when

694
00:39:16,280 --> 00:39:20,560
Speaker 1: we realize that private entity institutions are not the only

695
00:39:20,640 --> 00:39:23,920
Speaker 1: actors in this sphere. Indeed, they may be some of

696
00:39:23,960 --> 00:39:28,000
Speaker 1: the more innocuous. I love that you mentioned spyware NOL,

697
00:39:28,080 --> 00:39:31,319
Speaker 1: because the best spyware right now is being built not

698
00:39:31,440 --> 00:39:37,640
Speaker 1: by private industry but by state actors. We mentioned Amazon's partners, right,

699
00:39:37,920 --> 00:39:42,280
Speaker 1: Amazon's partners using the data. Amazon's partners are alphabet soup

700
00:39:42,440 --> 00:39:49,080
Speaker 1: intelligence agencies or strongly thought to be so especial, especially

701
00:39:49,080 --> 00:39:53,280
Speaker 1: thanks to that early cash injection. Right, exactly so. According

702
00:39:53,320 --> 00:39:56,720
Speaker 1: to a Washington Post article from seventeen, the United States

703
00:39:56,800 --> 00:40:00,600
Speaker 1: government has already turned theoretical exploits and vulnerable abilities and

704
00:40:00,640 --> 00:40:04,600
Speaker 1: this kind of stuff into functioning attack tools. One of

705
00:40:04,640 --> 00:40:10,600
Speaker 1: these goes by the objectively badass name Weeping Angel. Weeping

706
00:40:10,640 --> 00:40:14,759
Speaker 1: Angel is specifically meant to target Samsung TVs. This is

707
00:40:14,800 --> 00:40:17,719
Speaker 1: just a small, micro cosmic example, and this is at

708
00:40:17,800 --> 00:40:20,560
Speaker 1: least what it was doing two years ago. According to

709
00:40:20,800 --> 00:40:25,560
Speaker 1: Wiki leaks after infestation, Weeping Angel places a target TV

710
00:40:25,760 --> 00:40:29,040
Speaker 1: in a fake off mode so that the owner believes

711
00:40:29,080 --> 00:40:32,000
Speaker 1: the TVs off when it's still on. And then in

712
00:40:32,080 --> 00:40:35,120
Speaker 1: this fake off mode, the TV operates as a bug,

713
00:40:35,360 --> 00:40:38,640
Speaker 1: recording conversations in the room and then sending them over

714
00:40:38,680 --> 00:40:41,600
Speaker 1: the cloud to a covert c I A server. This

715
00:40:41,640 --> 00:40:44,839
Speaker 1: sounds bonkers, This sounds bananas. I can't believe it's real.

716
00:40:45,200 --> 00:40:52,920
Speaker 1: Why would anybody ever be paranoid? Why would they? And

717
00:40:53,080 --> 00:40:55,560
Speaker 1: I I hope whomever is listening to this around a

718
00:40:55,600 --> 00:40:59,240
Speaker 1: smart television has unplugged their headphones and is listening on speaker.

719
00:41:00,840 --> 00:41:04,480
Speaker 1: You know, Okay, look everything, I just have to say this,

720
00:41:04,600 --> 00:41:07,759
Speaker 1: everything we've been discussing today. If you are of a

721
00:41:07,800 --> 00:41:12,680
Speaker 1: certain mind, perhaps like myself quite a lot, quite frequently, UM,

722
00:41:12,719 --> 00:41:16,520
Speaker 1: it could lead you down dark pathway where it feels

723
00:41:16,560 --> 00:41:20,960
Speaker 1: as though there's surveillance everywhere and you're being targeted in

724
00:41:21,000 --> 00:41:24,239
Speaker 1: some way. We can assure you this is not just

725
00:41:24,320 --> 00:41:27,759
Speaker 1: about you, no matter no matter what you may think,

726
00:41:27,880 --> 00:41:31,480
Speaker 1: or no matter what you may believe. Uh, it is

727
00:41:32,360 --> 00:41:35,319
Speaker 1: it's mass it's it's it's everybody. And again, it is

728
00:41:35,360 --> 00:41:41,239
Speaker 1: not necessarily nefarious. Um, but it's real. That's a matter

729
00:41:41,280 --> 00:41:45,560
Speaker 1: of perspective. There is a certain self importance or self

730
00:41:45,800 --> 00:41:51,359
Speaker 1: aggrandizing that occurs when people are suffering from paranoid delusions. Right,

731
00:41:51,920 --> 00:41:55,840
Speaker 1: But being paranoid about this sort of stuff does not

732
00:41:56,000 --> 00:41:59,960
Speaker 1: make you delusional. It means that you have unfortunately turned

733
00:42:00,000 --> 00:42:03,120
Speaker 1: turned over the rock and you've seen the thing squirming

734
00:42:03,160 --> 00:42:06,799
Speaker 1: in the darkness beneath. This is very real stuff. I

735
00:42:06,840 --> 00:42:10,719
Speaker 1: love that, and I also am terrified by it. But

736
00:42:11,560 --> 00:42:14,080
Speaker 1: you know this, it's not all bad. I mean, there

737
00:42:14,120 --> 00:42:18,359
Speaker 1: are ways of kind of at least stemming some of

738
00:42:18,400 --> 00:42:21,200
Speaker 1: this stuff a little bit. Right. Um So, how to

739
00:42:21,320 --> 00:42:23,359
Speaker 1: Geek actually has an easy to follow a guide on

740
00:42:23,360 --> 00:42:26,359
Speaker 1: how to stop Google Home from recording you all the time.

741
00:42:26,400 --> 00:42:29,000
Speaker 1: Google Home has a thing where it actually saves your

742
00:42:29,080 --> 00:42:31,279
Speaker 1: voice memos. You can check that out. Um, you have

743
00:42:31,360 --> 00:42:35,040
Speaker 1: to opt in for constant recording allegedly, while you can

744
00:42:35,200 --> 00:42:37,880
Speaker 1: if you're an existing user opt out. Yeah, that's the

745
00:42:38,320 --> 00:42:40,760
Speaker 1: that's the whole thing. They've updated their terms of service

746
00:42:41,120 --> 00:42:45,279
Speaker 1: basically Google Home as right, and actually, uh, Amazon has

747
00:42:45,320 --> 00:42:48,520
Speaker 1: done something similar there where you have more choices now. Um,

748
00:42:48,520 --> 00:42:51,120
Speaker 1: but if you're I think, if you're a legacy user,

749
00:42:51,360 --> 00:42:53,560
Speaker 1: you actually can't get out of some of the agreements

750
00:42:53,560 --> 00:42:58,200
Speaker 1: you already signed into. Yeah, somebody somebody fact checked me

751
00:42:58,239 --> 00:43:01,440
Speaker 1: on that, but I recall reading that this more. Um,

752
00:43:01,480 --> 00:43:03,719
Speaker 1: here's the good thing. Remember Samba TV we were talking

753
00:43:03,719 --> 00:43:06,640
Speaker 1: about that felt so creepy. Literally, all you have to

754
00:43:06,680 --> 00:43:09,320
Speaker 1: do is say disable when you get to that screen

755
00:43:09,400 --> 00:43:11,840
Speaker 1: and you're installing your TV. That's all you have to

756
00:43:11,880 --> 00:43:13,799
Speaker 1: do and you're done. Do you really not think it

757
00:43:13,800 --> 00:43:16,000
Speaker 1: has something like why do you think people are so prone?

758
00:43:16,440 --> 00:43:19,200
Speaker 1: It's such a massive amount, Like are so prone to

759
00:43:19,320 --> 00:43:22,839
Speaker 1: click enable because you've got a new toy and want

760
00:43:23,239 --> 00:43:26,160
Speaker 1: you want to take full advantage because it's presented, like

761
00:43:26,200 --> 00:43:29,520
Speaker 1: I said, as this lovely way of like making this

762
00:43:29,560 --> 00:43:32,440
Speaker 1: a better experience for you the user. Why wouldn't I

763
00:43:32,480 --> 00:43:34,680
Speaker 1: want that? Well, And it's a menu that you have

764
00:43:34,719 --> 00:43:36,880
Speaker 1: to click through, right, So think about it this way.

765
00:43:37,040 --> 00:43:40,400
Speaker 1: If it's on enable, so your your cursor is on enable,

766
00:43:40,440 --> 00:43:42,760
Speaker 1: when the screen pops up, you'd have to go down

767
00:43:43,000 --> 00:43:45,840
Speaker 1: to terms of service, down to privacy policy, down to

768
00:43:46,000 --> 00:43:49,040
Speaker 1: learn more, down one more to disable the clicks the

769
00:43:49,520 --> 00:43:54,200
Speaker 1: as stupid as that sounds, and you know, benign as

770
00:43:54,320 --> 00:43:58,280
Speaker 1: five clicks or four clicks, people will take the easier

771
00:43:58,360 --> 00:44:01,720
Speaker 1: route and just say, Okay, fine, enable, I'm in a hurry.

772
00:44:01,880 --> 00:44:03,840
Speaker 1: I can't do I got m F places to be,

773
00:44:04,000 --> 00:44:07,360
Speaker 1: you know what I mean. It's so, it's it is true,

774
00:44:07,480 --> 00:44:10,640
Speaker 1: and it's uh. It's an exploit not just of technology,

775
00:44:10,640 --> 00:44:15,200
Speaker 1: but an exploit of our own hardwired physiology. We're our

776
00:44:15,280 --> 00:44:20,160
Speaker 1: brains are built to function this way, right, and this

777
00:44:20,440 --> 00:44:24,120
Speaker 1: leads us to uh some conclusions and what is very

778
00:44:24,200 --> 00:44:27,920
Speaker 1: much an ongoing events. Right. The first conclusion is that

779
00:44:28,200 --> 00:44:31,719
Speaker 1: there's some issues remaining. There's a lack of accountability. One

780
00:44:31,760 --> 00:44:35,720
Speaker 1: of the primary issues in this conversation is the utter

781
00:44:36,000 --> 00:44:39,359
Speaker 1: lack of accountability on the part of private institutions as

782
00:44:39,360 --> 00:44:43,880
Speaker 1: well as government agencies. It is not difficult to imagine

783
00:44:43,880 --> 00:44:50,360
Speaker 1: these companies cooperating with intelligence agencies, further exacerbating the legal

784
00:44:50,400 --> 00:44:54,680
Speaker 1: pitfalls involved. And again it's important to point out just

785
00:44:54,840 --> 00:44:57,439
Speaker 1: as a cheap skate, it's important to point out that

786
00:44:57,520 --> 00:45:01,080
Speaker 1: the people getting their data gathered are not paid for

787
00:45:01,080 --> 00:45:04,400
Speaker 1: that information. Quite the opposite. It used to be. You know,

788
00:45:04,440 --> 00:45:06,560
Speaker 1: what's that old adage we always said, if you're not

789
00:45:06,600 --> 00:45:10,239
Speaker 1: paying for it. You're not the customer, you're the product. Right.

790
00:45:10,520 --> 00:45:14,680
Speaker 1: But now the pendulum swings a little bit further in

791
00:45:14,719 --> 00:45:17,000
Speaker 1: the in the wrong direction, in my opinion, because we

792
00:45:17,040 --> 00:45:21,399
Speaker 1: are paying for these services, we are paying Amazon, we're

793
00:45:21,440 --> 00:45:25,440
Speaker 1: paying Google to spy on us to whatever end, and

794
00:45:25,480 --> 00:45:28,120
Speaker 1: we are not we are not accounting not only for this,

795
00:45:28,239 --> 00:45:31,799
Speaker 1: we're not accounting for the larger problem, which is that

796
00:45:32,080 --> 00:45:38,560
Speaker 1: insurance companies aggregate this information, your financial institutions aggregate this information,

797
00:45:38,960 --> 00:45:43,239
Speaker 1: and there is nothing that stops them from cooperating together

798
00:45:43,400 --> 00:45:47,520
Speaker 1: to build a footprint of you close enough. The The

799
00:45:47,600 --> 00:45:51,560
Speaker 1: idea is that this, this footprint, this uh, this digital

800
00:45:51,560 --> 00:45:54,440
Speaker 1: impression of you will one day have the fidelities such

801
00:45:54,520 --> 00:45:58,200
Speaker 1: that it can predict future actions you will take. So

802
00:45:58,239 --> 00:46:02,359
Speaker 1: you're saying that it could, in theory be used against you, Yes,

803
00:46:02,480 --> 00:46:05,280
Speaker 1: very much. So we're saying they're gonna make Android versions

804
00:46:05,320 --> 00:46:08,080
Speaker 1: of you knowl I'm cool with that, that's what help. Yeah,

805
00:46:08,080 --> 00:46:09,800
Speaker 1: but it's not going to be about you anymore. No,

806
00:46:10,840 --> 00:46:14,879
Speaker 1: it's gonna be Amazon Android cloud clown of me. And

807
00:46:15,320 --> 00:46:17,680
Speaker 1: and it's it's fascinting when you think about it, because

808
00:46:18,719 --> 00:46:21,239
Speaker 1: I know you're not joking because it's it's it's like

809
00:46:21,280 --> 00:46:23,719
Speaker 1: a shape of me that is my data, you know,

810
00:46:23,800 --> 00:46:26,160
Speaker 1: like it's out there in the matrix. It's a knoll

811
00:46:26,239 --> 00:46:30,239
Speaker 1: shaped data cluster or a mat shaped data cluster, Seth

812
00:46:30,280 --> 00:46:35,360
Speaker 1: shaped cluster. Seth shaped cluster sounds like a band. It

813
00:46:35,440 --> 00:46:37,640
Speaker 1: does like a tasty treat. It does. I feel like

814
00:46:37,680 --> 00:46:40,520
Speaker 1: it's maybe a it's maybe like a hostess thing. So

815
00:46:41,040 --> 00:46:45,800
Speaker 1: we are brilliant ideas for desserts to treat the side.

816
00:46:46,400 --> 00:46:50,279
Speaker 1: We are all in this together. We are looking at

817
00:46:50,320 --> 00:46:52,960
Speaker 1: the end of privacy as we recognize it. And that's

818
00:46:52,960 --> 00:46:55,440
Speaker 1: sort of tricky. That sounds more dramatic than it really is,

819
00:46:55,520 --> 00:46:58,160
Speaker 1: because the concept of privacy is we know and enjoy

820
00:46:58,200 --> 00:47:02,759
Speaker 1: it today is relatively recent, yes, right, And everything we've

821
00:47:02,880 --> 00:47:06,319
Speaker 1: learned indicates that type of privacy we idealize may end

822
00:47:06,400 --> 00:47:11,120
Speaker 1: up becoming a short lived fat to future historians. We're entering.

823
00:47:11,480 --> 00:47:13,680
Speaker 1: You know that you and I talked about this a

824
00:47:13,719 --> 00:47:17,320
Speaker 1: long time ago, an inequality of privacy. Right, Privacy is

825
00:47:17,360 --> 00:47:22,240
Speaker 1: a new currency. Some of the world's most influential, powerful,

826
00:47:22,280 --> 00:47:27,080
Speaker 1: successful people still have this kind of privacy. Right. A

827
00:47:27,080 --> 00:47:29,760
Speaker 1: weird example is just think about how much it costs

828
00:47:29,760 --> 00:47:35,200
Speaker 1: to get a good tint on your windows. I'm not kidding.

829
00:47:35,800 --> 00:47:38,240
Speaker 1: I'm not kidding. If you if you see someone drive

830
00:47:38,320 --> 00:47:43,200
Speaker 1: by with perfectly tinted like the darkest windows you've ever seen,

831
00:47:43,480 --> 00:47:48,280
Speaker 1: that is expensive. M m well, and that's literally privacy

832
00:47:48,320 --> 00:47:50,600
Speaker 1: just in your car anyway. I'm sorry, I feel like

833
00:47:51,160 --> 00:47:54,879
Speaker 1: something going on is your car, Okay, No, no, I'm

834
00:47:54,920 --> 00:47:57,440
Speaker 1: just saying that that amount of privacy just to be

835
00:47:57,520 --> 00:48:02,000
Speaker 1: on the road driving money, I see. And if you

836
00:48:02,000 --> 00:48:05,000
Speaker 1: think about really good shutters on a home or something

837
00:48:05,040 --> 00:48:11,000
Speaker 1: like that, in those little examples, it takes quite a

838
00:48:11,040 --> 00:48:15,360
Speaker 1: bit of means to protect yourself just from someone viewing

839
00:48:15,360 --> 00:48:17,920
Speaker 1: with their eyeballs where you are at any time. And

840
00:48:17,960 --> 00:48:21,439
Speaker 1: then if you apply that to the digital space, uh,

841
00:48:21,480 --> 00:48:24,880
Speaker 1: it gets more and more expensive. It's it's creating something

842
00:48:25,000 --> 00:48:27,880
Speaker 1: very similar in nuts and bolts in the mechanics of

843
00:48:27,880 --> 00:48:31,480
Speaker 1: it to the infamous sesame credit that's occurring in the

844
00:48:31,560 --> 00:48:35,080
Speaker 1: Chinese mainland. And I'm not being alarmist about this, and

845
00:48:35,080 --> 00:48:37,279
Speaker 1: they don't, you know, I don't want people to be

846
00:48:37,640 --> 00:48:41,080
Speaker 1: any more frightened. That is absolutely appropriate. You should be

847
00:48:41,120 --> 00:48:44,960
Speaker 1: a little the we're at the Pandora problem right once

848
00:48:45,080 --> 00:48:48,719
Speaker 1: the Pandora's jars unscrewed. Once the lid is off, there

849
00:48:48,800 --> 00:48:52,040
Speaker 1: is no going back. There were some rumblings in Congress

850
00:48:52,040 --> 00:48:55,680
Speaker 1: about investigating what is essentially a smart TV spy ring,

851
00:48:56,040 --> 00:48:58,960
Speaker 1: but the advantages of keeping the technology and play for

852
00:48:59,080 --> 00:49:03,000
Speaker 1: now seemed to out way the problems of consent. Then,

853
00:49:03,000 --> 00:49:05,720
Speaker 1: the fact that consent is not occurring, and the fact

854
00:49:05,760 --> 00:49:09,799
Speaker 1: that yes, this could partner up with your with your

855
00:49:09,840 --> 00:49:13,200
Speaker 1: information from other places, such that it might affect your

856
00:49:13,200 --> 00:49:15,839
Speaker 1: ability to get a car loan, It might affect where

857
00:49:15,880 --> 00:49:19,680
Speaker 1: you can live. This can get very dirty, very quickly.

858
00:49:19,680 --> 00:49:24,080
Speaker 1: It's a slippery slope, and especially once I mean, what

859
00:49:24,160 --> 00:49:26,480
Speaker 1: what if, like we can't opt out anymore? You know,

860
00:49:26,680 --> 00:49:30,320
Speaker 1: if if that goes away, Like are we really owed

861
00:49:30,400 --> 00:49:32,160
Speaker 1: that right to opt out? Like it's sort of like

862
00:49:32,200 --> 00:49:34,919
Speaker 1: almost a pr move to allow us to opt out,

863
00:49:35,120 --> 00:49:37,440
Speaker 1: Like you you could very easily say, is the manufacturer

864
00:49:37,440 --> 00:49:39,759
Speaker 1: of a product say well, if you don't want us

865
00:49:39,800 --> 00:49:42,239
Speaker 1: to have your data, don't buy the products. Like it's

866
00:49:42,239 --> 00:49:44,120
Speaker 1: sort of almost a courtesy if you think about it,

867
00:49:44,160 --> 00:49:46,200
Speaker 1: to allow people to opt out of this. Yeah, but

868
00:49:46,239 --> 00:49:49,120
Speaker 1: what it could just are you owed a fancy television?

869
00:49:49,280 --> 00:49:53,040
Speaker 1: But but are you owed and are you owed are

870
00:49:53,080 --> 00:49:56,799
Speaker 1: you required to participate in some of these systems? Insurance

871
00:49:56,840 --> 00:49:59,879
Speaker 1: one is required to do so. Absolutely, that's different, I think.

872
00:49:59,880 --> 00:50:01,520
Speaker 1: But I guess what I'm saying is like with the

873
00:50:01,520 --> 00:50:04,040
Speaker 1: the television, all these are gadgets that, like you could

874
00:50:04,040 --> 00:50:09,560
Speaker 1: not necessarily call necessities. Well, think about think about most

875
00:50:09,719 --> 00:50:15,480
Speaker 1: people with a steady job, think about email communication nowadays,

876
00:50:15,600 --> 00:50:18,799
Speaker 1: or an app that's used wherever you work or you

877
00:50:18,840 --> 00:50:22,040
Speaker 1: know some there. You you have to have some kind

878
00:50:22,040 --> 00:50:25,879
Speaker 1: of connection like that, you really do, and with most

879
00:50:25,920 --> 00:50:28,360
Speaker 1: of these devices, you're going to run into these issues

880
00:50:29,239 --> 00:50:33,160
Speaker 1: or add to that the compounding complicating factor that for

881
00:50:33,239 --> 00:50:37,080
Speaker 1: the for a huge proportion of people who have mobile phones,

882
00:50:37,320 --> 00:50:41,600
Speaker 1: it's their only way to access uh, not just the Internet,

883
00:50:41,640 --> 00:50:45,440
Speaker 1: but it's their primary tool for any financial deals like

884
00:50:45,520 --> 00:50:49,400
Speaker 1: people's lives hinge on this thing. So I I see

885
00:50:49,520 --> 00:50:53,319
Speaker 1: both sides of that. But here's what I think we

886
00:50:53,360 --> 00:50:55,279
Speaker 1: can end with. We can say it's not just the

887
00:50:55,400 --> 00:50:59,200
Speaker 1: United States. Way back in two seventeen when Wiki Leaks

888
00:50:59,239 --> 00:51:03,000
Speaker 1: released this, UH, they showed that digital spine is going

889
00:51:03,040 --> 00:51:05,000
Speaker 1: to continue to grow. It's not going to go away.

890
00:51:05,120 --> 00:51:07,200
Speaker 1: We're talking about the Weeping Angel thing right right, weeping

891
00:51:07,239 --> 00:51:10,240
Speaker 1: Angel in specific, which again is just for Samsung TVs

892
00:51:10,320 --> 00:51:12,040
Speaker 1: and it's relatively low tech. You have to put a

893
00:51:12,120 --> 00:51:15,799
Speaker 1: USB uh stick in there. But now you don't. Now

894
00:51:15,840 --> 00:51:18,640
Speaker 1: it's now it's a whole different thing. Uh. You know,

895
00:51:18,680 --> 00:51:21,719
Speaker 1: anybody got uh sort of irritated when you bought a

896
00:51:21,760 --> 00:51:24,160
Speaker 1: new cell phone and it had stuff pre installed that

897
00:51:24,200 --> 00:51:27,239
Speaker 1: you can't move. Think about this times a thousand. That's

898
00:51:27,280 --> 00:51:30,759
Speaker 1: what's happening. That's what's going to happen. And it's not

899
00:51:30,840 --> 00:51:35,280
Speaker 1: just happening in the US. Other advanced nations China, Russia, Britain,

900
00:51:35,480 --> 00:51:40,360
Speaker 1: Israel and so on are creating newer, more robust, powerful

901
00:51:40,400 --> 00:51:44,759
Speaker 1: tools to do this, and any any nation that can

902
00:51:44,840 --> 00:51:48,000
Speaker 1: gain access to this kind of spine technology is going

903
00:51:48,080 --> 00:51:49,799
Speaker 1: to do so, and they can do it through a

904
00:51:49,840 --> 00:51:52,799
Speaker 1: web of private industry. There there are no laws. This

905
00:51:52,840 --> 00:51:56,040
Speaker 1: is wild West and it's very bad. It's very bad

906
00:51:56,080 --> 00:51:58,000
Speaker 1: for the people who are not at the top of

907
00:51:58,000 --> 00:52:01,719
Speaker 1: the food chain. And we that we all threw away

908
00:52:01,760 --> 00:52:06,520
Speaker 1: our devices. We got out our acoustic guitars or uku leles,

909
00:52:06,960 --> 00:52:10,279
Speaker 1: starting kumba. I started writing my version of Ralph water

910
00:52:10,400 --> 00:52:14,440
Speaker 1: Emerson's on Nature right, that's correct. I got our my

911
00:52:14,560 --> 00:52:20,040
Speaker 1: Jim bay out and we just started playing symbols for me. Yeah,

912
00:52:20,400 --> 00:52:22,680
Speaker 1: and we just you know, commune with nature for the

913
00:52:22,719 --> 00:52:26,759
Speaker 1: rest of our lives and watch the sunset dissipate over

914
00:52:26,800 --> 00:52:30,200
Speaker 1: the horizon. Had an ostrom in Quebec. Yeah, and then

915
00:52:30,239 --> 00:52:33,480
Speaker 1: we all woke up and went back to work. That's true.

916
00:52:33,600 --> 00:52:35,759
Speaker 1: And hey, listen, I'm just being Devil's advocating about like

917
00:52:35,760 --> 00:52:38,160
Speaker 1: are you oh to smart TV? And I agree it's

918
00:52:38,200 --> 00:52:40,600
Speaker 1: a great question with the with the phone though, You're right,

919
00:52:40,680 --> 00:52:43,759
Speaker 1: the phone is for many an affordable entry point to

920
00:52:43,760 --> 00:52:46,719
Speaker 1: the Internet because it doubles as a you know, a

921
00:52:46,719 --> 00:52:50,120
Speaker 1: crucial communication device and a way to access the Internet,

922
00:52:50,120 --> 00:52:52,560
Speaker 1: which we can all agree is a necessity for things

923
00:52:52,600 --> 00:52:57,319
Speaker 1: like banking everything, you know, everything starts on the Internet. Well,

924
00:52:57,680 --> 00:53:02,160
Speaker 1: of course, but I would argue that for the things

925
00:53:02,200 --> 00:53:04,319
Speaker 1: like you know, an Alexa, do we do we need

926
00:53:04,320 --> 00:53:08,160
Speaker 1: an Alexa? Maybe maybe for accessibility, Maybe maybe that's the thing.

927
00:53:08,320 --> 00:53:10,879
Speaker 1: Maybe maybe for like people with disabilities, an Alexa could

928
00:53:10,880 --> 00:53:15,280
Speaker 1: be a very important addition to a home. For others,

929
00:53:15,280 --> 00:53:16,799
Speaker 1: I think it's more of a luxury and sort of

930
00:53:16,800 --> 00:53:18,640
Speaker 1: like a neat little gadget. You know, you're absolutely right,

931
00:53:18,640 --> 00:53:22,480
Speaker 1: and you all nobody needs a smart television monitor right,

932
00:53:22,880 --> 00:53:28,319
Speaker 1: but very soon the only available televisions will be smart televisions,

933
00:53:28,360 --> 00:53:31,120
Speaker 1: at least ones that are easily purchased. I think what

934
00:53:31,160 --> 00:53:33,120
Speaker 1: I was getting at when Ben talked about the sesame

935
00:53:33,200 --> 00:53:36,120
Speaker 1: credit and the slippery slope of all this is what

936
00:53:36,239 --> 00:53:38,520
Speaker 1: if there does come a time where you can't opt

937
00:53:38,560 --> 00:53:41,360
Speaker 1: out anymore, and just by buying the thing and installing

938
00:53:41,400 --> 00:53:43,480
Speaker 1: it in your home, you're opting in. The Only way

939
00:53:43,520 --> 00:53:45,640
Speaker 1: to opt out is to not buy it, or to

940
00:53:45,719 --> 00:53:51,000
Speaker 1: buy something else there you go. Or And while we're

941
00:53:51,400 --> 00:53:54,239
Speaker 1: talking about needs and once, there is one thing that

942
00:53:54,360 --> 00:53:57,799
Speaker 1: we definitely want, and that is to hear from you.

943
00:53:57,920 --> 00:54:00,319
Speaker 1: Do you think this is alarmist? Are you are you

944
00:54:00,400 --> 00:54:02,799
Speaker 1: do find yourself more on the side of, well, if

945
00:54:02,800 --> 00:54:04,640
Speaker 1: you not do anything wrong, what do you worry about?

946
00:54:04,719 --> 00:54:07,080
Speaker 1: You know it's a big def right. Or are you

947
00:54:07,239 --> 00:54:09,400
Speaker 1: more on the side of where you think this is

948
00:54:09,440 --> 00:54:15,120
Speaker 1: an even more um potentially dangerous situation than what we've

949
00:54:15,160 --> 00:54:18,480
Speaker 1: outlined today. Let us know we would love to hear

950
00:54:18,520 --> 00:54:21,040
Speaker 1: from you. You can find us any number of ways.

951
00:54:21,160 --> 00:54:24,319
Speaker 1: We're all over the internet, not as not as like

952
00:54:24,440 --> 00:54:26,600
Speaker 1: widespread as the n s A. But you know, we're

953
00:54:26,600 --> 00:54:29,680
Speaker 1: out there. You can find us. We're on Facebook at

954
00:54:29,719 --> 00:54:31,200
Speaker 1: here's where it gets crazy, where you can talk to

955
00:54:31,200 --> 00:54:33,439
Speaker 1: our favorite part of the show. Your fellow listeners were

956
00:54:33,440 --> 00:54:37,640
Speaker 1: on Twitter. We're on Instagram, the whole the whole Kitten Caboodle,

957
00:54:37,680 --> 00:54:39,879
Speaker 1: the whole Bag of Badgers, the whole nine. And that's

958
00:54:39,920 --> 00:54:42,560
Speaker 1: not all. If you want to give us a phone call,

959
00:54:42,680 --> 00:54:45,239
Speaker 1: you can leave a message. Our number is one eight

960
00:54:45,400 --> 00:54:49,440
Speaker 1: three three st d w y t K. If you

961
00:54:49,440 --> 00:54:51,359
Speaker 1: do leave a message, let us know if you'd like

962
00:54:51,520 --> 00:54:53,319
Speaker 1: us to use your name on the air, if you

963
00:54:53,360 --> 00:54:55,440
Speaker 1: want to remain anonymous, if it's just for us, it's

964
00:54:55,520 --> 00:54:58,960
Speaker 1: for all the listeners. Just give us all that info upfront. Uh.

965
00:54:58,960 --> 00:55:01,160
Speaker 1: And if you don't want to do that, you can

966
00:55:01,200 --> 00:55:03,800
Speaker 1: send it doubt Oh yeah, you can't opt out. You

967
00:55:03,840 --> 00:55:05,879
Speaker 1: can opt out of this whole thing. Just turn off

968
00:55:05,960 --> 00:55:08,680
Speaker 1: your podcast player right now. But if you don't want

969
00:55:08,719 --> 00:55:10,200
Speaker 1: to do that and you want to send us an email,

970
00:55:10,440 --> 00:55:30,120
Speaker 1: you can. We are conspiracy at iHeartRadio dot com. Stuff

971
00:55:30,160 --> 00:55:31,799
Speaker 1: they Don't Want You to Know is a production of

972
00:55:31,800 --> 00:55:34,719
Speaker 1: iHeart Radio's How Stuff Works. For more podcasts from my

973
00:55:34,800 --> 00:55:37,759
Speaker 1: heart Radio, visit the i heart Radio app, Apple Podcasts

974
00:55:37,800 --> 00:55:39,680
Speaker 1: or wherever you listen to your favorite shows,