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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 Radio. Hello, welcome back to the show.

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Speaker 1: My name is Matt, my name is no They call

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Speaker 1: me Ben. We're joined as always with our super producer

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Speaker 1: Ball mission control decades. 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. Shout out to everybody listening to today's

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Speaker 1: episode on a smartphone or mobile device. In a way,

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Speaker 1: this is very much for you. It's for everybody all

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Speaker 1: the time, but this one's especially for you. One question

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Speaker 1: I thought we could start with today. Guys, what did

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Speaker 1: you do on your phone today? Just however much you

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Speaker 1: feel comfortable disclosing to millions of people in podcast land,

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Speaker 1: too too much, too much. I mean, it's it's like

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Speaker 1: the mission control center of my life. I do a

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Speaker 1: lot of my work on my phone. I like inner

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Speaker 1: data into Google Docs on my phone. I do research

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Speaker 1: on my phone. I do social media on my phone.

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Speaker 1: It's kind of embarrassing, honestly. Well it's yeah, it's interesting,

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Speaker 1: So I think, well, I'm not sure for all of us,

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Speaker 1: but I'm on a laptop and almost all of my

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Speaker 1: work happens there. But if I ever have to leave

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Speaker 1: my home office for any reason, that phone is just

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Speaker 1: in my hand and it's doing all that same stuff,

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Speaker 1: or of course playing Call of Duty or Best Fiends.

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Speaker 1: Right there, we go check that one off the box.

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Speaker 1: We got in front of it this time. So, uh,

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Speaker 1: you know, that's a really great point because a people

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Speaker 1: in the curtain, your individual mileage may very folks, but

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Speaker 1: Matt Noel and I do a ton of stuff all

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Speaker 1: the time. As a matter of fact. Before I guess

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Speaker 1: it's okay to say this publicly, before I've complained to

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Speaker 1: you guys about it, and I've said, you know, the

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Speaker 1: fact that we're kind of always available makes us like

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Speaker 1: very underpaid and enthusiologists. We're just sort of always on

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Speaker 1: the clock, you know, get someone prepared to fix a problem. Surgeons.

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Speaker 1: Firefighters there, we surgeons. I think we're surgeons. We also

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Speaker 1: refer to like problems in the podcast world as fire

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Speaker 1: drills quite often, so we are sort of firefighters in

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Speaker 1: our own ways. Fire surgeons there we go, fire surgeons,

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Speaker 1: rocket fighters there we go. Put it on the T

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Speaker 1: shirts and uh so personally, I did a lot of

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Speaker 1: stuff on my phone today and I did something that

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Speaker 1: I don't usually do. Uh well, I did this yesterday.

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Speaker 1: I kept track of what I was doing. I didn't

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Speaker 1: check every time I touched my phone, but I checked

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Speaker 1: all the weird things I did. I bought stuff, I

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Speaker 1: I looked through social media and blah blah blah, all

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Speaker 1: all the YadA YadA yadas. But one of the things

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Speaker 1: I did today was post an informal question on Twitter.

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Speaker 1: They asked, uh, has your phone or an app on

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Speaker 1: your phone ever seemed to know too much about you?

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Speaker 1: And if so, what freaked you out the most? You

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Speaker 1: can find the responses there on app and bull and

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Speaker 1: hs W. But for our purposes today, uh one thing

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Speaker 1: that most people talked about was, of course, targeted advertising.

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Speaker 1: We see stories about someone saying, you know, I coughed

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Speaker 1: around my phone and then instantly when I pulled up

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Speaker 1: Instagram or something, I was receiving sponsored ads for halls

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Speaker 1: the yeah, and a lot of people reporting like their

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Speaker 1: microphones somehow seemed to know stuff, or their conversations with

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Speaker 1: someone even away from their devices somehow lead to what

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Speaker 1: they see as a targeted ad. There's a little bit

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Speaker 1: of better mind hoff in there, for sure, but there

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Speaker 1: are also a lot of shenanigans. But the thing is,

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Speaker 1: there's a problem with this. We've talked about targeted ads before,

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Speaker 1: everyone knows they exist. These are the things your smartphones

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Speaker 1: and your telecom your ad industries want you to know about.

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Speaker 1: They want you to see an ad for halls or

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Speaker 1: Best Fiends or whatever. But that that's because it's the

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Speaker 1: stuff they want you to know that they know about you.

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Speaker 1: But today's episode is different. Today's episode goes in a

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Speaker 1: different direction. It is about the stuff they don't want

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Speaker 1: you to know about you and your phone. Here are

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Speaker 1: the facts. So what what? What is a smartphone? It's

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Speaker 1: sort of like just a phone these days. But you know,

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Speaker 1: I know people that have decided to not go that

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Speaker 1: route and still use a dumb phone. I as nobody

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Speaker 1: really calls them that, but they're basically phones that, if

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Speaker 1: they have Internet connectivity, are rudimentary at best. Maybe they

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Speaker 1: can send text messages, probably can't send pictures very well. Oftentimes,

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Speaker 1: when you're communicating on a smart phone with somebody with

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Speaker 1: a dumb phone, things appear in blocks or weird ways

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Speaker 1: or you have a little message sent kind of things,

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Speaker 1: because these are much more old school communication tools. Smart

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Speaker 1: their phones their phones first and foremost. I remember I

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Speaker 1: used to have a razor. You guys remember the razor? Yeah,

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Speaker 1: and that was that was like, oh god, it's a

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Speaker 1: color screen. And it was like, you know, a tiny

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Speaker 1: little color screen. Was looking back at now seems laughable.

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Speaker 1: But a smart phone is is essentially a cell phone

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Speaker 1: with a bevy of highly advanced features like what we're

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Speaker 1: talking about. Yeah, oh man, Matt, is that your burner? Us?

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Speaker 1: This was my first cell phone, you guys, Oh my god,

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Speaker 1: it was a Motorola. It's a Kio Sarah, I don't

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Speaker 1: even know that brand. Q CP thirt I am. I

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Speaker 1: have a Nokia, but I just attached to chain to

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Speaker 1: it and use it for personal defense because indestructible. But

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Speaker 1: but you're I love the point you're making old because

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Speaker 1: it's like, if you own a smartphone, or if you

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Speaker 1: buy an iPhone or an Android or something, saying that

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Speaker 1: you're going to call someone or knowing that you can

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Speaker 1: use it to make phone calls is very much like

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Speaker 1: a lower priority feature. Now you want it to be online.

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Speaker 1: You want to have uh, certain slick apps and so on. Well, yeah,

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Speaker 1: and we recently talked about on a listener Mail episode

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Speaker 1: about you know, robocall scams and things like that, and

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Speaker 1: how they're often targeted to older generations because they're the

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Speaker 1: ones that are still using phones to make calls or

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Speaker 1: have landlines. You know, I haven't had a landline and

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Speaker 1: probably fifteen years. You know, Um, and I very where

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Speaker 1: I mean. I use my phone to make calls for

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Speaker 1: work often because we do conference calls, but now that's

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Speaker 1: pivoted to you know, Google hangouts or or Microsoft teams

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Speaker 1: or Zoom or what have you. So very rarely use

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Speaker 1: my phone to make calls. And oftentimes if I get

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Speaker 1: a call that from a number I don't recognize, I

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Speaker 1: don't answer it. And if someone calls me out of

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Speaker 1: the blue, I low key resent them for it. No not,

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Speaker 1: I'm not you, Matt. I'm always happy to hear from

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Speaker 1: either of you, guys, But I'm just saying in general,

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Speaker 1: and out of the blue call feels like, why didn't

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Speaker 1: we schedule this? You know, this should have been like

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Speaker 1: on the books. You know, you can't just call me

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Speaker 1: out of nowhere because it implies it requires an immediate reaction,

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Speaker 1: although there's also that kind of expectation with texting to

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Speaker 1: people text you aggressively because they want you to text

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Speaker 1: back right away and if you don't, it can kind

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Speaker 1: of weird people out sometimes. But basically we are in

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Speaker 1: the world of smartphones. There's no putting that badger back

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Speaker 1: in the bag or Genie back in the jar or

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Speaker 1: what have you. Um, because people are using their phones

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Speaker 1: for so many their things, uh, calling being absolutely secondary

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Speaker 1: and at this point it really might as well be

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Speaker 1: an extra feature. Um, but I guess it's bundled in

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Speaker 1: because the telecom companies still want to have that infrastructure

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Speaker 1: for making calls, right, I mean yeah, and they want

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Speaker 1: that voice data right so they can frank a bite

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Speaker 1: you later and alright, alright, allegedly sure. But the uh,

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Speaker 1: the one thing that's fascinating to me about this is

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Speaker 1: how quickly this became normalized, especially in the West. I mean,

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Speaker 1: I have if you ever want to have a fun

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Speaker 1: rabbit hole, try looking into all the and if you're

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Speaker 1: a hip hop head like I am, trying looking into

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Speaker 1: all the old technological brags of hip hop songs of yesteryear.

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Speaker 1: You know, when like jay Z is like I'm too cold,

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Speaker 1: Motorola two way pager like that was fancy. That was

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Speaker 1: a razor at the time, And now that stuff seems

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Speaker 1: so antiqually because it evolves so quickly. But that's the

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Speaker 1: front of the curtain. Evolution behind the curtain stuff is

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Speaker 1: much different and also evolving at a much faster pace. Yeah,

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Speaker 1: but it's it's harder to trace the stuff with a

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Speaker 1: two A patrio. I'm just you know, that's true. That's true,

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Speaker 1: that's why it's so cold. But in a very short

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Speaker 1: amount of time, as Drake would say this stuff, the

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Speaker 1: smartphone usage went from zero to a hundred and as

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Speaker 1: we record this episode right now. This is statistic that

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Speaker 1: baffled me. There are approximately ten billion mobile devices in use.

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Speaker 1: And yes, to confirm, that's more than the current human

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Speaker 1: population of the planet. I checked just in case. So

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Speaker 1: is that just for like people that have like two phones?

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Speaker 1: That's part of you and why would you do that?

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Speaker 1: That's very suspicious. Oh, that's true. You might get issued

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Speaker 1: one for work. That's the good point. Side side piece

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Speaker 1: burners everywhere. I also think there may be more than

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Speaker 1: ten billion in use as we record this because one thing,

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Speaker 1: that one thing I think a lot of people, especially

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Speaker 1: in the US, don't know, is that there are some

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Speaker 1: phones that are designed to have to SIM cards in

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Speaker 1: the phone so they can function like two different phones.

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Speaker 1: I found out about it when I saw some news

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Speaker 1: in China, I can't remember which city about. Uh, these

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Speaker 1: guys who were cheating on their spouses and then their

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Speaker 1: their secret SIM cards got found. Tut tut. That's like

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Speaker 1: prison rules, man, you know, like seriously. Uh. And also,

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Speaker 1: you know, because of these smart devices, we hear a

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Speaker 1: lot of other stories like that, Like I think you

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Speaker 1: know Gavin Rossdale from the band Bush he used to

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Speaker 1: be married to Gwen Stefani, you know, amazing solo artists,

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Speaker 1: but also from the band No Doubt. And I believe

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Speaker 1: that he got caught cheating because he had the family

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Speaker 1: iPad sinked with his personal device because with Apple you

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Speaker 1: sink your Apple products together, and so it came up

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Speaker 1: on the family iPad the like nudes that his mistress

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Speaker 1: was sending him, and so his wife found out, possibly

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Speaker 1: even his kids. And I can either confirm nor deny that. Okay,

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Speaker 1: so prison rules, you're talking about multiple SIM cards, not marriage.

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Speaker 1: I'm talking about multiple SIM cards. Yeah, for sure the way,

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Speaker 1: we don't hear about SIM cards. Remember that that heroin

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Speaker 1: smuggling cat, that cat also had SIM cards in the

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Speaker 1: little pouch around uh its neck. It really feels like

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Speaker 1: we need to consult Professor Wilson on this whole thing.

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Speaker 1: I feel like he would know a lot about all

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Speaker 1: of this legend legend. Professor Wilson. We started, uh, if

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Speaker 1: you're listening, Doc, we started a little late today because

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Speaker 1: we had to talk about the amazing emails this guy

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Speaker 1: has been sending. Just check Professor Wilson on on Twitter.

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Speaker 1: I'm sure I'll show up and hope he's well. Uh,

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Speaker 1: Professor Wilson. Probably as a cell phone or smartphone, excuse me,

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Speaker 1: not a cellular phone. We wanted to gather some up

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Speaker 1: to date statistics about just the lay of the digital

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Speaker 1: land for smartphones, and we've got info from as recent

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Speaker 1: as we could get it. We've got a lot from

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Speaker 1: There's some things where we had to go back to

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Speaker 1: nineteen and there are a couple of little slips. But

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Speaker 1: some of this is going to be news to a

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Speaker 1: lot of us, just the enormity of what's going on

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Speaker 1: with smartphones. Yes, so we talked about the ten billion

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Speaker 1: devices that are being used. Well, as of this year,

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Speaker 1: there are three point five billion humans, well mostly humans hopefully,

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Speaker 1: who are actually using these smartphones. And it's pretty crazy

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Speaker 1: because in twenty nineteen of the United States residents people

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Speaker 1: living in the US had a smartphone, and that is

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Speaker 1: obviously a number that is going to continue to rise.

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Speaker 1: And here are some of the stats. Forty seven percent

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Speaker 1: say they absolutely could not live without a smartphone. I

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Speaker 1: certainly believe that. As an sure you do too. In comparison,

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Speaker 1: nine three of all Internet users in China use mobile

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Speaker 1: devices to go online, so not a laptop, not a

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Speaker 1: laptop at all. When you think about saying they couldn't

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Speaker 1: live without one, I'm just going to assume that a

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Speaker 1: good portion of that number has to do with people

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Speaker 1: who just use their their smartphone to access the Internet

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Speaker 1: and things. In comparison in China, it's like so many

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Speaker 1: people are just using their mobile devices. It makes me

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Speaker 1: act really quickly, Matt, like, what were we doing before smartphones?

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Speaker 1: Clearly not living and what was that? Like? We were blackberrying,

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Speaker 1: we were, as Ben said, razoring, we were playing snake um,

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Speaker 1: texting each other forgetting, we were actively forgetting all of

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Speaker 1: the phone numbers that we had in our heads. Game

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Speaker 1: Boys were d Nintendo ds. I guess is the is

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Speaker 1: the Homo sapien to that neanderthal. But the I would

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Speaker 1: say it's affected our ignition for sure. We're thinking less

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Speaker 1: deeply about things, and now we're thinking about more things.

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Speaker 1: We've said this before. We're thinking across the axis rather

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Speaker 1: than up and down. So we know, like we have,

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Speaker 1: like the first paragraph of Wikipedia, knowledge about a ton

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Speaker 1: of stuff, but we don't have as much depth of learning.

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Speaker 1: Right just this is not a ding on any individual.

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Speaker 1: This is a purposeful, brutal ding on our species because

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Speaker 1: part of this where we would store all that stuff,

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Speaker 1: it's now here in your hand. Oh god, that that

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Speaker 1: was kind of weird. And here it's not here, it's

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Speaker 1: it's it's on this. Look at who refresh the tape

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Speaker 1: for this episode. I think we've been the before. Times.

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Speaker 1: We even had like kind of bar conversations about what

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Speaker 1: happens to that part of our brain that used to

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Speaker 1: store phone numbers. Does it evolve into something cooler or

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Speaker 1: do we just lose it? And I don't know the

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Speaker 1: answer to that. I tend towards we just lose it,

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Speaker 1: or I just get subsumed with more kind of useless,

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Speaker 1: shallow dive facts that we can then spit out at parties. Mainly,

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Speaker 1: I would which we and every every one of our

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Speaker 1: colleagues are like the worst at parties. We're just we're

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Speaker 1: gonna have to start a game called the actual ease.

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Speaker 1: I'm kidding, I do. I I have put concerted efforts

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Speaker 1: into uh not not being that person at parties. But

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Speaker 1: but you're right, I would say, if we wanted to

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Speaker 1: be optimistic about it, perhaps we could say that that, uh,

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Speaker 1: that skill of memorization, rather than being atrophied, has just

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Speaker 1: been re channeled because for a time we were memorizing

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Speaker 1: many more passwords, right, which would I think occur in

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Speaker 1: the same part of the brain that retains phone numbers.

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Speaker 1: But now you know, increasingly your phone or your device

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Speaker 1: will call passwords for you who or just say hey,

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Speaker 1: let me go good, look at your face? All right,

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Speaker 1: here's all your banking information. Uh. That's pretty common with

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Speaker 1: with iPhones especially, and we use them a lot. I'm

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Speaker 1: still working this one out, and I wanted to see

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Speaker 1: how you guys felt about this number. You Matt, you

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Speaker 1: know everybody listening, So overall it seems that the average

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Speaker 1: smartphone user across the planet checks their device, whatever it is,

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Speaker 1: at least fifty eight times per day. We also tend

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Speaker 1: to vastly underestimate how often we check our phones, and

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Speaker 1: there's fifty eight is probably still a really low number.

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Speaker 1: Because there's a study we're gonna get to later in

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Speaker 1: today's episode that found in the United Kingdom, people on

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Speaker 1: average thought they checked their phone thirty seven times a day.

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Speaker 1: That was their best guests when they asked all these people,

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Speaker 1: but the actual number was much closer to eighty five

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Speaker 1: times a day. Does that saw reasonable to you, guys?

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Speaker 1: Or does that sound like off base one way or another?

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Speaker 1: That does not sound off base. If you if you

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Speaker 1: use an iOS device and you want to get insights

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Speaker 1: into yourself and how you are your phone, UM, open

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Speaker 1: up the thing that's in your settings. It's very close

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Speaker 1: to the top. That's called screen time, and you will

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Speaker 1: see I have, just so you know, I've disabled mine

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Speaker 1: on my phone. I disabled it almost as soon as

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Speaker 1: it became a feature, UM, and I think you should too,

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Speaker 1: unless you are using it for a specific reason like

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Speaker 1: preventing children your children from using your phone, or preventing

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Speaker 1: yourself even from using your phone at certain times or

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Speaker 1: certain apps um as a self regulating technique. Um, because

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Speaker 1: that thing alone, that little feature stores a ton of

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Speaker 1: information about you as your phone does it. So wait though,

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Speaker 1: but that does disabling it prevent the device from collecting

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Speaker 1: that information or just prevented from displaying that information to you.

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Speaker 1: You can disable a lot of stuff in your iOS

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Speaker 1: device that has to do with what we're gonna talk

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Speaker 1: about today. Um. And that is one of the one

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Speaker 1: of the things that you can do. It's also a

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Speaker 1: good way to feel like an absolute technology junkie when

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Speaker 1: it like serves you up with that information weekly, like

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Speaker 1: there's like automatically. I think by default it gives you

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Speaker 1: reports like your screen time is up, you know, blah

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Speaker 1: blah blah. And I'm certain that because of all this

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Speaker 1: COVID business people screen times are way the hell up,

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Speaker 1: you know. And then it becomes like, Okay, I'm an alcoholic,

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Speaker 1: I need to drink less. You know, it's bad for me. Um,

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Speaker 1: how do I self regulate? Like you say? And the

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Speaker 1: fact that we even have to think about it like

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Speaker 1: that sort of proves the whole idea that it is

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Speaker 1: hijacking our brains and making us crave that feedback that

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Speaker 1: we get from checking the phone. What if there's a

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Speaker 1: new thing. What if I get a notification? Oh, let

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Speaker 1: me drag down and refresh my Facebook feed. Maybe there's

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Speaker 1: a cool new thing that I must know about instantly. Exactly, Yeah,

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Speaker 1: and well put so we so we know that that

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Speaker 1: number tracks. If anything, it's it's probably going to be

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Speaker 1: a little bit low for at least half of the

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Speaker 1: logically for about half the audience. Right. Uh, more than

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Speaker 1: sixty of smartphone users have made a purchase of some

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Speaker 1: sort on their device. Uh, not to pick on Apple,

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Speaker 1: but the way that they sandbox is purposely designed to

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Speaker 1: make it easy, or they would say, seamless to buy

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Speaker 1: things on the device, to the chagrin if I imagine

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Speaker 1: many many parents who later find out that their kid

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Speaker 1: has bought YadA, YadA, YadA and spouses just kidding. So

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Speaker 1: while we're on the subject of money, let's also point

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Speaker 1: out in app advertising is going to rise to two

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Speaker 1: hundred billion dollars US by just next year. In four

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Speaker 1: years after that by this number is projected to grow

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Speaker 1: as long as we don't burn everything down, projected to

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Speaker 1: grow around two six billion and uh, it's gonna keep going.

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Speaker 1: We spend so much time staring at these little screens

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Speaker 1: for one reason or another. In fact, uh, smartphones are

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Speaker 1: leaving smartphones as the doorway to the internet for a

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Speaker 1: lot of people are leaving other media platforms in the dust.

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Speaker 1: Seventy percent of all the media time like around ends

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Speaker 1: up being spent on smartphones, which is nuts. It's not

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Speaker 1: saying that people are, you know, necessarily listening to a

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Speaker 1: ton less radio or something. There's just a ton more

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Speaker 1: people with very easy access to stuff. It's just all integrated.

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Speaker 1: I mean, I remember when the first iPhone came out out.

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Speaker 1: It seemed like magic, you know, everything from the touch

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Speaker 1: screen and proventation to the way the keyboard was virtual

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Speaker 1: and obviously it was clunky at first, but it seemed

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Speaker 1: amazing at the time, and just the idea that oh,

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Speaker 1: I can watch YouTube on my phone or I can

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Speaker 1: it's literally like a handheld computer. And it is more

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Speaker 1: so every single new generation because of the way that

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Speaker 1: you know, the way that rose to prominence so quickly.

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Speaker 1: That's just how technology works now, because of the speed

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Speaker 1: of processors and the exponential improvement of technology and streamlining

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Speaker 1: of technology. Not to mention that, like, you know, all

359
00:21:28,400 --> 00:21:31,040
Speaker 1: of this is built on the idea of stuff is free.

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Speaker 1: You know, Oh, the apps are free. You can buy

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Speaker 1: an app stuff if you want to, but you don't

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Speaker 1: have to. But it sure does make it a better

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Speaker 1: experience if you buy those extra widgets or gems or

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Speaker 1: power ups or what have you, or you pay for

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Speaker 1: the premium version so you don't have to get served

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Speaker 1: those ads all the time. Yeah, that brings me to

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Speaker 1: another question, only tangentially related. We all know a lot

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Speaker 1: of early adopters, right, just the nature of our social

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Speaker 1: networks and friendships. Are you guys people who buy the

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Speaker 1: latest version of an iPhone? Like you were? You Twitter

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00:22:04,680 --> 00:22:09,560
Speaker 1: painted about the iPhone twelve? Not? My My first iPhone

372
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Speaker 1: was a four. I had an early one I had

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Speaker 1: I think I had one of the real small ones,

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Speaker 1: the original that were kind of beveled edges, you know,

375
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Speaker 1: that was kind of shiny on the back. I had

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Speaker 1: one of those. Um And the thing about those they

377
00:22:22,000 --> 00:22:24,560
Speaker 1: just become bricks man like, it's probably it's probably in

378
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Speaker 1: a drawer somewhere, you know, no idea, because they become useless,

379
00:22:28,280 --> 00:22:32,359
Speaker 1: you know, because they basically designed the software so that

380
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Speaker 1: they no longer work on the old phones. And obviously

381
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Speaker 1: we we understand all of that about planned obso lescence,

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00:22:36,800 --> 00:22:39,240
Speaker 1: and that's a whole another discussion. But no, I wait

383
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Speaker 1: till it's affordable. I wait till it's like part of

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Speaker 1: a deal to re up my plan or whatever. I'm

385
00:22:44,359 --> 00:22:48,520
Speaker 1: never going to drop the full price on a new device.

386
00:22:49,200 --> 00:22:53,520
Speaker 1: I'm not that guy. I I gotta halfheartedly apologize and

387
00:22:53,600 --> 00:22:55,920
Speaker 1: misled you guys just a bit. Part of the reason

388
00:22:55,920 --> 00:23:01,040
Speaker 1: I specifically asking about the Apple I've owned twelve pro

389
00:23:01,960 --> 00:23:05,960
Speaker 1: is that I got a ton of questions over the

390
00:23:06,000 --> 00:23:10,199
Speaker 1: past few days, people asking whether I had done the

391
00:23:10,280 --> 00:23:14,040
Speaker 1: v O for an Apple announcement. And we record so

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Speaker 1: much stuff that you know, it's easy for the three

393
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Speaker 1: of us to not remember all the stuff we may

394
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Speaker 1: have recorded. And uh, I went back and checked after

395
00:23:23,080 --> 00:23:26,359
Speaker 1: like the fifth or tenth person reached out to me,

396
00:23:26,800 --> 00:23:29,840
Speaker 1: and I've got what I've decided to call a voppel

397
00:23:29,920 --> 00:23:32,959
Speaker 1: ganger like v O plus doppel ganger. That dude sounds

398
00:23:33,000 --> 00:23:37,359
Speaker 1: like me. I don't Apple me have like done something like?

399
00:23:37,440 --> 00:23:40,399
Speaker 1: It's weird? Tell us how to find it? How do

400
00:23:40,440 --> 00:23:43,080
Speaker 1: we find it? Yeah, you can check it out by

401
00:23:43,119 --> 00:23:49,080
Speaker 1: going to uh YouTube and search for Apple event October.

402
00:23:50,240 --> 00:23:54,919
Speaker 1: It's uh, it's weird. I I don't think there's anything

403
00:23:54,960 --> 00:23:57,680
Speaker 1: to fairy. I think it's just that somewhere out there,

404
00:23:57,720 --> 00:24:02,120
Speaker 1: I have a vocal twin. Who are you mysterious voppel Ganger?

405
00:24:02,160 --> 00:24:04,000
Speaker 1: I got one of those two somebody sent me if

406
00:24:04,040 --> 00:24:05,399
Speaker 1: I don't remember what it was, but it was some

407
00:24:05,600 --> 00:24:07,919
Speaker 1: like ad or something, and maybe it was on one

408
00:24:07,960 --> 00:24:10,640
Speaker 1: of the message boards or the show pages for either

409
00:24:10,680 --> 00:24:12,800
Speaker 1: this a ridiculous history. But I went back and listen

410
00:24:12,840 --> 00:24:14,679
Speaker 1: to you, and it was it was real, it was

411
00:24:14,680 --> 00:24:17,360
Speaker 1: spot on like it. It freaked me out a little bit,

412
00:24:17,440 --> 00:24:19,520
Speaker 1: you know, So I don't know what what's the what's

413
00:24:19,520 --> 00:24:24,760
Speaker 1: that play here? Your next bet? Europe next? But anyway,

414
00:24:24,800 --> 00:24:28,239
Speaker 1: we digress. We're just confirming that we're not we're not

415
00:24:28,560 --> 00:24:31,479
Speaker 1: uh secretly recording stuff and claiming we don't know what

416
00:24:31,520 --> 00:24:35,280
Speaker 1: it is. With all this stuff in mind about smartphones

417
00:24:35,320 --> 00:24:40,400
Speaker 1: and about how they have entrenched themselves into society and culture,

418
00:24:40,840 --> 00:24:43,680
Speaker 1: it shouldn't come as a surprise that millions upon millions

419
00:24:43,680 --> 00:24:46,840
Speaker 1: of people somehow work in this industry. Uh. The current

420
00:24:46,880 --> 00:24:49,959
Speaker 1: guests I found said that there are about fourteen million

421
00:24:50,080 --> 00:24:53,639
Speaker 1: jobs that are directly related to the mobile industry, but

422
00:24:53,760 --> 00:24:57,879
Speaker 1: the number of associated jobs has to be much much higher. Right.

423
00:24:58,000 --> 00:25:02,080
Speaker 1: Think of marketing firms where there's one person who specializes

424
00:25:02,119 --> 00:25:06,240
Speaker 1: in mobile experience, right, or or someone out of tech

425
00:25:06,280 --> 00:25:11,040
Speaker 1: company who specializes in mobile ux, they're still associated. There

426
00:25:11,119 --> 00:25:13,000
Speaker 1: is a great deal of money. We already talked about it.

427
00:25:13,040 --> 00:25:15,960
Speaker 1: There's more on the horizon. And make no mistake. If

428
00:25:16,000 --> 00:25:19,199
Speaker 1: you own a smartphone, or somebody who lives in close

429
00:25:19,240 --> 00:25:23,119
Speaker 1: proximity to you, especially in your house, if they've got

430
00:25:23,160 --> 00:25:27,280
Speaker 1: a smartphone, you are a piece of this ecosystem and equation.

431
00:25:28,080 --> 00:25:31,560
Speaker 1: Uh and and just get ready because as we keep

432
00:25:31,600 --> 00:25:37,560
Speaker 1: going in this episode, it's gonna get weirder and scarier. Yeah. Right,

433
00:25:38,359 --> 00:25:42,160
Speaker 1: And if you're listening to this show, you know you're

434
00:25:42,160 --> 00:25:45,320
Speaker 1: probably already very well aware of how this process works.

435
00:25:45,480 --> 00:25:48,800
Speaker 1: You like us, have seen the social dilemma. But more importantly,

436
00:25:48,800 --> 00:25:52,560
Speaker 1: you've experienced yourself your data on social apps, that's a

437
00:25:52,600 --> 00:25:55,240
Speaker 1: revenue stream, and you don't get a piece of that.

438
00:25:55,320 --> 00:25:59,320
Speaker 1: Pigh your data from your telecom carrier, same thing your

439
00:25:59,320 --> 00:26:03,000
Speaker 1: Internet brow there every single app or virtually every single

440
00:26:03,040 --> 00:26:06,200
Speaker 1: app on your phone, Each of those aggregations of information

441
00:26:06,400 --> 00:26:09,359
Speaker 1: are packaged up and they're sold to different places with

442
00:26:09,520 --> 00:26:13,720
Speaker 1: varying levels of anonymity. And uh, you do not get

443
00:26:13,760 --> 00:26:15,960
Speaker 1: a piece of that either, which I think is one

444
00:26:15,960 --> 00:26:18,280
Speaker 1: of the main things, one of the pettiest things we

445
00:26:18,320 --> 00:26:21,840
Speaker 1: winged about in the Big Data episode. So instead we

446
00:26:21,920 --> 00:26:26,080
Speaker 1: all stare into this digital abyss and there's this dizzy,

447
00:26:26,320 --> 00:26:32,600
Speaker 1: neurochemically manipulative ping of likes and follows, subscribes notifications. They

448
00:26:32,640 --> 00:26:35,480
Speaker 1: blow up our synapsies like these gaudy lights of a

449
00:26:35,560 --> 00:26:39,520
Speaker 1: casino slot machine. And that's that's where we're at. Like

450
00:26:39,560 --> 00:26:42,399
Speaker 1: you said, this caused This has caused some people to

451
00:26:42,440 --> 00:26:45,920
Speaker 1: consciously limit their time or to maybe be more mindful

452
00:26:45,960 --> 00:26:48,959
Speaker 1: of it, like get those focus apps than say, you know,

453
00:26:49,320 --> 00:26:53,520
Speaker 1: hey jo Brownie, get out of Instagram, you're you're here

454
00:26:53,640 --> 00:26:57,120
Speaker 1: for your outlook email or something like that. Yeah, there's

455
00:26:57,160 --> 00:26:59,879
Speaker 1: some apps that will even block you from accessing sir

456
00:27:00,080 --> 00:27:03,000
Speaker 1: and other apps. It's like you literally have to like

457
00:27:03,119 --> 00:27:06,040
Speaker 1: it's like a digital chastity belt or something like that,

458
00:27:06,119 --> 00:27:08,760
Speaker 1: you know, or you have to make sure that you

459
00:27:09,080 --> 00:27:13,439
Speaker 1: won't be tempted by you know, the sweet, sweet evil

460
00:27:13,520 --> 00:27:17,640
Speaker 1: fruit of digital connectivity. You know what I mean? How

461
00:27:17,720 --> 00:27:21,200
Speaker 1: is that different from medicine that is prescribed to address

462
00:27:21,240 --> 00:27:24,200
Speaker 1: the side effects of another medication. That's exactly what. No,

463
00:27:24,320 --> 00:27:28,600
Speaker 1: it's I think it's uh, it's not different at all, terrifying.

464
00:27:28,640 --> 00:27:32,200
Speaker 1: But today's question, right, is this, how far does this

465
00:27:32,320 --> 00:27:36,040
Speaker 1: data gathering go? How will it affect you, your loved ones,

466
00:27:36,200 --> 00:27:39,399
Speaker 1: your pocketbook, your region, and this species in the future.

467
00:27:39,760 --> 00:27:44,040
Speaker 1: Why are more and more tech savvy people becoming just

468
00:27:44,080 --> 00:27:48,480
Speaker 1: like in social dilemma, doomsday profits telling us you are

469
00:27:48,800 --> 00:27:54,120
Speaker 1: your full we'll tell you afterward. Oddly enough from our sponsor.

470
00:28:02,080 --> 00:28:07,000
Speaker 1: Here's where it gets crazy hyperbole aside. They are saying

471
00:28:07,000 --> 00:28:10,000
Speaker 1: it because they are absolutely correct. They've been trying to

472
00:28:10,040 --> 00:28:12,560
Speaker 1: warn us about this for a while. But this goes

473
00:28:13,160 --> 00:28:15,320
Speaker 1: This goes back to one of my problems with social dilemma.

474
00:28:15,320 --> 00:28:18,280
Speaker 1: I think we've talked about it, but maybe we haven't

475
00:28:18,320 --> 00:28:24,240
Speaker 1: talked about it. While those folks are providing valid, valuable insight,

476
00:28:24,840 --> 00:28:29,000
Speaker 1: they're doing it after they made a fortune, and morally

477
00:28:29,119 --> 00:28:33,400
Speaker 1: I am conflicted with by you know, I I don't

478
00:28:33,440 --> 00:28:35,960
Speaker 1: know how to address the immense privilege of that right,

479
00:28:36,240 --> 00:28:38,760
Speaker 1: Like you feel bad after you've got your dragon's hoard

480
00:28:38,840 --> 00:28:41,200
Speaker 1: of gold and you sit on that hill and tell

481
00:28:41,280 --> 00:28:45,200
Speaker 1: people about the dangers of the thing you created. But

482
00:28:45,200 --> 00:28:47,600
Speaker 1: I don't see him given the money away. Yeah, but

483
00:28:47,720 --> 00:28:49,800
Speaker 1: what would what would the money do? Is this is

484
00:28:49,880 --> 00:28:53,400
Speaker 1: my only counterpoint. What what would I mean? I guess

485
00:28:53,400 --> 00:28:54,920
Speaker 1: if they were just trying to do good in the

486
00:28:54,920 --> 00:28:58,000
Speaker 1: world and just be you know, proactive about giving their

487
00:28:58,000 --> 00:29:01,000
Speaker 1: money to some charity. Right, we know, we know that

488
00:29:01,040 --> 00:29:04,320
Speaker 1: doesn't always work, just throwing money at a problem. I'm

489
00:29:04,880 --> 00:29:07,880
Speaker 1: i I'm not saying I'm completely on their side. I

490
00:29:08,000 --> 00:29:11,160
Speaker 1: just know that I know for a fact that the

491
00:29:11,240 --> 00:29:14,160
Speaker 1: human beings, the very low number of human beings that

492
00:29:14,240 --> 00:29:18,720
Speaker 1: were in the rooms that created the the the pioneering

493
00:29:18,800 --> 00:29:23,320
Speaker 1: apps in things that we use now ubiquitously, those people

494
00:29:23,440 --> 00:29:26,800
Speaker 1: didn't fully understand what they were doing, and they knew

495
00:29:26,800 --> 00:29:30,320
Speaker 1: they were trying to build something like uh like that

496
00:29:30,480 --> 00:29:33,680
Speaker 1: was addictive to some extent. Right, No, it wasn't there, guys,

497
00:29:33,720 --> 00:29:37,040
Speaker 1: isn't there wasn't there a class or something that everybody took.

498
00:29:37,440 --> 00:29:39,680
Speaker 1: There's like connective tissue between a lot of these things.

499
00:29:39,960 --> 00:29:43,040
Speaker 1: There is, and I would I would need to double

500
00:29:43,080 --> 00:29:45,080
Speaker 1: check what the name of the class was, but essentially

501
00:29:45,480 --> 00:29:47,160
Speaker 1: it was a class that was offered at Stanford and

502
00:29:47,360 --> 00:29:50,480
Speaker 1: you know, Stanford is kind of like a feeder colony,

503
00:29:50,520 --> 00:29:54,800
Speaker 1: I guess for you know, Silicon Valley startup culture essentially,

504
00:29:55,240 --> 00:29:58,160
Speaker 1: um and there was a particular class that everyone that

505
00:29:58,320 --> 00:30:01,280
Speaker 1: ended up in high levels of this ux design for

506
00:30:01,320 --> 00:30:04,440
Speaker 1: these types of apps all took. And it essentially had

507
00:30:04,480 --> 00:30:09,600
Speaker 1: to do with harnessing psychology, uh and weaponizing it essentially.

508
00:30:09,640 --> 00:30:12,400
Speaker 1: I mean this really wouldn't have said it like that

509
00:30:12,480 --> 00:30:14,600
Speaker 1: at the time, but everyone kind of knew what they

510
00:30:14,600 --> 00:30:17,760
Speaker 1: were doing and they thought it very clever and obviously

511
00:30:17,800 --> 00:30:21,080
Speaker 1: it was. But hindsight, a lot of these folks that

512
00:30:21,080 --> 00:30:25,080
Speaker 1: that spoke to this in the Social Dilemma kind of

513
00:30:25,240 --> 00:30:27,120
Speaker 1: make the argument of, oh, we didn't realize how far

514
00:30:27,120 --> 00:30:29,520
Speaker 1: it would go, but we knew exactly what it was,

515
00:30:29,600 --> 00:30:32,600
Speaker 1: so I see your dilemma, Ben, that there is sort

516
00:30:32,600 --> 00:30:34,800
Speaker 1: of like you can't have it both ways thing. One

517
00:30:34,800 --> 00:30:37,200
Speaker 1: of the guys who's featured in the Social Dilemma UM

518
00:30:37,520 --> 00:30:40,000
Speaker 1: can Sorry, guys, I'm being bad with names, but he's

519
00:30:40,000 --> 00:30:42,560
Speaker 1: one of the main speakers, and he does a lot

520
00:30:42,600 --> 00:30:45,400
Speaker 1: of ted talk type things about the evils of this

521
00:30:45,520 --> 00:30:53,360
Speaker 1: technology and has a essentially a program that's about um AI. Uh,

522
00:30:53,760 --> 00:30:57,280
Speaker 1: you know, basically kindness in AI or sort of like

523
00:30:57,440 --> 00:31:03,040
Speaker 1: rethinking AI and rethinking these kinds of technologies. But you're right,

524
00:31:03,240 --> 00:31:05,640
Speaker 1: like is he given the money away? Like he made

525
00:31:05,760 --> 00:31:07,880
Speaker 1: a mint, you know, being a part of this thing.

526
00:31:08,240 --> 00:31:10,400
Speaker 1: But he was sort of the guy who flagged with

527
00:31:10,480 --> 00:31:12,840
Speaker 1: Facebook early on. He he probably is the one who

528
00:31:12,840 --> 00:31:15,719
Speaker 1: has the best argument. That's the Tristan guy, but it's

529
00:31:15,720 --> 00:31:21,680
Speaker 1: spelled pronounced differently. But he has the best argument of

530
00:31:21,720 --> 00:31:24,360
Speaker 1: like being somewhat benevolent in this whole thing, because he

531
00:31:24,440 --> 00:31:28,760
Speaker 1: flagged it early at Facebook and essentially got shut down

532
00:31:29,200 --> 00:31:31,880
Speaker 1: even after it made a bunch of noise, uh, this

533
00:31:31,960 --> 00:31:34,640
Speaker 1: idea that this was going to lead to something really bad,

534
00:31:35,120 --> 00:31:37,240
Speaker 1: and then he got sort of shut down, and then

535
00:31:37,280 --> 00:31:39,760
Speaker 1: he he left because he couldn't be a part of

536
00:31:39,760 --> 00:31:42,800
Speaker 1: it anymore. So I kind of see him as being

537
00:31:43,240 --> 00:31:45,680
Speaker 1: the kind of winner, the guy that comes out looking

538
00:31:45,720 --> 00:31:48,640
Speaker 1: a little bit more like he's practicing what he preaches.

539
00:31:48,720 --> 00:31:51,920
Speaker 1: In this documentary, Yeah I understood, and thank you guys again.

540
00:31:52,080 --> 00:31:58,640
Speaker 1: I don't know how to intellectually navigate it, but the

541
00:31:58,720 --> 00:32:04,240
Speaker 1: social dilemma is is worth watching. My personal principle is

542
00:32:04,280 --> 00:32:07,120
Speaker 1: I don't like to judge people, uh too harshly. When

543
00:32:07,120 --> 00:32:09,560
Speaker 1: I'm seeing a curated version of them, like on a

544
00:32:09,600 --> 00:32:13,480
Speaker 1: documentary or something. So uh, the social dilemma exists, though

545
00:32:13,920 --> 00:32:18,360
Speaker 1: tangentially related to this episode. To go back to the

546
00:32:18,440 --> 00:32:23,640
Speaker 1: concept of what we're talking about today, you are your

547
00:32:23,680 --> 00:32:28,400
Speaker 1: phone as a concept goes far far beyond targeted advertising

548
00:32:28,560 --> 00:32:34,720
Speaker 1: and psychologically manipulative ux design. Uh, way back and as

549
00:32:34,760 --> 00:32:38,560
Speaker 1: far back as and to be honest before people were

550
00:32:38,560 --> 00:32:42,320
Speaker 1: sounding the alarm a few years back and there were

551
00:32:42,360 --> 00:32:44,960
Speaker 1: a couple of startups in Silicon Valley that had a

552
00:32:45,000 --> 00:32:47,720
Speaker 1: bright idea. They were lenders who want They wanted to

553
00:32:47,760 --> 00:32:50,920
Speaker 1: be disruptors and the financial market, and you know, disruptors

554
00:32:50,960 --> 00:32:53,719
Speaker 1: is one of those buzzwords against thrown around. Here's what

555
00:32:53,760 --> 00:32:56,600
Speaker 1: they wanted to do. They said, why don't we base

556
00:32:56,880 --> 00:33:02,080
Speaker 1: personal loan decisions on an analyzes of data that we

557
00:33:02,160 --> 00:33:05,640
Speaker 1: get from people's phones. That means exactly what you think

558
00:33:05,680 --> 00:33:08,760
Speaker 1: it means, folks, knowing how you use your phone on

559
00:33:08,800 --> 00:33:12,480
Speaker 1: a granular level, it reveals a lot about you. They wanted,

560
00:33:12,600 --> 00:33:15,000
Speaker 1: you know, they were what's another buzzword, They were going

561
00:33:15,000 --> 00:33:18,160
Speaker 1: blue sky right, and they were saying, look, we want

562
00:33:18,280 --> 00:33:22,000
Speaker 1: all the text, we want all the emails, the GPS coordinates,

563
00:33:22,240 --> 00:33:25,640
Speaker 1: want social media post, We want all the receipts that

564
00:33:25,720 --> 00:33:28,160
Speaker 1: are sent, you know, for like your Uber ride or

565
00:33:28,240 --> 00:33:32,080
Speaker 1: your your purchase through an app, And we want to

566
00:33:32,680 --> 00:33:36,360
Speaker 1: take all of that stuff and then build a collage

567
00:33:36,960 --> 00:33:42,840
Speaker 1: about this person, build like a very accurate persona and profile.

568
00:33:44,960 --> 00:33:49,440
Speaker 1: And these patterns of behavior that by themselves are grains

569
00:33:49,440 --> 00:33:53,920
Speaker 1: of sand and innocuus together they can be fused to

570
00:33:54,040 --> 00:33:58,240
Speaker 1: make this gigantic glass sculpture of you, which is weirdly

571
00:33:59,200 --> 00:34:01,200
Speaker 1: bad announce. Okay, these aren't all gonna work, but you

572
00:34:01,240 --> 00:34:05,160
Speaker 1: see what I'm saying. And this behavior can correlate in

573
00:34:05,240 --> 00:34:09,239
Speaker 1: their minds with a person's likelihood to repay a loan

574
00:34:10,080 --> 00:34:13,000
Speaker 1: or to default on a loan. And we've got like

575
00:34:13,719 --> 00:34:17,560
Speaker 1: specific stuff they found, Like it's even more obscure than

576
00:34:18,960 --> 00:34:22,400
Speaker 1: this person, you know, goes to Applebee's at five thirty

577
00:34:22,440 --> 00:34:26,600
Speaker 1: every Thursday, which would be a great indicator that you

578
00:34:26,719 --> 00:34:29,279
Speaker 1: are just going to get the best loans, that you

579
00:34:29,280 --> 00:34:33,480
Speaker 1: are a paragon um. But yeah, it's it's things like

580
00:34:34,040 --> 00:34:38,000
Speaker 1: how often do you recharge your phone's battery? How many

581
00:34:38,040 --> 00:34:41,919
Speaker 1: miles do you travel in a given day? Oh, here

582
00:34:41,960 --> 00:34:45,600
Speaker 1: here's my personal favorite one. Uh, and thank you for

583
00:34:45,680 --> 00:34:49,600
Speaker 1: finding this. Ben. When you enter a new contact into

584
00:34:49,640 --> 00:34:52,920
Speaker 1: your phone, do you take the time to put a

585
00:34:53,040 --> 00:34:56,799
Speaker 1: last name in there? And are you capitalizing the first letter?

586
00:34:56,800 --> 00:35:00,960
Speaker 1: Are you making it look like a true good rolodex

587
00:35:01,000 --> 00:35:04,120
Speaker 1: within your phone? Because if you are, you my friend,

588
00:35:04,280 --> 00:35:06,880
Speaker 1: are worthy of the highest of credits? Or do you

589
00:35:06,920 --> 00:35:11,439
Speaker 1: just put Steve weed guy? You know? Like what these

590
00:35:11,480 --> 00:35:14,120
Speaker 1: things matter? I mean it's interesting because it's like it's

591
00:35:14,120 --> 00:35:17,200
Speaker 1: not that far removed from the current credit rating system.

592
00:35:17,280 --> 00:35:21,279
Speaker 1: I mean, it's all about mapping our decisions and penalizing

593
00:35:21,400 --> 00:35:24,200
Speaker 1: us or we're rewarding us accordingly. I mean it's like,

594
00:35:24,280 --> 00:35:29,040
Speaker 1: do we but they're all they're all financially linked, now

595
00:35:29,160 --> 00:35:31,279
Speaker 1: linked to your financials. I get it. But what I'm

596
00:35:31,280 --> 00:35:34,040
Speaker 1: asking you is do you opt in to being tracked

597
00:35:34,040 --> 00:35:37,319
Speaker 1: by experience? Do you opt into being tracked by all

598
00:35:37,360 --> 00:35:40,480
Speaker 1: these credit reporting agencies? It just happens by virtue of

599
00:35:40,480 --> 00:35:43,040
Speaker 1: you having a social Security number, And I mean you

600
00:35:43,040 --> 00:35:45,680
Speaker 1: don't when you get that social Security number, you're an infant.

601
00:35:45,760 --> 00:35:48,319
Speaker 1: You don't have the ability to say I don't want that,

602
00:35:48,760 --> 00:35:51,040
Speaker 1: get me off the grid, you know, so you are

603
00:35:51,120 --> 00:35:54,960
Speaker 1: basically by default part of this system. So we're already

604
00:35:55,000 --> 00:35:57,319
Speaker 1: kind of in this This is just an escalation of it,

605
00:35:57,440 --> 00:36:00,480
Speaker 1: or like almost more something like approaching sets any credit,

606
00:36:00,520 --> 00:36:03,400
Speaker 1: which we've talked about, and the way that uh in

607
00:36:03,400 --> 00:36:06,640
Speaker 1: in China, I believe they use social media status is

608
00:36:06,960 --> 00:36:09,880
Speaker 1: to track you and to prove you for entrance and

609
00:36:10,000 --> 00:36:12,800
Speaker 1: exit and premium flights and all the kind of black

610
00:36:12,840 --> 00:36:16,480
Speaker 1: mirror stuff. You know. So wait, mischion control, give me

611
00:36:16,480 --> 00:36:21,440
Speaker 1: a record scratch rewind. Does this mean some of us

612
00:36:21,480 --> 00:36:24,680
Speaker 1: are asking that always having your phone around like four

613
00:36:25,440 --> 00:36:28,760
Speaker 1: charge or something means you'll be considered a risky person

614
00:36:29,000 --> 00:36:32,319
Speaker 1: loan wise? The answer is yeah, well something like that

615
00:36:32,440 --> 00:36:35,960
Speaker 1: is in the cards. Well let me plug this in then, right.

616
00:36:36,080 --> 00:36:39,759
Speaker 1: The only real question in the conspiracy here is how

617
00:36:39,880 --> 00:36:43,480
Speaker 1: much data they can get, and this is their conspiracy,

618
00:36:43,520 --> 00:36:45,880
Speaker 1: these kinds of entities, and how much they have to

619
00:36:46,000 --> 00:36:51,520
Speaker 1: disclose about their analytical methods, their proprietary algorithms. It is

620
00:36:51,560 --> 00:36:53,839
Speaker 1: safe to say, and this is an assumption, but it's

621
00:36:53,840 --> 00:36:56,279
Speaker 1: safe to say Number one, they want all of the

622
00:36:56,360 --> 00:37:00,719
Speaker 1: data picture some version of that Gary Oldman meme or

623
00:37:00,800 --> 00:37:04,319
Speaker 1: gift where he's screaming everything uh and too, they want

624
00:37:04,320 --> 00:37:07,279
Speaker 1: none of the oversight. Why would you this this as

625
00:37:07,280 --> 00:37:10,520
Speaker 1: a business, it loses its edge if other people can

626
00:37:10,600 --> 00:37:13,560
Speaker 1: do the same thing. So wait, you might if you

627
00:37:13,640 --> 00:37:17,400
Speaker 1: saying what guys, guys, guys, I'm a longtime listener conspiracy realists.

628
00:37:17,640 --> 00:37:20,320
Speaker 1: I don't have a bunch of garbage apps on my phone, Okay,

629
00:37:20,480 --> 00:37:22,520
Speaker 1: and you know, heck, now that I know this might

630
00:37:22,560 --> 00:37:25,920
Speaker 1: affect my financial future, I'm just gonna stick to text.

631
00:37:26,400 --> 00:37:29,000
Speaker 1: I'm just gonna stick to calls because if I don't

632
00:37:29,040 --> 00:37:32,799
Speaker 1: generate a bunch of information, then these people will have

633
00:37:32,960 --> 00:37:36,920
Speaker 1: nothing to use against me, and to that we can

634
00:37:36,920 --> 00:37:43,920
Speaker 1: only respond, well, don't be so sure, Yeah, I wouldn't

635
00:37:43,920 --> 00:37:47,200
Speaker 1: bet on a uh study published in Science. That's right.

636
00:37:47,280 --> 00:37:52,759
Speaker 1: Science found the metadata alone of this information, you know,

637
00:37:52,760 --> 00:37:54,120
Speaker 1: in the same way that we know the n s

638
00:37:54,160 --> 00:37:57,640
Speaker 1: A was tracking getting really good info using only metadata.

639
00:37:57,840 --> 00:38:00,319
Speaker 1: They didn't have to monitor your call. They could just

640
00:38:00,360 --> 00:38:03,080
Speaker 1: tell things by the length of the call and analyze

641
00:38:03,080 --> 00:38:05,040
Speaker 1: that web of who you're calling and who those people

642
00:38:05,040 --> 00:38:07,400
Speaker 1: are calling, etcetera, and then just tracking all of that,

643
00:38:07,440 --> 00:38:10,480
Speaker 1: they can get a pretty decent picture just based on

644
00:38:10,520 --> 00:38:14,360
Speaker 1: that alone. And this study pointed out that this information

645
00:38:14,400 --> 00:38:19,839
Speaker 1: actually can reveal interesting economic UH status type information, just

646
00:38:19,920 --> 00:38:24,000
Speaker 1: things like when the calls were made, the length of

647
00:38:24,040 --> 00:38:28,920
Speaker 1: the calls, um when they were received, when text messages

648
00:38:28,960 --> 00:38:32,000
Speaker 1: were sent, and which cell phone towers the texts or

649
00:38:32,080 --> 00:38:35,840
Speaker 1: calls were pinging off of. And the researchers analyzed again,

650
00:38:36,320 --> 00:38:39,200
Speaker 1: just the metadata we just described, and we're able to

651
00:38:39,239 --> 00:38:42,760
Speaker 1: build a one of those profiles that we're talking about,

652
00:38:43,000 --> 00:38:46,320
Speaker 1: or taking a step further, an algorithm that could predict

653
00:38:46,480 --> 00:38:51,720
Speaker 1: behavior and and could correlate that with wealth or lack

654
00:38:51,960 --> 00:38:56,360
Speaker 1: thereof of a given phone user. And it gets even crazier,

655
00:38:56,520 --> 00:39:00,200
Speaker 1: even more granular. This is I don't know when we

656
00:39:00,239 --> 00:39:03,080
Speaker 1: talk about this stuff, I'm always torn between being like,

657
00:39:03,200 --> 00:39:08,000
Speaker 1: that's amazing and objectively fascinating and impressive, and going that's

658
00:39:08,880 --> 00:39:14,279
Speaker 1: terrifying and objectively frightening. Because they're able to uh, these

659
00:39:14,280 --> 00:39:18,040
Speaker 1: scientists were able to answer even more specific questions again

660
00:39:18,080 --> 00:39:21,040
Speaker 1: just based on that very bare bones data. They were

661
00:39:21,080 --> 00:39:25,400
Speaker 1: able to say, this house obviously doesn't have electricity and therefore,

662
00:39:25,800 --> 00:39:28,719
Speaker 1: if they, you know, can't pay their electric bill, how

663
00:39:28,760 --> 00:39:32,080
Speaker 1: does that work out for their loans? Oh, because it

664
00:39:32,160 --> 00:39:36,560
Speaker 1: wasn't being charged while it was being GEO located there? Wow, Okay,

665
00:39:36,560 --> 00:39:40,040
Speaker 1: but is this somewhere in the terms of service like

666
00:39:40,120 --> 00:39:42,600
Speaker 1: at some point you have to sort of give consent

667
00:39:42,719 --> 00:39:45,440
Speaker 1: for this information to be used in these ways, right

668
00:39:46,000 --> 00:39:48,960
Speaker 1: or no? Is it just by virtue of having the device?

669
00:39:49,000 --> 00:39:51,400
Speaker 1: Like at what point? At what line of text? And

670
00:39:51,440 --> 00:39:55,240
Speaker 1: these massive terms of service? Is that? Is it per app?

671
00:39:55,560 --> 00:39:58,799
Speaker 1: Is it for the whole phone at large? It's tricky. Yeah,

672
00:39:58,840 --> 00:40:02,800
Speaker 1: here's here's my mission for you know, find that piece

673
00:40:02,840 --> 00:40:09,239
Speaker 1: of text. I dare you basically speaking, I'm speaking not hypothetically,

674
00:40:09,320 --> 00:40:12,200
Speaker 1: but it's it's it's of course a a needle in

675
00:40:12,239 --> 00:40:15,960
Speaker 1: a haystack situation. If it even exists. It does, it

676
00:40:16,040 --> 00:40:18,640
Speaker 1: does exist. One of my one of my old colleagues

677
00:40:18,680 --> 00:40:22,640
Speaker 1: actually was mentioned this person on air before, but I'll

678
00:40:22,640 --> 00:40:25,040
Speaker 1: try to keep it kind of anonymous. Uh. They were

679
00:40:25,120 --> 00:40:31,360
Speaker 1: having some pretty good success making readable terms of service

680
00:40:32,000 --> 00:40:35,360
Speaker 1: and conditions. Uh, and then they got their funding pulled

681
00:40:35,840 --> 00:40:39,160
Speaker 1: because there is no benefit to many of these entities

682
00:40:39,239 --> 00:40:43,520
Speaker 1: for uh, the end user to understand those TS documents,

683
00:40:43,880 --> 00:40:46,880
Speaker 1: And usually the line will be something like I'm not

684
00:40:46,960 --> 00:40:50,279
Speaker 1: citing a specific example here, but the line will be

685
00:40:50,360 --> 00:40:55,640
Speaker 1: something like, by agreeing to this service, the customer, the

686
00:40:55,760 --> 00:41:02,920
Speaker 1: user also agrees that the provid fighter can use data

687
00:41:03,040 --> 00:41:08,000
Speaker 1: collected and provide to third parties as necessary to improve service,

688
00:41:08,440 --> 00:41:12,760
Speaker 1: and so they're like, third parties is a huge chasm

689
00:41:12,840 --> 00:41:17,160
Speaker 1: of a term, and so is improved service. Right, they're saying,

690
00:41:17,200 --> 00:41:20,080
Speaker 1: we're improving your service. If they can find any kind

691
00:41:20,080 --> 00:41:22,600
Speaker 1: of rationalization for that, then they can do whatever they want,

692
00:41:22,840 --> 00:41:25,080
Speaker 1: especially because the other thing that always goes with it,

693
00:41:25,400 --> 00:41:28,400
Speaker 1: just like as forest compoud SAPs and carrots, is the

694
00:41:29,080 --> 00:41:32,960
Speaker 1: is that lovely little line. The terms of service can

695
00:41:33,040 --> 00:41:35,240
Speaker 1: change at any time, and they do. They get updated

696
00:41:35,680 --> 00:41:38,759
Speaker 1: pretty frequently. But doesn't I mean you have to like,

697
00:41:38,960 --> 00:41:41,360
Speaker 1: do they serve it to you again? I don't recall

698
00:41:41,560 --> 00:41:45,600
Speaker 1: having been reserved terms of service to to to agree

699
00:41:45,680 --> 00:41:49,480
Speaker 1: again when things have been significantly changed. Sometimes I'll have

700
00:41:49,560 --> 00:41:52,360
Speaker 1: to say there's a privacy announcement or something, but you

701
00:41:52,360 --> 00:41:54,759
Speaker 1: you don't have to sign anything. They're just telling you

702
00:41:54,800 --> 00:41:57,920
Speaker 1: what's happening. Yeah. Well, and sometimes you'll notice, not necessarily

703
00:41:57,920 --> 00:42:00,840
Speaker 1: with iOS but with other device is, in other apps

704
00:42:00,840 --> 00:42:03,879
Speaker 1: and things like that. With an update, you'll just have

705
00:42:03,960 --> 00:42:07,560
Speaker 1: to click I agree again, and you won't even realize

706
00:42:07,560 --> 00:42:10,399
Speaker 1: that you're doing it. I'm serious. You're opening a new

707
00:42:10,440 --> 00:42:12,440
Speaker 1: app that's just being updated, and you're let me get

708
00:42:12,440 --> 00:42:15,000
Speaker 1: past this you don't even realize. I've done it so

709
00:42:15,040 --> 00:42:17,839
Speaker 1: many times in my life. It's insane, so ridiculous. And

710
00:42:17,880 --> 00:42:23,279
Speaker 1: I love the the slick psychological UX design where it's

711
00:42:23,480 --> 00:42:27,520
Speaker 1: um clicking a button that's said like the the yes

712
00:42:27,600 --> 00:42:35,080
Speaker 1: button is disguised as something like uh, okay or thank you, continue, continue, yeah,

713
00:42:35,120 --> 00:42:40,000
Speaker 1: and the no button is nested several different interactions down.

714
00:42:40,360 --> 00:42:43,160
Speaker 1: It's like under a learn more, under a learn more

715
00:42:43,400 --> 00:42:46,040
Speaker 1: under a learn more, or you just can't you can't

716
00:42:46,080 --> 00:42:48,080
Speaker 1: move forward. If you say no, then you're okay, you

717
00:42:48,120 --> 00:42:51,440
Speaker 1: can use it. You will occasionally see this is rarer

718
00:42:51,440 --> 00:42:53,960
Speaker 1: and rarer, I think ones where they will actually force

719
00:42:54,040 --> 00:42:56,520
Speaker 1: you to at the very least scroll all the way

720
00:42:56,560 --> 00:43:00,440
Speaker 1: to the bottom, the implication being okay, I I lasted

721
00:43:00,440 --> 00:43:02,759
Speaker 1: through this. I all of the text was in front

722
00:43:02,760 --> 00:43:05,319
Speaker 1: of my eyeballs at some point. And that's obviously maybe

723
00:43:05,320 --> 00:43:08,880
Speaker 1: to provide more protection for the for the developer, you know,

724
00:43:08,960 --> 00:43:11,719
Speaker 1: for the company, um, but it doesn't seem like a necessity.

725
00:43:11,760 --> 00:43:13,680
Speaker 1: It seems like something they're legal was like, we should

726
00:43:13,760 --> 00:43:17,600
Speaker 1: probably do this just to like cover our asses a

727
00:43:17,640 --> 00:43:22,200
Speaker 1: little more in the most token effort possible. And so

728
00:43:22,480 --> 00:43:24,680
Speaker 1: here we have proven that it doesn't take a bunch

729
00:43:24,719 --> 00:43:28,280
Speaker 1: of data, right. So as for the strategy of using

730
00:43:28,320 --> 00:43:32,279
Speaker 1: a phone less and less right or disclosing less and

731
00:43:32,360 --> 00:43:36,480
Speaker 1: less info UH to later be used against you or

732
00:43:36,520 --> 00:43:39,400
Speaker 1: to just be used in some way with your informed consent,

733
00:43:39,560 --> 00:43:42,360
Speaker 1: which we just talked about, how tricky that is. UM.

734
00:43:42,520 --> 00:43:45,640
Speaker 1: As for that strategy, we're going to have to return

735
00:43:45,800 --> 00:43:48,320
Speaker 1: to the study we mentioned at the top of the show,

736
00:43:48,719 --> 00:43:59,239
Speaker 1: and we'll do this afterward from our sponsor. So we're back.

737
00:43:59,360 --> 00:44:02,000
Speaker 1: Here's this stuff day we mentioned about how often you

738
00:44:02,160 --> 00:44:05,160
Speaker 1: touch your phone or interact with it. There were four

739
00:44:05,320 --> 00:44:09,520
Speaker 1: researchers based in the United Kingdom. They installed a usage

740
00:44:09,680 --> 00:44:14,400
Speaker 1: tracking app consentually on the smartphones of twenty three students

741
00:44:14,400 --> 00:44:17,440
Speaker 1: and faculty at the University of Lincoln. They let it

742
00:44:17,560 --> 00:44:20,840
Speaker 1: run for two weeks and then they examine the results

743
00:44:20,920 --> 00:44:24,279
Speaker 1: and there's an excellent UH summarization of this by an

744
00:44:24,320 --> 00:44:28,040
Speaker 1: author named Nicholas car They realized that just by measuring

745
00:44:28,280 --> 00:44:32,120
Speaker 1: one simple thing, they could tell a whole host of information,

746
00:44:32,160 --> 00:44:34,840
Speaker 1: a whole bunch of things about a person's daily routine.

747
00:44:35,080 --> 00:44:39,040
Speaker 1: And all that is is when an individual is using

748
00:44:39,040 --> 00:44:41,759
Speaker 1: their phone. That's really all you have to measure, and

749
00:44:41,800 --> 00:44:45,080
Speaker 1: you can see almost the whole picture. When are you asleep?

750
00:44:45,840 --> 00:44:48,080
Speaker 1: Phone usage will tell you when do you wake up.

751
00:44:48,200 --> 00:44:50,440
Speaker 1: It turns out that all of these test subjects except

752
00:44:50,480 --> 00:44:53,320
Speaker 1: one use their phone as an alarm clock, and a

753
00:44:53,800 --> 00:44:56,400
Speaker 1: pent of them said the last thing they do before

754
00:44:56,400 --> 00:44:59,360
Speaker 1: they go to sleep is check their phone as for

755
00:44:59,400 --> 00:45:02,759
Speaker 1: gaps in when usage during the day. Pretty good indicator

756
00:45:02,800 --> 00:45:06,520
Speaker 1: of a nap. It turns out, how crazy a nap?

757
00:45:07,000 --> 00:45:08,560
Speaker 1: I can't. I don't know how to nap. I'm really

758
00:45:08,560 --> 00:45:11,120
Speaker 1: bad at napping. Do you guys know how to nap? Oh?

759
00:45:11,200 --> 00:45:13,160
Speaker 1: We need to ask everybody out in the UK, like,

760
00:45:13,400 --> 00:45:16,640
Speaker 1: is it easier to nap there? Or what's the deal?

761
00:45:17,000 --> 00:45:19,680
Speaker 1: Is it the gloomy weather that helps? Could do it?

762
00:45:19,760 --> 00:45:23,759
Speaker 1: I could do? I actually have the opposite problem. No,

763
00:45:23,960 --> 00:45:27,400
Speaker 1: I can't sleep for a like six hours in a stretch,

764
00:45:27,520 --> 00:45:30,719
Speaker 1: So I just kind of The pandemic has made a

765
00:45:30,760 --> 00:45:33,840
Speaker 1: real weird too, you know, grab grab it where you

766
00:45:33,880 --> 00:45:37,719
Speaker 1: can A few winks here and there, As they say, exactly,

767
00:45:38,000 --> 00:45:41,560
Speaker 1: and why does this not sleep betterns? But why does

768
00:45:41,600 --> 00:45:44,319
Speaker 1: this matter that so much can be gleaned from this

769
00:45:44,480 --> 00:45:49,080
Speaker 1: innocuous information. It's because both of those studies depend entirely

770
00:45:49,160 --> 00:45:54,800
Speaker 1: on this very basic info, and that means that there's

771
00:45:54,840 --> 00:45:58,600
Speaker 1: an entire new universe out there. When we look at

772
00:45:58,640 --> 00:46:00,920
Speaker 1: the other stuff, the other dad to that can be pulled,

773
00:46:00,960 --> 00:46:03,520
Speaker 1: we get to the world of apps, how we use them,

774
00:46:03,719 --> 00:46:07,360
Speaker 1: when we use them, When, for instance, do you tend

775
00:46:07,400 --> 00:46:10,319
Speaker 1: to order delivery food? Or when do you when do

776
00:46:10,360 --> 00:46:12,560
Speaker 1: you search? What do you search for? What do we watch,

777
00:46:12,640 --> 00:46:15,479
Speaker 1: what do we listen to? When do we do that? What?

778
00:46:15,480 --> 00:46:18,080
Speaker 1: What kind of pictures do we post on social media?

779
00:46:18,080 --> 00:46:20,560
Speaker 1: And what kind of pictures do we like? Even if

780
00:46:20,600 --> 00:46:23,880
Speaker 1: those are private to you, they are not private to

781
00:46:24,160 --> 00:46:28,799
Speaker 1: the companies that have the ability to wield this information.

782
00:46:29,160 --> 00:46:31,880
Speaker 1: We're building the sculptures of ourselves, and most of the

783
00:46:31,920 --> 00:46:34,920
Speaker 1: time we don't know how sophisticated they are well. And

784
00:46:35,040 --> 00:46:37,319
Speaker 1: I don't know if we've ever gotten fully to the

785
00:46:37,320 --> 00:46:38,920
Speaker 1: bottom of this, but I think we've all had that

786
00:46:38,960 --> 00:46:43,319
Speaker 1: experience or we had some little throwaway conversation about a thing,

787
00:46:43,840 --> 00:46:47,160
Speaker 1: a topic, a movie, a record, what have you, and

788
00:46:47,160 --> 00:46:49,120
Speaker 1: then all of a sudden you're getting served up ads

789
00:46:49,160 --> 00:46:51,640
Speaker 1: for that thing, and in your mind it could only

790
00:46:51,680 --> 00:46:54,440
Speaker 1: be based on this notion that your phone is listening

791
00:46:54,480 --> 00:46:57,479
Speaker 1: to you. And I think we we did cover something

792
00:46:57,520 --> 00:47:00,600
Speaker 1: along these lines where you know the microphone is on

793
00:47:01,200 --> 00:47:04,600
Speaker 1: and transmitting or what or what. I don't especially if

794
00:47:04,680 --> 00:47:09,360
Speaker 1: you're using on an iOS devicerie or on any other device.

795
00:47:09,600 --> 00:47:11,839
Speaker 1: Your what is the what is the term for that,

796
00:47:11,880 --> 00:47:17,120
Speaker 1: the concierge or your assistant whatever, whatever the personal assistant is,

797
00:47:17,360 --> 00:47:20,920
Speaker 1: it is always listening. There is a Google Home like

798
00:47:21,719 --> 00:47:24,400
Speaker 1: on the other side of this wall. I'm pointing directly

799
00:47:24,560 --> 00:47:29,120
Speaker 1: ahead of me for everyone listening. And I realized that

800
00:47:29,160 --> 00:47:31,480
Speaker 1: while I'm in my office with the door closed, on

801
00:47:31,520 --> 00:47:34,200
Speaker 1: the other side of that wall, it can hear me.

802
00:47:34,680 --> 00:47:38,160
Speaker 1: So I I am just now I'm having this realization

803
00:47:38,160 --> 00:47:42,479
Speaker 1: in real time. Every time we podcast, my Google Home

804
00:47:42,719 --> 00:47:47,000
Speaker 1: is listening to everything. I'm saying, Hey Google, no, no, no,

805
00:47:50,080 --> 00:47:58,120
Speaker 1: but everyone at homes Google Homes just went bonkers. Just okay, sorry, um,

806
00:47:58,360 --> 00:47:59,919
Speaker 1: I don't even know where we were. That That really

807
00:48:00,080 --> 00:48:03,279
Speaker 1: just weirded me out. I'm gonna have to disabled that

808
00:48:03,320 --> 00:48:07,319
Speaker 1: thing somehow. Here's a here's a jet. I'm not being sarcastic.

809
00:48:07,320 --> 00:48:09,920
Speaker 1: Here's a genuinely fun thing. I've been doing an experiment

810
00:48:10,200 --> 00:48:13,560
Speaker 1: that you can try at home, folks. When I was

811
00:48:13,680 --> 00:48:17,280
Speaker 1: convinced about this, and that was several years ago, based

812
00:48:17,320 --> 00:48:19,680
Speaker 1: on you know, our collective work here on stuff they want.

813
00:48:19,760 --> 00:48:23,440
Speaker 1: You know, I decided a while back that I was

814
00:48:23,480 --> 00:48:26,440
Speaker 1: going to try to hack my targeted ads if I

815
00:48:26,440 --> 00:48:29,160
Speaker 1: couldn't get away from them, because you can't. It's very

816
00:48:29,160 --> 00:48:35,080
Speaker 1: difficult to a hundred percent eliminate this phenomenon. So I said, Okay, well,

817
00:48:35,120 --> 00:48:39,480
Speaker 1: maybe I'll just try to make the digital autobiography of

818
00:48:39,520 --> 00:48:43,919
Speaker 1: me into a very like elitist, wealthy person. I think

819
00:48:43,920 --> 00:48:46,279
Speaker 1: we mentioned this earlier, right when I started like just

820
00:48:46,400 --> 00:48:52,120
Speaker 1: searching for fancy watches, yachts, Yes, yachts, and I've had

821
00:48:52,239 --> 00:48:56,000
Speaker 1: I've I've actually had some good results well exclusively listening

822
00:48:56,040 --> 00:48:59,960
Speaker 1: to Steely Dan, you know, and just really putting out

823
00:49:00,040 --> 00:49:02,239
Speaker 1: that vibe into the universe. You know that you are

824
00:49:02,280 --> 00:49:06,840
Speaker 1: a yachtsman, Yeah, searching searching for stuff like dangers of

825
00:49:06,920 --> 00:49:13,200
Speaker 1: peasant uprising and and order endangered me, you know, all

826
00:49:13,280 --> 00:49:17,520
Speaker 1: all the hits dogs, best Fox, that's a good one.

827
00:49:17,600 --> 00:49:20,799
Speaker 1: Hang on, I'm gonna make a note. But but you're right,

828
00:49:21,239 --> 00:49:25,360
Speaker 1: I mean, we were, We're right here. The companies that

829
00:49:25,400 --> 00:49:28,080
Speaker 1: are seeking to use this data are going to make big,

830
00:49:28,200 --> 00:49:32,280
Speaker 1: life changing decisions based on their perceived their self perceived

831
00:49:32,320 --> 00:49:36,480
Speaker 1: ability to predict what they see as your future actions.

832
00:49:36,719 --> 00:49:40,920
Speaker 1: This could be one of the most amazing, noble, beautiful

833
00:49:41,040 --> 00:49:44,880
Speaker 1: things in the story of human technology, because think about it,

834
00:49:45,520 --> 00:49:48,320
Speaker 1: this would mean that it is possible for the group's

835
00:49:48,440 --> 00:49:51,960
Speaker 1: add that are aggregating the information like this to step

836
00:49:52,000 --> 00:49:56,480
Speaker 1: in and say, provide preventative financial or mental health counseling.

837
00:49:56,880 --> 00:49:59,440
Speaker 1: If their algorithm indicates that someone's going to be in

838
00:49:59,440 --> 00:50:02,120
Speaker 1: trouble down the road, they could save people in a

839
00:50:02,200 --> 00:50:04,799
Speaker 1: very real way. Oh yeah, and and that's exactly what's

840
00:50:04,800 --> 00:50:11,960
Speaker 1: going to happen. Yeah, well right, I mean, are we

841
00:50:12,000 --> 00:50:17,680
Speaker 1: relying on like benevolence on the part of these technology companies. Well,

842
00:50:17,800 --> 00:50:20,839
Speaker 1: I mean maybe we're seeing a turn, guys. Maybe this

843
00:50:20,920 --> 00:50:23,839
Speaker 1: is this is like our bright future. Maybe we're gonna

844
00:50:23,840 --> 00:50:27,200
Speaker 1: be okay, yeah, maybe they'll all be like Bill Murray's

845
00:50:27,320 --> 00:50:29,719
Speaker 1: character at the end of Scooged. I don't know, but

846
00:50:29,880 --> 00:50:33,800
Speaker 1: it's you can tell where a lot of fun at parties, folks,

847
00:50:33,840 --> 00:50:37,279
Speaker 1: Because that's not going to happen. That's not what's happening now.

848
00:50:37,600 --> 00:50:40,640
Speaker 1: There's just more money to be made in creating these

849
00:50:40,719 --> 00:50:46,600
Speaker 1: extremely educated guesses about your future and then punishing you

850
00:50:46,960 --> 00:50:51,480
Speaker 1: for those guesses. Again, they are guesses in advance. To

851
00:50:51,600 --> 00:50:56,719
Speaker 1: paraphrase minority report, this is sort of like financial pre crime. Um.

852
00:50:56,760 --> 00:51:00,399
Speaker 1: And I like the point you made earlier about how

853
00:51:00,440 --> 00:51:05,960
Speaker 1: nobody really opts into credit bureaus in the US at least,

854
00:51:07,120 --> 00:51:11,160
Speaker 1: and it's it's the same thing. But to be fair,

855
00:51:11,280 --> 00:51:14,560
Speaker 1: it would be misleading for us to talk about these

856
00:51:14,600 --> 00:51:20,000
Speaker 1: inarguably terrible consequences inheriting the strategy if we didn't also

857
00:51:20,080 --> 00:51:23,640
Speaker 1: point out the arguments made by the proponents. And these

858
00:51:23,920 --> 00:51:27,759
Speaker 1: arguments are are pretty valid if theoretical. This is the

859
00:51:27,960 --> 00:51:30,680
Speaker 1: sort of the other side of the money grab. Yeah,

860
00:51:30,719 --> 00:51:34,440
Speaker 1: I mean, there is of course this notion that this

861
00:51:34,520 --> 00:51:37,279
Speaker 1: is exactly what we want, This is exactly what we need,

862
00:51:37,800 --> 00:51:41,640
Speaker 1: we deserve this, this is giving us better results, It's

863
00:51:41,640 --> 00:51:46,200
Speaker 1: allowing us to be served better information, less redundant you know.

864
00:51:46,560 --> 00:51:50,600
Speaker 1: First off, as as is discussed in behavior Revealed in

865
00:51:50,680 --> 00:51:55,200
Speaker 1: Mobile Phone Usage Predicts Credit Repayment by Daniel bjork A,

866
00:51:55,280 --> 00:51:59,320
Speaker 1: grin Uh and Darryl Grisson, many households in the developing

867
00:51:59,320 --> 00:52:04,400
Speaker 1: world do not have formal financial history period, no established credit,

868
00:52:04,920 --> 00:52:07,440
Speaker 1: meaning the odds are massively stacked against them when it

869
00:52:07,440 --> 00:52:09,840
Speaker 1: comes time to ask for a loan. So, outside of

870
00:52:09,840 --> 00:52:12,680
Speaker 1: what I just said initially, um, the idea of serving

871
00:52:12,719 --> 00:52:15,239
Speaker 1: us better results, this is a very very important and

872
00:52:15,280 --> 00:52:18,279
Speaker 1: potentially positive thing. I know plenty of people that just

873
00:52:18,320 --> 00:52:20,400
Speaker 1: decided they were too freaked out to ever get a

874
00:52:20,440 --> 00:52:23,640
Speaker 1: credit card, and now they're thirty six, thirty seven years

875
00:52:23,640 --> 00:52:26,800
Speaker 1: old and have zero credit. Where do you go from there? Well,

876
00:52:27,040 --> 00:52:31,279
Speaker 1: thankfully you've you've got your mobile phone and you're doing

877
00:52:31,320 --> 00:52:33,799
Speaker 1: all your stuff on it. And these companies now have

878
00:52:33,880 --> 00:52:37,719
Speaker 1: an opportunity to look at that data and maybe, just

879
00:52:37,840 --> 00:52:40,560
Speaker 1: maybe by using it, they're going to be able to

880
00:52:40,600 --> 00:52:44,440
Speaker 1: extend credit to you or to any you know, to

881
00:52:44,520 --> 00:52:47,279
Speaker 1: anyone on the what would be considered the fringes of

882
00:52:47,320 --> 00:52:50,800
Speaker 1: the financial world, people that don't have that established credit,

883
00:52:51,280 --> 00:52:54,239
Speaker 1: and with that data, it's giving them an insight in

884
00:52:54,920 --> 00:52:59,080
Speaker 1: to essentially predict what your credit will look like, what

885
00:52:59,239 --> 00:53:03,240
Speaker 1: your financial dual history will be like. That so weird,

886
00:53:04,160 --> 00:53:06,239
Speaker 1: I mean, And and it's a that's a positive right

887
00:53:06,840 --> 00:53:09,880
Speaker 1: somebody who needs alone or needs to establish credit but

888
00:53:09,960 --> 00:53:13,960
Speaker 1: hasn't yet what this could be a way in And

889
00:53:14,000 --> 00:53:18,080
Speaker 1: their method actually is better than the traditional methods using

890
00:53:18,080 --> 00:53:20,600
Speaker 1: credit borrow information. But wouldn't you think you would have

891
00:53:20,640 --> 00:53:23,600
Speaker 1: to be like, Okay, I'm on board. Here's my stuff,

892
00:53:24,120 --> 00:53:26,640
Speaker 1: take a look, make an assessment in the same way

893
00:53:26,680 --> 00:53:30,680
Speaker 1: you'd submit documents for a credit check or whatever for

894
00:53:30,760 --> 00:53:34,480
Speaker 1: like getting a mortgage, like they already have it. Like

895
00:53:34,520 --> 00:53:36,439
Speaker 1: that's my question. I mean, I guess the answer is yes.

896
00:53:37,040 --> 00:53:38,480
Speaker 1: A least I would just want to know that I

897
00:53:38,480 --> 00:53:41,239
Speaker 1: could sort of turn the switch on and off and

898
00:53:41,280 --> 00:53:44,160
Speaker 1: be like, Okay, I need you to use this information here.

899
00:53:44,200 --> 00:53:46,920
Speaker 1: I consent for you to use my data in this way.

900
00:53:47,239 --> 00:53:51,040
Speaker 1: But that's blue sky. I mean, that's I don't know. Yeah,

901
00:53:51,239 --> 00:53:55,480
Speaker 1: it's tough, and it's it's it's hidden in byzantine fine

902
00:53:55,560 --> 00:53:59,600
Speaker 1: prints pretty often. And when we're talking about this approach,

903
00:53:59,840 --> 00:54:02,640
Speaker 1: or at least this specific study, they're talking about the

904
00:54:02,719 --> 00:54:05,680
Speaker 1: developing world, and it is valid. It could be huge

905
00:54:06,280 --> 00:54:11,080
Speaker 1: because this would open possibly open the doors of financial

906
00:54:11,080 --> 00:54:16,719
Speaker 1: opportunity for people that the industry calls unbanked, which I

907
00:54:16,760 --> 00:54:19,960
Speaker 1: think is a dehumanizing term. It basically means people who

908
00:54:20,040 --> 00:54:23,880
Speaker 1: don't have that financial history. They don't have mortgages, credit cards,

909
00:54:24,480 --> 00:54:28,960
Speaker 1: checking accounts, etcetera, etcetera. Uh, they probably use their mobile

910
00:54:29,000 --> 00:54:33,600
Speaker 1: phone or us an entirely online banking system or transactional

911
00:54:33,640 --> 00:54:36,840
Speaker 1: app to trade stuff. So this could help those people.

912
00:54:36,880 --> 00:54:39,839
Speaker 1: Of course, if the models are accurate, which they seem

913
00:54:39,920 --> 00:54:42,520
Speaker 1: to be, and if they're used in an ethical way.

914
00:54:43,200 --> 00:54:51,120
Speaker 1: Ha ha. Yes, it's not too too I mean it's

915
00:54:51,120 --> 00:54:54,279
Speaker 1: sort of an escalation in a different, uh you know,

916
00:54:54,560 --> 00:54:57,800
Speaker 1: step in this process. But it's like Venmo gave people

917
00:54:57,800 --> 00:55:00,560
Speaker 1: that didn't have a bank account the ability to digitally

918
00:55:00,680 --> 00:55:03,400
Speaker 1: send and receive funds, and that's a big deal for

919
00:55:03,440 --> 00:55:05,319
Speaker 1: a lot of people too. So I mean, I can

920
00:55:05,360 --> 00:55:09,479
Speaker 1: I can see the potential positive side of this. Yeah,

921
00:55:09,480 --> 00:55:12,840
Speaker 1: but they had to have bank accounts. Do you do

922
00:55:12,840 --> 00:55:15,120
Speaker 1: you have some kind of money? Oh well, okay, so

923
00:55:15,160 --> 00:55:16,920
Speaker 1: you have to have a PayPal account. That's I don't

924
00:55:16,920 --> 00:55:18,400
Speaker 1: think they even have to anymore. You can have it.

925
00:55:18,440 --> 00:55:22,279
Speaker 1: You can get a Venmo debit card where independent of

926
00:55:22,320 --> 00:55:24,600
Speaker 1: any bank, you can link a bank account to Venmo,

927
00:55:24,719 --> 00:55:28,640
Speaker 1: but Venmo money can go into a Venmo debit card. Um.

928
00:55:28,719 --> 00:55:30,719
Speaker 1: And then there's even stuff for like kids, like my

929
00:55:30,800 --> 00:55:33,200
Speaker 1: daughter has this thing called green Light that's a debit

930
00:55:33,239 --> 00:55:35,279
Speaker 1: card for kids, and she doesn't she's not old enough

931
00:55:35,320 --> 00:55:37,520
Speaker 1: to have a bank account. So it's you know, there

932
00:55:37,520 --> 00:55:40,439
Speaker 1: are things that again, in this financial side of things

933
00:55:40,480 --> 00:55:43,120
Speaker 1: could be seen as like, you know, forward thinking and

934
00:55:43,400 --> 00:55:47,280
Speaker 1: positive because if you're not, if you don't have access

935
00:55:47,320 --> 00:55:50,160
Speaker 1: to funds online, you are cut out of a whole

936
00:55:50,200 --> 00:55:54,080
Speaker 1: lot of the economy, you know, because especially being stuck

937
00:55:54,120 --> 00:55:56,920
Speaker 1: at home like we have been for so long. I mean, well,

938
00:55:56,920 --> 00:55:59,080
Speaker 1: if you don't want to go to the stories, you're immunocompromise.

939
00:55:59,120 --> 00:56:01,120
Speaker 1: You need to be able to your grocery is using

940
00:56:01,480 --> 00:56:03,759
Speaker 1: you know, one of these apps, and you need to

941
00:56:03,800 --> 00:56:05,480
Speaker 1: be able to pay for it somehow. Yeah, and I

942
00:56:05,480 --> 00:56:08,480
Speaker 1: think this really comes into play in again in the

943
00:56:08,520 --> 00:56:11,880
Speaker 1: developing world. Will you live in a region with no infrastructure?

944
00:56:12,120 --> 00:56:15,399
Speaker 1: You know what I mean, there's there's literally not an

945
00:56:15,400 --> 00:56:18,560
Speaker 1: a t M in eighty miles of you or something

946
00:56:18,640 --> 00:56:22,919
Speaker 1: like that, uh, or the kilometers. Your results may vary.

947
00:56:23,280 --> 00:56:29,280
Speaker 1: So this this stuff, we can agree can be tremendously helpful.

948
00:56:29,680 --> 00:56:32,080
Speaker 1: But what we're talking about is the next step in

949
00:56:32,080 --> 00:56:36,759
Speaker 1: that process using that information for or against someone. And

950
00:56:36,960 --> 00:56:39,680
Speaker 1: there are people who are trying to make a more

951
00:56:39,800 --> 00:56:44,200
Speaker 1: nuanced approach, people like Alaying Shima. He's been working on

952
00:56:44,520 --> 00:56:49,120
Speaker 1: limited applications of the strategy, trying to build some fences

953
00:56:49,160 --> 00:56:52,359
Speaker 1: around what can and can't be used. Just last year

954
00:56:52,560 --> 00:56:56,360
Speaker 1: he wrote something called effective credit scoring using limited mobile

955
00:56:56,440 --> 00:57:00,640
Speaker 1: phone data, and he says, look, there are uns of

956
00:57:01,600 --> 00:57:06,120
Speaker 1: potential privacy risk in these companies knowing everything about you,

957
00:57:06,600 --> 00:57:09,680
Speaker 1: especially if you don't have again a real kind of

958
00:57:09,719 --> 00:57:13,160
Speaker 1: informed consent. So he says, we can get the same

959
00:57:13,719 --> 00:57:17,680
Speaker 1: results with a more ethical approach. And all that he

960
00:57:17,760 --> 00:57:23,280
Speaker 1: did was measure what's called airtime recharge data or data

961
00:57:23,440 --> 00:57:26,800
Speaker 1: whatever you want to refer to it as uh, this

962
00:57:27,000 --> 00:57:31,320
Speaker 1: is this is a term that describes when people paid

963
00:57:31,480 --> 00:57:34,880
Speaker 1: or re up on their prepaid mobile phones. Right, so

964
00:57:35,240 --> 00:57:38,880
Speaker 1: you know, I've I've prepaid for like a month or

965
00:57:39,000 --> 00:57:41,920
Speaker 1: or whatever or x amount of hours, and then I

966
00:57:42,000 --> 00:57:45,400
Speaker 1: come back and I re up at this given schedule.

967
00:57:45,720 --> 00:57:49,960
Speaker 1: Just using that, they can build a similar credit prediction plan.

968
00:57:50,040 --> 00:57:51,960
Speaker 1: But isn't the whole point of a prepaid phone that

969
00:57:52,000 --> 00:57:55,120
Speaker 1: you have anonymity and and that you you aren't your

970
00:57:55,680 --> 00:57:59,200
Speaker 1: name or identity isn't tied to it. I guess that's

971
00:57:59,240 --> 00:58:00,720
Speaker 1: not the same as a burn her phone. You could

972
00:58:00,720 --> 00:58:03,600
Speaker 1: have like a prepaid service where you use the same

973
00:58:03,600 --> 00:58:07,560
Speaker 1: phone and then re up at But there's two completely

974
00:58:07,560 --> 00:58:10,680
Speaker 1: different things. Or there are a lot of people in

975
00:58:10,720 --> 00:58:13,520
Speaker 1: the world who have a a phone that they just

976
00:58:13,560 --> 00:58:18,720
Speaker 1: pay for the the amount of data rather than you know,

977
00:58:18,760 --> 00:58:21,720
Speaker 1: a monthly charge or anything like that. But there's also

978
00:58:21,800 --> 00:58:24,480
Speaker 1: ones where you can just buy a card, pay for

979
00:58:24,560 --> 00:58:26,240
Speaker 1: it at the gas station and then just enter the

980
00:58:26,280 --> 00:58:29,959
Speaker 1: code and then you don't have any identity information tied

981
00:58:30,000 --> 00:58:33,760
Speaker 1: to it. That's all similar technology to different uses, you

982
00:58:33,760 --> 00:58:37,200
Speaker 1: know what I mean? Got it? Uh? And for a

983
00:58:37,280 --> 00:58:42,000
Speaker 1: lot of people, the entry point into buying full phone

984
00:58:42,040 --> 00:58:45,800
Speaker 1: and then subscribing to a yearly plan is just too high.

985
00:58:45,840 --> 00:58:49,920
Speaker 1: It's just unrealistic. So mobile phones have I would prepaid

986
00:58:49,920 --> 00:58:52,320
Speaker 1: mobile phones, I would say I have to a degree

987
00:58:52,320 --> 00:58:57,720
Speaker 1: greatly democratized access to information. But again, none of this

988
00:58:57,800 --> 00:59:04,040
Speaker 1: stuff is without potential misuse. And then here's here's the

989
00:59:04,160 --> 00:59:08,280
Speaker 1: third thing. So the third argument for it is lending

990
00:59:08,320 --> 00:59:13,040
Speaker 1: institutions are capitalistic. They don't get to continue existing if

991
00:59:13,080 --> 00:59:15,920
Speaker 1: every loan they make results in defaulting, then they're in

992
00:59:15,960 --> 00:59:19,280
Speaker 1: deep water. So we can't expect them not to use

993
00:59:19,360 --> 00:59:23,800
Speaker 1: every single level available to maximize their profits while minimizing

994
00:59:23,840 --> 00:59:28,120
Speaker 1: their risk. And to be extremely blunt, we cannot expect

995
00:59:28,120 --> 00:59:31,800
Speaker 1: these institutions to adhere to codes of ethics unless those

996
00:59:31,840 --> 00:59:38,040
Speaker 1: things are continually enforced with serious consequences. Crime and fines

997
00:59:38,080 --> 00:59:42,600
Speaker 1: for crime have since we began this show been just

998
00:59:42,640 --> 00:59:46,000
Speaker 1: a cost of doing business for most banks. Yeah, I

999
00:59:46,640 --> 00:59:50,200
Speaker 1: think we've proven that countless times on on just on

1000
00:59:50,280 --> 00:59:55,200
Speaker 1: this show, and you know, history and articles and reality

1001
00:59:55,520 --> 01:00:00,320
Speaker 1: have further proven it way more than that. And so

1002
01:00:01,360 --> 01:00:04,720
Speaker 1: you know that that that kind of resigned, resigned grown

1003
01:00:04,960 --> 01:00:06,800
Speaker 1: means that we're close to the end of the show.

1004
01:00:07,120 --> 01:00:09,200
Speaker 1: There are some other things we've yet to talk about

1005
01:00:09,280 --> 01:00:13,439
Speaker 1: that can also leverage this technology. The medical industry using

1006
01:00:13,480 --> 01:00:17,840
Speaker 1: similar methods to predict future or present medical conditions. The

1007
01:00:17,920 --> 01:00:21,760
Speaker 1: law enforcement industry expanding its existing use of these tactics

1008
01:00:21,800 --> 01:00:25,000
Speaker 1: to predict crime, other rogue entities. If we want to

1009
01:00:25,040 --> 01:00:28,760
Speaker 1: get really crazy from foreign powers, whatever your country is,

1010
01:00:28,800 --> 01:00:32,880
Speaker 1: somebody from another country using those tactics to say, identify

1011
01:00:33,040 --> 01:00:37,120
Speaker 1: target and turn assets. The dark sky is really the

1012
01:00:37,160 --> 01:00:40,520
Speaker 1: limit here. We're way past the blue version. And it's

1013
01:00:40,520 --> 01:00:43,680
Speaker 1: not a conspiracy theory. It's not some scary future thing.

1014
01:00:43,960 --> 01:00:48,800
Speaker 1: It is a conspiracy. It's real. It's happening, and uh,

1015
01:00:48,920 --> 01:00:50,840
Speaker 1: a lot of people are just not aware that their

1016
01:00:50,960 --> 01:00:53,400
Speaker 1: data is being used in this way or will be

1017
01:00:53,520 --> 01:00:56,520
Speaker 1: used in this way very soon. Yeah, so what do

1018
01:00:56,560 --> 01:00:58,320
Speaker 1: you think I mean? Is this something that keeps you

1019
01:00:58,440 --> 01:01:01,120
Speaker 1: up nights? Are you like any folks or you're you know,

1020
01:01:01,680 --> 01:01:04,919
Speaker 1: we've done the research. We know this stuff has nefarious

1021
01:01:05,400 --> 01:01:08,160
Speaker 1: kind of implications. But it's like a trade off. But

1022
01:01:08,240 --> 01:01:10,640
Speaker 1: I get my cool free apps and I get all

1023
01:01:10,640 --> 01:01:12,800
Speaker 1: this other stuff, and it's worth it to me to

1024
01:01:12,880 --> 01:01:15,120
Speaker 1: do that trade off. Is that I'm saying speaking the

1025
01:01:15,200 --> 01:01:18,160
Speaker 1: Royal we hypothetically Do you feel like that or do

1026
01:01:18,200 --> 01:01:20,720
Speaker 1: you feel like you need to limit your use of

1027
01:01:20,760 --> 01:01:22,680
Speaker 1: this stuff and get as off the grid as humanly

1028
01:01:22,760 --> 01:01:25,240
Speaker 1: possible in this day and age. Is this a good thing?

1029
01:01:25,360 --> 01:01:28,120
Speaker 1: Is this a bad thing? Let us know what you think. Yeah,

1030
01:01:28,200 --> 01:01:31,800
Speaker 1: and especially contact us if you have any good ways

1031
01:01:31,840 --> 01:01:35,520
Speaker 1: to subvert some of the plans that are at work

1032
01:01:35,560 --> 01:01:40,040
Speaker 1: here um where we're particularly interested in those, you know,

1033
01:01:40,120 --> 01:01:44,000
Speaker 1: anything we've discussed it before, anything from a VPN to

1034
01:01:44,720 --> 01:01:47,600
Speaker 1: you know, your your actual settings on your device, like

1035
01:01:47,640 --> 01:01:50,080
Speaker 1: what are some things that you do to protect yourself

1036
01:01:50,440 --> 01:01:53,760
Speaker 1: and what can help out your fellow listeners by letting

1037
01:01:53,760 --> 01:01:57,280
Speaker 1: them know about it. You can find us on Twitter, Facebook,

1038
01:01:57,360 --> 01:02:02,120
Speaker 1: Oh god, wait what are you doing again? Instagram? Uh,

1039
01:02:02,200 --> 01:02:07,760
Speaker 1: We're we're on tumbler and what else bumbles tender you

1040
01:02:07,800 --> 01:02:13,880
Speaker 1: can find. Yeah, we're on micro loans. It's all social media,

1041
01:02:14,000 --> 01:02:16,960
Speaker 1: it's all coming together, it's all one. We are one,

1042
01:02:18,040 --> 01:02:21,360
Speaker 1: this castile soap. Wait what I thought you were going

1043
01:02:21,440 --> 01:02:25,640
Speaker 1: to say? We are one eight three three stt w

1044
01:02:26,000 --> 01:02:30,800
Speaker 1: y t K. We are definitely that one for sure. Honestly,

1045
01:02:30,840 --> 01:02:35,160
Speaker 1: that's probably the least connected way you can get in

1046
01:02:35,200 --> 01:02:37,520
Speaker 1: touch with us, where you can just send us that

1047
01:02:37,800 --> 01:02:41,000
Speaker 1: send us your voice in electronic form and let us

1048
01:02:41,000 --> 01:02:42,920
Speaker 1: know if you want to be anonymized or don't want

1049
01:02:42,960 --> 01:02:44,680
Speaker 1: us to use it, or if you want us to

1050
01:02:44,680 --> 01:02:46,400
Speaker 1: refer to you as something else or what have you.

1051
01:02:46,440 --> 01:02:48,440
Speaker 1: Will we will abide by those things because we are

1052
01:02:48,440 --> 01:02:51,520
Speaker 1: not cold, uncarrying algorithms. We are in fact human people

1053
01:02:53,000 --> 01:02:55,640
Speaker 1: as such. It's true, but we just found out that

1054
01:02:56,240 --> 01:02:59,640
Speaker 1: these guys are trying to take our voices, right, what's

1055
01:02:59,640 --> 01:03:03,520
Speaker 1: going on? Vapp voppel gangers. We've we've gone too far.

1056
01:03:04,240 --> 01:03:09,960
Speaker 1: Oh no, And and if be afraid, it'd be very afraid.

1057
01:03:10,080 --> 01:03:13,920
Speaker 1: I mean you know, uh Likenel said he he had

1058
01:03:13,920 --> 01:03:17,800
Speaker 1: man or humans just like anybody else and to show

1059
01:03:18,000 --> 01:03:22,000
Speaker 1: here from you, So feel free to send us an email.

1060
01:03:22,080 --> 01:03:25,400
Speaker 1: If you don't care for social media or telephones, you

1061
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Speaker 1: can reach us seven until this whole thing burns down.

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Speaker 1: We are conspiracy at i heart radio dot com. Stuff

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Speaker 1: they don't want you to know is a production of

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Speaker 1: I heart Radio. For more podcasts from my heart Radio,

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Speaker 1: listen to your favorite shows.