1
00:00:00,280 --> 00:00:02,600
Speaker 1: Guess what will what's that man? Go? So do you

2
00:00:02,600 --> 00:00:05,320
Speaker 1: remember ao hell? Like, did you or your friends ever

3
00:00:05,400 --> 00:00:07,920
Speaker 1: use this? I mean, I know a O L. I

4
00:00:07,920 --> 00:00:12,240
Speaker 1: can't say I remember ao LL. Right. So ao hell

5
00:00:12,360 --> 00:00:14,120
Speaker 1: was kind of a hacking program you could use in

6
00:00:14,120 --> 00:00:16,200
Speaker 1: the early days of the Internet. And this was back

7
00:00:16,200 --> 00:00:19,079
Speaker 1: when I was like twelve or thirteen. I mean I

8
00:00:19,200 --> 00:00:21,720
Speaker 1: never had it, like I was never a great programmer

9
00:00:21,880 --> 00:00:24,040
Speaker 1: super into that side of the internet, like I was

10
00:00:24,120 --> 00:00:28,920
Speaker 1: too busy reading in Carter but right, but sometimes I'd

11
00:00:28,920 --> 00:00:30,840
Speaker 1: go over to my friend's houses and watched them play

12
00:00:30,880 --> 00:00:33,560
Speaker 1: with it. And the thing is, you could cause all

13
00:00:33,680 --> 00:00:35,760
Speaker 1: sorts of chaos with it, Like you could log on

14
00:00:35,840 --> 00:00:38,360
Speaker 1: for free and uh this is when a L was

15
00:00:38,440 --> 00:00:40,960
Speaker 1: charging you by the minute, and you could do various pranks.

16
00:00:41,040 --> 00:00:43,280
Speaker 1: But one of the least used and most powerful things

17
00:00:43,280 --> 00:00:45,080
Speaker 1: you could do was create a user name with a

18
00:00:45,240 --> 00:00:46,880
Speaker 1: O L in it. What do you mean, like you

19
00:00:46,880 --> 00:00:49,440
Speaker 1: you couldn't use AOL in your name? No, So that

20
00:00:49,520 --> 00:00:52,000
Speaker 1: was one of the things that AL used to protect itself.

21
00:00:52,040 --> 00:00:54,680
Speaker 1: But through ao hell, you could sign up as like

22
00:00:55,080 --> 00:00:57,680
Speaker 1: a O L cop thirteen or a O L Guide

23
00:00:57,720 --> 00:01:00,200
Speaker 1: twenty six, and you could make yourself to see even

24
00:01:00,280 --> 00:01:03,720
Speaker 1: like this legit agent of the company, and my friends

25
00:01:03,800 --> 00:01:06,720
Speaker 1: used to use this mercilessly. What were they doing, like

26
00:01:06,760 --> 00:01:10,240
Speaker 1: stealing credit cards or what I mean, we're not thieves,

27
00:01:10,360 --> 00:01:14,080
Speaker 1: Like my friends would use it for pranks. So so often,

28
00:01:14,120 --> 00:01:15,800
Speaker 1: like my power would go into a chat room where

29
00:01:15,840 --> 00:01:17,840
Speaker 1: it was clear that like thirteen year old boys were

30
00:01:17,880 --> 00:01:22,000
Speaker 1: trading photos of like scantily clad ladies, and and he'd say,

31
00:01:22,040 --> 00:01:24,840
Speaker 1: this is a O L cop thirteen, You've been busted.

32
00:01:25,160 --> 00:01:28,880
Speaker 1: And then he'd say, unless you write me a one

33
00:01:28,880 --> 00:01:31,679
Speaker 1: page apology for your actions, your parents will be notified

34
00:01:31,680 --> 00:01:34,360
Speaker 1: and your account will be suspended. And by the end

35
00:01:34,400 --> 00:01:36,640
Speaker 1: of the by the end of the summer, you have

36
00:01:36,760 --> 00:01:39,280
Speaker 1: like a binder full of weird apologies from kids saying

37
00:01:39,319 --> 00:01:42,560
Speaker 1: they'd never trade bikini photos online again and just don't

38
00:01:42,560 --> 00:01:45,160
Speaker 1: tell their parents because they're supposed to be playing math games.

39
00:01:45,640 --> 00:01:49,240
Speaker 1: I mean, that is ruthless, I know, but the whole

40
00:01:49,240 --> 00:01:51,520
Speaker 1: thing did make me wonder, like how much of our

41
00:01:51,600 --> 00:01:54,440
Speaker 1: history is still online and how much does the internet

42
00:01:54,480 --> 00:01:56,639
Speaker 1: know about all of us? And that's what today's episode

43
00:01:56,640 --> 00:02:19,480
Speaker 1: it's all about. Hey, their podcast listeners, Welcome to Part

44
00:02:19,520 --> 00:02:22,120
Speaker 1: Time Genius. I'm Will Pearson and as always, I'm joined

45
00:02:22,160 --> 00:02:24,440
Speaker 1: by my good friend Man Gueshow Ticketer, and on the

46
00:02:24,480 --> 00:02:26,919
Speaker 1: other side of the soundproof glasses our friend and producer

47
00:02:27,000 --> 00:02:29,920
Speaker 1: Tristan McNeil. I don't know if you notice of, but

48
00:02:30,000 --> 00:02:33,880
Speaker 1: Tristan seems to be smirking today. Why is he so smirky? Smirks?

49
00:02:34,040 --> 00:02:36,080
Speaker 1: Good job, Tristan, I guess he's in a good mood.

50
00:02:36,120 --> 00:02:38,560
Speaker 1: But all right, so it's not Halloween yet, but today

51
00:02:38,560 --> 00:02:40,720
Speaker 1: we're gonna be exploring a topic that many of us

52
00:02:40,760 --> 00:02:43,840
Speaker 1: do find pretty creepy, and and that's asking the question,

53
00:02:44,080 --> 00:02:47,160
Speaker 1: what exactly does the Internet know about us? And so

54
00:02:47,240 --> 00:02:49,720
Speaker 1: to find out, we've been combing through user agreements just

55
00:02:49,760 --> 00:02:52,600
Speaker 1: to see what sort of personal information that we willingly

56
00:02:52,639 --> 00:02:55,120
Speaker 1: sign away. You know, these are two our favorite apps

57
00:02:55,160 --> 00:02:57,960
Speaker 1: and websites. And we'll also take a look behind the

58
00:02:58,000 --> 00:03:00,760
Speaker 1: digital curtain of the ad tracking industry, you know, just

59
00:03:00,800 --> 00:03:02,440
Speaker 1: to learn a little bit about how much of our

60
00:03:02,520 --> 00:03:05,760
Speaker 1: online habits reveal about who we are in the real world.

61
00:03:06,360 --> 00:03:08,560
Speaker 1: And this was actually a topic suggested by a listener

62
00:03:08,560 --> 00:03:10,800
Speaker 1: after a trip to the grocery store, and she had

63
00:03:10,800 --> 00:03:12,720
Speaker 1: explained that she had purchased a new type of soft

64
00:03:12,800 --> 00:03:15,200
Speaker 1: drink and then she'd never heard of this drink before,

65
00:03:15,280 --> 00:03:17,880
Speaker 1: and she spotted it there, picked it up, bought it,

66
00:03:18,000 --> 00:03:20,160
Speaker 1: went home. She had never looked it up on her phone,

67
00:03:20,560 --> 00:03:23,000
Speaker 1: never looked it up on her computer. But then later

68
00:03:23,040 --> 00:03:25,760
Speaker 1: she found herself getting ads for this same soft drink,

69
00:03:25,840 --> 00:03:28,880
Speaker 1: and so she was wondering do these offline purchases somehow

70
00:03:28,919 --> 00:03:31,920
Speaker 1: connect with what she's seeing online? And so we're gonna

71
00:03:31,919 --> 00:03:34,760
Speaker 1: be looking into questions like this. But I should take

72
00:03:34,760 --> 00:03:36,600
Speaker 1: a second to say that if you have a question

73
00:03:36,640 --> 00:03:39,560
Speaker 1: you'd like us to consider on a future episode, don't

74
00:03:39,560 --> 00:03:41,480
Speaker 1: forget to reach out to us here. We we'd love

75
00:03:41,520 --> 00:03:43,400
Speaker 1: to hear from you. It's part time genius at how

76
00:03:43,440 --> 00:03:46,880
Speaker 1: stuff works dot com and on our seven fact hot

77
00:03:46,880 --> 00:03:49,600
Speaker 1: line one eight four four pt genius. It is is

78
00:03:49,600 --> 00:03:53,000
Speaker 1: still seven right around the clock. That's amazing. There aren't

79
00:03:53,000 --> 00:03:57,840
Speaker 1: many fact hot lines that seven. It's true, It's true,

80
00:03:58,120 --> 00:04:00,120
Speaker 1: all right. Well, this is also a special up so

81
00:04:00,200 --> 00:04:02,640
Speaker 1: because we're teaming up with one of our favorite podcasts

82
00:04:02,680 --> 00:04:06,840
Speaker 1: to tackle two different but certainly related topics. So that's

83
00:04:06,920 --> 00:04:08,800
Speaker 1: that's right. To help us cope with some of the

84
00:04:08,880 --> 00:04:11,960
Speaker 1: unsettling secrets of online privacy, will be joined by some

85
00:04:12,000 --> 00:04:15,400
Speaker 1: of our favorite people, Ben Bolan, Noel Brown, and Matt Frederick.

86
00:04:15,680 --> 00:04:18,560
Speaker 1: They've joined us on the show before, but as a reminder,

87
00:04:18,640 --> 00:04:21,240
Speaker 1: they're the host of the awesome podcast Stuff they Don't

88
00:04:21,240 --> 00:04:23,120
Speaker 1: Want You to Know, and and this week the guys

89
00:04:23,160 --> 00:04:25,160
Speaker 1: did an episode on whether it's possible to wipe your

90
00:04:25,200 --> 00:04:27,840
Speaker 1: history from the web. So we'll talk to them and

91
00:04:27,920 --> 00:04:29,640
Speaker 1: see if they have any tips they can pass along

92
00:04:29,720 --> 00:04:31,520
Speaker 1: for how to get a little bit of privacy on

93
00:04:31,560 --> 00:04:34,560
Speaker 1: the Internet. But if you're interested in this topic, be

94
00:04:34,720 --> 00:04:36,840
Speaker 1: sure to check out today's episode of Stuff they Don't

95
00:04:36,880 --> 00:04:38,440
Speaker 1: Want You To Know. I love what those guys do.

96
00:04:38,680 --> 00:04:40,440
Speaker 1: They really are some of our favorite people. I know

97
00:04:40,520 --> 00:04:42,919
Speaker 1: sometimes we say that, but they actually are some of

98
00:04:42,920 --> 00:04:45,599
Speaker 1: our favorite people. All them, they're all good guys, all right.

99
00:04:45,640 --> 00:04:47,640
Speaker 1: So I thought we could start with just a general

100
00:04:47,760 --> 00:04:51,600
Speaker 1: overview of what web tracking is and and how it works.

101
00:04:51,600 --> 00:04:54,039
Speaker 1: And so to cover the first part of that, you know,

102
00:04:54,120 --> 00:04:56,520
Speaker 1: just just stop and think about the time you've googled

103
00:04:56,560 --> 00:04:59,520
Speaker 1: something like, you know, things to do in Denver, and

104
00:04:59,520 --> 00:05:01,599
Speaker 1: then the next time you've used Google, you've got a

105
00:05:01,600 --> 00:05:03,760
Speaker 1: bunch of ads that that you know, are trying to

106
00:05:03,760 --> 00:05:06,000
Speaker 1: convince you to book a flight to Denver or something.

107
00:05:06,040 --> 00:05:08,400
Speaker 1: Like that. Or maybe you've watched a Star Wars trailer

108
00:05:08,440 --> 00:05:10,760
Speaker 1: on YouTube and then you sign on to Facebook later

109
00:05:10,800 --> 00:05:13,520
Speaker 1: that night and your news feed contains a target ad

110
00:05:13,560 --> 00:05:17,000
Speaker 1: for a brand new Star Wars video game. And I

111
00:05:17,040 --> 00:05:19,400
Speaker 1: think most of us know by now that those early

112
00:05:19,440 --> 00:05:22,599
Speaker 1: appropriate ads they aren't by chance, and they're the result

113
00:05:22,640 --> 00:05:26,080
Speaker 1: of web tracking, which is it's one a series of companies.

114
00:05:26,120 --> 00:05:29,479
Speaker 1: They work together, they share information, They've compiled all this

115
00:05:29,560 --> 00:05:32,479
Speaker 1: information on consumers, and this is for the sake of

116
00:05:32,560 --> 00:05:36,880
Speaker 1: tailoring advertisements to suit specific people. So, Mango, I know

117
00:05:36,920 --> 00:05:38,960
Speaker 1: you engab did a bit of digging on this, and

118
00:05:39,080 --> 00:05:40,920
Speaker 1: so why don't you give us a breakdown on on

119
00:05:40,960 --> 00:05:43,960
Speaker 1: how all of this works. Sure? Well, there are actually

120
00:05:44,000 --> 00:05:46,640
Speaker 1: a few different methods that companies used to gather information

121
00:05:46,680 --> 00:05:49,400
Speaker 1: about people online, and one of them is this process

122
00:05:49,440 --> 00:05:53,800
Speaker 1: called canvas fingerprinting. Basically, websites have this feature written into

123
00:05:53,839 --> 00:05:56,240
Speaker 1: their script so that when you visit the site and

124
00:05:56,360 --> 00:05:58,760
Speaker 1: asked your browser to draw a hidden line of text

125
00:05:59,080 --> 00:06:01,680
Speaker 1: or even a three D image, And because of differences

126
00:06:01,720 --> 00:06:06,000
Speaker 1: between browsers and operating systems and computer hardware, the invisible

127
00:06:06,000 --> 00:06:08,920
Speaker 1: image that each device draws will be different. So I

128
00:06:08,920 --> 00:06:12,480
Speaker 1: guess this is where the fingerprinting part comes in exactly. So,

129
00:06:12,560 --> 00:06:14,760
Speaker 1: so the sites that use this method can then share

130
00:06:14,760 --> 00:06:18,279
Speaker 1: these device fingerprints with third party advertising companies and and

131
00:06:18,320 --> 00:06:20,640
Speaker 1: they in turn can use them to identify when and

132
00:06:20,880 --> 00:06:23,560
Speaker 1: how often the same user of the same device returns

133
00:06:23,600 --> 00:06:26,040
Speaker 1: to this site, as well as which other sites they're

134
00:06:26,120 --> 00:06:28,479
Speaker 1: visiting in between. All Right, so you're saying that these

135
00:06:28,520 --> 00:06:31,400
Speaker 1: techniques like canvas fingerprinting, which I've actually never heard that

136
00:06:31,520 --> 00:06:34,360
Speaker 1: term before, but they allow companies to track your browsing

137
00:06:34,400 --> 00:06:37,279
Speaker 1: history all across the internet. So it's not just the

138
00:06:37,360 --> 00:06:40,920
Speaker 1: site where you first have this image drawn, right, Yeah,

139
00:06:41,000 --> 00:06:43,880
Speaker 1: because the advertisers can see these fingerprints on any site

140
00:06:43,880 --> 00:06:46,520
Speaker 1: that allows them. So by looking for which sites the

141
00:06:46,560 --> 00:06:49,080
Speaker 1: fingerprints show up on, the advertiser can start to get

142
00:06:49,080 --> 00:06:51,400
Speaker 1: an idea of who this user is and which kinds

143
00:06:51,400 --> 00:06:54,159
Speaker 1: of products of services they might be most interested in. Actually,

144
00:06:54,200 --> 00:06:56,720
Speaker 1: I'm curious about this. So these invisible trackers, they're they're

145
00:06:56,760 --> 00:06:59,640
Speaker 1: hidden on websites, and they kind of sound like web cookies,

146
00:06:59,640 --> 00:07:02,320
Speaker 1: which we we've all heard of before. Our cookies a

147
00:07:02,400 --> 00:07:04,599
Speaker 1: form of this same thing. Yeah, so that's why I

148
00:07:04,640 --> 00:07:06,800
Speaker 1: thought too. But cookies are these small pieces of data

149
00:07:06,880 --> 00:07:09,440
Speaker 1: that a website stores on the browser, and then recalls

150
00:07:09,480 --> 00:07:12,320
Speaker 1: whenever you return to that specific site. So cookies are

151
00:07:12,320 --> 00:07:15,040
Speaker 1: how your favorite websites remember your name or address, or

152
00:07:15,080 --> 00:07:18,280
Speaker 1: your password, what's in your shopping cart, like all that stuff.

153
00:07:18,720 --> 00:07:22,240
Speaker 1: So they're definitely related to gathering and storing information about users,

154
00:07:22,240 --> 00:07:25,200
Speaker 1: but they aren't directly related to advertising on their own.

155
00:07:25,320 --> 00:07:27,800
Speaker 1: But I do remember Gape saying something about that. Advertisers

156
00:07:27,800 --> 00:07:30,200
Speaker 1: are still interested in cookies today. They find ways to

157
00:07:30,240 --> 00:07:33,800
Speaker 1: make use of them. There's this other process called cookie sinking.

158
00:07:34,080 --> 00:07:36,520
Speaker 1: It's a way that lets companies share the information they've

159
00:07:36,560 --> 00:07:39,720
Speaker 1: gathered about you through cookies, so they can trade notes

160
00:07:39,800 --> 00:07:41,840
Speaker 1: to come up with a clearer picture of who you are.

161
00:07:42,400 --> 00:07:44,680
Speaker 1: All right, So wait, just a method Because all these

162
00:07:44,760 --> 00:07:47,920
Speaker 1: data companies they collect and they share this information, but

163
00:07:47,960 --> 00:07:50,360
Speaker 1: it's it's supposed to be anonymous, right, Like, like based

164
00:07:50,360 --> 00:07:53,120
Speaker 1: on your phone or your computer, they might know where

165
00:07:53,160 --> 00:07:55,440
Speaker 1: you live, or what town you live in, or maybe

166
00:07:55,440 --> 00:07:57,520
Speaker 1: even how old you are, but they still don't know

167
00:07:57,560 --> 00:08:00,480
Speaker 1: your real name or anything too personal out to do

168
00:08:00,520 --> 00:08:04,360
Speaker 1: they Well, it's anonymous to a point. Like if someone

169
00:08:04,400 --> 00:08:07,800
Speaker 1: really wanted to, it's entirely possible to connect someone's anonymous

170
00:08:07,800 --> 00:08:11,360
Speaker 1: cookie data with their real world identity. I mean, we

171
00:08:11,400 --> 00:08:12,920
Speaker 1: see this kind of thing all the time with cases

172
00:08:12,960 --> 00:08:16,400
Speaker 1: of identity theft and hack social media profiles. In fact,

173
00:08:16,440 --> 00:08:19,280
Speaker 1: it's such a plausible danger that computer scientists don't even

174
00:08:19,360 --> 00:08:22,640
Speaker 1: use the term anonymous anymore. Instead, they say that companies

175
00:08:22,680 --> 00:08:25,960
Speaker 1: gather pseudonymous data on their users. Like the whole point

176
00:08:26,040 --> 00:08:28,640
Speaker 1: is that none of us are even anonymous online anymore.

177
00:08:29,000 --> 00:08:31,040
Speaker 1: Like we've really just been given a pseudonym in the

178
00:08:31,040 --> 00:08:34,280
Speaker 1: form of like these device fingerprints or these assigned numbers

179
00:08:34,400 --> 00:08:37,200
Speaker 1: or some other kind of digital trace, which is all

180
00:08:37,280 --> 00:08:39,199
Speaker 1: a little bit creepy. But I mean there's still one

181
00:08:39,200 --> 00:08:42,200
Speaker 1: thing I don't understand, and that's this connection between online

182
00:08:42,200 --> 00:08:46,280
Speaker 1: advertising and the spending we do in physical store. So

183
00:08:46,920 --> 00:08:48,720
Speaker 1: I kind of want to back up to that first

184
00:08:48,800 --> 00:08:50,480
Speaker 1: question that we asked at the very beginning of this,

185
00:08:50,520 --> 00:08:53,680
Speaker 1: and that's whether the Internet knew my friend had bought

186
00:08:53,760 --> 00:08:56,360
Speaker 1: that pack of soda. I mean, it sort of feels

187
00:08:56,400 --> 00:08:59,280
Speaker 1: like it had to know this, right, I Mean, otherwise,

188
00:08:59,280 --> 00:09:01,559
Speaker 1: why after it for the first time, that she suddenly

189
00:09:01,559 --> 00:09:05,200
Speaker 1: have Facebook ads recommending the same product to her. I know,

190
00:09:05,320 --> 00:09:07,719
Speaker 1: And honestly, that's a really good question. I want to know.

191
00:09:07,800 --> 00:09:10,080
Speaker 1: But but before that, I want to know what soda

192
00:09:10,200 --> 00:09:12,760
Speaker 1: she bought. What's the new I can't remember. We gotta

193
00:09:12,800 --> 00:09:14,320
Speaker 1: find out. It's gonna be a big one. Hopefully they'll

194
00:09:14,320 --> 00:09:18,520
Speaker 1: be a sponsor. But it is, you know, I wish

195
00:09:18,559 --> 00:09:20,719
Speaker 1: you could say it's for incidence. It's you know, it

196
00:09:20,760 --> 00:09:22,840
Speaker 1: feels a little strange that she bought the soda for

197
00:09:22,840 --> 00:09:25,080
Speaker 1: the first time, and and maybe that was the same

198
00:09:25,160 --> 00:09:28,520
Speaker 1: day that this big marketing push happened. But you know, realistically,

199
00:09:28,559 --> 00:09:31,040
Speaker 1: the odds were against that. I mean, the major data

200
00:09:31,080 --> 00:09:34,559
Speaker 1: companies gather an insane amount of information about their users.

201
00:09:34,600 --> 00:09:37,520
Speaker 1: And most folks know that search engines like Google or

202
00:09:37,600 --> 00:09:40,200
Speaker 1: Bing or Yahoo like they keep track of what we

203
00:09:40,240 --> 00:09:44,160
Speaker 1: search for, but big data's reach goes so much further. So,

204
00:09:44,559 --> 00:09:47,520
Speaker 1: for instance, like Google not only knows where you've traveled

205
00:09:47,520 --> 00:09:51,000
Speaker 1: thanks to Google Maps and the GPS tracking functions and

206
00:09:51,000 --> 00:09:53,959
Speaker 1: Android phones, but they also know how fast you were

207
00:09:53,960 --> 00:09:56,320
Speaker 1: going on the way there, and the same goes for

208
00:09:56,360 --> 00:09:59,760
Speaker 1: Apple and their iPhone. Of course, this means they likely

209
00:09:59,800 --> 00:10:02,600
Speaker 1: know where you live and work too, since those are

210
00:10:02,640 --> 00:10:05,560
Speaker 1: the places that you're traveling between the most often. You know.

211
00:10:05,600 --> 00:10:08,480
Speaker 1: But still, even if my phone and by extension Google

212
00:10:08,679 --> 00:10:10,679
Speaker 1: or Apple. You know, they knew I was at the

213
00:10:10,679 --> 00:10:13,320
Speaker 1: grocery store, how would they know what I bought? And

214
00:10:13,360 --> 00:10:16,120
Speaker 1: then and then how would Facebook find out about that?

215
00:10:16,480 --> 00:10:19,000
Speaker 1: So Gave did some heavy lifting on this and and

216
00:10:19,200 --> 00:10:22,800
Speaker 1: uh and in his research on Facebook, it turns out

217
00:10:22,880 --> 00:10:24,920
Speaker 1: they're actually ahead of the curve in terms of the

218
00:10:24,960 --> 00:10:27,520
Speaker 1: depth of data they collect on their users, as well

219
00:10:27,559 --> 00:10:30,080
Speaker 1: as in how they collect it. And the key to

220
00:10:30,080 --> 00:10:32,959
Speaker 1: that is an advertising tool called Atlas that the company

221
00:10:33,040 --> 00:10:35,839
Speaker 1: unveiled back in two thousand fourteen. So, according to the

222
00:10:35,920 --> 00:10:38,640
Speaker 1: vice president of ad Tech of Facebook, the Atlas system

223
00:10:38,679 --> 00:10:41,680
Speaker 1: can match the phone numbers and email addresses of Facebook

224
00:10:41,760 --> 00:10:45,120
Speaker 1: users with the phone numbers and email addresses that consumers

225
00:10:45,120 --> 00:10:48,680
Speaker 1: provide in physical stores. All right, So when the stores

226
00:10:48,720 --> 00:10:51,640
Speaker 1: ask for our email addresses or phone numbers that check out,

227
00:10:51,679 --> 00:10:54,200
Speaker 1: it's so that they can then sell that information to Facebook.

228
00:10:54,280 --> 00:10:56,080
Speaker 1: Is that that's the only reason they do this, well

229
00:10:56,360 --> 00:10:59,280
Speaker 1: kind of, I mean, sometimes that info is used for

230
00:10:59,280 --> 00:11:02,280
Speaker 1: that particular doors marketing purposes, you know, to email you

231
00:11:02,360 --> 00:11:06,000
Speaker 1: their monthly newsletter or coupons or whatever. But they're all

232
00:11:06,120 --> 00:11:09,280
Speaker 1: kinds of data collection companies that act as middlemen between

233
00:11:09,440 --> 00:11:13,800
Speaker 1: retail stores and online platforms. So, for instance, Facebook partners

234
00:11:13,800 --> 00:11:15,920
Speaker 1: with a company called Data Logics to get all its

235
00:11:15,920 --> 00:11:18,320
Speaker 1: store related info. Okay, so I got it. So I

236
00:11:18,360 --> 00:11:20,680
Speaker 1: scanned my grocery store club card, or I gave the

237
00:11:20,679 --> 00:11:24,360
Speaker 1: cashier my email address, and that information, along with the

238
00:11:24,440 --> 00:11:28,080
Speaker 1: purchase connected to it, was then passed along the Data Logics,

239
00:11:28,080 --> 00:11:31,040
Speaker 1: who then shared it with Facebook's advertising system, which you've

240
00:11:31,080 --> 00:11:34,480
Speaker 1: told us is called Atlas. That's right, exactly, So Atlas

241
00:11:34,600 --> 00:11:37,120
Speaker 1: knew that the person with your email address purchased a

242
00:11:37,160 --> 00:11:40,000
Speaker 1: new kind of soda that store, and from there, all

243
00:11:40,000 --> 00:11:42,080
Speaker 1: I had to do was compare that address with the

244
00:11:42,080 --> 00:11:44,560
Speaker 1: one you've linked to your Facebook account and presto, Like

245
00:11:45,040 --> 00:11:47,640
Speaker 1: now Facebook knows just what kind of ad you're likely

246
00:11:47,679 --> 00:11:49,920
Speaker 1: to respond to in your news feed. After all, you've

247
00:11:49,960 --> 00:11:52,400
Speaker 1: already bought that soda once. You know. It's weird because

248
00:11:52,400 --> 00:11:55,720
Speaker 1: I feel like I'm being clever sometimes when I used

249
00:11:55,800 --> 00:11:58,040
Speaker 1: this email address that I had never used for like

250
00:11:58,400 --> 00:12:00,360
Speaker 1: real purposes or whatever, you know, to have to a

251
00:12:00,480 --> 00:12:04,280
Speaker 1: cashier or to sign up for something account right product

252
00:12:04,360 --> 00:12:06,920
Speaker 1: you account. But I'm using the same one for all

253
00:12:06,960 --> 00:12:09,080
Speaker 1: of them, so they're still able to make this connection.

254
00:12:09,160 --> 00:12:11,800
Speaker 1: It's probably the same one that's on my Facebook account,

255
00:12:11,840 --> 00:12:14,319
Speaker 1: you know, So I don't know. I guess. I guess.

256
00:12:14,320 --> 00:12:17,400
Speaker 1: It is a pretty ingenious system from a marketing perspective,

257
00:12:17,440 --> 00:12:19,720
Speaker 1: but you know, not something that's going to generate all

258
00:12:19,760 --> 00:12:22,319
Speaker 1: this enthusiasm or goodwill among the public, at least I

259
00:12:22,320 --> 00:12:25,280
Speaker 1: wouldn't think. Yeah. But here's the creepous part, and and

260
00:12:25,320 --> 00:12:27,560
Speaker 1: that's that Facebook can do the same with ads that

261
00:12:27,600 --> 00:12:30,480
Speaker 1: aren't shown on Facebook. I don't even know what that means.

262
00:12:32,040 --> 00:12:34,640
Speaker 1: So Atlas was made to offer ads on all kinds

263
00:12:34,640 --> 00:12:37,439
Speaker 1: of different websites, not just Facebook, so the company can

264
00:12:37,440 --> 00:12:40,240
Speaker 1: match real world purchases to any ads source from the

265
00:12:40,240 --> 00:12:43,680
Speaker 1: Atlas network, no matter which side it appears on. That's

266
00:12:43,720 --> 00:12:46,280
Speaker 1: not all, though. Facebook can also keep track of its

267
00:12:46,360 --> 00:12:49,560
Speaker 1: users even when they're logged off of the platform. So

268
00:12:49,679 --> 00:12:52,320
Speaker 1: anytime you load a web page that features a Facebook

269
00:12:52,440 --> 00:12:55,120
Speaker 1: like or share button, the company gets in alert about

270
00:12:55,200 --> 00:12:59,240
Speaker 1: who's looking and where, which is basically like every page

271
00:12:59,240 --> 00:13:01,600
Speaker 1: out there internet. It's something I had not thought about.

272
00:13:01,640 --> 00:13:03,640
Speaker 1: I mean, so many of these tracking things they're not

273
00:13:03,800 --> 00:13:06,640
Speaker 1: that surprising, but the the depth of it, I think

274
00:13:06,720 --> 00:13:08,760
Speaker 1: is what's so surprising to me, and that all of

275
00:13:08,760 --> 00:13:11,520
Speaker 1: this seems to happen under the radar. I mean, I

276
00:13:11,559 --> 00:13:13,680
Speaker 1: do feel like most of us have this vague awareness

277
00:13:13,679 --> 00:13:16,600
Speaker 1: of web cookies and targeted advertising and all those sorts

278
00:13:16,640 --> 00:13:18,640
Speaker 1: of things, But I don't know, it's still a little

279
00:13:18,720 --> 00:13:21,080
Speaker 1: unsettling when you start to look into the specifics and

280
00:13:21,280 --> 00:13:23,840
Speaker 1: just how deep it all goes totally. And it only

281
00:13:23,880 --> 00:13:26,760
Speaker 1: gets more unnerving when you remember that Facebook doesn't exist

282
00:13:26,760 --> 00:13:29,880
Speaker 1: in a vacuum. I mean, companies like Twitter and Google like,

283
00:13:29,920 --> 00:13:32,920
Speaker 1: they've all taken notice and developed their own atlas like approaches,

284
00:13:33,400 --> 00:13:36,880
Speaker 1: and uh disability to prove the effectiveness of an online

285
00:13:36,880 --> 00:13:40,080
Speaker 1: ad gives them more bargaining power with potential clients, which

286
00:13:40,120 --> 00:13:42,400
Speaker 1: means the sale and trade of our data that's only

287
00:13:42,440 --> 00:13:45,080
Speaker 1: going to increase from here. All right, Well, well, maybe

288
00:13:45,080 --> 00:13:46,480
Speaker 1: our friends at Stuff they don't want you to know.

289
00:13:46,520 --> 00:13:48,360
Speaker 1: I have some ideas for how to shut off the

290
00:13:48,400 --> 00:13:51,600
Speaker 1: information valves that that are telling these companies so much

291
00:13:51,640 --> 00:13:53,120
Speaker 1: about our lives. So so why don't we go ahead

292
00:13:53,120 --> 00:14:02,880
Speaker 1: and bring them into the studio. Okay, So in this

293
00:14:02,920 --> 00:14:05,920
Speaker 1: episode we've been talking about all the things the Internet

294
00:14:06,040 --> 00:14:08,000
Speaker 1: knows about us, and as we mentioned at the beginning

295
00:14:08,000 --> 00:14:10,560
Speaker 1: of the show, our friends over at Stuff they don't

296
00:14:10,600 --> 00:14:13,120
Speaker 1: want you to know, are actually talking about how to

297
00:14:13,160 --> 00:14:16,560
Speaker 1: remove that information off of the web or or wherever

298
00:14:16,600 --> 00:14:18,920
Speaker 1: it is sitting. And we're joined by two thirds of

299
00:14:18,960 --> 00:14:21,240
Speaker 1: the crew, Ben Bulling and Matt Frederick. Welcome to Part

300
00:14:21,240 --> 00:14:25,520
Speaker 1: Time Genius. Yeah, thanks so much, you guys. We were

301
00:14:25,720 --> 00:14:30,800
Speaker 1: really excited to explore this, and uh, it's fascinating, if

302
00:14:31,000 --> 00:14:34,880
Speaker 1: a little bit unsettling, a little bit a lot of it.

303
00:14:35,200 --> 00:14:39,280
Speaker 1: Thank you, even even hearing just tidbits from you guys

304
00:14:39,280 --> 00:14:42,000
Speaker 1: as you're talking about putting the episode together. I typically

305
00:14:42,000 --> 00:14:44,280
Speaker 1: don't consider myself a paranoid person, but it was hard

306
00:14:44,320 --> 00:14:46,200
Speaker 1: not to go down that path. I think I'm okay.

307
00:14:46,200 --> 00:14:48,080
Speaker 1: But if you could give us just a little bit

308
00:14:48,120 --> 00:14:49,880
Speaker 1: of an overview of what you guys have been looking

309
00:14:49,920 --> 00:14:54,680
Speaker 1: into for the episode. Sure, we looked at a pretty

310
00:14:54,760 --> 00:14:57,760
Speaker 1: basic question, or so we thought in the beginning, which

311
00:14:57,960 --> 00:15:05,000
Speaker 1: was can you delete your online footprint, your your personal data.

312
00:15:05,080 --> 00:15:09,080
Speaker 1: We we stumbled on the phrase the digital you, because

313
00:15:09,120 --> 00:15:14,000
Speaker 1: there's there's so much information and so many leavings of

314
00:15:14,080 --> 00:15:18,640
Speaker 1: all your time brushing through the internet, right Uh, And

315
00:15:18,840 --> 00:15:23,040
Speaker 1: what we found was that there is no silver bullet,

316
00:15:23,560 --> 00:15:28,160
Speaker 1: and uh, you must be very very careful with the

317
00:15:28,320 --> 00:15:33,560
Speaker 1: types of terms that are used by various online entities,

318
00:15:33,560 --> 00:15:37,560
Speaker 1: whether they are a private or a public organization. Yeah,

319
00:15:37,600 --> 00:15:40,360
Speaker 1: specifically terms of services. What been is talking about here,

320
00:15:41,040 --> 00:15:43,120
Speaker 1: that little thing that you go, yeah, I accept that

321
00:15:43,200 --> 00:15:46,080
Speaker 1: you scroll through. Maybe maybe it makes you scroll to

322
00:15:46,120 --> 00:15:48,720
Speaker 1: the bottom of the page, just hit it and go okay.

323
00:15:48,800 --> 00:15:52,200
Speaker 1: Has anyone ever read an entire terms of service? I

324
00:15:52,240 --> 00:15:54,960
Speaker 1: mean that's the that's the whole thing, right, Yeah, I did.

325
00:15:55,200 --> 00:16:00,440
Speaker 1: I did once when my cable was out if pager

326
00:16:00,560 --> 00:16:02,200
Speaker 1: so you could kind of get through. It wasn't even

327
00:16:02,280 --> 00:16:05,040
Speaker 1: in my house, it was at someone else's house. If

328
00:16:05,040 --> 00:16:06,360
Speaker 1: I had brought a book, I wouldn't have read the

329
00:16:06,480 --> 00:16:11,280
Speaker 1: terms made for a much smarter digital you. So envious

330
00:16:11,280 --> 00:16:13,640
Speaker 1: of your digital you. So one of my favorite things

331
00:16:13,680 --> 00:16:16,480
Speaker 1: that I heard you guys talking about was about your

332
00:16:16,560 --> 00:16:18,760
Speaker 1: A O L account and Matt, you are actually looking

333
00:16:18,880 --> 00:16:22,960
Speaker 1: to go back and delete or cancel your ao L account.

334
00:16:23,200 --> 00:16:25,760
Speaker 1: I was like, what are we having this conversation? So

335
00:16:25,880 --> 00:16:31,600
Speaker 1: let's go back to two thousand five six Old Matt

336
00:16:31,680 --> 00:16:34,480
Speaker 1: Frederick is in a band, and every band at that time,

337
00:16:34,600 --> 00:16:40,400
Speaker 1: what do they have? My Okay? Well, also my my

338
00:16:40,560 --> 00:16:44,440
Speaker 1: email since n seven has been through a O L

339
00:16:44,560 --> 00:16:48,200
Speaker 1: at this time, So for some reason, I just stuck

340
00:16:48,280 --> 00:16:50,160
Speaker 1: with A O L because my parents had it and

341
00:16:50,160 --> 00:16:52,440
Speaker 1: I just kept going with it. Anyway, my my Space

342
00:16:52,480 --> 00:16:55,120
Speaker 1: page was linked to my A o L account, so

343
00:16:55,160 --> 00:16:58,640
Speaker 1: in order to like find my old password and reset

344
00:16:58,680 --> 00:17:00,400
Speaker 1: it for my Space, had to get in my AOL

345
00:17:00,480 --> 00:17:06,080
Speaker 1: email and then realized this is still here now the

346
00:17:06,119 --> 00:17:10,960
Speaker 1: one good thing and my ex girlfriend is still email. Well,

347
00:17:11,040 --> 00:17:13,359
Speaker 1: the one good thing is that the A o L service,

348
00:17:13,359 --> 00:17:15,520
Speaker 1: if you have a free account, they disable your account

349
00:17:15,520 --> 00:17:17,920
Speaker 1: after I think a hundred eighty days of an activity

350
00:17:18,520 --> 00:17:21,440
Speaker 1: that you you're not getting emails anymore, but it's still

351
00:17:21,480 --> 00:17:23,200
Speaker 1: there and if anyone wanted to get in there, and

352
00:17:23,280 --> 00:17:27,280
Speaker 1: my personal information is still inside the profile, which made

353
00:17:27,280 --> 00:17:30,960
Speaker 1: me super nervous because I haven't looked at it since then. Anyway,

354
00:17:31,119 --> 00:17:33,159
Speaker 1: you try and delete the thing. To get rid of

355
00:17:33,160 --> 00:17:36,040
Speaker 1: the A o L and the my Space my Space

356
00:17:36,040 --> 00:17:39,560
Speaker 1: relatively easy. But the A O L one they're supposed

357
00:17:39,600 --> 00:17:42,200
Speaker 1: to be a cancel your account little icon that you

358
00:17:42,240 --> 00:17:45,800
Speaker 1: can click on in this one specific area. It wasn't

359
00:17:45,840 --> 00:17:48,760
Speaker 1: there on the three browsers that I attempted to use,

360
00:17:49,440 --> 00:17:51,359
Speaker 1: and maybe a little nervous, so I called up a

361
00:17:51,480 --> 00:17:55,880
Speaker 1: o L with my phone? Can you believe that? Yeah,

362
00:17:56,160 --> 00:17:59,240
Speaker 1: I got ahold of somebody. He officially deleted it, and uh,

363
00:17:59,359 --> 00:18:01,159
Speaker 1: I can still log in right now, which makes me

364
00:18:01,200 --> 00:18:05,080
Speaker 1: super nervous. We'd like to make fun of you for that,

365
00:18:05,119 --> 00:18:07,919
Speaker 1: but you're looking at two people with a Yahoo and

366
00:18:08,280 --> 00:18:13,879
Speaker 1: uh stategy. We need to pull that up at some

367
00:18:13,880 --> 00:18:16,400
Speaker 1: point to see if it still exists. That's pretty great

368
00:18:16,400 --> 00:18:17,920
Speaker 1: and I'm glad to hear A O L is still

369
00:18:18,000 --> 00:18:19,479
Speaker 1: up to their old tricks. I remember when you used

370
00:18:19,520 --> 00:18:21,320
Speaker 1: to try to cancel after you get the free disc

371
00:18:21,400 --> 00:18:23,840
Speaker 1: and sign up for however many hours, and they were

372
00:18:23,880 --> 00:18:25,840
Speaker 1: just awful when you would call and say that you're

373
00:18:25,880 --> 00:18:29,000
Speaker 1: ready to cancel. I remember, I remember like begging a woman.

374
00:18:29,080 --> 00:18:30,760
Speaker 1: I was like, I know you're reading off a script,

375
00:18:30,800 --> 00:18:35,200
Speaker 1: just like please skip to like mine pages almost in tears,

376
00:18:35,359 --> 00:18:39,480
Speaker 1: and it's very much like a it's it's oddly like

377
00:18:39,520 --> 00:18:42,960
Speaker 1: a breakup. And in many cases, you know, and uh,

378
00:18:43,119 --> 00:18:46,280
Speaker 1: the old adage is true, breaking up is hard to do,

379
00:18:46,359 --> 00:18:49,920
Speaker 1: but in these cases it's um you run into some

380
00:18:50,560 --> 00:18:54,040
Speaker 1: misleading and pernicious things. Right. It's it's a point that

381
00:18:54,080 --> 00:18:57,880
Speaker 1: we've made it on our episodes before that your account,

382
00:18:58,119 --> 00:19:01,399
Speaker 1: your personal information and your use of whatever you know,

383
00:19:01,800 --> 00:19:05,680
Speaker 1: page or whatever app. It's highly valuable to these companies.

384
00:19:05,720 --> 00:19:07,800
Speaker 1: You were talking about it friends, though, One of the

385
00:19:07,840 --> 00:19:10,240
Speaker 1: things you guys talked about was the fact that even

386
00:19:10,240 --> 00:19:13,200
Speaker 1: if you don't have a social media profile, if you

387
00:19:13,240 --> 00:19:16,119
Speaker 1: are in your friends phones or whatever, it may be

388
00:19:16,280 --> 00:19:19,240
Speaker 1: your your phone number, your address, anything like that, it

389
00:19:19,320 --> 00:19:22,040
Speaker 1: doesn't mean that you're not out there and that your

390
00:19:22,080 --> 00:19:24,800
Speaker 1: digital you is still is still out there. So can

391
00:19:24,800 --> 00:19:27,120
Speaker 1: you talk a little bit about yeah, you're digital. You

392
00:19:27,560 --> 00:19:32,560
Speaker 1: will still exist in perhaps somewhat of a less substantial form. So,

393
00:19:33,280 --> 00:19:37,840
Speaker 1: for instance, if our co host and colleague Noel Brown,

394
00:19:38,359 --> 00:19:41,360
Speaker 1: uh did not have a Facebook for some reason, he's

395
00:19:41,400 --> 00:19:43,159
Speaker 1: actually the most likely of the three of us to

396
00:19:43,200 --> 00:19:46,560
Speaker 1: have a Facebook. You would agree with if Nol didn't

397
00:19:46,600 --> 00:19:51,320
Speaker 1: have a Facebook, but Matt or I had the Facebook

398
00:19:51,320 --> 00:19:53,080
Speaker 1: app on the phone, or one of you guys did

399
00:19:53,119 --> 00:19:57,480
Speaker 1: have the app on your phone, then depending on your

400
00:19:57,560 --> 00:20:00,520
Speaker 1: OS or the type of phone you're using, the app

401
00:20:00,600 --> 00:20:04,080
Speaker 1: will automatically have access to all your contacts, which means

402
00:20:04,119 --> 00:20:07,639
Speaker 1: every phone number, every email that you or your phone touch,

403
00:20:08,520 --> 00:20:10,960
Speaker 1: Which means that if any of us knew Noel Brown,

404
00:20:11,400 --> 00:20:15,880
Speaker 1: then they would already start building sort of a framework

405
00:20:16,040 --> 00:20:18,560
Speaker 1: for him. So they would say, Okay, we know there's

406
00:20:18,960 --> 00:20:22,080
Speaker 1: this guy. His name is Noel Brown, his phone number

407
00:20:22,119 --> 00:20:25,800
Speaker 1: is you know, five five five whatever, and uh, he

408
00:20:26,080 --> 00:20:30,439
Speaker 1: also has this email address, and he knows uh Mango,

409
00:20:30,720 --> 00:20:33,040
Speaker 1: and he knows Will and he knows Matt and he

410
00:20:33,119 --> 00:20:37,400
Speaker 1: knows Ben and they all work together. Therefore he probably

411
00:20:37,640 --> 00:20:39,600
Speaker 1: you know what I mean. And this this can come

412
00:20:39,720 --> 00:20:43,520
Speaker 1: from different sources. So even if you have somehow resisted

413
00:20:44,200 --> 00:20:47,080
Speaker 1: social media entirely, if you have, if you have a

414
00:20:47,119 --> 00:20:52,080
Speaker 1: phone number and or an email address and friends, yeah,

415
00:20:52,320 --> 00:20:56,120
Speaker 1: then which are fairly easy requirements to meet, then yeah,

416
00:20:56,200 --> 00:21:01,160
Speaker 1: the odds are overwhelmingly likely that there is some even

417
00:21:01,280 --> 00:21:07,080
Speaker 1: rudimentary version of you online already without your consent before

418
00:21:07,160 --> 00:21:08,760
Speaker 1: we let you go. I'm curious. We don't want to

419
00:21:08,760 --> 00:21:11,080
Speaker 1: give any spoilers because it is a terrific episode and

420
00:21:11,080 --> 00:21:13,840
Speaker 1: I hope everyone will will check it out. But do

421
00:21:13,960 --> 00:21:16,560
Speaker 1: you think you guys will will change your behaviors and

422
00:21:16,640 --> 00:21:20,440
Speaker 1: anyway based on what you've learned and putting together this episode? Well,

423
00:21:20,480 --> 00:21:24,560
Speaker 1: here's the thing, um, for a long time now we

424
00:21:24,840 --> 00:21:27,400
Speaker 1: have changed our behavior is because we've been looking into

425
00:21:27,440 --> 00:21:30,159
Speaker 1: this kind of stuff for a while. All we can

426
00:21:30,200 --> 00:21:33,720
Speaker 1: do is encourage everybody else to do your best to

427
00:21:33,920 --> 00:21:36,760
Speaker 1: just you know, don't give too much away for free.

428
00:21:37,280 --> 00:21:39,000
Speaker 1: And when you think, when you think about all of

429
00:21:39,119 --> 00:21:42,280
Speaker 1: the apps that you use on a daily, weekly, monthly

430
00:21:42,359 --> 00:21:46,600
Speaker 1: basis that you've got on whatever device you use, most

431
00:21:46,640 --> 00:21:48,440
Speaker 1: of them ask you for your contacts. Most of them

432
00:21:48,720 --> 00:21:51,080
Speaker 1: are trying to find out where you're going, what you're doing,

433
00:21:51,880 --> 00:21:54,600
Speaker 1: Take pictures of yourself and all your friends and your

434
00:21:54,680 --> 00:21:59,320
Speaker 1: dog and your family. Just think about it. I did, uh,

435
00:21:59,800 --> 00:22:04,119
Speaker 1: I I did assiduously go through and remove apps on

436
00:22:04,359 --> 00:22:08,240
Speaker 1: my phone until you know, you realize at some level

437
00:22:08,359 --> 00:22:11,840
Speaker 1: you're you become like the kid in the old Dutch

438
00:22:11,920 --> 00:22:15,520
Speaker 1: fairy tale trying to plug up a damn one hole

439
00:22:15,640 --> 00:22:19,160
Speaker 1: at a time. There are other avenues for this information exchange,

440
00:22:19,840 --> 00:22:24,399
Speaker 1: and this means that, uh, for a lot of people

441
00:22:24,600 --> 00:22:27,879
Speaker 1: and for myself included. When I was removing apps, it

442
00:22:28,000 --> 00:22:30,359
Speaker 1: hit me and I thought, am I really making a

443
00:22:30,440 --> 00:22:33,920
Speaker 1: difference or am I just making myself feel better? You

444
00:22:34,040 --> 00:22:36,600
Speaker 1: know what I mean? Alright, Well, I hope all of

445
00:22:36,640 --> 00:22:38,760
Speaker 1: our listeners will hop on over to stuff they don't

446
00:22:38,800 --> 00:22:41,080
Speaker 1: want you to know and check out this episode. Can

447
00:22:41,200 --> 00:22:43,760
Speaker 1: you really erase your digital self. But Matt and Ben,

448
00:22:43,840 --> 00:22:59,440
Speaker 1: thanks so much for joining us. Thank you. Thanks. You're

449
00:22:59,480 --> 00:23:01,439
Speaker 1: listening to part Time Genius and we're talking about all

450
00:23:01,520 --> 00:23:05,000
Speaker 1: the creepy things the Internet knows about us, all right, Mega,

451
00:23:05,040 --> 00:23:06,680
Speaker 1: So before the break, we were talking about how the

452
00:23:06,800 --> 00:23:10,480
Speaker 1: purchases we make in physical stores can inform advertisements we

453
00:23:10,600 --> 00:23:13,240
Speaker 1: see later. So there's this blurring of the line between

454
00:23:13,280 --> 00:23:15,680
Speaker 1: the digital world and I don't know, the real world,

455
00:23:15,760 --> 00:23:17,760
Speaker 1: I guess, And and it kind of got me thinking,

456
00:23:18,000 --> 00:23:19,879
Speaker 1: what are some of the other ways that are close

457
00:23:19,920 --> 00:23:23,639
Speaker 1: connection to the web affects our offline lives? Right? Because

458
00:23:23,680 --> 00:23:26,359
Speaker 1: with smartphones, tablets and all the other easy to use

459
00:23:26,400 --> 00:23:28,720
Speaker 1: recording devices we have now, the people of Live to

460
00:23:28,760 --> 00:23:31,000
Speaker 1: day are pretty much guaranteed to be the most self

461
00:23:31,080 --> 00:23:34,600
Speaker 1: documented generation of humans to date, which seems doubly true

462
00:23:34,640 --> 00:23:37,440
Speaker 1: when you add to that the fact that enormous companies

463
00:23:37,480 --> 00:23:40,639
Speaker 1: are now tracking and recording our interests and behaviors and

464
00:23:41,080 --> 00:23:44,800
Speaker 1: everything else for marketing purposes. And I mean, if widespread

465
00:23:44,880 --> 00:23:48,200
Speaker 1: personal documentation has never really been done on this level before,

466
00:23:48,640 --> 00:23:50,480
Speaker 1: you have to assume there will be all kinds of

467
00:23:50,560 --> 00:23:53,760
Speaker 1: interesting social and psychological outcomes from it. You know, for

468
00:23:53,920 --> 00:23:56,359
Speaker 1: better or for worse. Yeah, it's true, and not to

469
00:23:56,440 --> 00:23:58,560
Speaker 1: keep harping on Facebook, but but one of the most

470
00:23:58,640 --> 00:24:02,000
Speaker 1: interesting examples I found for how these digital platforms affect

471
00:24:02,040 --> 00:24:05,480
Speaker 1: our lives has to do with the company's memories algorithms.

472
00:24:05,520 --> 00:24:07,200
Speaker 1: You know where it where it will pop up, You'll

473
00:24:07,240 --> 00:24:09,520
Speaker 1: sign on and in your feed you'll see these memories

474
00:24:09,640 --> 00:24:11,760
Speaker 1: from over the years of the past year or whatever

475
00:24:11,800 --> 00:24:14,520
Speaker 1: it might have been. And so Facebook, you know, uses

476
00:24:14,600 --> 00:24:17,719
Speaker 1: this algorithm to select these pictures and post from our

477
00:24:17,800 --> 00:24:20,920
Speaker 1: past that it then hopes we're most likely to share it,

478
00:24:22,119 --> 00:24:24,600
Speaker 1: which is how they determined that like my yearine review

479
00:24:24,720 --> 00:24:27,000
Speaker 1: is best summed up by like when I was stuffing

480
00:24:27,040 --> 00:24:30,480
Speaker 1: my face with rom in last January, last January, last week,

481
00:24:30,560 --> 00:24:32,480
Speaker 1: whenever it was, I think that's pretty much it. And

482
00:24:32,520 --> 00:24:34,320
Speaker 1: then judging about off and I've seen you at that

483
00:24:34,440 --> 00:24:36,800
Speaker 1: exact scene, I'm gonna say they're not too off base

484
00:24:36,920 --> 00:24:40,080
Speaker 1: with them. But you know, but when you share these memories,

485
00:24:40,200 --> 00:24:42,920
Speaker 1: Facebook selects force. What we're doing is we're helping the

486
00:24:43,000 --> 00:24:45,800
Speaker 1: algorithm learn a little bit more about our preferences and

487
00:24:46,400 --> 00:24:48,439
Speaker 1: and then it can play to these more in the future.

488
00:24:49,119 --> 00:24:51,600
Speaker 1: And do we know at all how this digital memory

489
00:24:51,680 --> 00:24:54,119
Speaker 1: creation might be affecting us. Well. I did come across

490
00:24:54,200 --> 00:24:57,560
Speaker 1: this really interesting articles in Scientific American. It was written

491
00:24:57,600 --> 00:25:00,440
Speaker 1: by Julie Shaw, and it talks a little bit about

492
00:25:00,440 --> 00:25:03,720
Speaker 1: the implications of making forms of social media nostalgia like

493
00:25:03,840 --> 00:25:06,560
Speaker 1: this into a mainstream thing. And here's what she writes.

494
00:25:06,640 --> 00:25:10,159
Speaker 1: She says, by having Facebook choose which events are presented

495
00:25:10,200 --> 00:25:13,440
Speaker 1: as the most meaningful in our lives, it's potentially calling

496
00:25:13,520 --> 00:25:18,080
Speaker 1: the memories the algorithm ignores. Simultaneously, it's reinforcing the memories

497
00:25:18,160 --> 00:25:22,080
Speaker 1: it has chosen, potentially making some memories seem more meaningful

498
00:25:22,440 --> 00:25:25,760
Speaker 1: and memorable than they originally were. Both of these are

499
00:25:25,800 --> 00:25:30,159
Speaker 1: problematic processes that can distort our personal reality. We may

500
00:25:30,240 --> 00:25:33,680
Speaker 1: be helping Facebook learn to optimize its features, but the

501
00:25:33,760 --> 00:25:38,600
Speaker 1: relationship is not symbiotic. Facebook's nostalgia features are messing with

502
00:25:38,760 --> 00:25:41,840
Speaker 1: our memories, which is interesting. But I feel like the

503
00:25:41,880 --> 00:25:44,680
Speaker 1: photos we keep around have always done this. Like have

504
00:25:44,840 --> 00:25:47,680
Speaker 1: you read Susan Sontag's on photography essay? I haven't, and

505
00:25:48,000 --> 00:25:50,040
Speaker 1: I only vaguely remember it from college. But but she

506
00:25:50,119 --> 00:25:52,000
Speaker 1: talked about how the photo you have on your desk

507
00:25:52,040 --> 00:25:54,359
Speaker 1: from your family road trip is a picture of a

508
00:25:54,480 --> 00:25:57,760
Speaker 1: family smiling and in a gorgeous place, right, But in

509
00:25:57,920 --> 00:26:00,919
Speaker 1: capturing that, you're really only showing your most ideal photo.

510
00:26:01,400 --> 00:26:03,399
Speaker 1: But like you're forgetting the hours of bickering in the

511
00:26:03,480 --> 00:26:05,879
Speaker 1: car and and telling your kids to stop fighting, and

512
00:26:05,960 --> 00:26:09,640
Speaker 1: the boredom and all that arguing that happen, and you're

513
00:26:09,640 --> 00:26:12,920
Speaker 1: just focusing on this one kind of manufactured pick where

514
00:26:13,280 --> 00:26:16,359
Speaker 1: everyone's hugging and smiling, right. And it's true. I mean,

515
00:26:16,400 --> 00:26:18,200
Speaker 1: like we sell select the photos that go up on

516
00:26:18,280 --> 00:26:21,320
Speaker 1: social media to such a degree that we're already altering

517
00:26:21,359 --> 00:26:23,480
Speaker 1: our memories, and and Facebook only seems to be putting

518
00:26:23,480 --> 00:26:25,680
Speaker 1: that into hyper drive. I don't know about your family,

519
00:26:25,760 --> 00:26:27,840
Speaker 1: but all we do on our trips this hug and

520
00:26:28,000 --> 00:26:31,639
Speaker 1: smile and pose together. We're always like one inch apart

521
00:26:31,720 --> 00:26:34,400
Speaker 1: from each other. I don't know, Maybe you're right, Maybe

522
00:26:34,400 --> 00:26:36,600
Speaker 1: maybe we're wearing a little too much about this when

523
00:26:36,640 --> 00:26:39,520
Speaker 1: it comes to Facebook, and especially since it might give

524
00:26:39,600 --> 00:26:42,560
Speaker 1: us a case of paranoia, which is definitely something else

525
00:26:42,600 --> 00:26:45,159
Speaker 1: I wanted to talk about, because this is another common

526
00:26:45,240 --> 00:26:48,800
Speaker 1: condition that's connected to all this online data tracking. Well,

527
00:26:48,840 --> 00:26:51,240
Speaker 1: I mean, it's hard not to be paranoid, right, Like

528
00:26:51,359 --> 00:26:54,159
Speaker 1: this is almost universal feeling that our online movements are

529
00:26:54,200 --> 00:26:57,800
Speaker 1: being tracked and recorded, and and because the specifics are

530
00:26:57,880 --> 00:27:00,680
Speaker 1: so hazy, like it's it's just something that like you

531
00:27:00,840 --> 00:27:02,680
Speaker 1: can't get out of your mind. And and so this

532
00:27:02,800 --> 00:27:04,479
Speaker 1: is something that came up a lot during my research.

533
00:27:04,560 --> 00:27:07,520
Speaker 1: For example, I I I read this report about last

534
00:27:07,640 --> 00:27:11,440
Speaker 1: year's Consumer Electronics Show and The Guardian, and it talked

535
00:27:11,480 --> 00:27:14,480
Speaker 1: about how all these companies that make biometrics and tracking

536
00:27:14,520 --> 00:27:17,960
Speaker 1: gadgets have lately found themselves dealing with an entirely new

537
00:27:18,119 --> 00:27:21,680
Speaker 1: clientele and and so who would that be. Well, that's

538
00:27:21,720 --> 00:27:25,320
Speaker 1: the thing. It's like the new customers are ordinary everyday people.

539
00:27:25,720 --> 00:27:28,040
Speaker 1: I mean, previously, the people who are most interested in

540
00:27:28,119 --> 00:27:31,359
Speaker 1: fingerprint scanners for all their like electronic devices and the

541
00:27:31,560 --> 00:27:33,800
Speaker 1: zinc line cases to shield their phones from like the

542
00:27:33,880 --> 00:27:37,240
Speaker 1: electric fields, they were really paranoid. And and they're the

543
00:27:37,280 --> 00:27:39,680
Speaker 1: people that Nellie Bulls of The Guardian refers to as

544
00:27:39,800 --> 00:27:43,639
Speaker 1: the tinfoil hat Brigade. Right, Okay, I think I get it.

545
00:27:43,640 --> 00:27:46,320
Speaker 1: I mean these companies are mostly used by customers who

546
00:27:46,400 --> 00:27:49,560
Speaker 1: have I don't know, dabbled with conspiracy theory or two,

547
00:27:49,960 --> 00:27:52,879
Speaker 1: or perhaps they are a bit untrusting of large corporations

548
00:27:53,000 --> 00:27:54,920
Speaker 1: that monitor them too. Closely. I mean, I think we

549
00:27:55,000 --> 00:27:58,200
Speaker 1: all have an image of that type, I guess exactly.

550
00:27:58,320 --> 00:28:00,600
Speaker 1: But now they're finding the general public is starting to

551
00:28:00,640 --> 00:28:03,280
Speaker 1: feel those same kinds of concerns and and they're taking

552
00:28:03,280 --> 00:28:05,720
Speaker 1: an interest in the products as well, and that totally

553
00:28:05,840 --> 00:28:09,200
Speaker 1: frees these suppliers out. In that Guardian article I mentioned,

554
00:28:09,280 --> 00:28:12,360
Speaker 1: the author describes all these vendors that are pretty uneasy

555
00:28:12,440 --> 00:28:15,520
Speaker 1: at the thought of their whereas being mainstream. So listen

556
00:28:15,600 --> 00:28:18,680
Speaker 1: listen to how the author describes the scene. Quote the

557
00:28:18,760 --> 00:28:23,040
Speaker 1: Personal Security Department at CS, once a quiet overlooked corner

558
00:28:23,080 --> 00:28:26,480
Speaker 1: of the flashy gadget show, was packed and frenzied. This year,

559
00:28:27,000 --> 00:28:30,359
Speaker 1: it's popularity stirred and internal reckoning for the security gadget

560
00:28:30,440 --> 00:28:33,280
Speaker 1: makers who are now central to the conversation about privacy

561
00:28:33,320 --> 00:28:37,720
Speaker 1: and politics. Some longtime sellers are worried about their new buyers. Well,

562
00:28:37,760 --> 00:28:39,920
Speaker 1: I don't know, and maybe for for good reason. Honestly,

563
00:28:40,360 --> 00:28:42,920
Speaker 1: what does it say about society that the average Joe

564
00:28:43,080 --> 00:28:46,400
Speaker 1: is now suddenly taking an interest in these privacy apps

565
00:28:46,520 --> 00:28:49,440
Speaker 1: and the anti surveillance gadgets and all that kind of

566
00:28:49,720 --> 00:28:52,960
Speaker 1: nothing good. It actually makes me think of, you know,

567
00:28:53,080 --> 00:28:55,920
Speaker 1: this new parenting technology that you see all over. I mean,

568
00:28:55,960 --> 00:28:58,240
Speaker 1: this is a little bit different, but you've seen this

569
00:28:58,320 --> 00:29:00,280
Speaker 1: stuff and and it's stuff that I'm kind of glad

570
00:29:00,360 --> 00:29:02,600
Speaker 1: didn't exist that when we were, you know, when our

571
00:29:02,680 --> 00:29:05,720
Speaker 1: kids were much younger. But stuff like the smart baby

572
00:29:05,800 --> 00:29:08,200
Speaker 1: beds and infant heart rate readers that I have to

573
00:29:08,280 --> 00:29:10,920
Speaker 1: put parents at ease, and you know, it keeps them

574
00:29:11,120 --> 00:29:14,680
Speaker 1: over informed about every little detail of their little ones health.

575
00:29:14,760 --> 00:29:17,080
Speaker 1: I mean, have you heard of this new robot nanny tech?

576
00:29:17,240 --> 00:29:19,240
Speaker 1: I think Mattel put it out earlier this year, and

577
00:29:19,320 --> 00:29:23,760
Speaker 1: it's called Aristotle. Call it Aristot be so smart. It's

578
00:29:23,800 --> 00:29:27,720
Speaker 1: basically this three version of Amazon's Alexa, but for kids.

579
00:29:28,240 --> 00:29:30,480
Speaker 1: It's got all these high tech features like voice and

580
00:29:30,560 --> 00:29:34,000
Speaker 1: image recognition and live streaming. But what it also does

581
00:29:34,120 --> 00:29:36,640
Speaker 1: is it it watches and it listens and it learns

582
00:29:36,720 --> 00:29:39,680
Speaker 1: from these babies left under its care. And I don't know,

583
00:29:39,680 --> 00:29:41,680
Speaker 1: I mean, I guess it could help parents keep track

584
00:29:41,720 --> 00:29:45,600
Speaker 1: of stuff like diaper changes and feedings, but it could

585
00:29:45,640 --> 00:29:48,560
Speaker 1: also file away all of that user data for Mattel's

586
00:29:48,640 --> 00:29:51,880
Speaker 1: future commercial endeavors. Yeah, so that that's definitely something to

587
00:29:52,000 --> 00:29:54,200
Speaker 1: keep an eye on for sure. But I mean, I

588
00:29:54,280 --> 00:29:56,240
Speaker 1: want to make sure we aren't coming across as like

589
00:29:56,400 --> 00:29:59,200
Speaker 1: ludyte here because I mean, don't get me wrong, they're

590
00:29:59,240 --> 00:30:02,040
Speaker 1: all kinds of you technologies that can make childcare and

591
00:30:02,120 --> 00:30:05,400
Speaker 1: other aspects of parenting much much easier, And the same

592
00:30:05,520 --> 00:30:08,720
Speaker 1: is true for like technologies of for other non kid things.

593
00:30:08,840 --> 00:30:11,360
Speaker 1: But it's just that, like all this information can make

594
00:30:11,440 --> 00:30:14,400
Speaker 1: things more complicated and and leave parents more worried than

595
00:30:14,440 --> 00:30:16,640
Speaker 1: maybe they should be. Yeah, I mean that's true. And

596
00:30:16,960 --> 00:30:19,120
Speaker 1: having all the stat at their fingertips can make parents

597
00:30:19,200 --> 00:30:22,160
Speaker 1: a little paranoid or even obsessed with the things about

598
00:30:22,160 --> 00:30:24,640
Speaker 1: their child that really are no big deal. I mean,

599
00:30:24,880 --> 00:30:28,800
Speaker 1: it's just that constant biometric reporting and and these status

600
00:30:28,920 --> 00:30:31,520
Speaker 1: updates that can make even these minor details seem so

601
00:30:31,720 --> 00:30:34,040
Speaker 1: much more grim and dire. Again, I'm so glad this

602
00:30:34,080 --> 00:30:36,040
Speaker 1: stuff didn't exist because I would have totally been that

603
00:30:36,120 --> 00:30:39,040
Speaker 1: paranoid parent. Yeah. And then there's another angle on this

604
00:30:39,120 --> 00:30:42,160
Speaker 1: whole wearable technology smart device trend that that I want

605
00:30:42,200 --> 00:30:44,480
Speaker 1: to make sure we cover. So I wanted to talk

606
00:30:44,480 --> 00:30:46,480
Speaker 1: about the Internet of things, and that's the phrase of

607
00:30:46,600 --> 00:30:49,600
Speaker 1: tech developer named Kevin Ashton came up with to describe

608
00:30:49,640 --> 00:30:54,120
Speaker 1: the interconnected network of physical devices and vehicles that electronically

609
00:30:54,240 --> 00:30:57,160
Speaker 1: collect and share data. So I think of everything from

610
00:30:57,200 --> 00:31:01,040
Speaker 1: smartphones to smart refrigerators, robotic vacuums. I mean, the list

611
00:31:01,120 --> 00:31:02,960
Speaker 1: goes on and on, and pretty soon it's going to

612
00:31:03,000 --> 00:31:05,400
Speaker 1: be like every single product you know. And I feel

613
00:31:05,440 --> 00:31:07,880
Speaker 1: like most of us started hearing about this, this Internet

614
00:31:07,960 --> 00:31:10,560
Speaker 1: of things just a few years ago, but it's actually

615
00:31:10,640 --> 00:31:13,280
Speaker 1: an older term at this point. Right. I was reading

616
00:31:13,280 --> 00:31:14,840
Speaker 1: about some of this and it goes back to I

617
00:31:14,960 --> 00:31:17,520
Speaker 1: think the late nineties or so, and this was before

618
00:31:17,600 --> 00:31:20,240
Speaker 1: the smart tech boom of recent years. Yeah, so it

619
00:31:20,320 --> 00:31:23,520
Speaker 1: goes back to I think, and and it was definitely

620
00:31:23,600 --> 00:31:26,480
Speaker 1: forward looking. And I remember my friend was telling me

621
00:31:26,520 --> 00:31:28,760
Speaker 1: about it at the time and he said, m I

622
00:31:28,840 --> 00:31:30,960
Speaker 1: T was developing this table cloth that was gonna be

623
00:31:30,960 --> 00:31:32,680
Speaker 1: a smart table cloth. And I was like, how can

624
00:31:32,760 --> 00:31:35,360
Speaker 1: you make a smart table cloth? And he said, basically

625
00:31:35,440 --> 00:31:37,960
Speaker 1: like if you're putting a drink down, like a glass

626
00:31:38,000 --> 00:31:40,600
Speaker 1: of wine at a wrong angle, it'll account for that

627
00:31:40,800 --> 00:31:43,440
Speaker 1: and catch the glass. And he was also talking about

628
00:31:43,440 --> 00:31:45,640
Speaker 1: like umbrellas that would tell you it's about to rain

629
00:31:45,720 --> 00:31:47,320
Speaker 1: and remind you to take him with you. And and

630
00:31:47,400 --> 00:31:51,960
Speaker 1: this sound crazy, but but like flash forward twenty years

631
00:31:52,080 --> 00:31:56,360
Speaker 1: and according to the analysts, said Gartner, of the world

632
00:31:56,400 --> 00:32:00,600
Speaker 1: population is now online and around eight point four billion

633
00:32:00,760 --> 00:32:03,560
Speaker 1: web connected items are in use. Wow, that's a lot

634
00:32:03,680 --> 00:32:06,680
Speaker 1: of devices are especially when you consider that both of

635
00:32:06,720 --> 00:32:09,920
Speaker 1: those numbers they're only going to rise as time goes on.

636
00:32:10,520 --> 00:32:13,280
Speaker 1: You know, there's this growing catalog of the Internet of things,

637
00:32:13,360 --> 00:32:16,520
Speaker 1: and you think about how widespread they are, from cars

638
00:32:16,600 --> 00:32:20,280
Speaker 1: to household appliances or these health monitoring devices we were

639
00:32:20,320 --> 00:32:24,360
Speaker 1: talking about security sensors and all of these fitness trackers

640
00:32:24,400 --> 00:32:26,160
Speaker 1: that everybody seems to be using. And it's not just

641
00:32:26,280 --> 00:32:28,200
Speaker 1: for them. It's like their dogs and their cats and

642
00:32:28,240 --> 00:32:31,040
Speaker 1: their cows and their babies and all of these things.

643
00:32:31,080 --> 00:32:33,560
Speaker 1: So it's just it's everywhere, and it's led to this

644
00:32:33,800 --> 00:32:36,960
Speaker 1: level of connectedness that the world has never seen before.

645
00:32:37,480 --> 00:32:40,440
Speaker 1: And so with that comes this unique brand of paranoia.

646
00:32:40,680 --> 00:32:43,640
Speaker 1: That's right. So the Pew Research Center publishing report earlier

647
00:32:43,720 --> 00:32:46,560
Speaker 1: this year that highlighted the widespread concerns people have about

648
00:32:46,600 --> 00:32:50,240
Speaker 1: cyber text and account hacking and privacy violations related to

649
00:32:50,280 --> 00:32:53,360
Speaker 1: all these smart things, and you know, it's interesting, it's

650
00:32:53,440 --> 00:32:56,480
Speaker 1: it's you know, the very connectedness of the IoT is

651
00:32:56,560 --> 00:32:58,960
Speaker 1: what makes it seem like a liability, and it is

652
00:32:59,040 --> 00:33:02,400
Speaker 1: a liability. Like I was watching this thing on Wired

653
00:33:02,520 --> 00:33:05,080
Speaker 1: and and they showed how like hackers can hack into

654
00:33:05,120 --> 00:33:07,160
Speaker 1: a car on the highway and just slow it down

655
00:33:07,200 --> 00:33:09,480
Speaker 1: to twelve miles per hour. And in fact, I have

656
00:33:09,600 --> 00:33:12,840
Speaker 1: this one friend who won't buy cars from like after

657
00:33:12,920 --> 00:33:16,120
Speaker 1: a certain point in not late eighties or something, because

658
00:33:16,320 --> 00:33:18,760
Speaker 1: he has that same fear. But so, why do you

659
00:33:18,840 --> 00:33:20,880
Speaker 1: think so many of us buy into this idea of

660
00:33:21,400 --> 00:33:24,440
Speaker 1: connecting and monitoring all these different things when you know,

661
00:33:24,520 --> 00:33:27,480
Speaker 1: we do realize that they could be potentially dangerous or

662
00:33:27,520 --> 00:33:29,880
Speaker 1: somehow asking for trouble if we do so. So, I

663
00:33:29,920 --> 00:33:32,600
Speaker 1: don't know, why do we embrace this so wholeheartedly. Well,

664
00:33:32,760 --> 00:33:34,400
Speaker 1: it's it's for the same reason most of us don't

665
00:33:34,440 --> 00:33:37,640
Speaker 1: bother changing our privacy settings on Google or even adjusting

666
00:33:37,680 --> 00:33:40,440
Speaker 1: the ad preferences on our Facebook accounts, even though we're

667
00:33:40,560 --> 00:33:43,239
Speaker 1: vaguely aware that they're siphening our personal info for their

668
00:33:43,280 --> 00:33:48,760
Speaker 1: own game. And that reason is what convenience Okay, I mean,

669
00:33:48,840 --> 00:33:51,160
Speaker 1: it's it's so much easier to accept that our cool

670
00:33:51,240 --> 00:33:54,000
Speaker 1: tech comes with like a few unsightly strings attached and

671
00:33:54,120 --> 00:33:56,160
Speaker 1: and just move on from there. And I don't know,

672
00:33:56,200 --> 00:33:57,520
Speaker 1: I mean, I guess that makes sense. I mean, think

673
00:33:57,520 --> 00:33:59,720
Speaker 1: about how hard it would be for people to disconnect

674
00:33:59,760 --> 00:34:02,560
Speaker 1: from all these platforms and devices that have become a

675
00:34:02,720 --> 00:34:05,520
Speaker 1: bigger and bigger part of our lives. I mean, I

676
00:34:05,560 --> 00:34:08,239
Speaker 1: would think some people would probably trade any amount of

677
00:34:08,320 --> 00:34:11,440
Speaker 1: privacy just to hold onto that connection. Definitely. And that

678
00:34:11,600 --> 00:34:15,040
Speaker 1: same Pew report I mentioned earlier, like it basically says

679
00:34:15,120 --> 00:34:18,279
Speaker 1: the same thing. They talked over experts and we're able

680
00:34:18,320 --> 00:34:21,560
Speaker 1: to conclude from their responses that the desire for convenience

681
00:34:21,640 --> 00:34:24,840
Speaker 1: trump's concerns about safety in most people's minds. And and

682
00:34:24,920 --> 00:34:27,160
Speaker 1: here's a quote from Lee Rainey, the co author and

683
00:34:27,280 --> 00:34:31,920
Speaker 1: director of pew's Internet Technology and Science Research Center, The

684
00:34:32,040 --> 00:34:35,920
Speaker 1: IoT will bring advantages that are useful, that people's desire

685
00:34:36,000 --> 00:34:39,040
Speaker 1: for convenience will usually prevail over their concerns about risk,

686
00:34:39,120 --> 00:34:42,160
Speaker 1: and these factors will make it difficult, if not impossible,

687
00:34:42,360 --> 00:34:46,080
Speaker 1: for people to opt out of a highly connected life. Wow, alright, well,

688
00:34:46,120 --> 00:34:48,360
Speaker 1: I mean, I know the Internet of Things is supposed

689
00:34:48,360 --> 00:34:50,560
Speaker 1: to be this hopeful concept and it points to this,

690
00:34:51,040 --> 00:34:55,359
Speaker 1: I know, this more conclusive or connected society. But that's

691
00:34:55,360 --> 00:34:57,760
Speaker 1: a lot to think about it. It's it's pretty crazy,

692
00:34:57,920 --> 00:35:00,040
Speaker 1: but I don't want to go too far down a

693
00:35:00,080 --> 00:35:02,719
Speaker 1: paranoia path, because I do have to say that that.

694
00:35:02,840 --> 00:35:05,200
Speaker 1: On a funnier note, just looking around it was great

695
00:35:05,280 --> 00:35:07,920
Speaker 1: stumbling into some of these ridiculous attempts to cash in

696
00:35:08,080 --> 00:35:11,600
Speaker 1: on this growing IoT market, and I jotted down a

697
00:35:11,640 --> 00:35:13,319
Speaker 1: few of these, so I kind of want to take

698
00:35:13,320 --> 00:35:15,040
Speaker 1: a few minutes to share some of the more absurd

699
00:35:15,080 --> 00:35:17,360
Speaker 1: examples of these so called smart devices. What do you

700
00:35:17,400 --> 00:35:19,759
Speaker 1: say we do? Yeah? I love that idea, so I'm

701
00:35:19,800 --> 00:35:22,239
Speaker 1: gonna sorry. A funny one I found is called the

702
00:35:22,440 --> 00:35:24,600
Speaker 1: roll Scout, but you can go ahead and think of

703
00:35:24,640 --> 00:35:27,560
Speaker 1: it as the Internet of toilet paper. We needed an

704
00:35:27,600 --> 00:35:30,320
Speaker 1: Internet of toilet Basically, it's a toilet paper holder that

705
00:35:30,480 --> 00:35:33,680
Speaker 1: informs you via text, email or app notification when the

706
00:35:33,800 --> 00:35:38,080
Speaker 1: role is empty, and each holder costs about sixty I know,

707
00:35:38,600 --> 00:35:41,160
Speaker 1: but you know. According to the creators, roll Scout is

708
00:35:41,440 --> 00:35:45,800
Speaker 1: quote especially useful for small businesses such as cafes and

709
00:35:45,920 --> 00:35:49,040
Speaker 1: restaurants that have public restrooms and are focused on providing

710
00:35:49,080 --> 00:35:52,560
Speaker 1: the best customer experience possible. I have to admit I

711
00:35:52,640 --> 00:35:54,000
Speaker 1: was going to say that was one of the dumbest

712
00:35:54,040 --> 00:35:57,440
Speaker 1: things I'd heard of, but actually, for a restaurant or

713
00:35:57,480 --> 00:36:00,040
Speaker 1: a hotel or something like that. I kind of get it.

714
00:36:00,160 --> 00:36:01,719
Speaker 1: I also kind of want to buy one of these

715
00:36:01,800 --> 00:36:04,799
Speaker 1: just because it's so stupid, But sixty bucks, I think

716
00:36:04,840 --> 00:36:07,040
Speaker 1: I'm gonna have to pass on that. All right, Well,

717
00:36:07,120 --> 00:36:08,800
Speaker 1: here's one of a similar vein of things that we

718
00:36:08,960 --> 00:36:11,920
Speaker 1: put into this much easier to just check yourself category.

719
00:36:12,000 --> 00:36:14,279
Speaker 1: And it's it's a product from Thermos and it's called

720
00:36:14,360 --> 00:36:18,319
Speaker 1: the Connected Hydration Bottle and it it basically keeps track

721
00:36:18,400 --> 00:36:20,719
Speaker 1: of how much water you drink and sends your current

722
00:36:20,840 --> 00:36:24,080
Speaker 1: tally to either your fitbit app or your thermoss own

723
00:36:24,200 --> 00:36:28,240
Speaker 1: water tracking app. And it costs seven thousand dollars. Actually

724
00:36:28,239 --> 00:36:29,799
Speaker 1: didn't see how much it costs, but it just still

725
00:36:29,840 --> 00:36:33,920
Speaker 1: seemed unnecessary. So I found one called the Eggminder, and

726
00:36:34,000 --> 00:36:36,480
Speaker 1: it's a trade that fits inside your refrigerator and keeps

727
00:36:36,520 --> 00:36:39,200
Speaker 1: track with the quantity and freshness of up to fourteen

728
00:36:39,239 --> 00:36:41,960
Speaker 1: and your favorite eggs. I don't try putting a fifteenth

729
00:36:42,000 --> 00:36:44,080
Speaker 1: in there. So this is it's kind of like the

730
00:36:44,160 --> 00:36:47,600
Speaker 1: Internet of egg trays. What is it monitoring? Is it

731
00:36:47,680 --> 00:36:50,279
Speaker 1: monitoring like for cracks and their shells or something like

732
00:36:50,400 --> 00:36:54,000
Speaker 1: that or what? No, in fact, on structural integrity is

733
00:36:54,040 --> 00:36:57,200
Speaker 1: a little out of their scope, but it will send

734
00:36:57,239 --> 00:36:59,239
Speaker 1: a wireless signal to your phone to keep your breast.

735
00:36:59,280 --> 00:37:01,680
Speaker 1: An important develop have beens going on in your egg trays,

736
00:37:01,800 --> 00:37:04,920
Speaker 1: so things like how many eggs it currently contains and

737
00:37:05,160 --> 00:37:07,560
Speaker 1: whether any of them are at risk of spoiling. This

738
00:37:07,760 --> 00:37:10,839
Speaker 1: seems riveting. I mean, I know, we cover a lot

739
00:37:10,880 --> 00:37:12,759
Speaker 1: of topics on here that seems sort of silly at

740
00:37:12,800 --> 00:37:15,319
Speaker 1: first glance, and then then they kind of make more

741
00:37:15,400 --> 00:37:17,120
Speaker 1: sense once you look into them a bit more. And

742
00:37:17,200 --> 00:37:19,440
Speaker 1: I have to admit the toilet paper thing was that

743
00:37:19,600 --> 00:37:21,120
Speaker 1: for me. But I don't know. I'm going to go

744
00:37:21,160 --> 00:37:22,680
Speaker 1: out on a limb here and say the egg minder

745
00:37:22,840 --> 00:37:25,719
Speaker 1: is not one of those things. Yeah, it's probably the

746
00:37:25,760 --> 00:37:29,000
Speaker 1: safe bad, but you know, the worthiness of other IoT

747
00:37:29,160 --> 00:37:31,839
Speaker 1: products and even data tracking as a whole is still

748
00:37:31,960 --> 00:37:34,560
Speaker 1: something that's up for debate, and chances are we'll be

749
00:37:34,640 --> 00:37:37,200
Speaker 1: hearing a lot more about both their time saving advantages

750
00:37:37,320 --> 00:37:40,960
Speaker 1: and and their privacy infringing drawbacks in the years ahead. Yeah,

751
00:37:41,000 --> 00:37:43,600
Speaker 1: there's this. There's this quote from a writer and sociology

752
00:37:43,640 --> 00:37:46,600
Speaker 1: professor named Neil Gross, and it kind of seems fitting

753
00:37:46,680 --> 00:37:49,120
Speaker 1: for this discussion. I jotted it down here and it goes.

754
00:37:49,360 --> 00:37:52,240
Speaker 1: It goes like this. It says, um, in the next century,

755
00:37:52,320 --> 00:37:55,680
Speaker 1: planet Earth will done on electronic skin. It will use

756
00:37:55,760 --> 00:37:59,200
Speaker 1: the Internet as a scaffold to support and transmit its sensations.

757
00:37:59,640 --> 00:38:03,120
Speaker 1: This is already being stitched together. It consists of millions

758
00:38:03,160 --> 00:38:09,040
Speaker 1: of embedded electronic measuring devices, thermostats, pressure gauges, pollution detectors, cameras, microphones,

759
00:38:09,120 --> 00:38:13,799
Speaker 1: glucose sensors e k g s, electro and cephalographs. These

760
00:38:13,800 --> 00:38:17,799
Speaker 1: will probe and monitor cities and endangered species, the atmosphere,

761
00:38:17,880 --> 00:38:22,600
Speaker 1: our ships, highways and fleets of trucks, our conversations, our bodies,

762
00:38:23,080 --> 00:38:26,800
Speaker 1: even our dreams. Wow. So that that's definitely like smart

763
00:38:26,960 --> 00:38:29,560
Speaker 1: and poetic way to think about the future. But um,

764
00:38:29,800 --> 00:38:31,759
Speaker 1: you know what else is smart and poetic? The part

765
00:38:31,800 --> 00:38:45,520
Speaker 1: time genius fact off. That's right, let's do I can

766
00:38:45,640 --> 00:38:47,520
Speaker 1: kick us off here, all right. Here's something to add

767
00:38:47,520 --> 00:38:50,319
Speaker 1: to the already immense list of creepy things Facebook knows

768
00:38:50,400 --> 00:38:53,160
Speaker 1: about you. And that's whether or not your relationship will last.

769
00:38:53,560 --> 00:38:56,400
Speaker 1: In a two thousand fourteen study of Facebook data, scientists

770
00:38:56,440 --> 00:39:00,520
Speaker 1: concluded that, based on activities and status updates, the company

771
00:39:00,600 --> 00:39:03,480
Speaker 1: can make scarily accurate predictions about whether a couple will

772
00:39:03,520 --> 00:39:07,560
Speaker 1: sink or swim. According to his research, being Facebook official

773
00:39:08,040 --> 00:39:10,680
Speaker 1: really helps your chances. I wanted to congratulate you and

774
00:39:10,760 --> 00:39:14,440
Speaker 1: Lizzie being Facebook official, but about half of all Facebook

775
00:39:14,480 --> 00:39:17,440
Speaker 1: relationships that has survived three months are likely to survive

776
00:39:17,560 --> 00:39:21,719
Speaker 1: four years or longer. Well, speaking of gigantic companies that

777
00:39:21,840 --> 00:39:24,279
Speaker 1: know way too much information about us, do you know

778
00:39:24,400 --> 00:39:27,120
Speaker 1: that target can tell if the female customer is pregnant

779
00:39:27,400 --> 00:39:31,440
Speaker 1: occasionally even before she knows herself that. I know. So.

780
00:39:31,840 --> 00:39:34,520
Speaker 1: Back in two thousand two of the statistician named Andrew

781
00:39:34,600 --> 00:39:36,960
Speaker 1: Pole was hired to help the chain develop a pregnancy

782
00:39:37,080 --> 00:39:40,200
Speaker 1: prediction model to better advertised as soon to be mothers.

783
00:39:40,640 --> 00:39:43,759
Speaker 1: And as soon as the model was implemented, Targets Mom

784
00:39:43,840 --> 00:39:47,279
Speaker 1: and Baby sales have They've skyrocketed, and they've helped to

785
00:39:47,320 --> 00:39:51,399
Speaker 1: grow Targets revenue by thirteen billion dollars in the same period. God,

786
00:39:51,520 --> 00:39:54,000
Speaker 1: that's crazy. All right, Well, how about I Know Where

787
00:39:54,040 --> 00:39:58,040
Speaker 1: Your Cat Lives dot com a site that helps make

788
00:39:58,080 --> 00:40:01,719
Speaker 1: the Internet a little more transparent. So using invisible geographic

789
00:40:01,800 --> 00:40:04,640
Speaker 1: location data embedded in the cat photos we upload to

790
00:40:04,680 --> 00:40:07,120
Speaker 1: social media or other people do I've never uploaded the

791
00:40:07,160 --> 00:40:10,120
Speaker 1: cat photos social media. The site presents a sampling of

792
00:40:10,200 --> 00:40:13,640
Speaker 1: over one million public pictures of cats align with their

793
00:40:13,719 --> 00:40:18,759
Speaker 1: real locations on a world map. That sounds terrifying tonight. So,

794
00:40:18,960 --> 00:40:20,800
Speaker 1: we we've been talking so much about what the Internet

795
00:40:20,880 --> 00:40:22,759
Speaker 1: knows about us that I thought it'd be smart to

796
00:40:22,800 --> 00:40:24,840
Speaker 1: turn the tables and mentioned a few cool things we

797
00:40:25,000 --> 00:40:28,280
Speaker 1: know about the Internet. Yeah. So, so, for for starters,

798
00:40:28,400 --> 00:40:31,240
Speaker 1: all the moving information contained on the Internet weighs about

799
00:40:31,440 --> 00:40:35,400
Speaker 1: as much as a single strawberry. That's a going to

800
00:40:35,480 --> 00:40:38,880
Speaker 1: a physicist named Russell Sites who determined that the billions

801
00:40:38,960 --> 00:40:41,680
Speaker 1: of data and motion, like all those moving electrons on

802
00:40:41,719 --> 00:40:44,840
Speaker 1: the Internet, they only add up to roughly fifty grams

803
00:40:45,040 --> 00:40:48,239
Speaker 1: or two ounces. And and as for the Internet's data

804
00:40:48,280 --> 00:40:51,840
Speaker 1: at rest, the five million terrobytes or so of static

805
00:40:51,960 --> 00:40:54,839
Speaker 1: information and storage like that adds up to even less

806
00:40:54,880 --> 00:40:57,880
Speaker 1: mass than a grain of sand. Wow. That is incredible,

807
00:40:58,800 --> 00:41:00,600
Speaker 1: all right. Well, for for anyone who wants an eerie

808
00:41:00,600 --> 00:41:03,920
Speaker 1: illustration of web tracking at work, check out the experimental

809
00:41:03,960 --> 00:41:06,919
Speaker 1: website known as click The Once they are a stream

810
00:41:06,960 --> 00:41:09,640
Speaker 1: of detailed information, will call out all the info your

811
00:41:09,680 --> 00:41:12,839
Speaker 1: browser is leaking online, everything from the number of core

812
00:41:12,960 --> 00:41:15,680
Speaker 1: processors in your computer to where your cursor is currently

813
00:41:15,760 --> 00:41:17,840
Speaker 1: hovering on the page. If you want to try it

814
00:41:17,840 --> 00:41:20,760
Speaker 1: out for yourself, go to click click click dot click.

815
00:41:22,320 --> 00:41:25,600
Speaker 1: Pretty easy to remember. So here's another dirt we've got

816
00:41:25,680 --> 00:41:29,239
Speaker 1: on the Internet. Fact, according to an article and news scientists,

817
00:41:29,600 --> 00:41:32,960
Speaker 1: some researchers now estimate it takes us stunning a hundred

818
00:41:33,080 --> 00:41:36,400
Speaker 1: fifty two billion kill a lott hours per year simply

819
00:41:36,480 --> 00:41:39,280
Speaker 1: to power the data centers that allow the Internet to function.

820
00:41:39,480 --> 00:41:41,680
Speaker 1: So if you were to add that power to the

821
00:41:41,800 --> 00:41:44,479
Speaker 1: energy used by all the computers and other devices linked

822
00:41:44,480 --> 00:41:46,520
Speaker 1: to the Net, the total would account for as much

823
00:41:46,520 --> 00:41:49,080
Speaker 1: as two percent of all the CEO two emissions caused

824
00:41:49,120 --> 00:41:52,400
Speaker 1: by humans. And just to give that a little perspective,

825
00:41:52,840 --> 00:41:54,879
Speaker 1: that two percent will put the Internet on the same

826
00:41:55,040 --> 00:41:59,480
Speaker 1: level as the entire aviation industry. That's a lot, Okay,

827
00:42:00,040 --> 00:42:02,120
Speaker 1: Well that I do have to say that large carbon

828
00:42:02,160 --> 00:42:04,920
Speaker 1: footprint is definitely something we can use to incriminate the

829
00:42:04,960 --> 00:42:07,000
Speaker 1: Internet should it ever come to this. We'll see if

830
00:42:07,040 --> 00:42:10,080
Speaker 1: that happens. But but on that basis alone, I think

831
00:42:10,120 --> 00:42:12,440
Speaker 1: you get to take home today's title and that's it

832
00:42:12,520 --> 00:42:14,319
Speaker 1: for today's show, But be sure to hop on over

833
00:42:14,400 --> 00:42:15,839
Speaker 1: to stuff they don't want you to know to check

834
00:42:15,880 --> 00:42:18,440
Speaker 1: out their episode on how people are attempting to remove

835
00:42:18,520 --> 00:42:21,640
Speaker 1: their identity from the Internet. Thanks again to Noel, Ben

836
00:42:21,760 --> 00:42:23,640
Speaker 1: and Matt for joining us, and thanks so much to

837
00:42:23,680 --> 00:42:39,320
Speaker 1: all of you for listening. Everybody, Thanks again for listening.

838
00:42:39,520 --> 00:42:41,640
Speaker 1: Part Time Genius is a production of how stuff works

839
00:42:41,680 --> 00:42:44,200
Speaker 1: and wouldn't be possible without several brilliant people who do

840
00:42:44,320 --> 00:42:47,320
Speaker 1: the important things we couldn't even begin to understand. CHRISTA

841
00:42:47,400 --> 00:42:49,960
Speaker 1: McNeil does the editing thing. Noel Brown made the theme

842
00:42:50,040 --> 00:42:52,920
Speaker 1: song and does the mixy mixy sound thing. Jerry Rowland

843
00:42:52,960 --> 00:42:56,240
Speaker 1: does the exact producer thing. Gabeluesier is our lead researcher,

844
00:42:56,320 --> 00:42:59,280
Speaker 1: with support from the Research Army including Austin Thompson, Nolan

845
00:42:59,320 --> 00:43:01,480
Speaker 1: Brown and Lucas Sadam and Eve Jeff Cook gets the

846
00:43:01,520 --> 00:43:03,759
Speaker 1: show to your ears. Good job, Eves. If you like

847
00:43:03,880 --> 00:43:05,640
Speaker 1: what you heard, we hope you'll subscribe, And if you

848
00:43:05,760 --> 00:43:07,719
Speaker 1: really really like what you've heard, maybe you could leave

849
00:43:07,719 --> 00:43:09,720
Speaker 1: a good review for us. Do we did? We forget

850
00:43:09,800 --> 00:43:10,960
Speaker 1: Jason Jason, who