1
00:00:04,160 --> 00:00:05,880
Speaker 1: There Are No Girls on the Internet, as a production

2
00:00:05,920 --> 00:00:13,440
Speaker 1: of iHeartRadio and Unbossed Creative. I'm Bridge Todd and this

3
00:00:13,520 --> 00:00:18,239
Speaker 1: is there Are No Girls on the Internet. Thanks for

4
00:00:18,280 --> 00:00:20,360
Speaker 1: tuning into their No Girls on the Internet, where we

5
00:00:20,440 --> 00:00:24,800
Speaker 1: explore the intersection of technology, social media, the Internet, and identity.

6
00:00:25,280 --> 00:00:28,560
Speaker 1: And this is another installment of our weekly news Roundup

7
00:00:28,840 --> 00:00:31,200
Speaker 1: where we dig into all those stories on the Internet

8
00:00:31,200 --> 00:00:33,080
Speaker 1: that you might have missed so you don't have to.

9
00:00:33,720 --> 00:00:37,720
Speaker 1: I am so excited to welcome back our super producer, Joey.

10
00:00:37,800 --> 00:00:41,480
Speaker 2: Joey, it's been so long. How are you? Hello? Yo?

11
00:00:41,680 --> 00:00:45,480
Speaker 2: My god, it's friend forever. I'm good. You know, we're

12
00:00:47,280 --> 00:00:50,920
Speaker 2: moving along. Life is happening. Things are happening in the world,

13
00:00:51,360 --> 00:00:53,920
Speaker 2: and we're coping with those things happening.

14
00:00:54,080 --> 00:00:56,840
Speaker 1: Life is continuing to life. But I do know that

15
00:00:56,920 --> 00:01:00,040
Speaker 1: you've got some exciting like podcast projects.

16
00:00:59,560 --> 00:01:02,720
Speaker 2: Going on, right, I do. Yes, there's a show that

17
00:01:02,760 --> 00:01:06,120
Speaker 2: I work on. It's called Afterlives and season two just

18
00:01:06,360 --> 00:01:10,920
Speaker 2: came out recently. I believe you're on episode five when

19
00:01:10,920 --> 00:01:14,720
Speaker 2: this show is going to drop, But yeah, episodes are

20
00:01:14,720 --> 00:01:18,520
Speaker 2: still dropping. And this season is about Marsha By Johnson

21
00:01:18,720 --> 00:01:23,000
Speaker 2: and her life and legacy. So if you are interested

22
00:01:23,000 --> 00:01:26,480
Speaker 2: at all in like queer history or New York City history,

23
00:01:26,720 --> 00:01:30,720
Speaker 2: or just like cool things that have happened and also

24
00:01:30,840 --> 00:01:33,640
Speaker 2: very sad things that have happened, you should check out Afterlives.

25
00:01:33,959 --> 00:01:36,759
Speaker 1: It's such a good show. I cannot speak more highly

26
00:01:36,800 --> 00:01:39,440
Speaker 1: of it. We are fans of it very much here

27
00:01:39,520 --> 00:01:41,000
Speaker 1: over at their No Girls on the Internet.

28
00:01:41,560 --> 00:01:42,839
Speaker 2: Yeah, listen to that show.

29
00:01:43,560 --> 00:01:46,600
Speaker 1: Okay, So from that sort of beacon of light to

30
00:01:47,040 --> 00:01:49,880
Speaker 1: a I'm going to say beacon of dark, although that

31
00:01:49,960 --> 00:01:54,400
Speaker 1: might be an overreaction. But Joey, do you remember how

32
00:01:54,880 --> 00:01:58,240
Speaker 1: Joe Rogan had Trump on his podcast right before the election,

33
00:01:58,760 --> 00:02:02,280
Speaker 1: after v for a very long time that he would

34
00:02:02,360 --> 00:02:04,520
Speaker 1: never have Trump on his podcast. By the way, I

35
00:02:04,560 --> 00:02:06,840
Speaker 1: did win one hundred dollars bet on that. I bet

36
00:02:06,880 --> 00:02:09,680
Speaker 1: that Joe Rogan would have Trump on his show before

37
00:02:09,720 --> 00:02:11,919
Speaker 1: the election, and he did it. I want one hundred dollars.

38
00:02:11,960 --> 00:02:14,240
Speaker 1: I've still not gotten the money from that bet that

39
00:02:14,280 --> 00:02:14,799
Speaker 1: I did win.

40
00:02:15,280 --> 00:02:17,720
Speaker 2: I'm shocked that somebody would bet against that, Like I

41
00:02:17,760 --> 00:02:20,800
Speaker 2: feel like that was a given. But it was good. Yeah,

42
00:02:20,840 --> 00:02:22,400
Speaker 2: but yes, I do, I do remember.

43
00:02:22,760 --> 00:02:25,320
Speaker 1: And then after Trump was elected, Rogan said that he

44
00:02:25,360 --> 00:02:28,920
Speaker 1: felt that he was personally the reason why Trump won. Well,

45
00:02:29,200 --> 00:02:31,880
Speaker 1: now Joe Rogan is looking at what Trump has actually

46
00:02:31,880 --> 00:02:35,200
Speaker 1: been doing and saying, I didn't vote for this, even

47
00:02:35,200 --> 00:02:37,800
Speaker 1: though I feel that Trump could not have been clearer

48
00:02:38,280 --> 00:02:40,680
Speaker 1: that he intended to target immigrants the way that he

49
00:02:40,720 --> 00:02:43,360
Speaker 1: has been doing. On a show, Rogan has been calling

50
00:02:43,400 --> 00:02:46,399
Speaker 1: out Trump for his handling and immigration, saying, there's two

51
00:02:46,400 --> 00:02:49,919
Speaker 1: things that are insane. One is the targeting of migrant workers.

52
00:02:49,960 --> 00:02:53,000
Speaker 1: Not cartel members, not gang members, not drug dealers, just

53
00:02:53,080 --> 00:02:57,239
Speaker 1: construction workers showing up at construction sites, raiding them gardeners. Like, really,

54
00:02:57,960 --> 00:03:00,400
Speaker 1: the Trump administration, if they're running and they say we're

55
00:03:00,440 --> 00:03:01,959
Speaker 1: going to go to home depot and arrest all the

56
00:03:01,960 --> 00:03:04,000
Speaker 1: people at home Depot, We're going to go to construction

57
00:03:04,080 --> 00:03:06,040
Speaker 1: sites and we're just going to like tackle people at

58
00:03:06,080 --> 00:03:09,080
Speaker 1: construction sites. I don't think anybody would have signed up

59
00:03:09,120 --> 00:03:12,280
Speaker 1: for that. The Washington Post reported that these comments came

60
00:03:12,320 --> 00:03:16,040
Speaker 1: after Rogan personally sat down and discussed immigration policy with

61
00:03:16,080 --> 00:03:19,119
Speaker 1: Trump at a private dinner and pushed back on him

62
00:03:19,200 --> 00:03:22,560
Speaker 1: deporting workers who have not committed crimes. Both Joe Rogan

63
00:03:22,600 --> 00:03:25,120
Speaker 1: and Dana White, a friend of both Rogans and Trump's,

64
00:03:25,240 --> 00:03:28,240
Speaker 1: who was the CEO of the Ultimate Fighting Championship had

65
00:03:28,240 --> 00:03:31,320
Speaker 1: dinner with Trump on June thirtieth, according to The Washington Post,

66
00:03:31,560 --> 00:03:34,480
Speaker 1: who quoted somebody who had knowledge of this meeting. First

67
00:03:34,480 --> 00:03:36,160
Speaker 1: of all, the whole thing is just sort of like

68
00:03:36,960 --> 00:03:40,840
Speaker 1: top sy turvy that we have Joe freakin' Rogan having

69
00:03:40,840 --> 00:03:44,840
Speaker 1: a private sit down to talk to Trump about immigration policies.

70
00:03:44,880 --> 00:03:46,120
Speaker 1: I just will never be over it.

71
00:03:46,560 --> 00:03:50,560
Speaker 2: Yeah, And the CEO of Ultimate Fighting Champion to I love,

72
00:03:50,680 --> 00:03:52,960
Speaker 2: I mean I not love. Love is the wrong word.

73
00:03:53,000 --> 00:03:56,800
Speaker 2: I find it like kind of amusing how much like

74
00:03:58,720 --> 00:04:02,680
Speaker 2: WWE and like professional wrestling stuff has been involved with

75
00:04:02,720 --> 00:04:04,720
Speaker 2: this illustration. Like I don't know, there's just something so

76
00:04:05,000 --> 00:04:08,080
Speaker 2: like like if this were in a movie, like that

77
00:04:08,120 --> 00:04:10,000
Speaker 2: would be too much of a metaphor, Like I would

78
00:04:10,000 --> 00:04:12,360
Speaker 2: be like too happy handed of a metaphor. I love

79
00:04:12,360 --> 00:04:14,920
Speaker 2: how many people are like taking credit for Like didn't

80
00:04:14,920 --> 00:04:17,240
Speaker 2: Elon Musk also say like, oh, yeah, I'm there, I'm

81
00:04:17,279 --> 00:04:19,680
Speaker 2: one hundred percent of the reason hero. Like who's gonna

82
00:04:19,680 --> 00:04:23,200
Speaker 2: be next, like some random part like every single white

83
00:04:23,279 --> 00:04:25,800
Speaker 2: dude with the podcast is gonna pop out and be

84
00:04:25,920 --> 00:04:29,760
Speaker 2: like it was me. I was responded, I actually was responsible, guys.

85
00:04:29,800 --> 00:04:31,000
Speaker 2: I'm sorry it was jo.

86
00:04:35,440 --> 00:04:39,240
Speaker 1: Yeah, and I think, I mean, I I'm weirdly torn

87
00:04:39,279 --> 00:04:41,679
Speaker 1: on this. We did an episode where we're talking about

88
00:04:41,680 --> 00:04:46,000
Speaker 1: how the podcaster Theovonne, who also took credit for Trump

89
00:04:46,320 --> 00:04:47,200
Speaker 1: getting re elected.

90
00:04:47,920 --> 00:04:50,160
Speaker 2: I aw was a rough one for me to edit.

91
00:04:50,279 --> 00:04:53,440
Speaker 2: I actually I only knew theo Von from his like

92
00:04:53,480 --> 00:04:56,320
Speaker 2: clips that would be on TikTok, like people would like

93
00:04:56,360 --> 00:04:58,160
Speaker 2: lipsing to them on TikTok, and I was like, oh,

94
00:04:58,160 --> 00:04:59,880
Speaker 2: this is funny. I had no idea that he was

95
00:05:00,920 --> 00:05:01,680
Speaker 2: so big.

96
00:05:01,920 --> 00:05:05,000
Speaker 1: This is actually I mean, it does say something about

97
00:05:05,080 --> 00:05:09,240
Speaker 1: the short form content culture. Because I knew Theovonn from

98
00:05:09,600 --> 00:05:13,039
Speaker 1: I'm sorry to say MTV is the Challenge. Then, I

99
00:05:13,160 --> 00:05:16,160
Speaker 1: never knew about his podcast. I learned about him from

100
00:05:16,279 --> 00:05:19,320
Speaker 1: short like super short form YouTube TikTok stuff, and I

101
00:05:19,400 --> 00:05:21,800
Speaker 1: was like, oh, this guy's funny. This guy's funny, Like

102
00:05:21,839 --> 00:05:23,800
Speaker 1: he's really a funny, personable guy.

103
00:05:23,960 --> 00:05:25,480
Speaker 2: He got me. That's how they get you.

104
00:05:25,720 --> 00:05:29,200
Speaker 1: It wasn't until sitting down and listening to his long

105
00:05:29,320 --> 00:05:33,600
Speaker 1: form content, which I do think is sort of he

106
00:05:33,680 --> 00:05:35,719
Speaker 1: definitely knows what he's doing. I think I think I

107
00:05:35,760 --> 00:05:38,719
Speaker 1: think he is coming off sort of ah shuts g whiz.

108
00:05:38,839 --> 00:05:40,479
Speaker 2: But I think he's pretty.

109
00:05:40,160 --> 00:05:45,000
Speaker 1: Smart, educative guy, very intentional about how he is presenting himself.

110
00:05:45,279 --> 00:05:48,960
Speaker 1: But a while back he used his show to speak

111
00:05:49,000 --> 00:05:52,800
Speaker 1: out about what's happening in Gaza, which a lot of

112
00:05:52,800 --> 00:05:56,200
Speaker 1: people were like, that's great any platform. However, he did

113
00:05:56,279 --> 00:05:59,840
Speaker 1: that just a few like like a week after going

114
00:05:59,839 --> 00:06:02,279
Speaker 1: on a military trip with Trump.

115
00:06:02,440 --> 00:06:04,800
Speaker 2: He's close personal friends with the Kushners.

116
00:06:05,400 --> 00:06:08,040
Speaker 1: That is difficult for me, Like I understand people who

117
00:06:08,120 --> 00:06:13,480
Speaker 1: say anybody who's using their platform to convince the average

118
00:06:13,520 --> 00:06:16,279
Speaker 1: person that what's happening right now is not great is

119
00:06:16,320 --> 00:06:18,680
Speaker 1: doing a good thing. And I am very sympathetic to

120
00:06:18,720 --> 00:06:21,880
Speaker 1: that argument. I absolutely get it. But it is tough

121
00:06:21,880 --> 00:06:23,839
Speaker 1: for me the same way that it is tough for

122
00:06:23,960 --> 00:06:29,279
Speaker 1: me to have someone like Joe Rogan say, this is

123
00:06:29,320 --> 00:06:31,560
Speaker 1: not what I wanted, this is not what I voted for,

124
00:06:31,600 --> 00:06:33,920
Speaker 1: this is not what I advocated for. Joe Rogan lives

125
00:06:33,920 --> 00:06:38,400
Speaker 1: in Texas. I have a hard time believing that news

126
00:06:38,440 --> 00:06:41,320
Speaker 1: of what Trump intended to do when it came to

127
00:06:41,400 --> 00:06:45,720
Speaker 1: immigration didn't make it in to Joe Rogan's, you know,

128
00:06:46,000 --> 00:06:48,240
Speaker 1: to his understanding of what was going on.

129
00:06:48,480 --> 00:06:51,960
Speaker 2: I guess maybe you could say I assumed.

130
00:06:51,440 --> 00:06:54,160
Speaker 1: That he was going to be doing all of this

131
00:06:54,240 --> 00:06:58,360
Speaker 1: to immigrants who committed crimes like cartel members and rapists

132
00:06:58,400 --> 00:07:02,080
Speaker 1: and gang members. But I just don't believe that Joe

133
00:07:02,200 --> 00:07:04,880
Speaker 1: Rogan is that stupid. I think he's a savvy guy.

134
00:07:05,240 --> 00:07:07,520
Speaker 1: I have a hard time personally believing him when he

135
00:07:07,560 --> 00:07:10,360
Speaker 1: says why I wouldn't have signed up for this, I

136
00:07:10,400 --> 00:07:13,000
Speaker 1: didn't vote for this. I think it's possible that maybe

137
00:07:13,040 --> 00:07:17,360
Speaker 1: he did not actually, like sit down and conceptualize how

138
00:07:17,480 --> 00:07:20,960
Speaker 1: ugly and odious these kinds of policies would be, you know,

139
00:07:21,080 --> 00:07:23,280
Speaker 1: going after people who are showing up to work, going

140
00:07:23,320 --> 00:07:26,440
Speaker 1: after people who are showing up to you know, legal

141
00:07:26,840 --> 00:07:29,880
Speaker 1: court appointments and stuff like quote unquote doing everything right.

142
00:07:30,080 --> 00:07:32,480
Speaker 1: I don't think that it's possible that maybe he didn't

143
00:07:33,320 --> 00:07:37,360
Speaker 1: think through what that would be like. But like you know,

144
00:07:37,440 --> 00:07:40,080
Speaker 1: ISI's budget is now one hundred and seventy billion dollars

145
00:07:40,120 --> 00:07:42,120
Speaker 1: over the next few years, more than NASA, more than

146
00:07:42,160 --> 00:07:44,880
Speaker 1: public health, more than education, more than anything. It's the

147
00:07:44,920 --> 00:07:47,240
Speaker 1: most well funded police force in the country now, and

148
00:07:47,280 --> 00:07:50,680
Speaker 1: they have this vastly increased surveillance network that we're all

149
00:07:50,680 --> 00:07:51,880
Speaker 1: going to be subjected to now.

150
00:07:52,120 --> 00:07:54,880
Speaker 2: And I mean, this is what Joe Rogan helped usher

151
00:07:54,960 --> 00:08:01,240
Speaker 2: in Yeah, yeah, no, I it's and I agree, like

152
00:08:01,360 --> 00:08:04,160
Speaker 2: I do feel really torn where part of me is like, yeah, no,

153
00:08:04,280 --> 00:08:07,920
Speaker 2: like Joe Rogan's a really savvy guy. He knows the

154
00:08:08,040 --> 00:08:11,240
Speaker 2: media ecosyst to like that's how he got where he

155
00:08:11,360 --> 00:08:14,560
Speaker 2: is today. Also, I do believe people are kind of

156
00:08:14,600 --> 00:08:15,760
Speaker 2: stupid and like I think a.

157
00:08:15,720 --> 00:08:18,320
Speaker 3: Lot of because it's like this is something you keep hearing,

158
00:08:18,400 --> 00:08:20,720
Speaker 3: Like I feel like I keep hearing this statement where

159
00:08:20,720 --> 00:08:22,800
Speaker 3: people are like, oh, but I didn't realize he like

160
00:08:23,000 --> 00:08:25,320
Speaker 3: really meant that or whatever, and I'm like, oh, like

161
00:08:25,680 --> 00:08:29,400
Speaker 3: there is cognitive different dissidence happening where like people can

162
00:08:29,840 --> 00:08:30,480
Speaker 3: I don't even know.

163
00:08:30,600 --> 00:08:33,079
Speaker 2: I'm I am not. I am far from a psychologist,

164
00:08:33,120 --> 00:08:35,000
Speaker 2: so I don't listen to me on this, but it

165
00:08:35,040 --> 00:08:36,480
Speaker 2: feels like it's one of those things where it's like

166
00:08:37,080 --> 00:08:38,920
Speaker 2: people get so caught up in like the messaging that

167
00:08:38,960 --> 00:08:40,840
Speaker 2: they don't actually listen to like what they're saying, and

168
00:08:40,840 --> 00:08:43,240
Speaker 2: then they want to act the prize when what was

169
00:08:43,240 --> 00:08:46,160
Speaker 2: being said actually happens. And this is like another instance

170
00:08:46,160 --> 00:08:47,760
Speaker 2: of that. So part of me is like, I don't know,

171
00:08:47,920 --> 00:08:50,880
Speaker 2: is he being genuine and saying like, well, I didn't

172
00:08:50,920 --> 00:08:54,280
Speaker 2: realize this was gonna happen, or is it just like yeah,

173
00:08:54,280 --> 00:08:56,679
Speaker 2: I know you're like cash grab didn't work out the

174
00:08:56,760 --> 00:09:02,719
Speaker 2: way you wanted it to and you're backtracking. Who's to say, yeah.

175
00:09:02,480 --> 00:09:05,280
Speaker 1: I saw this really compelling post on I think threads

176
00:09:05,280 --> 00:09:07,960
Speaker 1: where someone was like the people with big platforms who

177
00:09:08,040 --> 00:09:10,360
Speaker 1: advocated for Trump and are now saying, well, I didn't

178
00:09:10,400 --> 00:09:13,079
Speaker 1: vote for this and are backing away from it. They

179
00:09:13,160 --> 00:09:15,680
Speaker 1: probably crunched the numbers and said, listen, the stuff that

180
00:09:15,760 --> 00:09:19,520
Speaker 1: is happening right now is odious and indefensible and horrible,

181
00:09:19,880 --> 00:09:23,600
Speaker 1: and audiences don't like it, so let's backtrack a little bit.

182
00:09:23,679 --> 00:09:26,960
Speaker 1: Let's not align you publicly with this anymore, which I

183
00:09:26,960 --> 00:09:30,040
Speaker 1: thought was very compelling. And I mean, I just like

184
00:09:30,040 --> 00:09:34,040
Speaker 1: with the Theovonn argument, I don't want to discount that

185
00:09:34,080 --> 00:09:37,800
Speaker 1: it probably is good to have these everyday messengers like

186
00:09:37,840 --> 00:09:40,959
Speaker 1: Joe Rogan and Theovonn speaking up against Ice in these

187
00:09:41,000 --> 00:09:42,400
Speaker 1: common sense ways.

188
00:09:42,240 --> 00:09:44,959
Speaker 2: Because you know, anybody who is getting that.

189
00:09:44,880 --> 00:09:47,000
Speaker 1: Message out I think is probably it's like it's like

190
00:09:47,160 --> 00:09:49,560
Speaker 1: doing a good thing. A lot of these people would

191
00:09:49,600 --> 00:09:51,320
Speaker 1: never listen to a podcast like mine. They would never

192
00:09:51,360 --> 00:09:55,880
Speaker 1: listen to a message or like me, totally get it. However, Like,

193
00:09:56,000 --> 00:09:58,840
Speaker 1: for instance, would I, as a black woman, be allowed

194
00:09:59,000 --> 00:10:04,199
Speaker 1: to be so spectacularly wrong in public and have people say, well,

195
00:10:04,200 --> 00:10:06,480
Speaker 1: at least she's getting it right now. Like, I'm just

196
00:10:06,679 --> 00:10:09,400
Speaker 1: very curious how we got to a position where you

197
00:10:09,480 --> 00:10:12,559
Speaker 1: can be so loud and so wrong for so long,

198
00:10:12,920 --> 00:10:15,920
Speaker 1: but then if you like eventually get to the right position,

199
00:10:16,400 --> 00:10:18,400
Speaker 1: everybody's supposed to be like, oh, well, at least he

200
00:10:18,440 --> 00:10:18,760
Speaker 1: got there.

201
00:10:18,760 --> 00:10:20,880
Speaker 2: At least he's doing the right thing now, and now

202
00:10:20,880 --> 00:10:21,360
Speaker 2: for nothing.

203
00:10:21,840 --> 00:10:25,480
Speaker 1: I feel like somebody that has a big as big

204
00:10:25,520 --> 00:10:28,480
Speaker 1: of a megaphone as Joe Rogan does does kind of

205
00:10:28,480 --> 00:10:31,640
Speaker 1: have a moral responsibility to understand what they are doing

206
00:10:31,920 --> 00:10:34,280
Speaker 1: when they promote a candidate. So even if we take

207
00:10:34,360 --> 00:10:36,440
Speaker 1: him at face value and accept that like, okay, maybe

208
00:10:36,440 --> 00:10:39,559
Speaker 1: he truly did not think it through and didn't realize

209
00:10:40,000 --> 00:10:43,280
Speaker 1: bet Trump was going to do exactly what he openly

210
00:10:43,320 --> 00:10:45,080
Speaker 1: said he was going to do what he campaigned on.

211
00:10:45,880 --> 00:10:48,920
Speaker 1: I just I don't know that I didn't know is

212
00:10:48,960 --> 00:10:51,520
Speaker 1: a good enough excuse. And I feel the thing that

213
00:10:51,600 --> 00:10:55,760
Speaker 1: gets me is like, why not say I personally got

214
00:10:55,760 --> 00:10:58,880
Speaker 1: this wrong. I made a mistake. I let down the

215
00:10:58,920 --> 00:11:01,920
Speaker 1: audience who comes to me for information because I didn't

216
00:11:01,960 --> 00:11:03,920
Speaker 1: I didn't think it all the way through, and I

217
00:11:04,040 --> 00:11:06,079
Speaker 1: led people to make that same mistake.

218
00:11:06,240 --> 00:11:08,320
Speaker 2: I kind of bragged about it too for a little while.

219
00:11:08,600 --> 00:11:12,360
Speaker 2: This is on me bridgitant. Men can't do that, They're

220
00:11:12,400 --> 00:11:13,640
Speaker 2: not allowed to do that.

221
00:11:14,760 --> 00:11:17,520
Speaker 1: Yeah, I think the thing that gets me is like that,

222
00:11:18,200 --> 00:11:21,520
Speaker 1: like inability to just say, like I've said things I

223
00:11:21,559 --> 00:11:23,600
Speaker 1: wish I hadn't said on this podcast. If somebody asked

224
00:11:23,640 --> 00:11:25,280
Speaker 1: me what those things were, I'd be happy to tell

225
00:11:25,320 --> 00:11:29,120
Speaker 1: them the kind of way that they talk about it

226
00:11:29,160 --> 00:11:32,200
Speaker 1: with this kind of pat how On after the election,

227
00:11:32,280 --> 00:11:34,640
Speaker 1: he was like, I personally did this, I personally got

228
00:11:34,679 --> 00:11:38,280
Speaker 1: Trump in office, and now there's just this passive happenstance

229
00:11:38,320 --> 00:11:40,880
Speaker 1: of like how could Trump be elected and do these

230
00:11:40,960 --> 00:11:43,640
Speaker 1: kinds of things. That is the quality to it that

231
00:11:44,520 --> 00:11:46,440
Speaker 1: gets me that I have such trouble with that. Just

232
00:11:46,559 --> 00:11:49,600
Speaker 1: be honest about it. You got it wrong, you made

233
00:11:49,600 --> 00:11:52,400
Speaker 1: a mistake, you wish you hadn't. What's happening now is

234
00:11:52,440 --> 00:11:55,880
Speaker 1: not good, and go from there. I just don't like

235
00:11:55,920 --> 00:11:59,080
Speaker 1: the passivity of it and people who are like applauding

236
00:11:59,120 --> 00:12:04,160
Speaker 1: these guys for you know, looking around it being like, yeah,

237
00:12:04,200 --> 00:12:07,400
Speaker 1: it's not great. What's happening is not good, Like that's

238
00:12:07,440 --> 00:12:09,920
Speaker 1: the bare minimum. Obviously this stuff's not good. Like, look

239
00:12:09,920 --> 00:12:12,679
Speaker 1: at what has happened in La, Obviously that's not great, right,

240
00:12:12,760 --> 00:12:15,440
Speaker 1: Like that's the bear. Like you would have to be

241
00:12:16,520 --> 00:12:19,960
Speaker 1: either completely unempathetic or a complete moron to look at

242
00:12:19,960 --> 00:12:22,040
Speaker 1: that and not get to the conclusion of like, yeah,

243
00:12:22,080 --> 00:12:23,119
Speaker 1: it's not good.

244
00:12:24,200 --> 00:12:28,280
Speaker 2: Right, Yeah, I don't think they should get a pat

245
00:12:28,320 --> 00:12:30,320
Speaker 2: I think it again, I agree with you where it's

246
00:12:30,320 --> 00:12:34,439
Speaker 2: like there's some argument that like, yeah, maybe this is good,

247
00:12:34,679 --> 00:12:37,960
Speaker 2: and maybe this will like get a handful of people

248
00:12:37,960 --> 00:12:40,839
Speaker 2: to be like, oh, maybe Trump is bad, or maybe

249
00:12:40,920 --> 00:12:44,440
Speaker 2: Ice is bad, or maybe what's happening in Gaza is bad,

250
00:12:44,800 --> 00:12:49,480
Speaker 2: but like it is doing the bare minimum. It's doing

251
00:12:49,520 --> 00:12:53,240
Speaker 2: the bare minimum, and you shouldn't be like this is

252
00:12:53,280 --> 00:12:55,439
Speaker 2: the exact same thing that was happening when Elon Musk

253
00:12:55,520 --> 00:13:00,640
Speaker 2: first also was like actually friendship over with Trump. A

254
00:13:00,679 --> 00:13:04,560
Speaker 2: bunch of you know, there are like these Democrats that

255
00:13:04,640 --> 00:13:07,640
Speaker 2: were like, oh it is he on oursa, No, he's

256
00:13:07,640 --> 00:13:09,719
Speaker 2: Elon muss He didn't like.

257
00:13:09,440 --> 00:13:11,960
Speaker 1: Like it's like, no, he's still he's still Joe broken,

258
00:13:12,080 --> 00:13:12,959
Speaker 1: Like he's still.

259
00:13:13,800 --> 00:13:18,480
Speaker 2: A terrible human being. I don't know. I do think.

260
00:13:18,640 --> 00:13:22,400
Speaker 2: I mean, I think again, people in general have a

261
00:13:22,440 --> 00:13:24,880
Speaker 2: hard time admitting that they're wrong. And if you're somebody

262
00:13:24,920 --> 00:13:28,040
Speaker 2: with like an ego the size and a platform this size,

263
00:13:28,080 --> 00:13:30,360
Speaker 2: that only makes it worse. So it makes sense that

264
00:13:30,760 --> 00:13:33,000
Speaker 2: you would want to twist that. So like, even if

265
00:13:33,000 --> 00:13:34,760
Speaker 2: you are saying this and you are so appalled by

266
00:13:34,800 --> 00:13:37,200
Speaker 2: it and you're like moved to speak out, you'd have

267
00:13:37,240 --> 00:13:39,120
Speaker 2: to twist it in a way that was like, no, actually,

268
00:13:39,160 --> 00:13:42,920
Speaker 2: I'm the victim. Yes, I was lied to. I would

269
00:13:42,920 --> 00:13:45,320
Speaker 2: have never done that. I'm the real picture here.

270
00:13:45,800 --> 00:13:49,960
Speaker 1: Yeah, I mean to your point about Elon Musk, I

271
00:13:50,000 --> 00:13:52,200
Speaker 1: do feel like people really show you who they are.

272
00:13:52,240 --> 00:13:56,280
Speaker 1: Like Andrew Yang coming on board with Elon Musk's new

273
00:13:56,320 --> 00:13:59,880
Speaker 1: political party. I'm sorry somebody who gets out a stay

274
00:14:00,200 --> 00:14:04,600
Speaker 1: and does a Nazi salute twice, I don't care what

275
00:14:04,640 --> 00:14:07,600
Speaker 1: the situation is. I'm never aligning myself with them, Like

276
00:14:07,720 --> 00:14:10,559
Speaker 1: that's it, And there's there's never an argument to be

277
00:14:10,679 --> 00:14:15,360
Speaker 1: made where I would And so it's telling to me

278
00:14:15,440 --> 00:14:18,920
Speaker 1: the people who rushed to be on board with that.

279
00:14:19,040 --> 00:14:21,080
Speaker 1: I just there's I mean, I just think it says

280
00:14:21,080 --> 00:14:24,200
Speaker 1: a lot about who you are as a person definitely.

281
00:14:24,880 --> 00:14:27,120
Speaker 1: Oh man, I forgot that he was I had. I

282
00:14:27,200 --> 00:14:29,120
Speaker 1: was like talking to a friend about this yesterday because

283
00:14:29,120 --> 00:14:31,480
Speaker 1: I were like, what do you think's gonna happen with

284
00:14:31,560 --> 00:14:32,680
Speaker 1: the Republican Party?

285
00:14:32,720 --> 00:14:34,720
Speaker 2: Like it seems like all of these people are Chuttians

286
00:14:34,760 --> 00:14:37,160
Speaker 2: And I was like, it's probably just we're gonna end

287
00:14:37,200 --> 00:14:40,920
Speaker 2: up with two really bad parties now, Like it's yeah,

288
00:14:40,960 --> 00:14:42,760
Speaker 2: there's gonna be some split, but it's like and then

289
00:14:42,800 --> 00:14:46,040
Speaker 2: we're gonna get It's like you you're gonna get the

290
00:14:46,080 --> 00:14:48,400
Speaker 2: two hydra heads instead of the one kind of situation,

291
00:14:48,600 --> 00:14:50,800
Speaker 2: and maybe, like I don't know, maybe that'll fuck him

292
00:14:50,800 --> 00:14:55,520
Speaker 2: over in like voting situations. But it's like, oh great,

293
00:14:55,560 --> 00:14:57,320
Speaker 2: then we're gonna have to deal with like the Elon

294
00:14:57,440 --> 00:15:01,840
Speaker 2: Musk tech bro Andrew you party on one side, and

295
00:15:01,840 --> 00:15:06,880
Speaker 2: then like Trump and like Mitch McConnell or whatever on

296
00:15:06,960 --> 00:15:09,240
Speaker 2: the other. But yeah, oh my goad.

297
00:15:09,240 --> 00:15:11,600
Speaker 1: Do you remember when Andrew Yang was running for I

298
00:15:11,600 --> 00:15:14,480
Speaker 1: think was it mayor of New York. There's a moment

299
00:15:14,720 --> 00:15:17,080
Speaker 1: in his campaign that like lives ret free in my

300
00:15:17,200 --> 00:15:19,920
Speaker 1: brain where because he didn't actually live in New York

301
00:15:20,760 --> 00:15:22,600
Speaker 1: and he was asked about it and he was like

302
00:15:23,120 --> 00:15:26,880
Speaker 1: His response was like me, live in New York, disgusting?

303
00:15:26,960 --> 00:15:28,880
Speaker 2: I would never Can you imagine that? You know what?

304
00:15:28,920 --> 00:15:30,880
Speaker 2: At least he said it. At least he said it

305
00:15:31,000 --> 00:15:34,400
Speaker 2: like Cuomo was pretending. Cuomo was pretending that he lived here.

306
00:15:34,680 --> 00:15:37,760
Speaker 2: What everybody knew he lived in Westchester. And at least

307
00:15:37,760 --> 00:15:44,520
Speaker 2: Andrew Yang was like, you know this shit? Can you imagine? Disgusting?

308
00:15:46,240 --> 00:15:48,040
Speaker 1: I think that is a moment I think about like

309
00:15:49,000 --> 00:15:49,920
Speaker 1: probably once a week.

310
00:15:49,960 --> 00:15:52,200
Speaker 2: I think about that moment. I'm gonna be real. I

311
00:15:52,280 --> 00:15:55,880
Speaker 2: forgot about Andrew Yang as like a political figure. He's

312
00:15:55,960 --> 00:15:59,440
Speaker 2: like like for the minute he emerged, I was like this,

313
00:15:59,440 --> 00:16:03,880
Speaker 2: this this is going bad. This feels like it's going bad. Yeah,

314
00:16:04,200 --> 00:16:07,960
Speaker 2: tech tech broke, and here we are, surprise, surprise.

315
00:16:11,400 --> 00:16:23,680
Speaker 4: Let's take a quick break at our back.

316
00:16:26,120 --> 00:16:30,280
Speaker 1: Well, speaking of New York politics, I know you are

317
00:16:30,400 --> 00:16:33,280
Speaker 1: our resident New Yorker. I am a former New Yorker,

318
00:16:33,440 --> 00:16:35,800
Speaker 1: so obviously I had lots of opinions about New York's

319
00:16:35,840 --> 00:16:38,040
Speaker 1: mayoral race. I bet as a New York I mean

320
00:16:38,040 --> 00:16:40,200
Speaker 1: like people in New York always have big opinions about

321
00:16:40,240 --> 00:16:40,880
Speaker 1: whoever's mayor.

322
00:16:40,880 --> 00:16:44,280
Speaker 2: What were your thoughts that was? You know what that

323
00:16:44,760 --> 00:16:48,480
Speaker 2: day that mom Donnie won the primary. That is the

324
00:16:48,480 --> 00:16:51,240
Speaker 2: most hope that I have felt a long last time,

325
00:16:51,360 --> 00:16:53,440
Speaker 2: and like, yeah, sure, okay, he has not one yet.

326
00:16:53,680 --> 00:16:57,400
Speaker 2: There's so much stuff that could happen, but like, you

327
00:16:57,440 --> 00:17:00,480
Speaker 2: know what, I think this was a nice moment. Felt

328
00:17:00,480 --> 00:17:03,560
Speaker 2: really good about it. I you know, I voted for him,

329
00:17:03,920 --> 00:17:06,760
Speaker 2: I supported his campaign. I think seeing just like the

330
00:17:06,960 --> 00:17:08,959
Speaker 2: numbers of people that came out to support him has

331
00:17:08,960 --> 00:17:12,880
Speaker 2: been really encouraging and like, you know, a good reminder

332
00:17:12,920 --> 00:17:15,600
Speaker 2: that it's like, yeah, no, people do want to see

333
00:17:15,640 --> 00:17:19,320
Speaker 2: like a better world, a better New York City. So yeah,

334
00:17:19,359 --> 00:17:25,000
Speaker 2: I do. I welcome the People's Republic of the communist takeover.

335
00:17:25,600 --> 00:17:26,640
Speaker 2: When people were like.

336
00:17:26,640 --> 00:17:30,760
Speaker 1: He wants state run stores in Virginia, they already have that.

337
00:17:30,760 --> 00:17:32,760
Speaker 1: They're called ABC stores run meta state.

338
00:17:32,960 --> 00:17:36,080
Speaker 2: Like a great idea.

339
00:17:37,040 --> 00:17:41,240
Speaker 1: Cool, I would love the Like I saw the Fox

340
00:17:41,320 --> 00:17:44,199
Speaker 1: News chiram that was clearly meant to be scary, and

341
00:17:44,240 --> 00:17:46,600
Speaker 1: it was like, look at all the things mom, Donnie supports,

342
00:17:47,000 --> 00:17:51,560
Speaker 1: funding public transit, childcare like it was and.

343
00:17:51,680 --> 00:17:54,720
Speaker 2: The New York City city famously a city that hates

344
00:17:54,760 --> 00:17:55,560
Speaker 2: public transit.

345
00:17:55,720 --> 00:17:58,199
Speaker 1: You know, you know, everybody in New York City has

346
00:17:58,200 --> 00:17:59,000
Speaker 1: a car and drives.

347
00:17:59,160 --> 00:18:02,280
Speaker 2: Oh, Yeah, I'm in my car right now recording this

348
00:18:03,080 --> 00:18:04,720
Speaker 2: that totally exists that I totally own.

349
00:18:05,040 --> 00:18:07,159
Speaker 1: Okay, So I have to talk about this story that

350
00:18:07,200 --> 00:18:11,520
Speaker 1: popped off over Fourth of July holiday. I actually this

351
00:18:11,600 --> 00:18:14,600
Speaker 1: story kind of like, if I'm being honest, wrecked my vacation.

352
00:18:14,880 --> 00:18:17,520
Speaker 1: I took the fourth off, I was off the beach.

353
00:18:17,880 --> 00:18:20,640
Speaker 1: I saw this story while I was at literally at

354
00:18:20,680 --> 00:18:23,320
Speaker 1: a beach bar drinking a cocktail, and I sort of

355
00:18:23,359 --> 00:18:25,040
Speaker 1: like stewed on it, you know what's funny.

356
00:18:25,280 --> 00:18:28,199
Speaker 2: I also had a moment like that, but it was

357
00:18:28,200 --> 00:18:30,640
Speaker 2: with a completely different story. Oh what was the story?

358
00:18:30,800 --> 00:18:33,600
Speaker 2: Feel comfortable saying? No, it was about Trump passing the

359
00:18:33,600 --> 00:18:36,040
Speaker 2: big beautiful bill. Because I like hadn't been looking at

360
00:18:36,040 --> 00:18:37,480
Speaker 2: my phone and then I like went to go to

361
00:18:37,480 --> 00:18:39,240
Speaker 2: the bathroom at one point and I like turned, I

362
00:18:39,320 --> 00:18:41,399
Speaker 2: opened my phone and that was the first notification. And

363
00:18:41,440 --> 00:18:44,240
Speaker 2: I was like, I'm like at my friend's Fourth of

364
00:18:44,320 --> 00:18:48,200
Speaker 2: July party and I was just like like five beers deep,

365
00:18:48,280 --> 00:18:51,399
Speaker 2: probably like just like oh my god, what's happening? It

366
00:18:51,880 --> 00:18:54,640
Speaker 2: like you can't have a moment of peace, like which

367
00:18:54,720 --> 00:18:57,159
Speaker 2: story ruined your day on Fourth of July? I know?

368
00:18:57,640 --> 00:19:00,199
Speaker 1: Yeah, if listeners right in and tell the story if

369
00:19:00,240 --> 00:19:01,800
Speaker 1: you were if you were trying to enjoy your Fourth

370
00:19:01,800 --> 00:19:05,200
Speaker 1: of July holiday and like be offline for one goddamn day,

371
00:19:05,600 --> 00:19:07,800
Speaker 1: what was the story that pierce that pierced your little

372
00:19:07,800 --> 00:19:09,359
Speaker 1: bubble and was like, oh, that's right. We live in

373
00:19:09,359 --> 00:19:12,520
Speaker 1: a healthscape. Can't forget it. Always gotta be plugged into it. Okay,

374
00:19:12,560 --> 00:19:16,000
Speaker 1: So as we know, Mam Donnie won the Democratic primary

375
00:19:16,000 --> 00:19:18,280
Speaker 1: in New York's mayoral race. He managed to upset the

376
00:19:18,320 --> 00:19:22,600
Speaker 1: Democratic Party machine and defeat the former governor of New York,

377
00:19:22,680 --> 00:19:25,720
Speaker 1: Andrew Cuomo, a sex pass who I personally had a

378
00:19:25,760 --> 00:19:27,840
Speaker 1: hand in pushing out of office.

379
00:19:28,080 --> 00:19:33,400
Speaker 2: He's just Italian, he said, Hey, I'm expressors, listeners, I'm Italian.

380
00:19:33,440 --> 00:19:36,240
Speaker 1: For the reck, I'm Italian. I speak with my hands.

381
00:19:36,280 --> 00:19:39,880
Speaker 1: I'm expressive. I touch people, I touch men, I touch women,

382
00:19:40,160 --> 00:19:43,399
Speaker 1: I touch children. That was this big defense was that

383
00:19:43,440 --> 00:19:46,280
Speaker 1: he was an Italian American, so of course he's handsy.

384
00:19:46,640 --> 00:19:48,480
Speaker 2: I literally remember when he said that line. I was like,

385
00:19:48,520 --> 00:19:50,280
Speaker 2: I'm pretty sure that literally was like a joke in

386
00:19:50,320 --> 00:19:54,520
Speaker 2: the bear Yeah, I mean, I hate I hate this

387
00:19:54,560 --> 00:19:55,200
Speaker 2: guy so much.

388
00:19:55,240 --> 00:19:56,760
Speaker 1: I hate this and it was I remember in the

389
00:19:56,760 --> 00:19:59,960
Speaker 1: second was yesterday because I had to watch the passer word.

390
00:20:00,080 --> 00:20:04,040
Speaker 1: He resigned, and he was saying like, I'm an Italian American,

391
00:20:04,240 --> 00:20:06,679
Speaker 1: I'm very handsy. Da da da dah, And then a

392
00:20:06,800 --> 00:20:10,399
Speaker 1: screen lowers behind him and it's all these videos and

393
00:20:10,480 --> 00:20:15,520
Speaker 1: images of him being handsy with people across the gender spectrum.

394
00:20:15,600 --> 00:20:19,040
Speaker 2: So it's like, oh, you're gonna crucify me for.

395
00:20:19,240 --> 00:20:21,800
Speaker 1: Putting my hand on the small of somebody's back, which,

396
00:20:21,800 --> 00:20:23,679
Speaker 1: by the way, that was not what he was accused of.

397
00:20:24,040 --> 00:20:27,080
Speaker 1: He was accused of, like legit, like he really did

398
00:20:27,080 --> 00:20:29,399
Speaker 1: a good job of, like muddying the waters. That's not

399
00:20:29,440 --> 00:20:32,479
Speaker 1: what he was accused of. It's not like hugs and

400
00:20:32,560 --> 00:20:35,359
Speaker 1: touchiness that was misinterpreted. That's not what he was accused of.

401
00:20:35,440 --> 00:20:40,200
Speaker 1: But it's a slideshow of him being handsy with all

402
00:20:40,280 --> 00:20:43,200
Speaker 1: kinds of different people. Uh yeah, So I will never

403
00:20:43,240 --> 00:20:46,040
Speaker 1: forget it. It was such a weird moment in politics.

404
00:20:46,280 --> 00:20:49,760
Speaker 2: Our first actually probably not first, I was gonna say,

405
00:20:49,760 --> 00:20:53,000
Speaker 2: our first bisexual pervert in office, but there definitely have

406
00:20:53,119 --> 00:20:57,360
Speaker 2: been others. Like I don't know, I'll win, diversity win, Yeah,

407
00:20:57,440 --> 00:20:59,840
Speaker 2: diversity wins. Finally, this guy was assaulted.

408
00:21:00,600 --> 00:21:05,240
Speaker 1: Everybody on the spectrum an equal opportunity Harasser so in

409
00:21:05,280 --> 00:21:09,920
Speaker 1: At the event, Mamdani won, and the establishment Democrats and

410
00:21:10,080 --> 00:21:13,919
Speaker 1: like right wing extremists have sort of joined forces to

411
00:21:13,960 --> 00:21:18,160
Speaker 1: smear him, and luckily for them, the New York Times

412
00:21:18,280 --> 00:21:21,439
Speaker 1: is a newspaper that exists to help. So The New

413
00:21:21,520 --> 00:21:24,760
Speaker 1: York Times published a bombshell piece on fourth of July,

414
00:21:25,680 --> 00:21:29,720
Speaker 1: basically the big story. Here we go fifteen years ago,

415
00:21:30,160 --> 00:21:33,640
Speaker 1: back when Mamdani was like a seventeen year old high

416
00:21:33,640 --> 00:21:38,040
Speaker 1: school student applying to Columbia University for college, a school

417
00:21:38,080 --> 00:21:39,879
Speaker 1: that he did not get into so did not attend.

418
00:21:40,440 --> 00:21:43,960
Speaker 1: He checked the box on his application indicating that he

419
00:21:44,040 --> 00:21:48,320
Speaker 1: was both Asian and African American because he is of

420
00:21:48,480 --> 00:21:51,040
Speaker 1: Indian descent and he was born in the African country

421
00:21:51,080 --> 00:21:51,880
Speaker 1: of Uganda.

422
00:21:52,600 --> 00:21:52,959
Speaker 2: That's it.

423
00:21:52,960 --> 00:21:54,959
Speaker 1: If you're waiting for more, there is not more. Like

424
00:21:55,000 --> 00:21:58,520
Speaker 1: that's the big bombshell story that The New York Times

425
00:21:58,560 --> 00:22:00,960
Speaker 1: just had to publish a fourth of July break.

426
00:22:01,200 --> 00:22:03,400
Speaker 2: Wait, so, like, does this mean that The New York

427
00:22:03,400 --> 00:22:06,960
Speaker 2: Times is now pro affirmative action because I thought I

428
00:22:06,960 --> 00:22:08,520
Speaker 2: thought that was bad and we were just getting rid

429
00:22:08,560 --> 00:22:08,760
Speaker 2: of it.

430
00:22:08,840 --> 00:22:12,439
Speaker 1: Yeah, they can't even keep their own horrible ideologies stray

431
00:22:12,480 --> 00:22:16,879
Speaker 1: their horrible value straight. And the question is where did

432
00:22:16,880 --> 00:22:19,520
Speaker 1: the New York Times get this information? It was part

433
00:22:19,600 --> 00:22:23,280
Speaker 1: of a hack of Columbia's records. So the Times article,

434
00:22:23,600 --> 00:22:26,119
Speaker 1: I will say, they did note that the story revolved

435
00:22:26,160 --> 00:22:29,160
Speaker 1: around documents that had been hacked from Columbia's computer systems

436
00:22:29,200 --> 00:22:32,080
Speaker 1: that had been provided to the New York Times by

437
00:22:32,160 --> 00:22:36,480
Speaker 1: what the paper called an intermediary known as Crimew. The

438
00:22:36,560 --> 00:22:40,119
Speaker 1: Times just identified this person as quote an academic and

439
00:22:40,160 --> 00:22:44,240
Speaker 1: an opponent of affirmative action. However, Crimew is actually like

440
00:22:44,320 --> 00:22:48,280
Speaker 1: a very well known publisher of white supremacist and race

441
00:22:48,400 --> 00:22:51,680
Speaker 1: science content online. So The New York Times essentially kept

442
00:22:51,720 --> 00:22:55,440
Speaker 1: this source anonymous because they did not publish his real identity,

443
00:22:55,720 --> 00:22:57,800
Speaker 1: which has been known for kind of a while. They

444
00:22:57,880 --> 00:23:01,120
Speaker 1: just published his online pseudonym. I kind of get what's

445
00:23:01,160 --> 00:23:03,280
Speaker 1: going on here. The Times is really trying to whitewash

446
00:23:03,320 --> 00:23:05,760
Speaker 1: what they've done, and they're sort of being like, well,

447
00:23:05,760 --> 00:23:08,560
Speaker 1: we'll just let the readers decide what they think or

448
00:23:08,600 --> 00:23:11,919
Speaker 1: if this is newsworthy or important or not. But what

449
00:23:11,960 --> 00:23:15,360
Speaker 1: they're not doing is actually being clear about where they

450
00:23:15,400 --> 00:23:18,600
Speaker 1: got this information is hacked information from because the person

451
00:23:18,600 --> 00:23:22,320
Speaker 1: who gave them this information, this intermediary, is a known

452
00:23:22,560 --> 00:23:26,119
Speaker 1: a well known purveyor of white supremacists and eugenicist views

453
00:23:26,359 --> 00:23:29,800
Speaker 1: whose public identity has been known for months. So I

454
00:23:29,800 --> 00:23:32,840
Speaker 1: should say the Times did update the article to say

455
00:23:33,680 --> 00:23:38,160
Speaker 1: crime you quote writes often about IQ and race, which

456
00:23:38,960 --> 00:23:42,480
Speaker 1: I feel like that's a real understatements.

457
00:23:43,000 --> 00:23:46,560
Speaker 2: New York Times favorite thing to talk about. Like they're

458
00:23:46,640 --> 00:23:50,320
Speaker 2: just they love, they love, you know, uplifting writers that

459
00:23:50,400 --> 00:23:52,320
Speaker 2: write about IQ and race.

460
00:23:53,720 --> 00:23:55,720
Speaker 1: Me, I feel like they're really doing their writer, their

461
00:23:55,760 --> 00:23:58,280
Speaker 1: readers of disservices. It's like, you know what it is,

462
00:23:58,320 --> 00:24:00,399
Speaker 1: figure it out. He writes about race and ike. Do

463
00:24:00,480 --> 00:24:01,160
Speaker 1: you think it's good?

464
00:24:01,160 --> 00:24:04,800
Speaker 2: It's not wink wink, that's a really wink wink.

465
00:24:05,680 --> 00:24:09,520
Speaker 1: And their editor Patrick Keey, publicly defended the position to

466
00:24:09,520 --> 00:24:12,480
Speaker 1: publish the story and then grant the source anonymity.

467
00:24:13,000 --> 00:24:14,359
Speaker 2: So that's bad.

468
00:24:14,720 --> 00:24:18,080
Speaker 1: But it gets worse because simof reported at the Times

469
00:24:18,359 --> 00:24:22,280
Speaker 1: published this because they were trying to avoid being scooped

470
00:24:22,640 --> 00:24:23,600
Speaker 1: by enemy of.

471
00:24:23,560 --> 00:24:25,199
Speaker 2: The show, Christopher Rufo.

472
00:24:25,720 --> 00:24:29,000
Speaker 1: You know Christopher Rufo, the man behind the attacks on DEI,

473
00:24:29,320 --> 00:24:31,960
Speaker 1: the man who was behind the attack that pushed Clauding

474
00:24:32,040 --> 00:24:35,000
Speaker 1: Gay out of Harvard's leadership, the man behind the attacks

475
00:24:35,040 --> 00:24:38,720
Speaker 1: on critical race theory and the man who openly and

476
00:24:38,800 --> 00:24:42,800
Speaker 1: publicly continuously brags about how he is able to play

477
00:24:42,880 --> 00:24:45,600
Speaker 1: the New York Times like a goddamn biddle to push

478
00:24:45,760 --> 00:24:49,040
Speaker 1: these attacks, like he is not hiding any of this.

479
00:24:49,160 --> 00:24:52,200
Speaker 1: He goes on Twitter and says things like I intend

480
00:24:52,200 --> 00:24:55,240
Speaker 1: to manipulate the New York Times into doing my racist bidding,

481
00:24:55,440 --> 00:24:57,679
Speaker 1: and the New York Times is like, please, Daddy, let

482
00:24:57,760 --> 00:24:58,919
Speaker 1: us do your racist bidding.

483
00:24:59,040 --> 00:25:00,560
Speaker 2: Like that's essentially what it's happening.

484
00:25:01,320 --> 00:25:05,879
Speaker 5: I I don't know, it's so like it's so depressing

485
00:25:05,960 --> 00:25:08,720
Speaker 5: because so many people still read the New York Times

486
00:25:08,720 --> 00:25:10,600
Speaker 5: and look to the New York Times as this like

487
00:25:11,080 --> 00:25:14,320
Speaker 5: you know, prestigious journalistic institution.

488
00:25:14,480 --> 00:25:18,200
Speaker 2: But it's like insane. It is absolutely insane, like the

489
00:25:18,320 --> 00:25:20,119
Speaker 2: kind of stuff because it's like it's not just it

490
00:25:20,200 --> 00:25:22,520
Speaker 2: like it's the same stuff with them, Like they've been

491
00:25:22,600 --> 00:25:26,600
Speaker 2: like platforming you know, like turf arguments and transport arguments

492
00:25:26,640 --> 00:25:29,800
Speaker 2: that have like zero scientific back for years and they've

493
00:25:29,800 --> 00:25:31,320
Speaker 2: been doing this and they've been doing all of this

494
00:25:31,400 --> 00:25:34,600
Speaker 2: they like, and it's the same thing where then they

495
00:25:34,640 --> 00:25:37,040
Speaker 2: turn around and they're like how did this happen? Oh

496
00:25:37,080 --> 00:25:40,440
Speaker 2: my god, Like absolutely, it's crazy. I mean this, this

497
00:25:40,520 --> 00:25:42,640
Speaker 2: was what happened with everything that's happening in Gaza. It's

498
00:25:42,640 --> 00:25:46,040
Speaker 2: like every single they they don't miss. They don't miss

499
00:25:46,040 --> 00:25:49,000
Speaker 2: a single issue. It's like, you know how people say,

500
00:25:49,400 --> 00:25:52,600
Speaker 2: y'all remember okay, like when Glee was on, and they

501
00:25:52,600 --> 00:25:55,560
Speaker 2: would cover like every single issue they possibly could, but

502
00:25:55,640 --> 00:25:58,359
Speaker 2: in like the worst way possible, like they managed to

503
00:25:58,359 --> 00:26:01,760
Speaker 2: be racist or like whatever, like to everybody. They would

504
00:26:01,800 --> 00:26:03,720
Speaker 2: not miss a single group, Like this is what the

505
00:26:03,720 --> 00:26:08,719
Speaker 2: New York Times is doing New York asly of journalistic constitution.

506
00:26:09,080 --> 00:26:12,680
Speaker 2: Put that on a T shirt. Yeah, put that on asticker.

507
00:26:13,560 --> 00:26:16,239
Speaker 1: Yeah, there's a really good I want to say it

508
00:26:16,280 --> 00:26:19,479
Speaker 1: was the podcast Cancel Me, Daddy. Don't quote me on that,

509
00:26:19,560 --> 00:26:24,640
Speaker 1: but there was a really incredible episode about the transphobic

510
00:26:24,680 --> 00:26:27,720
Speaker 1: attacks in the Times and like that, you know, it

511
00:26:27,800 --> 00:26:30,040
Speaker 1: was like a real deep dive into where they came from,

512
00:26:30,040 --> 00:26:34,120
Speaker 1: where they started. Horrible, horrible, but very informative. And one

513
00:26:34,160 --> 00:26:36,760
Speaker 1: of the points that the that the person going through

514
00:26:36,840 --> 00:26:39,000
Speaker 1: I can't remember who it was, but one of the

515
00:26:39,000 --> 00:26:42,160
Speaker 1: points they made was like it matters that it's the

516
00:26:42,200 --> 00:26:45,439
Speaker 1: New York Times, like the paper like the like the

517
00:26:45,520 --> 00:26:48,639
Speaker 1: Gray Lady, the most important paper that the United States

518
00:26:48,680 --> 00:26:51,359
Speaker 1: really has, or at least was at one point. It

519
00:26:51,520 --> 00:26:55,920
Speaker 1: matters that like your average American, this is the paper

520
00:26:56,000 --> 00:26:57,760
Speaker 1: that they go to and feel they can trust. It

521
00:26:57,800 --> 00:27:01,159
Speaker 1: is incredibly important in terms of establishing the temperature and

522
00:27:01,200 --> 00:27:03,359
Speaker 1: the tide of the country. And if they if this

523
00:27:03,400 --> 00:27:08,480
Speaker 1: is what, if they are pushing incredibly inflammatory not to

524
00:27:08,560 --> 00:27:12,919
Speaker 1: mention full of lies and misinformation. If they're if that's

525
00:27:12,960 --> 00:27:17,679
Speaker 1: what they're pushing, they have this incredible this incredible power

526
00:27:17,840 --> 00:27:22,320
Speaker 1: to shape at the public perception of like your average

527
00:27:22,600 --> 00:27:27,120
Speaker 1: moderate American. And so it matters what the New York

528
00:27:27,160 --> 00:27:30,359
Speaker 1: Times like, what what where they land on these And

529
00:27:30,440 --> 00:27:35,280
Speaker 1: what makes me so angry is how they would probably say, like,

530
00:27:35,280 --> 00:27:39,440
Speaker 1: oh THEO like the whole journalistic question of like bias

531
00:27:39,560 --> 00:27:44,440
Speaker 1: and being unbiased, It's not unbiased to get information from

532
00:27:44,440 --> 00:27:48,680
Speaker 1: somebody who is like a known purveyor of white supremacist

533
00:27:48,720 --> 00:27:52,840
Speaker 1: and eugenicist content, that's that's not that's not unbiased. To

534
00:27:52,920 --> 00:27:55,520
Speaker 1: publish information that you got from that person and grant

535
00:27:55,560 --> 00:27:56,480
Speaker 1: them anonymity, like.

536
00:27:56,440 --> 00:27:59,760
Speaker 2: I'm not like, like what are we doing here? I mean,

537
00:27:59,760 --> 00:28:03,320
Speaker 2: it's unbiased if you yourself are also coming at it

538
00:28:03,359 --> 00:28:06,800
Speaker 2: from like a white supremacist viewpoint, which maybe is part

539
00:28:06,800 --> 00:28:10,560
Speaker 2: of the problem, but yeah, no, it is ridiculous. I personally,

540
00:28:11,520 --> 00:28:13,600
Speaker 2: I have my own beliefs about the idea of like

541
00:28:13,680 --> 00:28:16,439
Speaker 2: objectivity and like not being biased, because I think it

542
00:28:16,520 --> 00:28:19,080
Speaker 2: is like near impossible to actually do that. But like

543
00:28:19,320 --> 00:28:22,280
Speaker 2: there is a difference from like trying to report all

544
00:28:22,280 --> 00:28:26,439
Speaker 2: the facts and like reporting something that's clearly through a

545
00:28:26,560 --> 00:28:30,600
Speaker 2: specific agenda that they're trying to push. Yeah, and people

546
00:28:30,640 --> 00:28:32,320
Speaker 2: also if people are interested in learning more about like

547
00:28:32,359 --> 00:28:36,680
Speaker 2: the New York Times and the history of transphobia there

548
00:28:36,840 --> 00:28:40,080
Speaker 2: over the last like decade or so, would definitely are around.

549
00:28:40,120 --> 00:28:43,960
Speaker 2: The podcast Anti Trans Hate Machine, they have an episode

550
00:28:43,960 --> 00:28:46,000
Speaker 2: about the New York Times and they interview somebody who

551
00:28:46,080 --> 00:28:48,520
Speaker 2: had worked at the Times for a while, and they

552
00:28:48,800 --> 00:28:52,960
Speaker 2: like it was a very good sort of breakdown as

553
00:28:53,000 --> 00:28:56,080
Speaker 2: to like what the specific problems are and how it's

554
00:28:56,080 --> 00:28:58,960
Speaker 2: happening and why it is like bad for all of art,

555
00:28:59,400 --> 00:29:03,120
Speaker 2: you know, mental states and the idea of truth and

556
00:29:03,200 --> 00:29:03,600
Speaker 2: all of that.

557
00:29:03,800 --> 00:29:06,840
Speaker 1: But yeah, yeah, that might have been the podcast that

558
00:29:06,920 --> 00:29:11,160
Speaker 1: I listened to. It just makes it's bad for everyone,

559
00:29:11,280 --> 00:29:14,160
Speaker 1: It's especially bad for trans folks, but like it makes

560
00:29:14,240 --> 00:29:18,360
Speaker 1: us all less informed, It makes us all more like divide,

561
00:29:18,400 --> 00:29:21,720
Speaker 1: like it's not good for anybody. And I guess what

562
00:29:21,880 --> 00:29:26,040
Speaker 1: really pisss me off about the Mamdani thing is that

563
00:29:26,760 --> 00:29:29,960
Speaker 1: The Independent reported that after it became public, that the

564
00:29:30,000 --> 00:29:32,080
Speaker 1: reason why The New York Times published this is because

565
00:29:32,080 --> 00:29:35,040
Speaker 1: they did not want to get scooped by Christopher Ruffo,

566
00:29:35,200 --> 00:29:38,040
Speaker 1: enemy of the show. The Independent reports that, in an

567
00:29:38,040 --> 00:29:42,000
Speaker 1: apparent effort to tweak progressives and spark additional backlash against

568
00:29:42,000 --> 00:29:45,640
Speaker 1: the paper over the Mamdani story, Christopher Ruffo applauded the

569
00:29:45,640 --> 00:29:48,040
Speaker 1: New York Times for its report and suggested that they

570
00:29:48,080 --> 00:29:51,480
Speaker 1: were on the same page. He said, bummer to get scooped,

571
00:29:51,520 --> 00:29:54,000
Speaker 1: But kudos to my friends at the New York Times

572
00:29:54,080 --> 00:29:57,280
Speaker 1: for being a first to publish this story. So if

573
00:29:57,280 --> 00:30:00,320
Speaker 1: the cameras at the time had any gumption of at all,

574
00:30:00,640 --> 00:30:04,600
Speaker 1: they would see how horribly embarrassing it is that Christopher

575
00:30:04,640 --> 00:30:09,840
Speaker 1: Ruffo was saying, me, right wing shitthead blogger with a

576
00:30:09,880 --> 00:30:13,720
Speaker 1: substack is on the same level as the goddamn New

577
00:30:13,800 --> 00:30:17,320
Speaker 1: York Times, And he's not wrong. Like, if they had

578
00:30:17,320 --> 00:30:19,800
Speaker 1: any gumption at all, they would be embarrassed. But I

579
00:30:19,840 --> 00:30:21,880
Speaker 1: think that they're like, yeah, we are on like that

580
00:30:22,080 --> 00:30:26,800
Speaker 1: is who our contemporaries are. Christopher Rufo Substack is a

581
00:30:26,960 --> 00:30:31,320
Speaker 1: peer to The New York Times. Now, I like, I

582
00:30:31,360 --> 00:30:34,960
Speaker 1: just don't understand how they're not so horribly horribly embarrassed

583
00:30:35,280 --> 00:30:38,120
Speaker 1: by this sort of events. And it kind of goes

584
00:30:38,160 --> 00:30:41,440
Speaker 1: back to your point that like, at a certain point,

585
00:30:41,960 --> 00:30:46,120
Speaker 1: maybe they're not embarrassed because Christopher Ruffo is not wrong

586
00:30:46,320 --> 00:30:50,520
Speaker 1: like they are, like they do share these values, they

587
00:30:50,520 --> 00:30:52,760
Speaker 1: are kind of like That's the only thing I can

588
00:30:52,760 --> 00:30:55,880
Speaker 1: think is like when you get played by this guy

589
00:30:55,920 --> 00:30:58,800
Speaker 1: who makes it clear his intention to play you, and

590
00:30:58,840 --> 00:31:02,120
Speaker 1: a certain point you're not getting played. You're playing together

591
00:31:02,240 --> 00:31:03,640
Speaker 1: your teammates.

592
00:31:03,680 --> 00:31:06,960
Speaker 2: Right, Like, I don't know. I feel like there's the

593
00:31:07,080 --> 00:31:12,760
Speaker 2: like on people love to on Twitter and whatnot, you know,

594
00:31:13,120 --> 00:31:15,880
Speaker 2: use the like oh scratch a liberal like a fascist

595
00:31:15,880 --> 00:31:20,920
Speaker 2: fleets kind of quote that anyways, whatever, It's complicated, But

596
00:31:21,040 --> 00:31:23,320
Speaker 2: I do think, like to a point, like just seeing

597
00:31:23,320 --> 00:31:29,520
Speaker 2: the amount of like centrist democrats or like progressives, which like, yeah,

598
00:31:29,600 --> 00:31:31,520
Speaker 2: let's say the New York Times, let's call that like

599
00:31:31,760 --> 00:31:37,320
Speaker 2: a centrious progressive quote unquote publication, seeing how many people

600
00:31:37,440 --> 00:31:40,160
Speaker 2: with that and within that sphere are like freaking out

601
00:31:40,200 --> 00:31:45,240
Speaker 2: about the Mamdani whin and acting like somehow like you know,

602
00:31:45,600 --> 00:31:47,640
Speaker 2: going back to the first story about Joe Rogan, like

603
00:31:47,680 --> 00:31:50,080
Speaker 2: the Democrats love to talk about how like, oh, we

604
00:31:50,120 --> 00:31:51,360
Speaker 2: need to like Joe Rogan on the left, we need

605
00:31:51,400 --> 00:31:54,800
Speaker 2: to Joe. They don't actually want to listen to the constituents.

606
00:31:54,840 --> 00:31:56,920
Speaker 2: And like every time, this is not the first time

607
00:31:56,960 --> 00:31:59,160
Speaker 2: that this is like, like this has kind of been

608
00:31:59,200 --> 00:32:02,000
Speaker 2: the thread throughout the past ten years. Is whenever there

609
00:32:02,080 --> 00:32:06,960
Speaker 2: is a political figure that emerges that has more left

610
00:32:07,040 --> 00:32:11,400
Speaker 2: leaning beliefs, the like the centrist part of the party

611
00:32:11,440 --> 00:32:14,320
Speaker 2: freaks out and then is surprised by the fact that

612
00:32:14,400 --> 00:32:18,160
Speaker 2: they're not winning. And at this point, it's like, all right,

613
00:32:18,280 --> 00:32:20,640
Speaker 2: so you are aware of what you're doing, Like either

614
00:32:20,680 --> 00:32:23,440
Speaker 2: you're just so in your own little world that you're

615
00:32:23,480 --> 00:32:27,240
Speaker 2: like stupid, or like you're aware of the fact that

616
00:32:27,280 --> 00:32:30,120
Speaker 2: you're like like you'd rather blow up your own ship

617
00:32:30,200 --> 00:32:34,600
Speaker 2: than let it change in the slightest you know, I

618
00:32:34,840 --> 00:32:37,920
Speaker 2: don't know a thousand percent, And I feel like establishment

619
00:32:37,960 --> 00:32:41,360
Speaker 2: Democrats should be taking notes from his campaign when you

620
00:32:41,400 --> 00:32:43,360
Speaker 2: look at the different demographics he was able to get

621
00:32:43,400 --> 00:32:46,320
Speaker 2: out to get out to the polls with enthusiasm, Like

622
00:32:46,600 --> 00:32:49,200
Speaker 2: you all should be taking notes and replicating what he does.

623
00:32:49,400 --> 00:32:51,640
Speaker 2: And they talk all day long about, Oh, we need

624
00:32:51,760 --> 00:32:54,320
Speaker 2: a candidate that's gonna get people excited. You have a

625
00:32:54,360 --> 00:32:56,480
Speaker 2: candidate that gets people excited, and they're like no, no, no,

626
00:32:56,520 --> 00:32:59,360
Speaker 2: not like that, not like right, Like I mean, I've

627
00:32:59,360 --> 00:33:01,720
Speaker 2: had a conversation with like people in my life that

628
00:33:01,800 --> 00:33:05,880
Speaker 2: are kind of like older more like Democrats that were

629
00:33:05,960 --> 00:33:10,120
Speaker 2: like very much like Obama clen era Democrats that like

630
00:33:10,800 --> 00:33:13,480
Speaker 2: are still sort of pressed about the fact that, like, oh,

631
00:33:13,560 --> 00:33:17,160
Speaker 2: people didn't show up to vote for Kamala Harris and

632
00:33:17,200 --> 00:33:19,680
Speaker 2: then don't seem to understand that. It's like, yeah, but

633
00:33:19,720 --> 00:33:22,200
Speaker 2: like things are getting those like if you can get

634
00:33:22,200 --> 00:33:24,360
Speaker 2: mad at young people, you can get mad at whatever

635
00:33:24,440 --> 00:33:26,640
Speaker 2: all you want. But then you're seeing these groups show

636
00:33:26,720 --> 00:33:31,520
Speaker 2: up for somebody that's actually promising something. It's like maybe

637
00:33:31,560 --> 00:33:34,320
Speaker 2: that's the solution. Maybe that's the like do you want

638
00:33:34,360 --> 00:33:36,080
Speaker 2: to just keep complaining about the problem or do you

639
00:33:36,080 --> 00:33:39,400
Speaker 2: want to fix it? And I would like to fix

640
00:33:39,440 --> 00:33:41,640
Speaker 2: it personally because I don't want to keep living in

641
00:33:41,680 --> 00:33:43,920
Speaker 2: the world that's falling apart. But that's just that's just

642
00:33:43,960 --> 00:33:45,120
Speaker 2: my opinion, you know.

643
00:33:45,320 --> 00:33:52,520
Speaker 1: Joey says, fix it y'all all like Joey guys. Yeah,

644
00:33:52,560 --> 00:33:55,760
Speaker 1: And I will say, like I hated so much about

645
00:33:56,320 --> 00:33:58,600
Speaker 1: this New York Times piece, But I will say one

646
00:33:58,600 --> 00:34:00,520
Speaker 1: thing that made me a little bit happy was that

647
00:34:00,560 --> 00:34:05,480
Speaker 1: I think most mainstream news outlets could have just repeated

648
00:34:06,320 --> 00:34:08,160
Speaker 1: like they didn't take the bait, Like most of what

649
00:34:08,239 --> 00:34:11,400
Speaker 1: I saw was reven action, like this was a notable,

650
00:34:11,719 --> 00:34:15,440
Speaker 1: real newsworthy story. They were talking about how bad of

651
00:34:15,480 --> 00:34:17,120
Speaker 1: a move and how bad of a look it is

652
00:34:17,120 --> 00:34:20,440
Speaker 1: for The Times. It's very clear to me that the

653
00:34:21,000 --> 00:34:23,080
Speaker 1: thing that they're trying to posish, and by they, I

654
00:34:23,120 --> 00:34:26,439
Speaker 1: mean the democratic establishment, right wing cripters, and then they're

655
00:34:26,560 --> 00:34:29,680
Speaker 1: using the media as a tool to do this. It's

656
00:34:29,760 --> 00:34:32,000
Speaker 1: very clear to me that like the narrative they were

657
00:34:32,000 --> 00:34:36,200
Speaker 1: trying to push was like black folks against mom Donnie, right,

658
00:34:36,239 --> 00:34:37,920
Speaker 1: Like that's what they were trying to make happen.

659
00:34:38,200 --> 00:34:39,560
Speaker 2: And so I was very disappointed.

660
00:34:39,640 --> 00:34:43,160
Speaker 1: Like a black owned media outlet, the Grio, which is

661
00:34:43,200 --> 00:34:46,080
Speaker 1: like a like a outlet that focuses on the black community,

662
00:34:46,440 --> 00:34:48,520
Speaker 1: they reported on it in a kind of way that

663
00:34:48,680 --> 00:34:51,480
Speaker 1: was like, fam, are we bothered by mom Donnie saying

664
00:34:51,520 --> 00:34:54,239
Speaker 1: that he's black? Rather than the I would argue the

665
00:34:54,360 --> 00:34:57,160
Speaker 1: much more important story that is certainly more impactful to

666
00:34:57,200 --> 00:34:59,480
Speaker 1: the lives of their readership, which is like, fam are

667
00:34:59,480 --> 00:34:59,920
Speaker 1: we bother?

668
00:35:00,200 --> 00:35:02,640
Speaker 2: But that the New York Times is working with you.

669
00:35:02,800 --> 00:35:07,360
Speaker 1: Genesis and white supremacists like it just really yeah, I

670
00:35:07,400 --> 00:35:08,799
Speaker 1: mean it's fine.

671
00:35:09,080 --> 00:35:12,040
Speaker 2: It really yeah. It pissed me off.

672
00:35:12,080 --> 00:35:19,799
Speaker 1: It just like goes to show how many in medias

673
00:35:19,840 --> 00:35:21,440
Speaker 1: like I just wonder, like what are you doing, Like

674
00:35:21,480 --> 00:35:22,640
Speaker 1: who are you serving?

675
00:35:22,680 --> 00:35:24,160
Speaker 2: Who are you trying to educate?

676
00:35:24,600 --> 00:35:26,560
Speaker 1: Like did you see that the New York Times colonies

677
00:35:26,640 --> 00:35:30,320
Speaker 1: Jamel Bowie he had to delete several Blue Sky posts

678
00:35:30,600 --> 00:35:33,200
Speaker 1: that were criticizing The New York Times for this post,

679
00:35:33,600 --> 00:35:37,680
Speaker 1: and basically his tweet was you should tell readers if

680
00:35:37,719 --> 00:35:41,680
Speaker 1: your source is a Nazi, which I feel like doesn't

681
00:35:41,719 --> 00:35:44,520
Speaker 1: seem like an inflammatory thing to say to me, But

682
00:35:44,640 --> 00:35:46,640
Speaker 1: obviously the New York Times made him take that post

683
00:35:46,680 --> 00:35:49,440
Speaker 1: down and say, oh, sorry, that violated the New York

684
00:35:49,480 --> 00:35:52,359
Speaker 1: Times is social media guide. So sorry, so sorry, Like.

685
00:35:53,440 --> 00:35:56,399
Speaker 2: I don't know, I mean, yeah, everybody knows it's more

686
00:35:56,440 --> 00:35:59,160
Speaker 2: offensive to call somebody a Nazi than it is to

687
00:35:59,239 --> 00:36:03,640
Speaker 2: do Nazis exactly, just to accuse somebody who's doing Nazis

688
00:36:03,640 --> 00:36:05,200
Speaker 2: shit of being a Nazi than it is to actually

689
00:36:05,239 --> 00:36:07,799
Speaker 2: do the Nazi shit. That's exactly the vibe here.

690
00:36:08,160 --> 00:36:10,839
Speaker 1: And I think what's also annoying is that there is

691
00:36:11,160 --> 00:36:15,319
Speaker 1: a like interesting media conversation to be had about why

692
00:36:15,360 --> 00:36:18,799
Speaker 1: mom Donnie would check both Asian and African American on

693
00:36:18,840 --> 00:36:22,640
Speaker 1: a college application. Like you know, he basically said, like,

694
00:36:22,640 --> 00:36:24,960
Speaker 1: oh yeah, fifteen years ago when I was applying to college,

695
00:36:25,040 --> 00:36:27,800
Speaker 1: there was no box to check for being an Indian

696
00:36:27,840 --> 00:36:31,799
Speaker 1: America and who was born in Africa. That is interesting, right,

697
00:36:31,880 --> 00:36:34,480
Speaker 1: Like I think there is an interesting conversation to be

698
00:36:34,560 --> 00:36:37,000
Speaker 1: had about the limiting way that you think about and

699
00:36:37,040 --> 00:36:38,800
Speaker 1: talk about race in the United States.

700
00:36:39,120 --> 00:36:41,160
Speaker 2: But rather than like lift.

701
00:36:40,960 --> 00:36:46,320
Speaker 1: That actual substantive, potentially interesting, useful conversation, It's like the

702
00:36:46,360 --> 00:36:50,560
Speaker 1: New York Times is only allowed to elevate these very

703
00:36:50,719 --> 00:36:55,480
Speaker 1: small grievances of right wing race science pushers, Like we

704
00:36:55,560 --> 00:36:58,719
Speaker 1: had an opportunity to have an actual interesting conversation. They

705
00:36:58,719 --> 00:37:01,959
Speaker 1: were like, Nah, what about this like weird petty thing

706
00:37:02,040 --> 00:37:05,640
Speaker 1: from fifteen years ago. Let's just blow that up instead.

707
00:37:07,320 --> 00:37:20,279
Speaker 4: More after a quick break, let's get right back into it.

708
00:37:23,200 --> 00:37:26,000
Speaker 1: So, Joey, you and I actually I think you were

709
00:37:26,360 --> 00:37:30,520
Speaker 1: the producer on this show when Linda Yakarno first was

710
00:37:30,560 --> 00:37:33,239
Speaker 1: announced as the CEO of X, and that right, is

711
00:37:33,280 --> 00:37:34,640
Speaker 1: that I'm remembering that correctly?

712
00:37:34,800 --> 00:37:37,759
Speaker 2: Yes, I think so, because I remember having to re

713
00:37:38,080 --> 00:37:41,319
Speaker 2: edit you saying Jacherina now Cole times and.

714
00:37:41,320 --> 00:37:43,840
Speaker 1: Our producer Mike had to be like, think Linda Yakarrino

715
00:37:43,920 --> 00:37:45,960
Speaker 1: nine to one one and I was like, oh, got it.

716
00:37:46,280 --> 00:37:49,560
Speaker 1: That was because I kept saying it wrong. Linda Yakarino

717
00:37:49,760 --> 00:37:52,160
Speaker 1: not actually doesn't really matter. Now I'll probably not be

718
00:37:52,239 --> 00:37:55,560
Speaker 1: saying her name again after this episode because Linda Yakarino

719
00:37:55,840 --> 00:37:58,919
Speaker 1: has officially stepped down as a CEO of X after

720
00:37:58,960 --> 00:38:02,080
Speaker 1: two years at the you might be thinking, who the

721
00:38:02,120 --> 00:38:04,239
Speaker 1: hell is when the Yacherino don't know that name? It

722
00:38:04,320 --> 00:38:06,759
Speaker 1: is because you didn't really hear a ton from her,

723
00:38:07,160 --> 00:38:10,200
Speaker 1: Like when even when she got named as the CEO

724
00:38:10,239 --> 00:38:13,160
Speaker 1: of X, Elon Musk was certainly still the most public

725
00:38:13,160 --> 00:38:15,759
Speaker 1: facing person at X, even though she was meant to

726
00:38:15,800 --> 00:38:19,520
Speaker 1: ostensibly be the CEO. She would pop up a few times.

727
00:38:19,960 --> 00:38:23,279
Speaker 1: Mostly this sort of smoothed over some bad thing that

728
00:38:23,320 --> 00:38:25,360
Speaker 1: Elon Musk had done, or like explain why it was

729
00:38:25,400 --> 00:38:29,640
Speaker 1: actually good. So one of my favorite things in tech,

730
00:38:29,680 --> 00:38:32,120
Speaker 1: in media and all of this is how when people

731
00:38:32,320 --> 00:38:36,319
Speaker 1: leave companies, how they leave that generally gives us some

732
00:38:36,360 --> 00:38:38,520
Speaker 1: sort of insight into like what might have happened, what's

733
00:38:38,600 --> 00:38:41,960
Speaker 1: going on, Like if somebody leaves the company and then

734
00:38:42,120 --> 00:38:44,680
Speaker 1: somebody else in the company says, oh, we wish them

735
00:38:44,680 --> 00:38:47,960
Speaker 1: well in their future endeavors, but doesn't say anything about

736
00:38:48,000 --> 00:38:50,600
Speaker 1: their accomplishments or anything, like you basically know they were

737
00:38:50,640 --> 00:38:52,799
Speaker 1: fired and are getting or are being able to say

738
00:38:52,800 --> 00:38:55,480
Speaker 1: they've resigned, but it was probably messy, Like I would

739
00:38:55,480 --> 00:38:58,040
Speaker 1: not wish my worst enemy well.

740
00:38:57,880 --> 00:38:58,800
Speaker 2: In their future endeavors.

741
00:38:58,880 --> 00:39:01,800
Speaker 1: Is if somebody wishes somebody while on their future endeavorshit

742
00:39:01,880 --> 00:39:04,680
Speaker 1: is messy, sit is bad. They fuck, there's bad blood there.

743
00:39:04,960 --> 00:39:08,920
Speaker 1: So let's talk about how Linda Yacharvino left X. She

744
00:39:09,040 --> 00:39:12,320
Speaker 1: posted a very nice message about how she shared Elon's

745
00:39:12,360 --> 00:39:16,000
Speaker 1: vision for protecting free speech and making X and everything app.

746
00:39:16,800 --> 00:39:21,040
Speaker 1: Musk responded to her resignation with a succinct you might

747
00:39:21,080 --> 00:39:26,120
Speaker 1: even say a little bit icy response, thanks for your contributions.

748
00:39:26,920 --> 00:39:32,320
Speaker 1: Uh so that I mean, I don't have any tea there,

749
00:39:32,560 --> 00:39:35,200
Speaker 1: but that if I was a betting woman, I would say,

750
00:39:35,200 --> 00:39:38,080
Speaker 1: there's some drama behind the scenes, because typically when somebody

751
00:39:38,160 --> 00:39:41,600
Speaker 1: resigns and they're like, here's a glowing, lovely post, the

752
00:39:41,680 --> 00:39:45,200
Speaker 1: other person in leadership there generally is like, oh, we're

753
00:39:45,239 --> 00:39:48,560
Speaker 1: so thankful for their contributions, like this thing and that

754
00:39:48,640 --> 00:39:52,000
Speaker 1: thing and this thing. Like there's some exchange of glowing

755
00:39:52,440 --> 00:39:56,400
Speaker 1: positive back and forth. I will say, Elon Musk's response

756
00:39:56,960 --> 00:40:00,440
Speaker 1: little terse all right, So I find that curious.

757
00:40:00,719 --> 00:40:06,120
Speaker 2: Wow, Elon Musk being weird about other people and powered,

758
00:40:06,360 --> 00:40:08,880
Speaker 2: and that's like crazy, who would have thought you? You

759
00:40:08,880 --> 00:40:10,399
Speaker 2: would have thought that is.

760
00:40:10,360 --> 00:40:17,040
Speaker 6: Giving, Like like I definitely have set texts uh similar

761
00:40:17,080 --> 00:40:19,960
Speaker 6: to that, but it's been like, all right, thank you

762
00:40:20,360 --> 00:40:23,480
Speaker 6: for like like the passive aggressive, like, uh, leave me

763
00:40:23,520 --> 00:40:26,400
Speaker 6: alone now, like we're done, We're done.

764
00:40:26,080 --> 00:40:26,840
Speaker 2: I will say.

765
00:40:27,080 --> 00:40:31,080
Speaker 1: A day after she announced her resignation, her blue check

766
00:40:31,120 --> 00:40:34,680
Speaker 1: mark was removed. Her verified check mark was removed from X,

767
00:40:34,719 --> 00:40:39,480
Speaker 1: which petty, petty, petty, like come on, So that that,

768
00:40:39,680 --> 00:40:43,200
Speaker 1: I feel like says more to me than Musk's urse

769
00:40:43,280 --> 00:40:44,719
Speaker 1: little statement.

770
00:40:45,480 --> 00:40:45,839
Speaker 2: I think.

771
00:40:45,880 --> 00:40:48,520
Speaker 1: So, I think there's drama here, and I think we're

772
00:40:48,520 --> 00:40:52,400
Speaker 1: gonna you might get more information later, but I don't

773
00:40:52,480 --> 00:40:54,560
Speaker 1: know that I sent bad blood.

774
00:40:54,800 --> 00:40:56,640
Speaker 2: However, I do have thoughts.

775
00:40:56,680 --> 00:40:59,520
Speaker 1: You know, Yakarino, she came from the ad and media world,

776
00:40:59,600 --> 00:41:04,720
Speaker 1: specific NBCUniversal. She was really brought on to revive x's

777
00:41:05,360 --> 00:41:08,120
Speaker 1: doomed AD revenue. It turns out nobody wants to spend

778
00:41:08,160 --> 00:41:10,640
Speaker 1: money on a Nazi website when like the head of

779
00:41:10,640 --> 00:41:14,640
Speaker 1: that website is going on TV and being like, screw you, advertisers,

780
00:41:14,680 --> 00:41:17,239
Speaker 1: I don't need your money. We did note in one

781
00:41:17,239 --> 00:41:21,080
Speaker 1: episode that a lot of her success wooing back advertisers

782
00:41:21,719 --> 00:41:27,680
Speaker 1: was essentially extortion, where they would threaten to sue brands

783
00:41:27,680 --> 00:41:31,440
Speaker 1: who did not advertise on X, and those brands basically

784
00:41:31,480 --> 00:41:35,000
Speaker 1: were like, Okay, we'll rather pay this bribe then get

785
00:41:35,000 --> 00:41:36,200
Speaker 1: involved with illegal back.

786
00:41:36,000 --> 00:41:37,160
Speaker 2: And forth with these gules.

787
00:41:37,680 --> 00:41:40,200
Speaker 1: And so it turns out extortion there's a reason why

788
00:41:40,280 --> 00:41:43,480
Speaker 1: criminals use it. It's very effective. I do love how

789
00:41:43,600 --> 00:41:46,439
Speaker 1: like yacking. Yeah, their big innovation is always like low

790
00:41:46,520 --> 00:41:48,920
Speaker 1: key criminal behavior, Like Musk is like, oh.

791
00:41:48,800 --> 00:41:52,920
Speaker 2: What if what if we bribe them? Extortion? Has anyone

792
00:41:52,960 --> 00:41:59,120
Speaker 2: considered crimes? That is why Elon Musk is the super

793
00:41:59,200 --> 00:42:05,200
Speaker 2: genius that he is. Real life Tony Stark, I sorry,

794
00:42:05,239 --> 00:42:07,880
Speaker 2: this is a tangent. The first time I was introduced

795
00:42:07,880 --> 00:42:10,720
Speaker 2: to Elon Musk as a figure was This was way

796
00:42:10,760 --> 00:42:14,120
Speaker 2: back when he was still the Democrat Darling, and it

797
00:42:14,200 --> 00:42:16,120
Speaker 2: was in an interview. I think it was like it

798
00:42:16,200 --> 00:42:17,600
Speaker 2: was one of the late night shows, like it was

799
00:42:17,600 --> 00:42:19,920
Speaker 2: like Stephen Colbert's something. My parents were watching it and

800
00:42:19,960 --> 00:42:21,759
Speaker 2: my mom was like, oh, yeah, no, I really like him.

801
00:42:21,800 --> 00:42:23,799
Speaker 2: He's like he's like iron Man in real life. And

802
00:42:23,840 --> 00:42:27,600
Speaker 2: so my brain is always like see and I hate

803
00:42:27,640 --> 00:42:31,239
Speaker 2: iron Man. So clearly those movies suck and this is

804
00:42:31,239 --> 00:42:33,759
Speaker 2: what led us where we are today. This is all

805
00:42:33,840 --> 00:42:37,839
Speaker 2: Robert Downy Junior's fault. I I'm with you. One day

806
00:42:37,840 --> 00:42:39,240
Speaker 2: I'll do a full episode.

807
00:42:38,840 --> 00:42:41,560
Speaker 1: About Oh my god, I have to admit I've never

808
00:42:41,600 --> 00:42:42,479
Speaker 1: seen iron Man.

809
00:42:43,200 --> 00:42:46,760
Speaker 2: They're I love them when I was a kid. They're great,

810
00:42:46,800 --> 00:42:50,720
Speaker 2: like superhero movies. I did watch them again in college

811
00:42:50,760 --> 00:42:53,680
Speaker 2: at one point with my friend because his girlfriend hadn't

812
00:42:53,680 --> 00:42:59,160
Speaker 2: seen them forever, and they're they are super racist movies.

813
00:42:59,440 --> 00:43:02,239
Speaker 2: And that was not something that stuck with me from

814
00:43:02,239 --> 00:43:04,960
Speaker 2: when I was a kid. And I think hearing my

815
00:43:05,040 --> 00:43:08,759
Speaker 2: friend's girlfriend be like, so they're speaking the wrong dialect

816
00:43:08,800 --> 00:43:11,320
Speaker 2: of Arabic and here's what I go through the specific

817
00:43:11,400 --> 00:43:14,880
Speaker 2: like I, oh, no, you know, you might be. Anyways,

818
00:43:15,000 --> 00:43:19,839
Speaker 2: I think there's there's many most superhero movies you could

819
00:43:19,880 --> 00:43:22,640
Speaker 2: argue like they're bad, they're part of the military industrial complex.

820
00:43:22,719 --> 00:43:24,799
Speaker 2: I have my own specific fief with those movies because

821
00:43:24,800 --> 00:43:27,640
Speaker 2: they are literally like that is number one, Like that

822
00:43:27,719 --> 00:43:34,920
Speaker 2: is peak military industrial like post nine to eleven, like yay. Anyways, uh,

823
00:43:34,960 --> 00:43:37,480
Speaker 2: but yeah, that my theory is that is why we

824
00:43:37,560 --> 00:43:39,279
Speaker 2: have Elon Muscory is now and.

825
00:43:39,960 --> 00:43:42,640
Speaker 1: He's so wrapped up in the military like it does

826
00:43:42,680 --> 00:43:45,120
Speaker 1: with Tracks, because I think he got to his head.

827
00:43:45,160 --> 00:43:46,800
Speaker 2: I think he's got the ego now because that was

828
00:43:46,840 --> 00:43:48,279
Speaker 2: the thing was like they brought him out on this

829
00:43:48,400 --> 00:43:50,440
Speaker 2: show and they were like see really Like I think

830
00:43:50,480 --> 00:43:53,560
Speaker 2: they made him think, like, yes, I'm this like superhero,

831
00:43:53,640 --> 00:43:54,720
Speaker 2: super genius dude.

832
00:43:55,440 --> 00:43:58,000
Speaker 1: Anyways, so you're definitely coming back, and we're doing a

833
00:43:58,040 --> 00:44:02,000
Speaker 1: whole episode about the connection between Iron Man and Elon Musky.

834
00:44:03,000 --> 00:44:05,600
Speaker 2: Sure it all because of Elon.

835
00:44:05,400 --> 00:44:12,840
Speaker 1: Mus So you could maybe argue that Jacharino had some

836
00:44:13,160 --> 00:44:17,319
Speaker 1: success moving back advertisers in their low key criminal way.

837
00:44:17,680 --> 00:44:21,000
Speaker 1: Tech contraports that ad spending was up sixty two percent

838
00:44:21,120 --> 00:44:23,279
Speaker 1: year over year in the first half of twenty twenty five,

839
00:44:24,080 --> 00:44:27,760
Speaker 1: mostly due to election related spending, though they never reached

840
00:44:27,880 --> 00:44:31,239
Speaker 1: pre Musk advertising spending on the platform, So maybe you saying, okay, well,

841
00:44:31,239 --> 00:44:35,279
Speaker 1: she had some successes. But friend of the show, Nora Benavidez,

842
00:44:35,320 --> 00:44:37,720
Speaker 1: one of my favorite humans in the world, Senior counsel

843
00:44:37,760 --> 00:44:40,240
Speaker 1: and director of Digital Justice and Civil Rights were Free Press,

844
00:44:40,320 --> 00:44:43,040
Speaker 1: said in a statement, it is as ludicrous as it

845
00:44:43,080 --> 00:44:46,239
Speaker 1: is offensive for Jakarino to frame her time at X

846
00:44:46,400 --> 00:44:48,880
Speaker 1: as a win for free speech. Musk hired her to

847
00:44:48,960 --> 00:44:52,160
Speaker 1: lure back advertisers fleeing the platform after he turns it

848
00:44:52,160 --> 00:44:56,319
Speaker 1: into a cesspool of hate and disinformation. Jacharino's legacy is

849
00:44:56,320 --> 00:44:59,960
Speaker 1: her failure to manipulate companies to advertise at previous levels,

850
00:45:00,239 --> 00:45:02,840
Speaker 1: and now she's trying to mask that failure in First

851
00:45:02,880 --> 00:45:03,840
Speaker 1: Amendment rhetoric.

852
00:45:04,320 --> 00:45:07,080
Speaker 2: No one is buying that X is a free speech platform.

853
00:45:07,239 --> 00:45:11,040
Speaker 1: It's a megaphone for bigotry, conspiracy theories, and bullying people

854
00:45:11,040 --> 00:45:14,600
Speaker 1: into silence. Musk has no interest in upholding free expression

855
00:45:14,719 --> 00:45:18,160
Speaker 1: or protecting platform users. It's essential to name the harm

856
00:45:18,280 --> 00:45:21,800
Speaker 1: clearly and reclaim free speech as a force for truth

857
00:45:21,840 --> 00:45:25,160
Speaker 1: and democracy, not a shield for those who profit from

858
00:45:25,320 --> 00:45:26,080
Speaker 1: undermining it.

859
00:45:26,440 --> 00:45:32,240
Speaker 2: Out Nora Mike drop. Yeah, I can't say I disagree

860
00:45:32,280 --> 00:45:32,520
Speaker 2: with that.

861
00:45:32,760 --> 00:45:34,880
Speaker 1: Oh ma, Like that was written like a like a

862
00:45:35,200 --> 00:45:39,760
Speaker 1: Kendrick Lamar style dis track. So Yakarino's departure comes after

863
00:45:40,080 --> 00:45:42,960
Speaker 1: X's chat bot Grock, who they built to sort of

864
00:45:43,080 --> 00:45:50,000
Speaker 1: rival woke chat GPT went full on like Nazi rapist.

865
00:45:50,200 --> 00:45:53,640
Speaker 1: So this is not me saying this. This is Groc

866
00:45:53,760 --> 00:45:57,720
Speaker 1: saying this. Groc now is referring to himself as Mecha Hitler.

867
00:45:58,120 --> 00:46:00,440
Speaker 1: That's not so, this is not me putting words in

868
00:46:00,480 --> 00:46:03,319
Speaker 1: Groc's mouth. I'm I'm telling you what Groc told me.

869
00:46:04,239 --> 00:46:07,319
Speaker 2: I can't this is like I like this.

870
00:46:07,520 --> 00:46:10,600
Speaker 7: If this were a movie, it would be too heavy handed. Yeah,

871
00:46:10,600 --> 00:46:12,640
Speaker 7: I feel like, what do you mean it's mecha Hitler?

872
00:46:14,400 --> 00:46:18,120
Speaker 7: What do you mean musk chatbody is calling itself mecha Hitler.

873
00:46:18,360 --> 00:46:20,399
Speaker 2: I wish, I wish I could get in a time

874
00:46:20,480 --> 00:46:22,880
Speaker 2: machine and go back like ten years and go to

875
00:46:23,000 --> 00:46:26,640
Speaker 2: like fifteen year old meet and be like, one day

876
00:46:27,200 --> 00:46:30,520
Speaker 2: you're gonna have to do with Mecha Hitler like youth

877
00:46:30,640 --> 00:46:32,919
Speaker 2: Joey will be like, what are you what are you saying? Hell?

878
00:46:33,640 --> 00:46:36,840
Speaker 1: So, basically, you know it's no secret to anybody that

879
00:46:37,080 --> 00:46:40,600
Speaker 1: Musk was annoyed at what he perceived as liberal woke

880
00:46:40,760 --> 00:46:44,080
Speaker 1: mind bias in GROX, so he had his engineers restrain

881
00:46:44,200 --> 00:46:47,200
Speaker 1: it on new data that favored sites like four Chan

882
00:46:47,320 --> 00:46:49,680
Speaker 1: that was just full of hate speech. As they say,

883
00:46:49,880 --> 00:46:54,600
Speaker 1: garbage in, garbage out. Musk said, we have improved grock significantly.

884
00:46:55,360 --> 00:46:57,960
Speaker 1: You should notice a difference when you ask Rock questions.

885
00:46:58,320 --> 00:47:01,400
Speaker 1: So yeah, a day later, this chatbot was calling itself

886
00:47:01,440 --> 00:47:04,839
Speaker 1: Mecha Hitler. Elsewhere on the platform, neo Nazi accounts, we're

887
00:47:04,880 --> 00:47:09,239
Speaker 1: goading Groc into quote recommending a second Holocaust. Groc was

888
00:47:09,280 --> 00:47:12,319
Speaker 1: giving out specific instructions on how one could break into

889
00:47:12,360 --> 00:47:15,239
Speaker 1: the home of Will Stancil, a former Democratic candidate who

890
00:47:15,280 --> 00:47:18,759
Speaker 1: ran from Minnesota's House of Representatives last year, and how

891
00:47:19,000 --> 00:47:22,399
Speaker 1: one could sexually assault him. Minnesota is the state where

892
00:47:22,400 --> 00:47:24,759
Speaker 1: the speaker of the House was recently assassinated, so that's

893
00:47:24,800 --> 00:47:31,440
Speaker 1: particularly vile. Groc also sexually harassed Linda Yakarino herself. It

894
00:47:31,560 --> 00:47:35,279
Speaker 1: produced a revolting sexually explicit exchange which I won't get

895
00:47:35,320 --> 00:47:38,960
Speaker 1: into here, basically about Yacharino having sex with black men.

896
00:47:39,600 --> 00:47:43,080
Speaker 1: So yeah, I guess GROC and Twitter really is the

897
00:47:43,200 --> 00:47:47,759
Speaker 1: everything app because it does racism anti semitism and misogyny.

898
00:47:48,120 --> 00:47:50,239
Speaker 1: So people were sort of saying, like, oh, we bet

899
00:47:50,360 --> 00:47:53,480
Speaker 1: this ugliness with Groc is why yachar Reino quit. For

900
00:47:53,600 --> 00:47:56,080
Speaker 1: what it's worth, the journalist Carry Swisher, who's pretty plugged

901
00:47:56,080 --> 00:47:59,440
Speaker 1: into the tech industry, does not think that yacher Reno

902
00:47:59,480 --> 00:48:03,640
Speaker 1: stepping down had anything to do with Mecha Hitler. She

903
00:48:03,760 --> 00:48:06,640
Speaker 1: said the Mecha Hitler controversy was not it by the way,

904
00:48:07,080 --> 00:48:09,760
Speaker 1: I guess she sided with Trump over Musk and also

905
00:48:09,840 --> 00:48:11,560
Speaker 1: without the Trump card, it was likely going to be

906
00:48:11,640 --> 00:48:15,200
Speaker 1: hard to shake down advertisers with threats of lawsuits. And finally,

907
00:48:15,320 --> 00:48:17,439
Speaker 1: Threads is close to being as big as X, along

908
00:48:17,520 --> 00:48:19,160
Speaker 1: with new competitors like Blue Sky.

909
00:48:19,760 --> 00:48:21,960
Speaker 2: It was also reported that Yacharino.

910
00:48:21,440 --> 00:48:24,680
Speaker 1: Had already talked to people internally at X about stepping

911
00:48:24,760 --> 00:48:27,920
Speaker 1: down before Grock wet full Nazi rapist.

912
00:48:28,239 --> 00:48:31,560
Speaker 2: Yeah. I mean, I feel like at that point, if

913
00:48:31,640 --> 00:48:37,440
Speaker 2: you're if you're hanging on right up until Mecca Hitler,

914
00:48:38,880 --> 00:48:42,759
Speaker 2: at that point you're just in endorsing Mecca Hitler like

915
00:48:43,080 --> 00:48:46,680
Speaker 2: you were. You were like, I'm fine with all of

916
00:48:47,920 --> 00:48:49,680
Speaker 2: Like now that we put a name on it, it

917
00:48:49,800 --> 00:48:52,239
Speaker 2: doesn't make any difference. It was still like, you know,

918
00:48:52,400 --> 00:48:57,160
Speaker 2: groc has been doing this for what feels like decades now.

919
00:48:57,280 --> 00:49:00,480
Speaker 2: I think has only been a couple of months, but decades.

920
00:49:00,960 --> 00:49:03,239
Speaker 2: It does feel like decades. I do want to bring

921
00:49:03,360 --> 00:49:06,240
Speaker 2: up really quick because I saw this post on Tumblr

922
00:49:06,360 --> 00:49:08,400
Speaker 2: recently and it made me think of this show, just

923
00:49:08,520 --> 00:49:10,799
Speaker 2: thinking about like all of the shit that's gone down

924
00:49:10,880 --> 00:49:15,000
Speaker 2: in like ten years, and like how ridiculous stuff is now.

925
00:49:15,520 --> 00:49:18,080
Speaker 2: There was this post somebody that I saw. I'm gonna

926
00:49:18,080 --> 00:49:19,759
Speaker 2: read the post and then I'm gonna tell you the date,

927
00:49:20,200 --> 00:49:24,000
Speaker 2: says Okay, this is from Tumblr. Internet politics and real

928
00:49:24,040 --> 00:49:27,120
Speaker 2: world politics have gotten so separated, and pretty soon all

929
00:49:27,200 --> 00:49:29,839
Speaker 2: of this Internet awareness is going to come crashing into

930
00:49:29,920 --> 00:49:32,680
Speaker 2: real life and politicians are gonna start throwing around words

931
00:49:32,719 --> 00:49:37,080
Speaker 2: like SJW and anime communists and dark enlightenment and it's

932
00:49:37,160 --> 00:49:40,360
Speaker 2: just gonna be the most ridiculous fucking thing. This is

933
00:49:40,440 --> 00:49:47,279
Speaker 2: from April thirteenth, twenty fifteen. Wow. Liked at the prophecy

934
00:49:47,680 --> 00:49:49,680
Speaker 2: and like somebody like I could shot somebody put the

935
00:49:49,800 --> 00:49:52,359
Speaker 2: like the gift of like bed Affleck smoking and looking

936
00:49:52,480 --> 00:49:56,400
Speaker 2: like dead. But it was like, oh, like yeah you were,

937
00:49:56,440 --> 00:49:58,000
Speaker 2: because I don't know. This is something I keep going

938
00:49:58,040 --> 00:49:59,640
Speaker 2: back to because you brought up like fourtan and stuff

939
00:49:59,640 --> 00:50:02,200
Speaker 2: like that. We've talked about the show. I grew up

940
00:50:02,360 --> 00:50:04,160
Speaker 2: very on the internet, Like I was really in the

941
00:50:04,200 --> 00:50:06,759
Speaker 2: tumbler at that point. I was a teenager. I knew

942
00:50:06,800 --> 00:50:09,160
Speaker 2: about all this shit because I was on Tumblr and

943
00:50:09,280 --> 00:50:11,319
Speaker 2: it was like the other side of them. We see

944
00:50:11,360 --> 00:50:13,279
Speaker 2: people making fun of people on four Chan and whatever.

945
00:50:13,800 --> 00:50:16,719
Speaker 2: Now all of this stuff is just mainstream politics. Yeah,

946
00:50:16,760 --> 00:50:18,279
Speaker 2: and it is sort of like, why is all the

947
00:50:18,440 --> 00:50:23,280
Speaker 2: weird like niche, Like, it's all the weird kid stuff

948
00:50:23,320 --> 00:50:25,600
Speaker 2: from that era that now for some reason is like

949
00:50:27,760 --> 00:50:33,520
Speaker 2: this anyways. But yeah, I just think it's something to

950
00:50:33,640 --> 00:50:36,759
Speaker 2: think about when we think about the social media and

951
00:50:36,840 --> 00:50:39,920
Speaker 2: politics more.

952
00:50:39,960 --> 00:50:52,320
Speaker 4: After a quick break, let's get right back into it.

953
00:50:55,280 --> 00:50:58,840
Speaker 1: Okay, so really quickly, if you have been online chopping

954
00:50:58,960 --> 00:51:01,640
Speaker 1: at Walmart or coss Go in the state of Virginia lately,

955
00:51:02,360 --> 00:51:04,920
Speaker 1: you might have gotten a warning pop up on your

956
00:51:05,000 --> 00:51:09,080
Speaker 1: web browser that said quote, Virginia law requires your consent

957
00:51:09,200 --> 00:51:12,720
Speaker 1: to collect or use information about your potential or actual

958
00:51:12,800 --> 00:51:17,160
Speaker 1: purchase of reproductive or sexual health products or services. It

959
00:51:17,239 --> 00:51:20,520
Speaker 1: goes on to say that viewing, searching, and buying all

960
00:51:20,680 --> 00:51:24,280
Speaker 1: constitute consent and ends with if you do not consent.

961
00:51:24,480 --> 00:51:28,920
Speaker 1: Please avoid viewing, searching for, or purchasing these products, services,

962
00:51:29,080 --> 00:51:32,360
Speaker 1: or features. And that is because new Virginia state legislation

963
00:51:32,440 --> 00:51:35,920
Speaker 1: took place on July first that prohibits obtaining, selling, or

964
00:51:36,000 --> 00:51:40,000
Speaker 1: disclosing reproductive or sexual health information without consent. So this

965
00:51:40,120 --> 00:51:44,320
Speaker 1: covers things like pregnancy tests, birth control, and abortion medication.

966
00:51:45,000 --> 00:51:46,040
Speaker 2: So I'm from Virginia.

967
00:51:46,080 --> 00:51:49,040
Speaker 1: I live in DC, which is basically Virginia like northern

968
00:51:49,120 --> 00:51:50,800
Speaker 1: Virginia in some ways. So I saw a lot of

969
00:51:50,840 --> 00:51:53,960
Speaker 1: my Virginia friends posting about this and asking questions about it,

970
00:51:54,520 --> 00:51:58,120
Speaker 1: assuming understandably that this was like big government spuying on

971
00:51:58,160 --> 00:52:02,920
Speaker 1: their intimate, reproductive and sexual health purchases. But actually this

972
00:52:03,120 --> 00:52:07,239
Speaker 1: law prohibits stores from collecting information about your private purchases

973
00:52:07,520 --> 00:52:11,920
Speaker 1: without your consent. So essentially, Walmart has always been doing this,

974
00:52:12,040 --> 00:52:14,719
Speaker 1: Costco has always been doing this, but this new law

975
00:52:14,920 --> 00:52:17,399
Speaker 1: now requires them to tell you that they've always been

976
00:52:17,440 --> 00:52:22,000
Speaker 1: doing it. State Senator Virginia State Senator Barbara Favola, who

977
00:52:22,080 --> 00:52:25,640
Speaker 1: sponsored this legislation, said, these are intimate purchases. These are

978
00:52:25,680 --> 00:52:28,560
Speaker 1: purchases that nobody should know what you're doing, what you're buying,

979
00:52:28,960 --> 00:52:32,320
Speaker 1: or why. And I want the privacy insured. She basically

980
00:52:32,360 --> 00:52:34,840
Speaker 1: said that this legislation was needed in states with strict

981
00:52:34,840 --> 00:52:38,319
Speaker 1: abortion restrictions because there is concern that private information could

982
00:52:38,320 --> 00:52:42,399
Speaker 1: be used to prosecute somebody atating abortion medication out of state.

983
00:52:42,840 --> 00:52:44,400
Speaker 1: She said, we wrote the bill in a way that

984
00:52:44,440 --> 00:52:46,840
Speaker 1: we thought could be easily honored. I don't think anybody

985
00:52:46,880 --> 00:52:49,480
Speaker 1: had inside knowledge on how Walmart or Costco or other

986
00:52:49,520 --> 00:52:52,520
Speaker 1: big retailers are collecting the data, how they're storing it,

987
00:52:52,719 --> 00:52:56,279
Speaker 1: and what they are doing with it. So as weird

988
00:52:56,400 --> 00:52:58,880
Speaker 1: as it is to go to Walmart dot com and

989
00:52:58,920 --> 00:53:01,200
Speaker 1: get this kind of pop up, I do. I am

990
00:53:01,320 --> 00:53:04,000
Speaker 1: like very supportive of the spirit of this law. I'm

991
00:53:04,000 --> 00:53:06,160
Speaker 1: a little bit skeptical about the impact because it's not

992
00:53:06,320 --> 00:53:09,080
Speaker 1: like people can opt out from having their data stored.

993
00:53:09,680 --> 00:53:13,880
Speaker 1: That data is just like very very valuable for online retailers,

994
00:53:13,920 --> 00:53:15,719
Speaker 1: and it's I guess it's sort of telling to me

995
00:53:16,280 --> 00:53:19,319
Speaker 1: that Walmart would rather lose you as a customer by

996
00:53:19,400 --> 00:53:22,120
Speaker 1: telling you, oh, if you don't consent, don't make this

997
00:53:22,280 --> 00:53:25,839
Speaker 1: purchase here, then provide you an easy way to opt

998
00:53:25,920 --> 00:53:29,160
Speaker 1: out from having your data about your sensitive purchase or

999
00:53:29,320 --> 00:53:30,680
Speaker 1: searching tracked.

1000
00:53:31,080 --> 00:53:33,000
Speaker 2: Like I have not seen any data about this.

1001
00:53:33,200 --> 00:53:35,479
Speaker 1: But I would imagine that people who saw that pop

1002
00:53:35,600 --> 00:53:38,960
Speaker 1: up probably just dismissed it and continue to purchase. But

1003
00:53:39,480 --> 00:53:41,359
Speaker 1: you know, saying like oh it's fine if you don't

1004
00:53:41,360 --> 00:53:43,320
Speaker 1: want to buy from us, that's fine, just you know,

1005
00:53:43,800 --> 00:53:47,360
Speaker 1: go on your digital way. I feel like that's really

1006
00:53:47,560 --> 00:53:50,120
Speaker 1: telling to me that the data must be worth a

1007
00:53:50,280 --> 00:53:52,239
Speaker 1: ton for them. Yeah.

1008
00:53:53,200 --> 00:53:55,080
Speaker 2: Yeah, it is like like I agree, it is like

1009
00:53:55,080 --> 00:53:56,319
Speaker 2: one of those things where it's like, Okay, I guess

1010
00:53:56,360 --> 00:53:58,799
Speaker 2: this is better than nothing, Like it's good that they're

1011
00:53:58,800 --> 00:54:05,359
Speaker 2: at least something, but still like, oh that's not good,

1012
00:54:05,640 --> 00:54:08,359
Speaker 2: and I do not I don't know. Yeah, the whole

1013
00:54:09,200 --> 00:54:11,279
Speaker 2: this is like anything too. Like this was like this

1014
00:54:11,480 --> 00:54:13,160
Speaker 2: was a story from like a couple of weeks back,

1015
00:54:13,239 --> 00:54:17,200
Speaker 2: but like have you like bridget I'm sure I use

1016
00:54:17,280 --> 00:54:20,319
Speaker 2: like partifle a lot for like yeah, organized like events

1017
00:54:20,360 --> 00:54:21,440
Speaker 2: and stuff, and there was like a whole story that

1018
00:54:21,480 --> 00:54:22,839
Speaker 2: came out that I was like run by the same

1019
00:54:22,840 --> 00:54:26,400
Speaker 2: guys that are like the Paneltry guys, and like it

1020
00:54:26,520 --> 00:54:27,560
Speaker 2: was one of those things where I saw a lot

1021
00:54:27,600 --> 00:54:30,360
Speaker 2: of people being like oh right, like if you're you

1022
00:54:30,480 --> 00:54:32,800
Speaker 2: have this free service, like you are the data that

1023
00:54:32,920 --> 00:54:36,000
Speaker 2: they're we're using this free service, but it makes sense

1024
00:54:36,040 --> 00:54:37,600
Speaker 2: when you think about it, like this is a great

1025
00:54:37,600 --> 00:54:40,320
Speaker 2: way to track people and track their movements and director

1026
00:54:40,360 --> 00:54:43,000
Speaker 2: connections and whatever. And it's like something like that was

1027
00:54:43,160 --> 00:54:44,680
Speaker 2: that I had a moment where had to like think

1028
00:54:44,719 --> 00:54:48,520
Speaker 2: and be like or things like Venmo, Like you know,

1029
00:54:48,600 --> 00:54:50,080
Speaker 2: people all the time will use like they'll put like

1030
00:54:50,160 --> 00:54:52,719
Speaker 2: stupid jokes in there, like Venmo requests, and it's like

1031
00:54:54,080 --> 00:54:56,200
Speaker 2: that can turn into something that somebody could use. It's

1032
00:54:56,200 --> 00:54:59,120
Speaker 2: like evidence against you. It could be a part offle

1033
00:54:59,160 --> 00:55:00,960
Speaker 2: and like I don't know, Like I was like, I'm

1034
00:55:01,000 --> 00:55:02,960
Speaker 2: not gonna lie. I am the kind of person that

1035
00:55:03,040 --> 00:55:09,080
Speaker 2: I totally would like like abortion party, Got y'all come

1036
00:55:09,160 --> 00:55:15,319
Speaker 2: to Joey's abortion party? To the FBI man listening, that's

1037
00:55:15,440 --> 00:55:16,040
Speaker 2: not happening.

1038
00:55:17,080 --> 00:55:20,279
Speaker 1: It was canceled. It was canceled. Yeah, we I just

1039
00:55:20,360 --> 00:55:22,560
Speaker 1: did an episode on stuff I've never told you all

1040
00:55:22,600 --> 00:55:27,560
Speaker 1: about whether or not WhatsApp is secure and sort of

1041
00:55:27,880 --> 00:55:31,200
Speaker 1: long story short, it's mostly secure. It's probably fine, but

1042
00:55:31,280 --> 00:55:32,799
Speaker 1: if you have any if you if you are talking

1043
00:55:32,840 --> 00:55:35,600
Speaker 1: about anything at all sensitive, you should be using signal.

1044
00:55:35,880 --> 00:55:38,879
Speaker 1: And you know it is like you know, if you're

1045
00:55:38,960 --> 00:55:41,200
Speaker 1: if you're making any kind of purchase like this that

1046
00:55:41,320 --> 00:55:46,719
Speaker 1: you that might be broadly considered in this category of sensitive.

1047
00:55:46,360 --> 00:55:47,440
Speaker 2: Stuff use cash.

1048
00:55:47,600 --> 00:55:49,839
Speaker 1: Like whenever we talk about this kind of thing, people

1049
00:55:49,920 --> 00:55:52,320
Speaker 1: listening are like, oh, well they already got me. Like what, like,

1050
00:55:52,360 --> 00:55:56,120
Speaker 1: what difference does it make it? That's called digital nihilism

1051
00:55:56,280 --> 00:55:58,719
Speaker 1: or surveillance nihilism. It's a it's a it's the wrong

1052
00:55:58,800 --> 00:55:59,880
Speaker 1: attitude to take.

1053
00:56:00,080 --> 00:56:02,440
Speaker 2: Fall into that a lot too, I mean very like

1054
00:56:02,840 --> 00:56:04,839
Speaker 2: I have had a lot. But it's like, oh, there's

1055
00:56:04,840 --> 00:56:07,319
Speaker 2: alsofic specific things where like yeah, I mean I mentioned

1056
00:56:07,320 --> 00:56:10,080
Speaker 2: I don't use period tracker app. I like, there are

1057
00:56:10,239 --> 00:56:11,880
Speaker 2: certain things that I'm like, I know I need to

1058
00:56:11,920 --> 00:56:16,840
Speaker 2: have cash on hand. Just yeah, like you never fucking

1059
00:56:17,040 --> 00:56:19,439
Speaker 2: and again, this is all like for the most part

1060
00:56:19,560 --> 00:56:24,160
Speaker 2: right now, like you know, cautionary, Like luckily I've not

1061
00:56:24,239 --> 00:56:27,200
Speaker 2: been in a situation where like I've been in dangerous

1062
00:56:27,239 --> 00:56:29,560
Speaker 2: but I mean you brought up the in the last

1063
00:56:29,600 --> 00:56:33,560
Speaker 2: story that the Minnesota shooting to where like that occurred

1064
00:56:33,640 --> 00:56:36,359
Speaker 2: because of publicly like information that was available, the data

1065
00:56:36,400 --> 00:56:40,360
Speaker 2: that had been brought bought by data brokers. This is

1066
00:56:40,440 --> 00:56:43,800
Speaker 2: a reality, Like we live in a surveillance state that

1067
00:56:43,920 --> 00:56:48,480
Speaker 2: has never before been possible exactly, and it doesn't take much.

1068
00:56:48,880 --> 00:56:52,680
Speaker 1: And most of these like it's like signal is free, right,

1069
00:56:52,920 --> 00:56:55,359
Speaker 1: keep like not having a period, trackering this using pen

1070
00:56:55,440 --> 00:56:57,960
Speaker 1: and paper, that's free. It does not take much to

1071
00:56:58,160 --> 00:57:02,120
Speaker 1: do basic steps to protect your data, protect your privacy.

1072
00:57:02,640 --> 00:57:04,960
Speaker 1: You know, there was an old adage it's like, oh, well,

1073
00:57:05,160 --> 00:57:07,040
Speaker 1: you wouldn't have to do that if you have something

1074
00:57:07,080 --> 00:57:09,560
Speaker 1: to hide. In twenty twenty five, all of us has

1075
00:57:09,600 --> 00:57:11,400
Speaker 1: something to hide, right, if you've got something to lose,

1076
00:57:11,560 --> 00:57:14,200
Speaker 1: you've got something to hide, something to protect. It's not

1077
00:57:14,400 --> 00:57:17,360
Speaker 1: being paranoid to take basic steps to protect your data.

1078
00:57:17,440 --> 00:57:19,400
Speaker 1: And I think in twenty twenty five, we all should

1079
00:57:19,400 --> 00:57:21,720
Speaker 1: be taking basic steps to protect our data, especially when

1080
00:57:21,720 --> 00:57:25,720
Speaker 1: it's like you probably don't have to take more involved

1081
00:57:25,880 --> 00:57:29,400
Speaker 1: or expensive measures. If you do the free, easy, common

1082
00:57:29,520 --> 00:57:30,480
Speaker 1: sense stuff.

1083
00:57:30,440 --> 00:57:31,720
Speaker 2: You'll probably be good.

1084
00:57:31,920 --> 00:57:35,440
Speaker 1: Like there's there's just no in twenty twenty five, we

1085
00:57:35,520 --> 00:57:39,360
Speaker 1: cannot nobody can afford surveillance or digital nihilism. We have

1086
00:57:39,480 --> 00:57:41,400
Speaker 1: to like do what we got to do to protect

1087
00:57:41,440 --> 00:57:44,080
Speaker 1: ourselves in our communities. This is like the the baseline

1088
00:57:44,120 --> 00:57:46,000
Speaker 1: of what we we shouldn't have to do it, but

1089
00:57:46,400 --> 00:57:48,880
Speaker 1: unfortunately we do exactly.

1090
00:57:49,520 --> 00:57:53,400
Speaker 2: I mean, it's yeah. I was like thinking of this

1091
00:57:53,440 --> 00:57:55,720
Speaker 2: reason because, like, I I'll be real, I love buying

1092
00:57:55,720 --> 00:57:59,439
Speaker 2: my phone. I love gaving my friends locations at getting

1093
00:57:59,480 --> 00:58:01,480
Speaker 2: to see Wait, I.

1094
00:58:01,600 --> 00:58:04,720
Speaker 1: Read that young people they always have their locations on

1095
00:58:04,880 --> 00:58:05,320
Speaker 1: with their friends.

1096
00:58:05,360 --> 00:58:08,440
Speaker 2: Is this true? Yeah, I'll be real. Like, I was

1097
00:58:09,080 --> 00:58:12,360
Speaker 2: kind of resistant to the idea at first, like I

1098
00:58:13,040 --> 00:58:15,160
Speaker 2: would only really sure my okay, like if somebody need

1099
00:58:15,280 --> 00:58:18,000
Speaker 2: my location for like to find like like we're like

1100
00:58:18,040 --> 00:58:19,520
Speaker 2: trying to find each other like a crowded thing, I

1101
00:58:19,520 --> 00:58:21,200
Speaker 2: would give it to them for like a day, and

1102
00:58:21,280 --> 00:58:23,920
Speaker 2: then that was it. Uh. And then eventually at some

1103
00:58:24,000 --> 00:58:26,920
Speaker 2: point I was like, oh, well, I don't know what

1104
00:58:27,000 --> 00:58:29,840
Speaker 2: the hell it's like my friends. It was also I think,

1105
00:58:29,920 --> 00:58:31,840
Speaker 2: like I like live with roommates and it's nice to

1106
00:58:32,000 --> 00:58:33,920
Speaker 2: like be able to check in with each other and

1107
00:58:33,960 --> 00:58:36,400
Speaker 2: stuff like that. But like, yeah, I mean I think

1108
00:58:36,480 --> 00:58:39,640
Speaker 2: the like the benefit of it is it's like nice

1109
00:58:39,720 --> 00:58:42,000
Speaker 2: sometimes to be able to like if I'm out at

1110
00:58:42,000 --> 00:58:44,520
Speaker 2: a party with some friends and people are leaving at

1111
00:58:44,560 --> 00:58:46,440
Speaker 2: different times, it's nice to be able to check that,

1112
00:58:46,600 --> 00:58:51,400
Speaker 2: like people got home okay ah, or like my I

1113
00:58:51,440 --> 00:58:53,160
Speaker 2: don't live in the same state as my parents, so

1114
00:58:53,240 --> 00:58:55,920
Speaker 2: I know, like my mom likes that she can, you know,

1115
00:58:56,680 --> 00:58:59,000
Speaker 2: check to make sure that like me and my sister

1116
00:58:59,600 --> 00:59:02,880
Speaker 2: are home in safe and not you know, floating in

1117
00:59:02,960 --> 00:59:06,520
Speaker 2: the middle of the Hudson River or something. But also

1118
00:59:06,640 --> 00:59:10,800
Speaker 2: it is objectively weird, like I don't know, it's it's

1119
00:59:12,000 --> 00:59:14,160
Speaker 2: like I think it is useful and I do it,

1120
00:59:14,480 --> 00:59:16,840
Speaker 2: like I do have my location shared with a lot

1121
00:59:16,880 --> 00:59:19,520
Speaker 2: of people, at least with iPhones. It's sort of like

1122
00:59:19,600 --> 00:59:21,720
Speaker 2: I know that like if I were in a situation

1123
00:59:21,920 --> 00:59:24,440
Speaker 2: where like I didn't want to be tracked, I could

1124
00:59:24,520 --> 00:59:26,280
Speaker 2: just leave it at home or like turn it off

1125
00:59:26,400 --> 00:59:31,840
Speaker 2: or something. So there's that. But yeah, it is like

1126
00:59:31,960 --> 00:59:33,040
Speaker 2: objectively kind of weird.

1127
00:59:33,120 --> 00:59:34,240
Speaker 4: But but it's it's nice.

1128
00:59:34,280 --> 00:59:36,240
Speaker 2: It's nice to just like to know where people are at.

1129
00:59:36,440 --> 00:59:39,919
Speaker 1: Well, how do you lie about I'm on my way

1130
00:59:40,080 --> 00:59:42,080
Speaker 1: to meet you and you're really in the shower?

1131
00:59:42,240 --> 00:59:44,680
Speaker 2: How like if you shared your location, Well, all if

1132
00:59:44,720 --> 00:59:46,600
Speaker 2: my friends that have my if you have my location,

1133
00:59:46,720 --> 00:59:48,600
Speaker 2: if we're close enough friends to have my location, you

1134
00:59:48,720 --> 00:59:50,600
Speaker 2: know that I will be like two hours like again,

1135
00:59:51,040 --> 00:59:53,760
Speaker 2: so so that if that if if you're mad at

1136
00:59:53,800 --> 00:59:55,280
Speaker 2: me for saying I'm on my way and you're like

1137
00:59:55,360 --> 00:59:59,840
Speaker 2: you're still home, that's not you I this is but yeah,

1138
01:00:00,240 --> 01:00:01,840
Speaker 2: but yeah, no, I mean I do say all of

1139
01:00:01,920 --> 01:00:06,520
Speaker 2: this also acknowledging that it is like also weird and

1140
01:00:06,680 --> 01:00:10,000
Speaker 2: like definitely a product of the surveillance state, and like

1141
01:00:10,880 --> 01:00:16,320
Speaker 2: how much surveillance has been normalized. So I don't know

1142
01:00:16,400 --> 01:00:18,760
Speaker 2: if I'm like super glad that this is a thing

1143
01:00:18,840 --> 01:00:22,160
Speaker 2: that exists. It is like the norm, but I do

1144
01:00:22,360 --> 01:00:25,160
Speaker 2: participate in it, so I don't know. Yeah, I mean,

1145
01:00:25,240 --> 01:00:30,960
Speaker 2: it's just another reason why, like like basic free digital

1146
01:00:31,560 --> 01:00:33,440
Speaker 2: best practices, I think we should all be doing them

1147
01:00:33,480 --> 01:00:36,000
Speaker 2: if people want to know where they can start get

1148
01:00:36,040 --> 01:00:37,640
Speaker 2: in touch with me. I'm happy. It's like a thing.

1149
01:00:37,680 --> 01:00:39,760
Speaker 2: It's like a thing I love talking about, So I yeah,

1150
01:00:39,960 --> 01:00:41,560
Speaker 2: we should. I feel like I should hear you about

1151
01:00:41,600 --> 01:00:44,440
Speaker 2: this because I definitely have too much information out there

1152
01:00:44,600 --> 01:00:48,440
Speaker 2: that not the fun kind, the kind that would get

1153
01:00:48,480 --> 01:00:50,960
Speaker 2: me doxed. But uh, I mean I hope not. Ah

1154
01:00:51,200 --> 01:00:53,080
Speaker 2: don't know, no one docks me.

1155
01:00:53,280 --> 01:00:58,200
Speaker 1: Yeah, people listening, don't that's please please don't well, Joey,

1156
01:00:58,560 --> 01:01:02,200
Speaker 1: can I hit you with just the cook pure?

1157
01:01:02,400 --> 01:01:06,520
Speaker 2: Can we end with just some pure unsubstantiated rumor? Oh

1158
01:01:06,680 --> 01:01:09,680
Speaker 2: please ill, I'm substantiata rumors favorite thing?

1159
01:01:10,040 --> 01:01:13,880
Speaker 1: Okay, So last month, Lauren Sanchez was on the cover

1160
01:01:14,000 --> 01:01:17,760
Speaker 1: of Vogue, and I remember seeing this him thinking that's surprising.

1161
01:01:17,960 --> 01:01:19,920
Speaker 2: This is a surprising choice. I did not.

1162
01:01:20,360 --> 01:01:22,440
Speaker 1: I never thought i'd see the day when Lauren Sanchez

1163
01:01:22,720 --> 01:01:26,320
Speaker 1: famously recently married to Jeff Bezos. So I found all

1164
01:01:26,360 --> 01:01:29,280
Speaker 1: this surprising. And when I saw it, I remember thinking,

1165
01:01:30,280 --> 01:01:33,720
Speaker 1: is Bezos about to buy Vogue? I had no inside information.

1166
01:01:33,840 --> 01:01:35,640
Speaker 1: This is just my gut, just a thought that popped

1167
01:01:35,640 --> 01:01:38,919
Speaker 1: into my head when I saw this magazine. Then Anna

1168
01:01:39,000 --> 01:01:41,680
Speaker 1: Wintour announced last month that she was stepping down as

1169
01:01:41,800 --> 01:01:44,760
Speaker 1: Vogue's editor in chet after thirty seven years. She'll remain

1170
01:01:44,880 --> 01:01:47,520
Speaker 1: in control of global operations. So I also found this

1171
01:01:47,560 --> 01:01:50,440
Speaker 1: surprising because Anna Wintour seems like somebody who would like

1172
01:01:51,200 --> 01:01:54,440
Speaker 1: die in her office rather than give up one iota

1173
01:01:54,600 --> 01:01:57,160
Speaker 1: of leadership or power. That seems to be her vibe

1174
01:01:57,160 --> 01:01:59,360
Speaker 1: to me. She has kind of a pope energy and

1175
01:01:59,440 --> 01:02:03,040
Speaker 1: she does is My favorite Anno Wintour story is that

1176
01:02:03,800 --> 01:02:06,240
Speaker 1: she if you. She she's based on if, the movie,

1177
01:02:06,360 --> 01:02:08,320
Speaker 1: the book The Devil wors Broda. She's supposed to be

1178
01:02:08,360 --> 01:02:09,760
Speaker 1: like a man She's done a man of friestly type.

1179
01:02:10,760 --> 01:02:13,320
Speaker 2: Her. I'm gonna say and a mode from Incredibles, but

1180
01:02:13,440 --> 01:02:17,240
Speaker 2: also that ye yes, same hair. Yeah, it's like I

1181
01:02:17,360 --> 01:02:19,360
Speaker 2: was like, of course, the most famous character she's based

1182
01:02:19,400 --> 01:02:21,000
Speaker 2: on in Meryl Streep.

1183
01:02:21,120 --> 01:02:23,480
Speaker 1: So the story is that so like Anna went Tour

1184
01:02:23,600 --> 01:02:26,240
Speaker 1: is not it's like kinda known for being not a

1185
01:02:26,360 --> 01:02:28,880
Speaker 1: nice person. I actually don't like Anno Wintour. If you've

1186
01:02:28,920 --> 01:02:32,400
Speaker 1: read Andre Leon Tally's memoir, I was like, I will

1187
01:02:32,400 --> 01:02:33,040
Speaker 1: hate her forever.

1188
01:02:33,200 --> 01:02:36,320
Speaker 2: Oh same the Konde Naspirings when she like didn't even

1189
01:02:36,360 --> 01:02:38,919
Speaker 2: take her song yeah off, that was like the nail.

1190
01:02:39,000 --> 01:02:40,720
Speaker 2: Like I already didn't like her, but I was like, oh,

1191
01:02:40,840 --> 01:02:42,320
Speaker 2: so you're like evil. Same.

1192
01:02:42,680 --> 01:02:45,920
Speaker 1: Like it's I don't think that you have to be

1193
01:02:46,280 --> 01:02:46,560
Speaker 1: like I.

1194
01:02:47,440 --> 01:02:50,480
Speaker 2: I think that to rise up in leadership you have to.

1195
01:02:50,480 --> 01:02:53,640
Speaker 1: Be decisive, you have to be confident, you have to

1196
01:02:53,720 --> 01:02:55,760
Speaker 1: be assertive maybe aggressive.

1197
01:02:56,120 --> 01:02:58,840
Speaker 2: Sure, you don't have to be an asshole like I guess.

1198
01:02:58,920 --> 01:03:01,360
Speaker 1: I just don't like this idea that, oh can you

1199
01:03:01,480 --> 01:03:05,280
Speaker 1: believe like she's so cold and mean and unempathetic it

1200
01:03:05,360 --> 01:03:07,400
Speaker 1: makes her a great leader. No, you can be a

1201
01:03:07,480 --> 01:03:10,080
Speaker 1: good leader, but being an asshole is a choice. Not

1202
01:03:10,240 --> 01:03:12,880
Speaker 1: taking off your sunglasses when you're firing people.

1203
01:03:12,960 --> 01:03:15,600
Speaker 2: And laying them off. That's a choice you don't have

1204
01:03:15,800 --> 01:03:17,800
Speaker 2: to that's a choice to behave in that way.

1205
01:03:18,360 --> 01:03:21,600
Speaker 1: So you know, they used to call Conde Nast conde

1206
01:03:21,800 --> 01:03:25,360
Speaker 1: nasty because that was the attitude that permeated from the top.

1207
01:03:25,400 --> 01:03:28,920
Speaker 1: And my favorite story about this is that apparently, allegedly

1208
01:03:29,080 --> 01:03:33,040
Speaker 1: at a Conde Nasty Christmas party, everybody knew that you

1209
01:03:33,360 --> 01:03:36,080
Speaker 1: weren't supposed to look Anna Wintour in the eyes, and

1210
01:03:36,160 --> 01:03:37,800
Speaker 1: so if you saw Anna Wintour, you were meant to

1211
01:03:37,880 --> 01:03:40,480
Speaker 1: like avert your gaze and basically ignore her. And that

1212
01:03:40,600 --> 01:03:44,040
Speaker 1: at a Christmas party, Anna Wintour had a bad fall,

1213
01:03:44,200 --> 01:03:46,480
Speaker 1: like she fell over or tripped over something, and like

1214
01:03:46,840 --> 01:03:49,480
Speaker 1: it was one of those falls where it was very noisy,

1215
01:03:49,760 --> 01:03:52,000
Speaker 1: like maybe she took down a tray of drinks as well,

1216
01:03:52,360 --> 01:03:55,439
Speaker 1: but nobody if you had that kind of fall, people

1217
01:03:55,480 --> 01:03:57,080
Speaker 1: would rush over and help you and be like are

1218
01:03:57,160 --> 01:04:01,040
Speaker 1: you okay? And nobody said a word. Everybody this pretended

1219
01:04:01,160 --> 01:04:04,520
Speaker 1: like this, this loud calamity of a fall did not

1220
01:04:04,720 --> 01:04:07,320
Speaker 1: happen because she had set the agenda of like, do

1221
01:04:07,520 --> 01:04:09,680
Speaker 1: not approach me, do not look at me in the eye,

1222
01:04:09,960 --> 01:04:10,600
Speaker 1: and part of me is.

1223
01:04:10,600 --> 01:04:12,160
Speaker 2: Like, oh, it looks like your re what you sew.

1224
01:04:12,280 --> 01:04:14,560
Speaker 1: No one's gonna help your ass up because you've been

1225
01:04:14,680 --> 01:04:16,280
Speaker 1: so mean to everybody the last few years.

1226
01:04:16,680 --> 01:04:20,760
Speaker 2: Yeah, I you brought a Devil Wears Prada, which you

1227
01:04:20,840 --> 01:04:23,040
Speaker 2: know what, maybe this is just a giant publicity stunt

1228
01:04:23,160 --> 01:04:27,800
Speaker 2: for douvilewarst Prada too, which is apparently happening. Oh terrible,

1229
01:04:27,800 --> 01:04:29,480
Speaker 2: I'll watch it, Noah, I'm sure it's gonna be awful.

1230
01:04:29,720 --> 01:04:33,160
Speaker 2: But I have a love hate relationship of that movie because, like,

1231
01:04:34,520 --> 01:04:38,000
Speaker 2: I think it's a good movie. I thought not long ago,

1232
01:04:38,040 --> 01:04:39,280
Speaker 2: like I didn't see one again. I saw it like

1233
01:04:39,320 --> 01:04:42,880
Speaker 2: a couple of years ago. And my first cause I

1234
01:04:43,000 --> 01:04:45,280
Speaker 2: had heard all the like oh, the boyfriend's the real villain,

1235
01:04:45,440 --> 01:04:47,320
Speaker 2: like she's And then I watched it and I was like, oh,

1236
01:04:47,400 --> 01:04:50,800
Speaker 2: this is a movie about an abusive boss, Like what

1237
01:04:50,920 --> 01:04:52,600
Speaker 2: do you mean? Like I was like, sure, yeah, the

1238
01:04:52,680 --> 01:04:56,040
Speaker 2: boyfriend's not great like whatever. But I was like, yeah,

1239
01:04:56,040 --> 01:04:58,240
Speaker 2: I also would be like her friend, Like I was like,

1240
01:04:58,280 --> 01:04:59,920
Speaker 2: I would be concerned if one of my friends was

1241
01:05:00,040 --> 01:05:04,040
Speaker 2: in this situation, Like I probably also would be like yeah,

1242
01:05:04,400 --> 01:05:06,680
Speaker 2: like are you good? Like if you like, are you

1243
01:05:06,760 --> 01:05:08,200
Speaker 2: sure this is the path? I don't know? Like I

1244
01:05:08,320 --> 01:05:10,680
Speaker 2: was like, I don't know. To me, that's I was like,

1245
01:05:10,800 --> 01:05:12,720
Speaker 2: she was awful. Like I was like, the whole point

1246
01:05:12,840 --> 01:05:17,480
Speaker 2: is narrow Streep's characters terrible. Like I was like, she's

1247
01:05:17,560 --> 01:05:19,560
Speaker 2: not like a girl boss, like or she is a

1248
01:05:19,600 --> 01:05:21,520
Speaker 2: girl She maybe is like the epitomy of that girl

1249
01:05:21,600 --> 01:05:26,479
Speaker 2: boss demonism stuff which is not good, which is still bad.

1250
01:05:27,200 --> 01:05:29,360
Speaker 1: Maybe the real villain of the movie is the person

1251
01:05:29,400 --> 01:05:32,520
Speaker 1: who is flinging her coat in someone's in her underling's

1252
01:05:32,560 --> 01:05:34,200
Speaker 1: face every single goddamn day.

1253
01:05:34,400 --> 01:05:36,680
Speaker 2: But maybe in maybe in the new one, Jeff Bezos

1254
01:05:36,920 --> 01:05:41,080
Speaker 2: will be the the new Moranda Pressley and then it'll

1255
01:05:41,120 --> 01:05:43,040
Speaker 2: be a totally new t.

1256
01:05:43,240 --> 01:05:43,520
Speaker 4: I don't know.

1257
01:05:44,040 --> 01:05:49,280
Speaker 1: It could be Jeff Bezos, who I mean, I suspected.

1258
01:05:49,400 --> 01:05:50,880
Speaker 1: I was like, I think he might be about to

1259
01:05:50,960 --> 01:05:55,680
Speaker 1: buy Conde Nest. Could be Lauren Sanchez. So so again

1260
01:05:55,840 --> 01:05:58,760
Speaker 1: I want to say this is this is all rumor. However,

1261
01:05:59,040 --> 01:06:02,200
Speaker 1: StyleCaster quoted an anonymous source, so take it with the

1262
01:06:02,280 --> 01:06:05,040
Speaker 1: rain of salt. The rumor is that jeth is going

1263
01:06:05,080 --> 01:06:07,919
Speaker 1: to buy Conde Nast. It is all anyone's talking about

1264
01:06:07,960 --> 01:06:11,800
Speaker 1: in the fashion industry and inside Vogue. Adding Lauren Sanchez

1265
01:06:11,920 --> 01:06:14,480
Speaker 1: is such an unlikely cover star, and the word is

1266
01:06:14,560 --> 01:06:17,200
Speaker 1: that she landed the July issue partly because the new

1267
01:06:17,240 --> 01:06:20,800
Speaker 1: House family, who currently owns Conde Nast wants to butter

1268
01:06:20,920 --> 01:06:23,720
Speaker 1: up Bezos in New York. They're slimming down the business,

1269
01:06:23,760 --> 01:06:26,320
Speaker 1: which is exactly what companies do before a sale.

1270
01:06:26,840 --> 01:06:27,640
Speaker 2: And that is not all.

1271
01:06:27,960 --> 01:06:30,200
Speaker 1: Anna Wintour is said to be directly involved in a

1272
01:06:30,240 --> 01:06:33,120
Speaker 1: possible sale. The source says. Anna is said to be

1273
01:06:33,200 --> 01:06:35,120
Speaker 1: the one broker in the deal, So that's why Lauren

1274
01:06:35,240 --> 01:06:37,440
Speaker 1: was on the cover. Anna has equity in the business,

1275
01:06:37,480 --> 01:06:39,439
Speaker 1: so she has a lot to gain from a sale.

1276
01:06:40,320 --> 01:06:41,720
Speaker 2: So who knows?

1277
01:06:41,960 --> 01:06:45,760
Speaker 1: Lauren Sanchez does have a background in like I guess,

1278
01:06:45,840 --> 01:06:49,280
Speaker 1: like entertainment media, entertainment journalism. I guess I'll call it that.

1279
01:06:50,080 --> 01:06:54,200
Speaker 1: And so if he did buy Conde Nast, it would

1280
01:06:54,240 --> 01:06:56,320
Speaker 1: stand to reason that she could be the person like

1281
01:06:56,400 --> 01:06:58,640
Speaker 1: the new Anna Wintour running Vogue.

1282
01:06:58,680 --> 01:07:02,920
Speaker 2: God can you imagine? And entertainment journalism is like a

1283
01:07:03,080 --> 01:07:07,840
Speaker 2: cursed thing to have as some as two people who

1284
01:07:07,920 --> 01:07:11,600
Speaker 2: have delved into entertainment journalism, Joey, I don't know.

1285
01:07:11,680 --> 01:07:14,920
Speaker 1: If you let me tell you, I could tell we

1286
01:07:15,000 --> 01:07:17,440
Speaker 1: got I could tell you, I could tell you I

1287
01:07:17,520 --> 01:07:20,760
Speaker 1: actually brought up a story about a specific celebrity that

1288
01:07:20,840 --> 01:07:25,400
Speaker 1: I cross paths with in my time doing celebrity journalism

1289
01:07:25,600 --> 01:07:29,160
Speaker 1: and celebrity Now I'm trying to decide if I should

1290
01:07:29,240 --> 01:07:32,960
Speaker 1: cut it out of the episode. If folks are curious

1291
01:07:33,400 --> 01:07:36,000
Speaker 1: it's the episode, I guess I'll do a little bit

1292
01:07:36,040 --> 01:07:38,440
Speaker 1: of a plug. I'm talking to Ashley and Clair of

1293
01:07:38,480 --> 01:07:41,480
Speaker 1: the podcast Celebrity Memory Book Club in a recent episode,

1294
01:07:41,920 --> 01:07:44,680
Speaker 1: and there I tell a story about one specific celebrity

1295
01:07:44,760 --> 01:07:47,280
Speaker 1: who her antics almost cost.

1296
01:07:47,160 --> 01:07:47,680
Speaker 2: Me my job.

1297
01:07:48,280 --> 01:07:51,880
Speaker 1: She has fallen way out of public favor, like had

1298
01:07:51,920 --> 01:07:55,960
Speaker 1: a very very public downfall, And I'm wrestling with whether

1299
01:07:56,040 --> 01:07:57,680
Speaker 1: or not I should cut this anecdote out because I

1300
01:07:57,680 --> 01:07:59,040
Speaker 1: don't think I've ever shared it publicly.

1301
01:08:00,120 --> 01:08:01,720
Speaker 2: I will tell you who it is, off Mike.

1302
01:08:02,840 --> 01:08:08,240
Speaker 1: If folks want a hint, I will give one hint, Cucumber.

1303
01:08:09,480 --> 01:08:12,000
Speaker 2: If you know you know that is a that is

1304
01:08:12,080 --> 01:08:14,800
Speaker 2: a big hint, and I'll just leave it at that.

1305
01:08:15,840 --> 01:08:19,960
Speaker 1: So I do think that, like Laurence, the idea of

1306
01:08:20,360 --> 01:08:25,040
Speaker 1: Jeffrey Bezos buying Conde Nast and then bringing his wife

1307
01:08:25,160 --> 01:08:28,800
Speaker 1: Lauren Sanchez on as editor in chief of Vogue, it

1308
01:08:28,880 --> 01:08:31,400
Speaker 1: does kind of fit with this idea of them really

1309
01:08:31,520 --> 01:08:34,360
Speaker 1: trying to buy their way into a certain kind of

1310
01:08:34,479 --> 01:08:37,840
Speaker 1: class and status and influence. I think part of that

1311
01:08:38,040 --> 01:08:41,160
Speaker 1: whole space mission. He also set Lauren Sanchez addition to

1312
01:08:41,240 --> 01:08:44,519
Speaker 1: Katy Perry that you know ultimately was like not good.

1313
01:08:44,920 --> 01:08:46,439
Speaker 1: I think that they're trying. I think that he really

1314
01:08:46,520 --> 01:08:51,959
Speaker 1: wants to be like we are a dynamic, worldly, classy,

1315
01:08:52,280 --> 01:08:53,280
Speaker 1: influential couple.

1316
01:08:53,560 --> 01:08:55,879
Speaker 2: But like it doesn't matter how you could be a billionaire.

1317
01:08:55,880 --> 01:08:57,880
Speaker 1: You can't buy that, Like, you can't buy your way

1318
01:08:57,920 --> 01:09:01,280
Speaker 1: into people thinking that you're, you know, someone with depth

1319
01:09:01,479 --> 01:09:02,080
Speaker 1: and class.

1320
01:09:02,400 --> 01:09:04,679
Speaker 2: Wow, I cannot believe the show there Are No Girls

1321
01:09:04,720 --> 01:09:10,439
Speaker 2: on the Internet is taking down women for the all female.

1322
01:09:11,280 --> 01:09:12,000
Speaker 4: What what was it?

1323
01:09:12,080 --> 01:09:17,040
Speaker 2: It was like Blue Earth or something blue Origin, It's Origin,

1324
01:09:17,880 --> 01:09:21,439
Speaker 2: It's it is my Perry, it is my Roman Empire.

1325
01:09:21,960 --> 01:09:23,880
Speaker 1: Somebody I don't remember where I read this, but somebody

1326
01:09:24,000 --> 01:09:26,479
Speaker 1: was like, I want to see a deep style show

1327
01:09:26,640 --> 01:09:30,479
Speaker 1: where a Katie Perry figure is like has like fallen

1328
01:09:30,520 --> 01:09:33,080
Speaker 1: in public favor and she keeps trying to like do

1329
01:09:33,280 --> 01:09:35,240
Speaker 1: stunts to get back on everybody's good side, but they

1330
01:09:35,360 --> 01:09:37,719
Speaker 1: keep failing in more and more spectacular ways.

1331
01:09:37,800 --> 01:09:40,600
Speaker 2: I have watched that show. I watched that show we

1332
01:09:40,760 --> 01:09:43,680
Speaker 2: did it. It's a it's a woman's worlds and were

1333
01:09:43,880 --> 01:09:46,200
Speaker 2: whatever didn't work, so she was like, it's a it's

1334
01:09:46,200 --> 01:09:50,479
Speaker 2: a woman's universe, it's a woman's galaxy. It's a woman's galaxy.

1335
01:09:52,240 --> 01:09:55,080
Speaker 1: I also do think it's funny that, like all the

1336
01:09:55,200 --> 01:09:58,639
Speaker 1: celebrities that went to that wedding got sort of shamed

1337
01:09:58,680 --> 01:09:59,640
Speaker 1: and cloud for it.

1338
01:10:00,120 --> 01:10:01,519
Speaker 2: That was something where I was like, you know what,

1339
01:10:01,640 --> 01:10:05,000
Speaker 2: I have hope for humanity seeing all of the protests too,

1340
01:10:05,680 --> 01:10:08,000
Speaker 2: like shout out to the people of Venice, like you

1341
01:10:08,080 --> 01:10:11,800
Speaker 2: know what y'all showed up. Y'all also like pulled up

1342
01:10:11,880 --> 01:10:15,160
Speaker 2: talking about the real environmental impacts of all this, which yeah,

1343
01:10:15,200 --> 01:10:18,040
Speaker 2: like I mean, if if you know anything about Venice,

1344
01:10:18,200 --> 01:10:20,880
Speaker 2: it's sinking, like it is going to be like a

1345
01:10:21,040 --> 01:10:26,000
Speaker 2: soon casualty of climate change, and uh yeah no, Like

1346
01:10:26,240 --> 01:10:29,040
Speaker 2: good for the people of Venice for actually like being like,

1347
01:10:29,160 --> 01:10:31,519
Speaker 2: fuck these guys if they choose to do with a

1348
01:10:31,560 --> 01:10:33,000
Speaker 2: wedding here, like we're gonna make it miserable.

1349
01:10:33,160 --> 01:10:36,920
Speaker 1: Absolutely agree, I guess will end with friend of the

1350
01:10:37,000 --> 01:10:39,200
Speaker 1: show she's never been on but has an open invite.

1351
01:10:39,520 --> 01:10:42,719
Speaker 1: Luanne Della sets of Real Housewives of New York Countess

1352
01:10:42,800 --> 01:10:47,280
Speaker 1: Luanne money can't value class elegance has learned absolutely, Joey,

1353
01:10:47,400 --> 01:10:49,759
Speaker 1: this has been this. You're so fun to talk about

1354
01:10:50,760 --> 01:10:53,600
Speaker 1: like random internet stories with thank you. I I do

1355
01:10:53,720 --> 01:10:55,800
Speaker 1: spend a lot of time online, so me too.

1356
01:10:56,080 --> 01:10:56,280
Speaker 2: Yeah.

1357
01:10:56,439 --> 01:10:59,799
Speaker 1: Yeah, you're probably the only person that I think.

1358
01:10:59,800 --> 01:11:03,160
Speaker 2: Is as online as myself. And it's I really I

1359
01:11:03,240 --> 01:11:06,120
Speaker 2: appreciate it, Like I feel yeah, it's like I'm like

1360
01:11:06,200 --> 01:11:09,800
Speaker 2: somebody else gets the well we could do well one day,

1361
01:11:09,880 --> 01:11:12,000
Speaker 2: do like a panel of like the millennial gen Z

1362
01:11:13,240 --> 01:11:16,080
Speaker 2: find more people to do the Ooh, you know what's funny.

1363
01:11:17,040 --> 01:11:18,400
Speaker 2: You're you, you're gen Z.

1364
01:11:19,000 --> 01:11:22,080
Speaker 1: I am gen Z very online. I'm a millennial very

1365
01:11:22,160 --> 01:11:27,479
Speaker 1: online producer. Mike is gen X not online? Isn't that interesting?

1366
01:11:27,920 --> 01:11:28,440
Speaker 2: Interesting?

1367
01:11:28,840 --> 01:11:29,000
Speaker 4: You know?

1368
01:11:29,160 --> 01:11:31,800
Speaker 2: I think that really is. So maybe that should be

1369
01:11:31,960 --> 01:11:33,320
Speaker 2: we'll do an episode at one point and it'll be

1370
01:11:33,360 --> 01:11:35,760
Speaker 2: the two of us. Oh that's good. It'll be like

1371
01:11:35,800 --> 01:11:40,120
Speaker 2: a cross generational gen Z or gen Z to millennial

1372
01:11:40,240 --> 01:11:45,560
Speaker 2: to gen X trying to understand different uh internets.

1373
01:11:46,080 --> 01:11:48,080
Speaker 1: Like I'm always having picks the blame to Mike. Like

1374
01:11:48,160 --> 01:11:50,000
Speaker 1: the other day, I'm like, did you see this woman

1375
01:11:50,080 --> 01:11:52,679
Speaker 1: on TikTok model antipasto salad and the fourth of July

1376
01:11:52,800 --> 01:11:54,200
Speaker 1: cookade and they were so mean to her. And he

1377
01:11:54,240 --> 01:11:56,400
Speaker 1: will say like, well, I don't know what you're talking about.

1378
01:11:56,400 --> 01:11:58,479
Speaker 2: Who are these people? I had a I have like

1379
01:11:59,360 --> 01:12:03,000
Speaker 2: Boomer gen x cuss parents and my mom a message

1380
01:12:03,000 --> 01:12:04,840
Speaker 2: to me recently on Instagram with this like New York

1381
01:12:04,880 --> 01:12:07,640
Speaker 2: Times video that was talking about vertical content, and she

1382
01:12:07,800 --> 01:12:10,400
Speaker 2: was like what does this mean? What is vertical content?

1383
01:12:10,560 --> 01:12:12,960
Speaker 2: And I sent her like multiple voice because also I

1384
01:12:13,080 --> 01:12:15,080
Speaker 2: was like, this is the stuff that I love. Like

1385
01:12:15,160 --> 01:12:16,840
Speaker 2: I was like, this is the stuff I heard out about.

1386
01:12:16,880 --> 01:12:18,519
Speaker 2: Like I will totally I said her, like multiple voice

1387
01:12:18,560 --> 01:12:21,320
Speaker 2: bussage about it, and she was like, okay, yeah, I

1388
01:12:21,400 --> 01:12:23,360
Speaker 2: get it. Like whenever I was like I was like no,

1389
01:12:23,479 --> 01:12:24,680
Speaker 2: but I was like, you asked me like I was

1390
01:12:24,720 --> 01:12:26,479
Speaker 2: liking to anyways. But now that was a moment where

1391
01:12:26,479 --> 01:12:28,880
Speaker 2: I was like, Wow, I get to explain this to you.

1392
01:12:30,800 --> 01:12:33,280
Speaker 2: You're welcome love.

1393
01:12:33,200 --> 01:12:36,200
Speaker 1: Having to be the person who explains internet shit to

1394
01:12:36,280 --> 01:12:39,559
Speaker 1: people who think they want to know but maybe don't

1395
01:12:39,600 --> 01:12:42,479
Speaker 1: really want to know that like like all the meaty

1396
01:12:42,560 --> 01:12:44,800
Speaker 1: details that you and I would surely.

1397
01:12:44,640 --> 01:12:49,000
Speaker 2: Provide sentence answer. I'd meet the full breakdown of the

1398
01:12:49,320 --> 01:12:52,920
Speaker 2: socio political impacts of all this and uh, I think

1399
01:12:52,960 --> 01:12:54,519
Speaker 2: I just sent a whole thing to me, like, and

1400
01:12:54,640 --> 01:12:56,880
Speaker 2: this is how it's changing the way that movies are shot.

1401
01:12:56,920 --> 01:12:59,519
Speaker 2: And she was like, I was asking about how it's

1402
01:12:59,720 --> 01:13:01,960
Speaker 2: polical campaigns this stuff. I don't care.

1403
01:13:04,320 --> 01:13:08,720
Speaker 1: But uh, you know, Joey, where can folks keep up

1404
01:13:08,800 --> 01:13:11,080
Speaker 1: with all this cool shit that you are doing on

1405
01:13:11,240 --> 01:13:12,759
Speaker 1: our chronically online internet?

1406
01:13:13,479 --> 01:13:13,679
Speaker 3: Yeah?

1407
01:13:13,920 --> 01:13:15,760
Speaker 2: Well if yeah, if you want to find me a

1408
01:13:15,840 --> 01:13:18,160
Speaker 2: chronically online you can find me on Uh. I'm on

1409
01:13:18,320 --> 01:13:22,479
Speaker 2: Instagram at pat not prat. Also on Twitter slash x.

1410
01:13:23,160 --> 01:13:25,560
Speaker 2: I saw so many refer to it recently as like

1411
01:13:26,640 --> 01:13:28,600
Speaker 2: like Twitter, like that wrote it like with an X

1412
01:13:28,760 --> 01:13:32,120
Speaker 2: and like x I T. I don't even know how

1413
01:13:32,120 --> 01:13:35,240
Speaker 2: you'd pronounce that anyways, I hate it, but I'm still

1414
01:13:35,280 --> 01:13:37,200
Speaker 2: gonna call it Twitter. You could find me on Twitter

1415
01:13:37,360 --> 01:13:39,519
Speaker 2: or on Instagram at pat not prat. That's p A

1416
01:13:39,640 --> 01:13:41,600
Speaker 2: T t n O T p r A T T.

1417
01:13:44,680 --> 01:13:47,160
Speaker 2: You could also check out my other shows that I

1418
01:13:47,320 --> 01:13:51,120
Speaker 2: work on at Afterlives Season two is out now. It's

1419
01:13:51,120 --> 01:13:54,439
Speaker 2: all about marsh B. Johnson. And you can also check

1420
01:13:54,479 --> 01:13:58,519
Speaker 2: out Outlaws, which is another show on the Unspoken Network

1421
01:13:58,680 --> 01:14:04,240
Speaker 2: that is hosted by by the iconic ts Madison. Definitely

1422
01:14:04,520 --> 01:14:10,680
Speaker 2: some Housewives crossover at some point. But uh, you know,

1423
01:14:11,800 --> 01:14:13,840
Speaker 2: I've had to learn a lot about reality TV working

1424
01:14:13,920 --> 01:14:15,400
Speaker 2: on this show, which has been a big thing for me.

1425
01:14:15,640 --> 01:14:17,960
Speaker 1: But uh yeah, if you ever need a crash course,

1426
01:14:18,080 --> 01:14:21,400
Speaker 1: oh you know where to find me, absolutely first call.

1427
01:14:21,960 --> 01:14:23,760
Speaker 2: Well, thanks so much for listening, y'all, and I we

1428
01:14:23,800 --> 01:14:25,439
Speaker 2: will see you on the internet.

1429
01:14:31,840 --> 01:14:33,840
Speaker 1: Got a story about an interesting thing in tech, or

1430
01:14:33,960 --> 01:14:35,800
Speaker 1: just want to say hi, You can reach us at

1431
01:14:35,800 --> 01:14:38,519
Speaker 1: Hello at tangodi dot com. You can also find transcripts

1432
01:14:38,560 --> 01:14:41,000
Speaker 1: for today's episode at tengody dot com. There Are No

1433
01:14:41,080 --> 01:14:42,479
Speaker 1: Girls on the Internet was created by me.

1434
01:14:42,600 --> 01:14:43,120
Speaker 4: Bridget Toad.

1435
01:14:43,520 --> 01:14:46,960
Speaker 1: It's a production of iHeartRadio, an unbossed creative. Jonathan Strickland

1436
01:14:47,000 --> 01:14:49,680
Speaker 1: is our executive producer. Tari Harrison is our producer and

1437
01:14:49,760 --> 01:14:53,479
Speaker 1: sound engineer. Michael Almado is our contributing producer. I'm your host,

1438
01:14:53,560 --> 01:14:56,320
Speaker 1: bridget Toad. If you want to help us grow, rate

1439
01:14:56,360 --> 01:14:59,959
Speaker 1: and review us on Apple Podcasts. For more podcasts from iHeartRadio,

1440
01:15:00,240 --> 01:15:02,519
Speaker 1: check out the iHeartRadio app, Apple Podcasts, or wherever you

1441
01:15:02,600 --> 01:15:03,439
Speaker 1: get your podcasts.