1
00:00:04,400 --> 00:00:06,120
Speaker 1: There Are No Girls on the Internet. As a production

2
00:00:06,160 --> 00:00:13,680
Speaker 1: of iHeartRadio and Unbossed Creative. I'm Bridget Todd, and this

3
00:00:13,760 --> 00:00:15,120
Speaker 1: is there Are No Girls on the Internet.

4
00:00:17,720 --> 00:00:18,040
Speaker 2: Joey.

5
00:00:18,160 --> 00:00:20,040
Speaker 1: Thank you so much for being here. It has been

6
00:00:20,640 --> 00:00:25,119
Speaker 1: a whirlwind week. Honestly, there are not many people that

7
00:00:25,200 --> 00:00:28,640
Speaker 1: I would rather get into all of this with than you.

8
00:00:28,760 --> 00:00:32,000
Speaker 1: I feel like you really bring such an expertise and

9
00:00:32,440 --> 00:00:35,959
Speaker 1: a put together background that I really appreciate. So I'm

10
00:00:36,840 --> 00:00:40,360
Speaker 1: kind of as hard as things have been, I feel

11
00:00:40,520 --> 00:00:44,440
Speaker 1: grateful that I get to help understand, help myself understand

12
00:00:44,440 --> 00:00:45,640
Speaker 1: what's going on with you.

13
00:00:46,440 --> 00:00:49,520
Speaker 3: Thank you, Bridget. It's been a week.

14
00:00:49,640 --> 00:00:54,720
Speaker 4: It's been a wild two weeks. And you know, we

15
00:00:54,800 --> 00:00:56,520
Speaker 4: talked a bit before this recording, and.

16
00:00:58,120 --> 00:00:59,880
Speaker 3: It is it is rough. It is rough.

17
00:01:00,800 --> 00:01:07,959
Speaker 4: We are witnessing horrific events on a daily basis just

18
00:01:08,040 --> 00:01:11,800
Speaker 4: through our phones and having to grapple with that and

19
00:01:11,840 --> 00:01:16,320
Speaker 4: grapple with you know, a lot of very I hate

20
00:01:16,360 --> 00:01:19,039
Speaker 4: calling it complicated political realities because I feel like calling

21
00:01:19,120 --> 00:01:21,440
Speaker 4: it complicated quote unquote has been used a lot to

22
00:01:21,560 --> 00:01:24,399
Speaker 4: kind of divert attention away from the issue, but also yes,

23
00:01:24,600 --> 00:01:29,440
Speaker 4: very common and a lot of very complicated and at

24
00:01:29,440 --> 00:01:32,679
Speaker 4: the same time, very real and very horrific realities for

25
00:01:34,080 --> 00:01:38,720
Speaker 4: you know, people living in Gaza and living in Israel Palestine.

26
00:01:39,280 --> 00:01:44,120
Speaker 4: I think I've talked before on this podcast. I am Jewish.

27
00:01:44,319 --> 00:01:48,200
Speaker 4: I anti Zionism is a fundamental part of my Jewish identity.

28
00:01:48,800 --> 00:01:51,880
Speaker 4: What is happening to the Palestinian people right now is horrifying.

29
00:01:51,880 --> 00:01:56,440
Speaker 4: What has been happening is horrifying, and I you know,

30
00:01:56,600 --> 00:01:59,720
Speaker 4: I think just trying to sift through all of the

31
00:01:59,720 --> 00:02:03,440
Speaker 4: inform that we're being presented with is a lot.

32
00:02:03,520 --> 00:02:04,880
Speaker 3: It is a lot to go through.

33
00:02:04,920 --> 00:02:07,160
Speaker 4: I think like our brains were not meant to have

34
00:02:07,200 --> 00:02:09,320
Speaker 4: to deal with that amount of information on the daily.

35
00:02:10,520 --> 00:02:12,720
Speaker 3: That being said, you know, I.

36
00:02:12,639 --> 00:02:17,280
Speaker 4: Really I hope that somehow further deaths in destruction can

37
00:02:17,320 --> 00:02:23,320
Speaker 4: be preventable. And there's a lot of terrible, terrifying possibilities

38
00:02:23,360 --> 00:02:26,239
Speaker 4: that are I think, on the horizon, and we're just

39
00:02:26,280 --> 00:02:28,400
Speaker 4: gonna have to keep fighting and keep fighting for a

40
00:02:28,440 --> 00:02:29,040
Speaker 4: better future.

41
00:02:29,680 --> 00:02:33,839
Speaker 1: Yeah, we are in I mean, I feel the same

42
00:02:33,880 --> 00:02:41,120
Speaker 1: way when the conflict first, like last week, I thought,

43
00:02:41,600 --> 00:02:44,920
Speaker 1: I mean I was in a I don't know, I

44
00:02:44,919 --> 00:02:48,720
Speaker 1: found myself going to a dark place last week personally

45
00:02:48,960 --> 00:02:51,640
Speaker 1: when I was everything was unfolding, and it was still

46
00:02:51,680 --> 00:02:53,919
Speaker 1: still felt very kind of fresh and new. And I

47
00:02:55,240 --> 00:02:57,519
Speaker 1: generally kind of think of myself as somebody who was

48
00:02:57,639 --> 00:03:02,720
Speaker 1: very optimistic, who really, you know, often leans toward things

49
00:03:02,720 --> 00:03:05,960
Speaker 1: will work out, things will be okay. People are fundamentally good,

50
00:03:06,000 --> 00:03:09,440
Speaker 1: people fundamentally want to be united and together. That's not

51
00:03:09,480 --> 00:03:13,800
Speaker 1: always the case, but that's like my core alignment. And

52
00:03:13,960 --> 00:03:18,160
Speaker 1: last week I was just like, yeah, not in a

53
00:03:18,280 --> 00:03:24,160
Speaker 1: great place. I really was afraid because I sensed very

54
00:03:24,200 --> 00:03:26,640
Speaker 1: deeply that we were going to see more destruction and

55
00:03:26,680 --> 00:03:29,160
Speaker 1: more deaths and more harm, which we definitely have seen.

56
00:03:29,480 --> 00:03:32,240
Speaker 2: And you know, I wanted to.

57
00:03:32,200 --> 00:03:34,800
Speaker 1: Really focus on what I know that I can bring

58
00:03:34,840 --> 00:03:37,920
Speaker 1: to the table in moments of chaos and terror and anxiety.

59
00:03:38,080 --> 00:03:41,560
Speaker 1: And I have like deep expertise when it comes to

60
00:03:41,600 --> 00:03:44,240
Speaker 1: social media platforms and technology, and so the episode that

61
00:03:44,280 --> 00:03:48,160
Speaker 1: we made last week was really kind of narrow in

62
00:03:48,320 --> 00:03:54,200
Speaker 1: focus around the ways that I see Twitter really making

63
00:03:54,400 --> 00:03:58,440
Speaker 1: a tough, scary time worse because people don't know what's

64
00:03:58,480 --> 00:04:02,240
Speaker 1: going on. People are here, people are understandably confused and

65
00:04:02,240 --> 00:04:05,080
Speaker 1: are afraid and trying to find out information, and the

66
00:04:05,480 --> 00:04:08,520
Speaker 1: platform just like doesn't allow for that. So folks, we

67
00:04:08,560 --> 00:04:11,320
Speaker 1: have heard our episode last week that really broke that down,

68
00:04:12,560 --> 00:04:15,240
Speaker 1: and I think that one of the reasons why the

69
00:04:15,280 --> 00:04:19,160
Speaker 1: state of Twitter was amplifying a lot of the feelings

70
00:04:19,160 --> 00:04:22,359
Speaker 1: I was personally having was that I have sort of

71
00:04:22,520 --> 00:04:26,560
Speaker 1: known Twitter historically to be a platform that can, in

72
00:04:26,920 --> 00:04:31,000
Speaker 1: times of crisis, help people get information. If you're on

73
00:04:31,040 --> 00:04:33,640
Speaker 1: the ground, here's what you need to know, Here's where

74
00:04:33,640 --> 00:04:35,240
Speaker 1: you need to go if you need X, y Z.

75
00:04:35,800 --> 00:04:37,720
Speaker 1: If you're not on the ground, you're just following it.

76
00:04:38,000 --> 00:04:40,960
Speaker 1: Here's the best information. Here's information, here's here's voices that

77
00:04:41,000 --> 00:04:43,480
Speaker 1: are experiencing this on the ground. I have always known

78
00:04:43,520 --> 00:04:46,640
Speaker 1: it to be a platform that helped me feel more

79
00:04:46,640 --> 00:04:50,320
Speaker 1: informed and thus less afraid and less confused.

80
00:04:51,720 --> 00:04:52,760
Speaker 2: Unless reactionary.

81
00:04:53,680 --> 00:04:55,279
Speaker 1: Again, I will be the first person to tell you

82
00:04:55,279 --> 00:04:58,239
Speaker 1: that Twitter has never been perfect, So like I could

83
00:04:58,360 --> 00:05:01,080
Speaker 1: go on as long of a rant about it's problems,

84
00:05:01,120 --> 00:05:04,720
Speaker 1: even in the pre elon Musk Days, but Twitter was

85
00:05:04,760 --> 00:05:08,640
Speaker 1: always something that helped me get information that felt timely

86
00:05:08,760 --> 00:05:12,080
Speaker 1: and accurate and thus helped me feel kind of like

87
00:05:12,160 --> 00:05:14,880
Speaker 1: more in control. And when I went to Twitter to

88
00:05:14,960 --> 00:05:19,080
Speaker 1: sort of do what I recognized as like how I

89
00:05:19,160 --> 00:05:22,280
Speaker 1: try to cope when things are stressful and hard, and

90
00:05:22,320 --> 00:05:28,320
Speaker 1: this got more lies, more inflammatory content, more like really

91
00:05:29,160 --> 00:05:33,640
Speaker 1: emotionally charged content. Like I was riled up, and I'm

92
00:05:33,640 --> 00:05:35,520
Speaker 1: not somebody who I think of as like easy to

93
00:05:35,600 --> 00:05:37,080
Speaker 1: rile up from online content.

94
00:05:37,440 --> 00:05:38,520
Speaker 2: My heart was racing.

95
00:05:38,600 --> 00:05:41,560
Speaker 1: I was seeing images, of course, none of which prevetted

96
00:05:42,000 --> 00:05:45,520
Speaker 1: of things that really were causing a deep emotional response

97
00:05:45,520 --> 00:05:49,960
Speaker 1: in me, and it just really rattled me. It signaled

98
00:05:50,080 --> 00:05:53,919
Speaker 1: to me that we have reached a new low in

99
00:05:54,040 --> 00:05:58,440
Speaker 1: our digital landscape. I still feel that way. I still

100
00:05:58,480 --> 00:06:02,599
Speaker 1: feel like things are better, and I'm very concerned about

101
00:06:02,680 --> 00:06:06,840
Speaker 1: how much worse things can get. And going back to

102
00:06:06,880 --> 00:06:11,080
Speaker 1: this conversation a week later, I think the thing that

103
00:06:11,120 --> 00:06:18,320
Speaker 1: really upset me the most is how on social media,

104
00:06:18,360 --> 00:06:21,240
Speaker 1: but Twitter, particularly how easy it is to boil things

105
00:06:21,279 --> 00:06:23,800
Speaker 1: down to like you're talking about a football game, like teams,

106
00:06:23,920 --> 00:06:26,680
Speaker 1: like oh the other side, this side, that side. It

107
00:06:26,760 --> 00:06:34,200
Speaker 1: really creates this just not useful equivalency. And also we're

108
00:06:34,200 --> 00:06:37,520
Speaker 1: talking about people's lives and people like real humans lives,

109
00:06:37,560 --> 00:06:40,440
Speaker 1: and like the way that it lends itself to boiling

110
00:06:40,480 --> 00:06:44,479
Speaker 1: it down to talking about teams in this very crass way,

111
00:06:44,520 --> 00:06:46,920
Speaker 1: it just really did not fill me with good feelings

112
00:06:46,960 --> 00:06:47,720
Speaker 1: I'll put it that way.

113
00:06:48,520 --> 00:06:51,440
Speaker 3: It is sort of it's like almost surreal.

114
00:06:51,760 --> 00:06:56,480
Speaker 4: I A, yes, the fact that these are people's lives,

115
00:06:56,520 --> 00:07:00,200
Speaker 4: these are people being killed, these are your children and

116
00:07:00,360 --> 00:07:01,320
Speaker 4: being killed.

117
00:07:01,160 --> 00:07:02,960
Speaker 2: And just.

118
00:07:04,480 --> 00:07:07,120
Speaker 4: The way I talked about this a bit before when

119
00:07:07,160 --> 00:07:11,600
Speaker 4: we were off mic. But again, I feel like, as

120
00:07:11,680 --> 00:07:18,600
Speaker 4: I said, I'm Jewish, i am very staunchly an anti Zionist.

121
00:07:19,360 --> 00:07:21,320
Speaker 4: I feel like I've spent a lot of my time

122
00:07:21,440 --> 00:07:24,080
Speaker 4: the past week just trying to explain semantics to people

123
00:07:24,520 --> 00:07:29,880
Speaker 4: and trying to explain why Zionism is a political ideology

124
00:07:30,080 --> 00:07:34,160
Speaker 4: is not the same thing as Judaism is a diverse,

125
00:07:35,440 --> 00:07:39,200
Speaker 4: you know, cultural and religious identity.

126
00:07:39,760 --> 00:07:42,400
Speaker 3: And there is a part of me that just feels

127
00:07:42,440 --> 00:07:44,840
Speaker 3: so heartbroken.

128
00:07:44,320 --> 00:07:45,880
Speaker 4: That this is what I have to focus on, this

129
00:07:45,920 --> 00:07:47,080
Speaker 4: is what I have to spend so much of my

130
00:07:47,120 --> 00:07:49,880
Speaker 4: time and energy focusing on, when again, yeah, there are

131
00:07:49,920 --> 00:07:57,840
Speaker 4: people dying, there's actual human rights catastrophes happening. And I

132
00:07:57,880 --> 00:08:02,200
Speaker 4: will say this is an issue where there already has

133
00:08:02,320 --> 00:08:06,520
Speaker 4: been just sort of this stream of misinformation and propaganda

134
00:08:07,080 --> 00:08:09,800
Speaker 4: that has been difficult.

135
00:08:09,360 --> 00:08:09,880
Speaker 3: To sit through.

136
00:08:09,880 --> 00:08:13,120
Speaker 4: That has been difficult to sit through as somebody who

137
00:08:13,240 --> 00:08:17,560
Speaker 4: is somewhat connected to this conflict. I'm sure, and I'm

138
00:08:17,680 --> 00:08:20,880
Speaker 4: sure people that have no sort of background in it

139
00:08:20,880 --> 00:08:23,640
Speaker 4: it is even worse, and it is it's hard. It

140
00:08:23,720 --> 00:08:26,520
Speaker 4: is at this again. It has been a really heavy

141
00:08:26,760 --> 00:08:31,960
Speaker 4: last two weeks. What is happening in Gaza is horrifying.

142
00:08:32,640 --> 00:08:33,559
Speaker 3: And my.

143
00:08:35,040 --> 00:08:39,440
Speaker 4: Thoughts and are with the people on the ground there,

144
00:08:40,040 --> 00:08:44,079
Speaker 4: solidarity with the Palaestinam people. And it is crazy that

145
00:08:44,160 --> 00:08:45,920
Speaker 4: we are back to a point where, like I feel

146
00:08:45,960 --> 00:08:50,920
Speaker 4: like just the dehumanization of people has gotten so so intense,

147
00:08:51,000 --> 00:08:54,920
Speaker 4: and so in saying that it is it's really hard.

148
00:08:54,960 --> 00:08:56,560
Speaker 4: It is really hard to work through and it is

149
00:08:56,600 --> 00:09:00,880
Speaker 4: really hard to even as I said here, you know,

150
00:09:01,360 --> 00:09:04,280
Speaker 4: I am in the US, I am We're or less

151
00:09:04,280 --> 00:09:07,400
Speaker 4: safe right now. I'm not in any immediate danger and

152
00:09:07,640 --> 00:09:10,520
Speaker 4: that feels exhausting. I can't fucking imagine what it's got

153
00:09:10,559 --> 00:09:12,360
Speaker 4: to be like for people that are there, people that

154
00:09:12,440 --> 00:09:17,800
Speaker 4: have family there, a Israeli or Palestinian. Again, any loss

155
00:09:17,800 --> 00:09:20,800
Speaker 4: of human life is terrible and tragic, and.

156
00:09:22,160 --> 00:09:25,000
Speaker 3: It's yeah, it's it's been a lot.

157
00:09:25,400 --> 00:09:27,560
Speaker 1: Yeah, and we were talking about this off mic before

158
00:09:27,559 --> 00:09:34,680
Speaker 1: you were recording, But like the feeling of not necessarily

159
00:09:34,760 --> 00:09:40,600
Speaker 1: feeling like it's okay, to speak up in certain ways

160
00:09:40,800 --> 00:09:43,560
Speaker 1: I think is really hard. I think it creates a

161
00:09:43,600 --> 00:09:49,240
Speaker 1: climate where it's really hard to process and really hard

162
00:09:49,240 --> 00:09:51,839
Speaker 1: to like you know even.

163
00:09:51,640 --> 00:09:55,280
Speaker 4: More, Yeah, it really, I mean I keep thinking about

164
00:09:55,320 --> 00:10:00,319
Speaker 4: there have already been like a number of Jewish protestersicular

165
00:10:00,400 --> 00:10:05,040
Speaker 4: who have been arrested for speaking out against the US

166
00:10:05,120 --> 00:10:08,600
Speaker 4: to support the military support of Israel, or spooking out

167
00:10:08,840 --> 00:10:12,000
Speaker 4: or speaking in support of a ceasefire, have been protesting.

168
00:10:12,880 --> 00:10:16,559
Speaker 4: A number of these people are children of Holocaust survivors,

169
00:10:16,720 --> 00:10:21,000
Speaker 4: are have people in their family that directly experienced genocide

170
00:10:21,040 --> 00:10:25,320
Speaker 4: and directly directly experienced ethnic cleansing and everything that comes

171
00:10:25,360 --> 00:10:30,040
Speaker 4: along with that. And it's it is so messed up

172
00:10:30,080 --> 00:10:32,640
Speaker 4: that even talking about this now, like I feel nervous.

173
00:10:32,760 --> 00:10:36,679
Speaker 4: I'll be honest, Like I have almost been docked a

174
00:10:36,679 --> 00:10:39,360
Speaker 4: couple times. I have very good friends that have been

175
00:10:39,440 --> 00:10:43,480
Speaker 4: docks simply for saying like the mildest things in support

176
00:10:43,640 --> 00:10:48,720
Speaker 4: of Palaciti and human rights, mildest criticism of the Israeli government.

177
00:10:49,520 --> 00:10:52,000
Speaker 4: And that's not okay, That's not okay in any situation.

178
00:10:52,760 --> 00:10:56,559
Speaker 3: But yeah, it is. It is. It's a lot to process,

179
00:10:56,600 --> 00:11:00,320
Speaker 3: and it does a lot to a feel.

180
00:11:02,000 --> 00:11:04,200
Speaker 4: For people that sort of don't have any background in

181
00:11:04,240 --> 00:11:07,640
Speaker 4: this and don't have any understanding of what is happening

182
00:11:07,720 --> 00:11:09,640
Speaker 4: and are trying to learn it now. It is hard

183
00:11:09,679 --> 00:11:11,920
Speaker 4: to sift through that information that's being presented to you

184
00:11:12,000 --> 00:11:17,440
Speaker 4: and sift through disinformation, but then also feeling like you

185
00:11:17,480 --> 00:11:20,720
Speaker 4: can't say anything, You can't speak out in support of

186
00:11:21,240 --> 00:11:24,760
Speaker 4: things that are obviously wrong, things that are obviously crimes

187
00:11:24,760 --> 00:11:28,800
Speaker 4: against humanity without fearing for your own safety and your

188
00:11:28,800 --> 00:11:38,280
Speaker 4: own sort of reputation. In the most basic sense, it's scary,

189
00:11:38,440 --> 00:11:41,720
Speaker 4: and it's I really just wish people would not lose

190
00:11:41,720 --> 00:11:44,679
Speaker 4: sight of the fact that there are people in immediate

191
00:11:44,720 --> 00:11:48,480
Speaker 4: danger right now. There are people already who have been

192
00:11:48,640 --> 00:11:52,040
Speaker 4: killed and whose lives are already.

193
00:11:53,520 --> 00:11:55,400
Speaker 3: Again, I think just the fact that.

194
00:11:56,840 --> 00:12:02,160
Speaker 4: We're witnessing such horrific events unfolding, and the thing that

195
00:12:02,960 --> 00:12:06,360
Speaker 4: the fact that semantics and the fact that going over

196
00:12:06,520 --> 00:12:08,440
Speaker 4: like how to talk about this and how to talk

197
00:12:08,440 --> 00:12:10,080
Speaker 4: about this in a way that is not going to

198
00:12:10,080 --> 00:12:16,160
Speaker 4: get you immediately doxed by bad actors. That's a lot,

199
00:12:16,360 --> 00:12:20,160
Speaker 4: and that is that is only kind of making the

200
00:12:20,200 --> 00:12:24,760
Speaker 4: conversation around this more hostile and is only going to

201
00:12:24,920 --> 00:12:28,320
Speaker 4: lead to more death and more destruction exactly.

202
00:12:28,400 --> 00:12:30,600
Speaker 1: It really reminds me, you know, I'm a little older

203
00:12:30,600 --> 00:12:33,040
Speaker 1: than you, and it reminds me so much of the

204
00:12:33,280 --> 00:12:35,600
Speaker 1: aftermath of nine to eleven, which was like really my

205
00:12:35,720 --> 00:12:38,400
Speaker 1: kind of like political and social awakening, and that was

206
00:12:38,400 --> 00:12:41,559
Speaker 1: like when I got more seriously involved in, like the

207
00:12:41,600 --> 00:12:43,880
Speaker 1: anti war movement was like the thing that got me,

208
00:12:44,400 --> 00:12:46,400
Speaker 1: woke me up in terms of like my own political

209
00:12:46,480 --> 00:12:49,840
Speaker 1: understanding of the world. And there was a climate that,

210
00:12:49,960 --> 00:12:52,959
Speaker 1: like the climate of like you're for us, or you're

211
00:12:53,360 --> 00:12:56,400
Speaker 1: with us or against us. You're either with us or

212
00:12:56,400 --> 00:12:59,760
Speaker 1: you're a terrorist. And I think that's that's I'm seeing

213
00:13:00,120 --> 00:13:04,360
Speaker 1: goes of that climate now, you know. And last week

214
00:13:04,400 --> 00:13:06,760
Speaker 1: we were talking about Twitter, but it's important to remember

215
00:13:06,800 --> 00:13:09,920
Speaker 1: that Twitter is only one piece of our larger media ecosystem,

216
00:13:10,080 --> 00:13:12,720
Speaker 1: and was a pretty big scoop from four fur Media,

217
00:13:12,760 --> 00:13:16,080
Speaker 1: which is a journalist run tech media outlet, about how

218
00:13:16,120 --> 00:13:19,880
Speaker 1: things are playing out on Instagram. People on Instagram found

219
00:13:19,960 --> 00:13:24,400
Speaker 1: that the platform was auto translating their user bios that

220
00:13:24,520 --> 00:13:28,480
Speaker 1: included the word Palestinian and an airbrick phrase that means

221
00:13:28,520 --> 00:13:31,680
Speaker 1: praise be to God. Instagram was auto translating this to

222
00:13:31,720 --> 00:13:36,000
Speaker 1: say Palestinian terrorists are fighting for their freedom. So if

223
00:13:36,000 --> 00:13:39,720
Speaker 1: you had this perfectly innocuous phrase in your Instagram bio

224
00:13:39,920 --> 00:13:44,080
Speaker 1: Instagram is basically telling the world via translation that you

225
00:13:44,080 --> 00:13:45,400
Speaker 1: are a terrorist sympathizer.

226
00:13:45,840 --> 00:13:48,400
Speaker 4: Yeah, it's interesting you brought up nine to eleven, and

227
00:13:48,440 --> 00:13:51,480
Speaker 4: I guess you said, I'm I don't regress all for

228
00:13:51,480 --> 00:13:53,840
Speaker 4: how y'all got a I grew up in the aftermath

229
00:13:53,880 --> 00:13:56,480
Speaker 4: of nine to eleven, Like I was two when nine

230
00:13:56,520 --> 00:13:59,520
Speaker 4: to eleven happened, but I really like came of age

231
00:13:59,679 --> 00:14:02,400
Speaker 4: in that era of just very like I was a

232
00:14:02,480 --> 00:14:06,600
Speaker 4: child when Islamophobia and all of this racism and xenophobia

233
00:14:06,760 --> 00:14:09,640
Speaker 4: was at its height, and I think my teen years

234
00:14:09,640 --> 00:14:11,640
Speaker 4: were really the time when we were starting to unpack

235
00:14:11,720 --> 00:14:13,360
Speaker 4: that and starting to be like, hey.

236
00:14:13,920 --> 00:14:15,440
Speaker 3: Maybe a lot of this was bad.

237
00:14:15,520 --> 00:14:18,480
Speaker 4: Maybe we shouldn't have just jumped to very black and

238
00:14:18,520 --> 00:14:22,400
Speaker 4: white images like views of the world, and especially I

239
00:14:22,400 --> 00:14:25,320
Speaker 4: mean the word terrorists, Like you cannot take that word

240
00:14:26,080 --> 00:14:28,920
Speaker 4: out of the connotation that it has in the US

241
00:14:28,920 --> 00:14:33,040
Speaker 4: and the connotation that it has these past couple of decades,

242
00:14:35,360 --> 00:14:40,000
Speaker 4: And it is so strange to be seeing so much

243
00:14:40,040 --> 00:14:43,080
Speaker 4: of that kind of be recirculated and the way that

244
00:14:43,080 --> 00:14:47,400
Speaker 4: those terms are kind of used to. It is weird

245
00:14:47,440 --> 00:14:53,280
Speaker 4: to see that kind of that level of xenophobia returning

246
00:14:53,320 --> 00:14:55,880
Speaker 4: and almost the same exact patterns.

247
00:14:56,520 --> 00:14:59,880
Speaker 1: That's so, that's exactly, That's exactly how I feel that,

248
00:15:00,080 --> 00:15:04,520
Speaker 1: like we maybe didn't learn a lot from that era,

249
00:15:05,280 --> 00:15:10,560
Speaker 1: you know, we I wish we had. I was so

250
00:15:10,800 --> 00:15:12,720
Speaker 1: young and I thought we were gonna stop the war.

251
00:15:12,960 --> 00:15:15,880
Speaker 1: We were part Like if you were part of the

252
00:15:15,920 --> 00:15:19,400
Speaker 1: anti war movement after nine to eleven, you were part

253
00:15:19,440 --> 00:15:23,920
Speaker 1: of a historic, like the biggest anti war protest of

254
00:15:23,960 --> 00:15:26,920
Speaker 1: all time in the United States, Like I thought, like

255
00:15:27,680 --> 00:15:30,760
Speaker 1: it felt big and now here I am. However, many

256
00:15:30,840 --> 00:15:33,200
Speaker 1: years later, and it's like, did we really learn a lot?

257
00:15:33,200 --> 00:15:35,680
Speaker 1: Because it's like we're having these same conversations, and like,

258
00:15:36,280 --> 00:15:39,400
Speaker 1: back then, we did not have the level of like

259
00:15:40,240 --> 00:15:43,720
Speaker 1: tech like it wasn't We didn't have the tech infrastructure

260
00:15:43,920 --> 00:15:47,880
Speaker 1: to enable those conversations, to pour gasoline on those conversations,

261
00:15:47,960 --> 00:15:51,880
Speaker 1: to make platforms, and people who were financially invested in

262
00:15:51,960 --> 00:15:55,880
Speaker 1: those conversations being as inflamed and hostile as possible.

263
00:15:55,920 --> 00:15:58,320
Speaker 2: We didn't have that to the level that we haven't now, And.

264
00:15:58,280 --> 00:15:59,880
Speaker 1: So it almost feels like it's like, yeah, it's like

265
00:15:59,880 --> 00:16:02,360
Speaker 1: the same thing, but worse in some ways, which I

266
00:16:02,360 --> 00:16:07,840
Speaker 1: hate to say. So after Instagram was called out by

267
00:16:07,880 --> 00:16:12,400
Speaker 1: four oh for Media for sneaking terrorist sympathizer in like

268
00:16:12,520 --> 00:16:16,400
Speaker 1: language into this translation on Instagram bios, they I will say,

269
00:16:16,400 --> 00:16:18,240
Speaker 1: to their credit, they copped to it right away. They said,

270
00:16:18,480 --> 00:16:22,880
Speaker 1: we fixed a problem that briefly caused inappropriate Arabic translations

271
00:16:22,880 --> 00:16:26,760
Speaker 1: and some of our products. We sincerely apologized that this happened,

272
00:16:27,080 --> 00:16:29,440
Speaker 1: but they didn't explain how it happened. Like it's a

273
00:16:29,480 --> 00:16:33,280
Speaker 1: pretty like a telling translation, and I think it really

274
00:16:33,320 --> 00:16:36,680
Speaker 1: reveals some of the problems and the ways that like

275
00:16:37,360 --> 00:16:42,000
Speaker 1: big tech companies in a way that wasn't the case

276
00:16:42,160 --> 00:16:47,200
Speaker 1: right after nine to eleven, big tech companies really have

277
00:16:47,480 --> 00:16:52,160
Speaker 1: the power to shape a lot of the discourse around

278
00:16:52,600 --> 00:16:54,480
Speaker 1: what's happening with this conflict.

279
00:16:54,600 --> 00:16:55,560
Speaker 2: Like they really just have.

280
00:16:56,240 --> 00:16:58,640
Speaker 1: So like we've we've put a lot of trust in them,

281
00:16:58,880 --> 00:17:01,080
Speaker 1: and I would argue that these people, these they're not

282
00:17:01,120 --> 00:17:03,680
Speaker 1: always trustworthy actors, and so it's like, oh wow, like

283
00:17:04,240 --> 00:17:05,400
Speaker 1: this is really a problem.

284
00:17:05,760 --> 00:17:08,880
Speaker 4: Yeah, and that is really interesting. You were talking about

285
00:17:08,920 --> 00:17:11,440
Speaker 4: Twitter at the top and I Instagram. I do feel

286
00:17:11,440 --> 00:17:13,879
Speaker 4: like a lot of this has migrated over to Instagram,

287
00:17:13,920 --> 00:17:20,159
Speaker 4: and you know, hearing that Instagram is maybe not to

288
00:17:20,200 --> 00:17:22,000
Speaker 4: the same extent as Twitter, but it's falling into the

289
00:17:22,000 --> 00:17:26,800
Speaker 4: same sort of traps and misinformation and you know, mistranslating

290
00:17:26,880 --> 00:17:34,040
Speaker 4: things or prioritizing certain information about others. It really is

291
00:17:34,080 --> 00:17:36,919
Speaker 4: like a systemic problem that is not unique to Twitter

292
00:17:36,960 --> 00:17:39,199
Speaker 4: and is not unique to Elon Musk. It is a

293
00:17:39,280 --> 00:17:41,919
Speaker 4: problem of how we talk about these issues and how

294
00:17:41,960 --> 00:17:43,000
Speaker 4: we consume information.

295
00:17:43,840 --> 00:17:50,119
Speaker 3: And yeah, it's it's bad. It's yeah, yeah, Twitter.

296
00:17:50,280 --> 00:17:53,320
Speaker 1: So like I won't stop beating the drama about how

297
00:17:53,359 --> 00:17:55,479
Speaker 1: bad Twitter is because it's like it seems like Twitter

298
00:17:55,560 --> 00:17:57,520
Speaker 1: is like we are intentionally trying to be bad, Like

299
00:17:57,560 --> 00:18:00,199
Speaker 1: we want people to be confused and like they're to

300
00:18:00,200 --> 00:18:01,359
Speaker 1: be chaos.

301
00:18:01,200 --> 00:18:03,320
Speaker 2: Enjoy the show. I genuinely believe that.

302
00:18:03,400 --> 00:18:07,080
Speaker 1: Is Elon Musk's orientation, that it's like, yeah, even if

303
00:18:07,119 --> 00:18:09,159
Speaker 1: it's a shit show, you're paying attention, you know.

304
00:18:10,200 --> 00:18:14,600
Speaker 2: So. But Instagram, I think is unique.

305
00:18:15,280 --> 00:18:17,639
Speaker 1: This is I'm like totally going off script here, but

306
00:18:17,720 --> 00:18:21,800
Speaker 1: like Instagram to me is unique in that there's something

307
00:18:21,840 --> 00:18:27,720
Speaker 1: about the format of like a Canva created carousel like

308
00:18:27,880 --> 00:18:31,680
Speaker 1: graphic with text on it, and I make them too,

309
00:18:31,760 --> 00:18:35,080
Speaker 1: Like I'm not, but like they're just so easy for

310
00:18:35,160 --> 00:18:37,439
Speaker 1: anybody to make. If you have like I have Canva

311
00:18:37,520 --> 00:18:40,840
Speaker 1: pro I've thrown together an infographic and a carousel in

312
00:18:40,880 --> 00:18:43,119
Speaker 1: my day or two. But it's so easy for anybody

313
00:18:43,200 --> 00:18:45,639
Speaker 1: to make them. And there's something about them that I

314
00:18:45,640 --> 00:18:48,200
Speaker 1: think give a sheene of trustworthiness because it's like, oh,

315
00:18:48,400 --> 00:18:50,560
Speaker 1: who would take the time to make this carousel full

316
00:18:50,560 --> 00:18:53,760
Speaker 1: of information and words if they hadn't like that checked

317
00:18:53,800 --> 00:18:56,520
Speaker 1: it or if it wasn't true, And they're just so

318
00:18:56,640 --> 00:18:57,920
Speaker 1: easy to share on Instagram.

319
00:18:57,960 --> 00:19:00,080
Speaker 2: It is so easy. And I also think that like

320
00:19:00,720 --> 00:19:01,520
Speaker 2: Instagram is.

321
00:19:01,480 --> 00:19:04,320
Speaker 1: A platform that is like visual, and so I think

322
00:19:04,400 --> 00:19:08,760
Speaker 1: people not to like generalize, but I think that Instagram

323
00:19:08,880 --> 00:19:12,800
Speaker 1: is a platform where people who are very visual.

324
00:19:12,520 --> 00:19:13,240
Speaker 2: Spend a lot of time.

325
00:19:13,280 --> 00:19:16,760
Speaker 1: And so if you're like a celebrity, you Instagram might

326
00:19:16,800 --> 00:19:19,840
Speaker 1: have a different feeling that a platform like Twitter, which

327
00:19:19,880 --> 00:19:21,520
Speaker 1: is text based. Well, if you have to like really

328
00:19:21,800 --> 00:19:24,359
Speaker 1: it's really depends the way that you engage with through

329
00:19:24,400 --> 00:19:25,720
Speaker 1: what you have to what you write, what you have

330
00:19:25,800 --> 00:19:28,480
Speaker 1: to say. Instagram it's visuals. Was like, you might not

331
00:19:28,520 --> 00:19:31,639
Speaker 1: be much of a wordsmith, but if you are a

332
00:19:31,720 --> 00:19:33,679
Speaker 1: visual person, you can really succeed there. And so I

333
00:19:33,680 --> 00:19:36,800
Speaker 1: think that like it might have more people who aren't

334
00:19:36,840 --> 00:19:41,240
Speaker 1: really thinking about things in a super I don't know.

335
00:19:41,280 --> 00:19:42,800
Speaker 1: I don't want to stund like an asshole. How can

336
00:19:42,840 --> 00:19:45,960
Speaker 1: I put this? Do you don't trying to say like.

337
00:19:46,920 --> 00:19:48,320
Speaker 3: It's you know, it's a little bit.

338
00:19:49,119 --> 00:19:52,560
Speaker 4: Sometimes people will take things at service value, and there's nothing.

339
00:19:54,119 --> 00:19:57,000
Speaker 3: Wrong with you if you do that. That is enormal.

340
00:19:57,119 --> 00:19:59,399
Speaker 5: I do that, Yes, I do that exactly like we

341
00:19:59,480 --> 00:20:00,119
Speaker 5: all do that.

342
00:20:00,240 --> 00:20:04,239
Speaker 4: And I think this is this particular situation, a lot

343
00:20:04,280 --> 00:20:08,800
Speaker 4: of people feel very out of their element, and just

344
00:20:08,840 --> 00:20:12,520
Speaker 4: given the way that social media has kind of and

345
00:20:12,560 --> 00:20:14,159
Speaker 4: again I will say I do think there are benefits

346
00:20:14,200 --> 00:20:15,720
Speaker 4: of social media when it comes to activism, but the

347
00:20:15,760 --> 00:20:18,719
Speaker 4: same way it has commodified activism to an extent, and

348
00:20:18,760 --> 00:20:20,359
Speaker 4: it has turned it into a little bit of a

349
00:20:20,400 --> 00:20:21,160
Speaker 4: performative thing.

350
00:20:21,560 --> 00:20:25,520
Speaker 3: A lot of people feel very you know, back.

351
00:20:27,119 --> 00:20:30,320
Speaker 4: Now, over a week ago, when the attacks on Israel

352
00:20:30,400 --> 00:20:33,280
Speaker 4: first happened, there was a lot of initial misinformation that

353
00:20:33,359 --> 00:20:34,840
Speaker 4: was being spread just because I think a lot of

354
00:20:34,880 --> 00:20:36,639
Speaker 4: people felt like they had to make a statement. And

355
00:20:36,680 --> 00:20:39,800
Speaker 4: then again, this whole issue is complicated by the fact that, yes,

356
00:20:39,840 --> 00:20:43,520
Speaker 4: it has been very, very difficult to speak in support

357
00:20:43,600 --> 00:20:47,760
Speaker 4: of Palestine and human rights, just due to the way

358
00:20:47,800 --> 00:20:52,439
Speaker 4: that discourse has been framed and the way that it

359
00:20:52,480 --> 00:20:54,119
Speaker 4: has talked about, and a lot of the kind of

360
00:20:54,160 --> 00:21:00,119
Speaker 4: inherent biases that people have, especially in the US. I

361
00:21:00,119 --> 00:21:02,760
Speaker 4: think just a combination of a the way that social

362
00:21:02,800 --> 00:21:06,359
Speaker 4: media works and social media activism works and weren't moved

363
00:21:06,400 --> 00:21:10,080
Speaker 4: so quickly, combined with the fact that the last couple

364
00:21:10,040 --> 00:21:13,439
Speaker 4: of years, the last ten years, there are people I

365
00:21:13,480 --> 00:21:17,159
Speaker 4: know that made the most mild statements either criticizing the

366
00:21:17,200 --> 00:21:21,919
Speaker 4: Israeli government or in support of the Palestinian people and

367
00:21:22,119 --> 00:21:23,200
Speaker 4: have been docs for that.

368
00:21:23,520 --> 00:21:23,760
Speaker 2: It is.

369
00:21:27,080 --> 00:21:30,680
Speaker 4: That the fact that like that combination is just makes

370
00:21:30,720 --> 00:21:35,720
Speaker 4: it such a strange and difficult landscape I think to

371
00:21:35,920 --> 00:21:37,560
Speaker 4: navigate on social media.

372
00:21:37,760 --> 00:21:41,160
Speaker 1: Rachel Greenspan, a writer who I think is great, wrote

373
00:21:41,200 --> 00:21:44,600
Speaker 1: this piece at MSNBC called why I'm not expecting my

374
00:21:44,640 --> 00:21:48,080
Speaker 1: friends to make social media posts about Israel. Rachel rights,

375
00:21:48,280 --> 00:21:50,639
Speaker 1: there is now a values based currency in our social

376
00:21:50,720 --> 00:21:53,280
Speaker 1: media landscape that did not appear when Instagram launched in

377
00:21:53,320 --> 00:21:56,000
Speaker 1: twenty ten. We're now asking ourselves did I share the

378
00:21:56,080 --> 00:21:58,800
Speaker 1: right thing? Did I share enough? We're treating our social

379
00:21:58,800 --> 00:22:02,000
Speaker 1: media profiles that's communityation. Channels for the general public. But

380
00:22:02,040 --> 00:22:03,760
Speaker 1: we're afraid because we all live in a new kind

381
00:22:03,760 --> 00:22:05,640
Speaker 1: of public now, whether we like it or not. Even

382
00:22:05,680 --> 00:22:07,879
Speaker 1: though we've always known that what we post online shapes

383
00:22:07,880 --> 00:22:10,639
Speaker 1: how the world sees us, we now fear a specific

384
00:22:10,680 --> 00:22:12,800
Speaker 1: type of judgment that we won't be thought of as

385
00:22:12,840 --> 00:22:16,520
Speaker 1: good people. And of course our opinions of those we follow.

386
00:22:16,359 --> 00:22:17,320
Speaker 2: Shape what we believe.

387
00:22:17,920 --> 00:22:21,600
Speaker 1: And I think you're to your point about you know,

388
00:22:22,240 --> 00:22:24,680
Speaker 1: that time when people were posting things and then taking

389
00:22:24,680 --> 00:22:26,159
Speaker 1: them down, and then wanting to post the right thing,

390
00:22:26,200 --> 00:22:28,600
Speaker 1: and then feeling obligated to post something. I think that

391
00:22:29,080 --> 00:22:32,119
Speaker 1: I think that we're really seeing how our social media

392
00:22:32,240 --> 00:22:36,600
Speaker 1: landscape has led us to these responses and these reactions

393
00:22:36,600 --> 00:22:39,639
Speaker 1: that are not necessarily always helpful, Like I have learned

394
00:22:39,920 --> 00:22:43,440
Speaker 1: so much about my own activism what's going on in

395
00:22:43,480 --> 00:22:46,840
Speaker 1: the world from social media, but also on top of

396
00:22:46,920 --> 00:22:49,480
Speaker 1: like it's like a yes, and it can also be

397
00:22:49,560 --> 00:22:51,399
Speaker 1: hard if we're all feeling like, well, we have to

398
00:22:51,400 --> 00:22:53,440
Speaker 1: post the right thing and we have to like show

399
00:22:53,520 --> 00:22:55,480
Speaker 1: up with the exact right like there's not really it

400
00:22:55,480 --> 00:22:58,320
Speaker 1: doesn't feel like there's room for processing anymore. It's only

401
00:22:58,400 --> 00:23:01,480
Speaker 1: feels like there's only room for reaction publicly, which I

402
00:23:01,480 --> 00:23:04,560
Speaker 1: would argue, does that always get us like to the

403
00:23:04,600 --> 00:23:07,560
Speaker 1: most helpful thing all the time?

404
00:23:08,760 --> 00:23:09,240
Speaker 3: Exactly?

405
00:23:09,359 --> 00:23:13,680
Speaker 4: Yeah, I think because this definitely was a moment too

406
00:23:13,680 --> 00:23:16,359
Speaker 4: where I kind of you know, sat down with my

407
00:23:16,400 --> 00:23:19,120
Speaker 4: fault and I was thinking about what's the like, what

408
00:23:19,240 --> 00:23:21,159
Speaker 4: is going to be productive for me to post on

409
00:23:21,160 --> 00:23:23,360
Speaker 4: my Instagram? What is not going to be productive? And

410
00:23:23,560 --> 00:23:28,320
Speaker 4: I think, you know, every time there's some big sort

411
00:23:28,320 --> 00:23:30,640
Speaker 4: of this, a similar thing happened in twenty twenty when

412
00:23:30,800 --> 00:23:33,400
Speaker 4: it was there's certain things that kind of get circulated

413
00:23:33,440 --> 00:23:37,320
Speaker 4: that feel very sensatialized and exploitative, and then there's things

414
00:23:37,320 --> 00:23:40,560
Speaker 4: that get circulated that feel like they're actually pointing to.

415
00:23:41,000 --> 00:23:43,040
Speaker 4: If you feel helpless, right now, here's what you can do.

416
00:23:43,160 --> 00:23:45,399
Speaker 4: Here are things that you can look into. Here is

417
00:23:46,280 --> 00:23:49,600
Speaker 4: resources to help you understand if you don't understand it.

418
00:23:49,600 --> 00:23:52,520
Speaker 4: Also is okay to admit that you don't know everything.

419
00:23:52,600 --> 00:23:54,240
Speaker 4: I think that is really hard for people.

420
00:23:54,240 --> 00:23:58,960
Speaker 5: But like, and I like, I'm not going to pretend

421
00:23:59,160 --> 00:24:01,399
Speaker 5: like I am the spurt on all of this, but

422
00:24:01,480 --> 00:24:03,600
Speaker 5: like I had friends reached out to me like last

423
00:24:03,600 --> 00:24:05,919
Speaker 5: weekend that we're just sort of like, hey, can you, like,

424
00:24:06,720 --> 00:24:08,600
Speaker 5: would you be open to just kind of like chatting

425
00:24:08,640 --> 00:24:10,040
Speaker 5: with me about this for a little bit, and I

426
00:24:10,119 --> 00:24:12,200
Speaker 5: was like, sure, yeah, like I can totally.

427
00:24:12,280 --> 00:24:14,879
Speaker 4: I like, I can tell you what I know. I

428
00:24:14,920 --> 00:24:18,760
Speaker 4: can tell you the history that I know. Again, look

429
00:24:18,800 --> 00:24:21,719
Speaker 4: into your own stuff too. I like would send people research.

430
00:24:21,720 --> 00:24:23,920
Speaker 4: But it is also like it is it is okay

431
00:24:23,960 --> 00:24:25,119
Speaker 4: to speak a step back and do research.

432
00:24:25,119 --> 00:24:26,840
Speaker 3: It is okay to if you don't know things.

433
00:24:27,920 --> 00:24:31,760
Speaker 4: At the same time, you know, there are certain universal

434
00:24:31,760 --> 00:24:35,359
Speaker 4: things that are like I think we are at a

435
00:24:35,400 --> 00:24:39,000
Speaker 4: point now where we again, I think we are looking

436
00:24:39,040 --> 00:24:43,080
Speaker 4: at a genocide that is happening, and I think it

437
00:24:43,160 --> 00:24:46,919
Speaker 4: is there is a reason to speak up now, and

438
00:24:46,960 --> 00:24:50,840
Speaker 4: there is a reason to try to learn now and

439
00:24:50,920 --> 00:24:54,560
Speaker 4: to try to also learn like the way that the

440
00:24:54,760 --> 00:24:59,000
Speaker 4: US also you know, provides military support for Israel and

441
00:24:59,040 --> 00:25:04,480
Speaker 4: the role that that and just the history looking into

442
00:25:04,600 --> 00:25:07,160
Speaker 4: also the history of Jewish people in the region, and

443
00:25:07,200 --> 00:25:10,880
Speaker 4: how kind of Israel as a state as a political

444
00:25:11,000 --> 00:25:14,080
Speaker 4: entity is not necessarily representative of the Jewish people.

445
00:25:15,000 --> 00:25:15,560
Speaker 3: It's serting.

446
00:25:15,720 --> 00:25:18,480
Speaker 4: So it is anti Semitic, I will say that, But also,

447
00:25:19,119 --> 00:25:22,399
Speaker 4: you know the other side of that is also you

448
00:25:22,440 --> 00:25:23,959
Speaker 4: can criticize the state of Israel.

449
00:25:24,000 --> 00:25:25,640
Speaker 3: You can criticize Zionism.

450
00:25:25,280 --> 00:25:27,840
Speaker 4: As political ideology that in and of itself is not

451
00:25:27,880 --> 00:25:31,840
Speaker 4: anti Semitic, because Israel does not represent the Jewish people.

452
00:25:31,880 --> 00:25:34,720
Speaker 4: We are a community that exists all over the world

453
00:25:34,720 --> 00:25:36,200
Speaker 4: and that is very diverse.

454
00:25:37,720 --> 00:25:39,159
Speaker 3: Culturally politically.

455
00:25:40,320 --> 00:25:44,480
Speaker 4: Yeah, it is okay to ask questions, It is okay

456
00:25:44,520 --> 00:25:48,439
Speaker 4: to do research, and it is okay to not have

457
00:25:48,560 --> 00:25:50,439
Speaker 4: to respond right away to things.

458
00:25:51,040 --> 00:25:54,879
Speaker 1: And I wish for us that we had a landscape

459
00:25:54,880 --> 00:25:58,800
Speaker 1: that just we all understood that, and that really fostered

460
00:25:59,119 --> 00:26:02,720
Speaker 1: us to have more thoughtful conversations where we got to

461
00:26:02,800 --> 00:26:07,119
Speaker 1: really hear perspectives, you know, people's perspectives. And I know

462
00:26:07,200 --> 00:26:10,600
Speaker 1: that there's been a whole history of Palestinian folks who

463
00:26:10,640 --> 00:26:12,560
Speaker 1: say that they are really not able to do that

464
00:26:12,600 --> 00:26:14,760
Speaker 1: on social media with the landscape that we currently have

465
00:26:15,680 --> 00:26:19,639
Speaker 1: right now. Folks have said that if they express views

466
00:26:19,680 --> 00:26:23,200
Speaker 1: supportive of Palestinians on Instagram, that those views are being

467
00:26:23,240 --> 00:26:27,840
Speaker 1: algorithmically suppressed on the platform. Generally speaking, I usually when

468
00:26:27,840 --> 00:26:31,719
Speaker 1: people are like I'm being shadow band I generally I'm like, oh,

469
00:26:31,800 --> 00:26:34,160
Speaker 1: are you really being shadow band Like. It's an overused

470
00:26:34,200 --> 00:26:37,280
Speaker 1: accusation that is thrown around quite a bit, but it

471
00:26:37,320 --> 00:26:41,760
Speaker 1: does seem like something is going on on Instagram right now,

472
00:26:41,800 --> 00:26:45,760
Speaker 1: as it pertains to people trying to talk about Palestine.

473
00:26:46,200 --> 00:26:48,679
Speaker 1: In another instance, people were trying to upload images from

474
00:26:48,720 --> 00:26:51,600
Speaker 1: the hospital in Gaza that was blown up, and Instagram

475
00:26:51,800 --> 00:26:56,960
Speaker 1: removed those images, citing that they violated policies forbidding nudity

476
00:26:57,080 --> 00:27:00,119
Speaker 1: or sexual activity, even though the images did not have

477
00:27:00,200 --> 00:27:03,560
Speaker 1: nudity In some instances, they didn't have any people in them,

478
00:27:03,560 --> 00:27:06,879
Speaker 1: so it's like, how is it sexual? A Facebook spokesperson

479
00:27:06,920 --> 00:27:10,320
Speaker 1: Andy Stone explained in a statement, He said, we identified

480
00:27:10,320 --> 00:27:13,280
Speaker 1: a bug impacting all stories that re shared reels and

481
00:27:13,320 --> 00:27:16,240
Speaker 1: feed posts, meaning they weren't showing up properly in people's

482
00:27:16,280 --> 00:27:18,960
Speaker 1: stories tray, leading to significantly reduced reach.

483
00:27:19,280 --> 00:27:20,680
Speaker 2: This bug affected.

484
00:27:20,280 --> 00:27:22,560
Speaker 1: Accounts equally around the globe and had nothing to do

485
00:27:22,600 --> 00:27:24,040
Speaker 1: with subject matter of the content.

486
00:27:24,400 --> 00:27:27,639
Speaker 2: We fixed it as quickly as possible, So I don't know.

487
00:27:27,720 --> 00:27:31,959
Speaker 1: People are skeptical because Facebook is using and has used

488
00:27:32,320 --> 00:27:35,960
Speaker 1: this glitch reasoning quite a lot. The Guardian spoke to

489
00:27:35,960 --> 00:27:39,119
Speaker 1: a former Facebook and employee who explained that quote, you

490
00:27:39,200 --> 00:27:42,360
Speaker 1: cannot keep blaming it on glitches when it's spreading misinformation

491
00:27:42,440 --> 00:27:45,760
Speaker 1: into humanizing Palestinians by feeding into the narrative that all

492
00:27:45,800 --> 00:27:49,879
Speaker 1: Palestinians are terrorists. It's very overwhelming for a lot of

493
00:27:49,880 --> 00:27:52,600
Speaker 1: the employees of the company. So this is not even

494
00:27:52,720 --> 00:27:55,040
Speaker 1: at all close to the first time that Facebook's policies

495
00:27:55,080 --> 00:27:58,880
Speaker 1: have been questionable, as it pertains to how people talk

496
00:27:58,880 --> 00:28:01,440
Speaker 1: about Palestine, and book is very well aware. In twenty

497
00:28:01,480 --> 00:28:04,440
Speaker 1: twenty one, two hundred Facebook employees actually signed a letter

498
00:28:04,880 --> 00:28:08,400
Speaker 1: urging the platform to address concerns that pro Palestidian voices

499
00:28:08,680 --> 00:28:11,600
Speaker 1: on the platform were being suppressed by content moderation systems.

500
00:28:11,920 --> 00:28:13,560
Speaker 2: The employees were demanding a.

501
00:28:13,520 --> 00:28:16,119
Speaker 1: Third party review of how that kind of content was

502
00:28:16,200 --> 00:28:19,000
Speaker 1: moderated on the platform and the impact. So Facebook ended

503
00:28:19,040 --> 00:28:23,200
Speaker 1: up commissioning this independent consultancy called Business for Social Responsibility

504
00:28:23,560 --> 00:28:27,480
Speaker 1: or BSR, who put together this report about the company's

505
00:28:27,520 --> 00:28:31,119
Speaker 1: censorship practices and the allegations of bias during this previous

506
00:28:31,119 --> 00:28:34,880
Speaker 1: battle violence in Palestine. The report found the following quote.

507
00:28:35,119 --> 00:28:38,440
Speaker 1: Meta's actions in May twenty twenty one appeared to have

508
00:28:38,480 --> 00:28:40,840
Speaker 1: had an adverse human rights impact on the rights of

509
00:28:40,880 --> 00:28:46,080
Speaker 1: Palestinian users to freedom of expression, freedom of assembly, political participation,

510
00:28:46,200 --> 00:28:49,880
Speaker 1: and non discrimination, and therefore on the ability of Palestinians

511
00:28:49,880 --> 00:28:53,320
Speaker 1: to share information and insights about their experiences as they occurred.

512
00:28:53,800 --> 00:28:57,480
Speaker 1: As reported by the Intercept. Though BSR is clear in

513
00:28:57,560 --> 00:29:01,040
Speaker 1: stating that Meta harms Palestinian rights with the sensorship apparatus

514
00:29:01,280 --> 00:29:02,480
Speaker 1: it alone has constructed.

515
00:29:02,600 --> 00:29:04,120
Speaker 2: The report absolves.

516
00:29:03,680 --> 00:29:07,560
Speaker 1: Meta of quote intentional bias, but rather BSR pointed to

517
00:29:07,600 --> 00:29:12,360
Speaker 1: what it called unintentional bias instances where metas policy and practice,

518
00:29:12,440 --> 00:29:16,280
Speaker 1: combined with broader external dynamics do lead to different human

519
00:29:16,360 --> 00:29:19,920
Speaker 1: rights impact on Palestinian and Arabic speaking users, a nod

520
00:29:19,960 --> 00:29:22,200
Speaker 1: to the fact that these systemic flaws are by no

521
00:29:22,320 --> 00:29:24,640
Speaker 1: means limited to the events of twenty twenty one. Just

522
00:29:24,680 --> 00:29:29,240
Speaker 1: like what we're talking about now with Instagram changing bios

523
00:29:29,280 --> 00:29:33,440
Speaker 1: to like terrorist sympathizer language is not like. This is

524
00:29:33,480 --> 00:29:35,360
Speaker 1: not the first time that kind of thing has happened.

525
00:29:35,360 --> 00:29:38,040
Speaker 1: This has been a pattern. So, according to the Intercept,

526
00:29:38,120 --> 00:29:41,240
Speaker 1: Facebook has been long aware that their moderation policies are

527
00:29:41,600 --> 00:29:46,200
Speaker 1: to use their words lopsided. Not only do Palestinian users

528
00:29:46,240 --> 00:29:49,840
Speaker 1: face an algorithmic screening that Israeli users do not, a

529
00:29:50,120 --> 00:29:54,520
Speaker 1: quote Arabic hostile speech classifier that uses machine learning to

530
00:29:54,560 --> 00:29:59,000
Speaker 1: flag potential policy violations, and has no Hebrew equivalent. The

531
00:29:59,080 --> 00:30:02,080
Speaker 1: report also knows that the Arabic system does not work well.

532
00:30:02,760 --> 00:30:06,520
Speaker 1: Arabic classifiers are likely less accurate for Palestinian Arabic than

533
00:30:06,560 --> 00:30:10,080
Speaker 1: other dialects, both because the dialect is less common and

534
00:30:10,120 --> 00:30:12,480
Speaker 1: because the training data, which is based on the assessments

535
00:30:12,520 --> 00:30:16,960
Speaker 1: of human reviewers, likely reproduces the errors of human reviewers

536
00:30:17,240 --> 00:30:20,480
Speaker 1: due to the lack of linguistic and cultural competence. So, like,

537
00:30:21,440 --> 00:30:24,560
Speaker 1: I just really see the ways that our tech landscape

538
00:30:24,600 --> 00:30:27,840
Speaker 1: and how biased it is, and how white it is,

539
00:30:27,920 --> 00:30:30,600
Speaker 1: and how all the other things I've rant about on

540
00:30:30,600 --> 00:30:34,080
Speaker 1: this podcast constantly, how all of that is coming together

541
00:30:34,120 --> 00:30:38,560
Speaker 1: to create this system where folks are saying they cannot

542
00:30:39,320 --> 00:30:42,040
Speaker 1: express themselves, they cannot talk about what's going on, they

543
00:30:42,080 --> 00:30:43,920
Speaker 1: cannot talk about what they're seeing on the ground, they

544
00:30:43,920 --> 00:30:47,280
Speaker 1: cannot share images of what's happening without getting caught by

545
00:30:47,560 --> 00:30:51,239
Speaker 1: Facebook and Instagram's content moderation policies, and that this is

546
00:30:51,280 --> 00:30:55,080
Speaker 1: not an equally you know, use the report itself uses

547
00:30:55,080 --> 00:30:57,920
Speaker 1: the word lopsided, that this is not an equal landscape

548
00:30:57,920 --> 00:30:59,320
Speaker 1: in terms of how it is moderated.

549
00:31:00,400 --> 00:31:04,200
Speaker 4: Yeah. Absolutely, And like you said too, this isn't necessarily

550
00:31:04,240 --> 00:31:07,920
Speaker 4: a new issue. I think the fact that you know

551
00:31:08,040 --> 00:31:11,280
Speaker 4: it is in the spotlight now and it is. On

552
00:31:11,320 --> 00:31:13,320
Speaker 4: the other hand, this is maybe the good thing of

553
00:31:13,440 --> 00:31:17,040
Speaker 4: kind of like social media and this ability to share

554
00:31:17,080 --> 00:31:20,080
Speaker 4: information from wherever you are in the world, is it

555
00:31:20,120 --> 00:31:22,960
Speaker 4: is harder and harder to repress this stuff if more

556
00:31:22,960 --> 00:31:25,320
Speaker 4: people are talking about it and we're sharing it. But

557
00:31:25,480 --> 00:31:27,800
Speaker 4: at the same time, it is very clearly not a

558
00:31:27,840 --> 00:31:31,680
Speaker 4: new issue, and it is very clearly something that is

559
00:31:31,720 --> 00:31:35,680
Speaker 4: happening and something that is clearly biased to certain voices

560
00:31:35,920 --> 00:31:37,240
Speaker 4: and unlie others.

561
00:31:38,120 --> 00:31:40,080
Speaker 1: And I think you're I think we're kind of like

562
00:31:40,200 --> 00:31:42,120
Speaker 1: maybe thinking about this in the same way, and that

563
00:31:42,640 --> 00:31:45,320
Speaker 1: as awful as all of this is, I do think

564
00:31:45,320 --> 00:31:47,560
Speaker 1: that we're in a situation in twenty twenty three where

565
00:31:47,560 --> 00:31:52,880
Speaker 1: people are more prone to see clearly and be skeptical

566
00:31:52,960 --> 00:31:55,760
Speaker 1: of tech platforms and the way that they really are

567
00:31:56,360 --> 00:31:58,560
Speaker 1: guiding this conversation and have a lot of power to

568
00:31:58,680 --> 00:32:02,400
Speaker 1: shape the public perception than the public conversation. And I

569
00:32:02,440 --> 00:32:05,000
Speaker 1: think that like maybe even five years ago, that wouldn't

570
00:32:05,000 --> 00:32:06,120
Speaker 1: have been the case. I think that people would have

571
00:32:06,160 --> 00:32:09,680
Speaker 1: just thought, like, oh, like Facebook and technology is totally neutral.

572
00:32:09,720 --> 00:32:11,680
Speaker 1: They're not doing anything, They're not making it. They're not

573
00:32:12,200 --> 00:32:15,040
Speaker 1: they're not you know, making any kind of decisions. They're

574
00:32:15,120 --> 00:32:17,040
Speaker 1: just like a very neutral platform. I think that we

575
00:32:17,760 --> 00:32:20,880
Speaker 1: the fact that we're having this conversation makes me hopeful

576
00:32:20,920 --> 00:32:25,280
Speaker 1: that we've kind of abandoned that missed that incorrect notion

577
00:32:25,600 --> 00:32:28,600
Speaker 1: that tech platforms are neutral, because this is not This

578
00:32:28,680 --> 00:32:29,800
Speaker 1: is not what neutral looks like.

579
00:32:30,400 --> 00:32:31,000
Speaker 3: Absolutely.

580
00:32:31,600 --> 00:32:33,760
Speaker 1: So last week in our Twitter episode, we were talking

581
00:32:33,800 --> 00:32:37,280
Speaker 1: about how the EU is demanding platforms give more information

582
00:32:37,320 --> 00:32:40,600
Speaker 1: about how they're handling content moderation around the conflict. And

583
00:32:40,640 --> 00:32:43,160
Speaker 1: now the United States Senate is getting involved too, because

584
00:32:43,200 --> 00:32:46,320
Speaker 1: this week Colorado Democrat Senator Michael Bennett sent letters to

585
00:32:46,360 --> 00:32:50,120
Speaker 1: all the major platforms saying deceptive content has ricochet across

586
00:32:50,120 --> 00:32:53,719
Speaker 1: social media sites since the conflict began, sometimes receiving millions

587
00:32:53,720 --> 00:32:57,160
Speaker 1: of views. In many cases, your platform's algorithms have amplified

588
00:32:57,160 --> 00:33:00,720
Speaker 1: this content, contributing to a dangerous cycle of outrging engagement

589
00:33:00,760 --> 00:33:04,080
Speaker 1: and distribution. Bennett says that whatever steps platforms have taken

590
00:33:04,280 --> 00:33:06,600
Speaker 1: to curb this is not enough, and he is demanding

591
00:33:06,600 --> 00:33:10,280
Speaker 1: a response by October thirty first, And I think it's, yeah,

592
00:33:10,320 --> 00:33:13,000
Speaker 1: just a good reminder that as much as I talk

593
00:33:13,040 --> 00:33:15,280
Speaker 1: about Twitter, which is a lot, and I still think

594
00:33:15,320 --> 00:33:20,360
Speaker 1: it's warranted. Our larger information ecosystem is also trash, you know,

595
00:33:20,400 --> 00:33:22,680
Speaker 1: and so if Twitter is not a reliable place to

596
00:33:22,720 --> 00:33:26,160
Speaker 1: get accurate information, other platforms certainly are not either, and

597
00:33:26,200 --> 00:33:28,960
Speaker 1: it's just becoming harder and harder and harder to have

598
00:33:29,080 --> 00:33:33,200
Speaker 1: access to that accurate, thoughtful information that we all really deserve.

599
00:33:33,360 --> 00:33:34,920
Speaker 1: You know, when I talk about how we can't have

600
00:33:34,960 --> 00:33:37,760
Speaker 1: an equitable world without equitable platforms, this is really what

601
00:33:37,800 --> 00:33:39,120
Speaker 1: I mean. You know, when I talk about how we

602
00:33:39,160 --> 00:33:43,280
Speaker 1: can't have true, meaningful safety if our platforms are not

603
00:33:43,400 --> 00:33:46,800
Speaker 1: safe places for expression and the exchange of ideas and information,

604
00:33:47,240 --> 00:33:49,680
Speaker 1: this is what I mean. The way that tech companies

605
00:33:49,720 --> 00:33:52,440
Speaker 1: have really been tasked with shaping our understanding of not

606
00:33:52,520 --> 00:33:55,920
Speaker 1: just what's happening in the world, but like our perception

607
00:33:56,080 --> 00:33:58,480
Speaker 1: of the people who are involved, are understanding of who

608
00:33:58,480 --> 00:33:58,880
Speaker 1: they are.

609
00:33:59,280 --> 00:34:00,000
Speaker 2: That's a problem.

610
00:34:00,240 --> 00:34:03,160
Speaker 1: The decisions and policies of tech leaders can shape our

611
00:34:03,280 --> 00:34:07,000
Speaker 1: collective understanding of people's humanity, you know, what kind of

612
00:34:07,080 --> 00:34:10,440
Speaker 1: lives we think they deserve, And these platforms have been

613
00:34:10,440 --> 00:34:16,760
Speaker 1: given such a huge responsibility to impact people's actual, real lives.

614
00:34:16,800 --> 00:34:19,560
Speaker 1: You know, we're letting tech leaders like Elon Musk and

615
00:34:19,680 --> 00:34:23,120
Speaker 1: Mark Zuckerberg have such an outsized power to determine the

616
00:34:23,160 --> 00:34:27,239
Speaker 1: outcomes of these very real life and death situations, even

617
00:34:27,239 --> 00:34:30,120
Speaker 1: though these people have shown themselves to be not super

618
00:34:30,160 --> 00:34:31,840
Speaker 1: trustworthy again and again and again.

619
00:34:32,000 --> 00:34:34,200
Speaker 2: So yeah, all of that is to say that it

620
00:34:34,239 --> 00:34:36,040
Speaker 2: really just feels.

621
00:34:35,600 --> 00:34:39,239
Speaker 4: Like a lot yeah, yeah, and again, like back to

622
00:34:39,520 --> 00:34:43,480
Speaker 4: it is a life and death situation. Like people are dying,

623
00:34:44,040 --> 00:34:48,480
Speaker 4: more people are going to continue to die due to

624
00:34:50,000 --> 00:34:53,839
Speaker 4: the rhetoric and the level of dehumanization that leads to

625
00:34:53,880 --> 00:35:01,759
Speaker 4: this kind of mass catastrophe. That is the responsibility of

626
00:35:02,520 --> 00:35:06,960
Speaker 4: in the contemporary era. That is the responsibility of sites

627
00:35:07,000 --> 00:35:10,880
Speaker 4: like Twitter and Facebook and Instagram that are kind of

628
00:35:11,000 --> 00:35:15,400
Speaker 4: just like I'm like the contemporary version of like you know,

629
00:35:15,840 --> 00:35:18,640
Speaker 4: reading the newspaper in the morning is all open up Twitter,

630
00:35:18,840 --> 00:35:23,960
Speaker 4: Instagram that has a real world impact, that has real.

631
00:35:25,239 --> 00:35:30,880
Speaker 3: Lives on the line because of this, and there needs

632
00:35:30,920 --> 00:35:31,560
Speaker 3: that needs to.

633
00:35:31,480 --> 00:35:36,280
Speaker 1: Be addressed absolutely from your lips to Mark Zuckerberg's ears,

634
00:35:37,239 --> 00:35:55,239
Speaker 1: let's hope, let's take a quick break at our back.

635
00:35:58,239 --> 00:36:02,239
Speaker 1: So we talked a lot about disinformation, specifically election disinformation

636
00:36:02,320 --> 00:36:04,360
Speaker 1: on this podcast, and now folks might need to know

637
00:36:04,400 --> 00:36:08,520
Speaker 1: that election disinformation can get you jail time. That is

638
00:36:08,560 --> 00:36:10,719
Speaker 1: a lesson that Douglas Mackie, who used to go by

639
00:36:10,800 --> 00:36:14,560
Speaker 1: Ricky Vaughan on Twitter, should be taking away. This week,

640
00:36:14,680 --> 00:36:17,200
Speaker 1: Macki was sentenced to seven months in prison for his

641
00:36:17,360 --> 00:36:20,040
Speaker 1: part in a Twitter based scheme to conspire to deprive

642
00:36:20,160 --> 00:36:22,760
Speaker 1: others of their right to vote in the twenty sixteen election.

643
00:36:23,040 --> 00:36:25,720
Speaker 1: So most of what him and his circle of idiots

644
00:36:25,760 --> 00:36:30,359
Speaker 1: did was post memes, you know, stupid election memes, which

645
00:36:30,400 --> 00:36:32,800
Speaker 1: obviously is like protected by the First Amendment. Not a problem.

646
00:36:32,880 --> 00:36:34,960
Speaker 1: I mean, I don't love it, like, but not a problem.

647
00:36:35,200 --> 00:36:38,240
Speaker 1: But one of Macki's tactics crossed a very different line.

648
00:36:38,400 --> 00:36:41,000
Speaker 1: The Verge reports that a week before the twenty sixteen election,

649
00:36:41,160 --> 00:36:44,680
Speaker 1: Mackie and others began encouraging supporters of Hillary Clinton to

650
00:36:44,760 --> 00:36:47,840
Speaker 1: skip the voting lines and vote by text message, which

651
00:36:48,320 --> 00:36:51,160
Speaker 1: obviously is not a thing. You cannot vote by text,

652
00:36:51,840 --> 00:36:54,040
Speaker 1: that is not a thing. But they were trying to

653
00:36:54,040 --> 00:36:55,840
Speaker 1: convince people that you could just vote by texts and

654
00:36:55,880 --> 00:36:57,520
Speaker 1: you didn't have to you didn't have to go to

655
00:36:57,600 --> 00:37:01,200
Speaker 1: your polling place. They also posted pick that made it

656
00:37:01,200 --> 00:37:03,759
Speaker 1: look like they had been paid by Clinton's campaign of

657
00:37:03,800 --> 00:37:06,600
Speaker 1: people holding signs with the same messages and the same

658
00:37:06,640 --> 00:37:08,160
Speaker 1: phone number like vote by text.

659
00:37:08,160 --> 00:37:08,799
Speaker 2: Here's the number.

660
00:37:09,080 --> 00:37:12,000
Speaker 1: Mackie told conspirators that the goal was to suppress turnout

661
00:37:12,040 --> 00:37:15,600
Speaker 1: among black voters and other minoritized groups, saying Trump should

662
00:37:15,600 --> 00:37:17,920
Speaker 1: write off the black vote and as focus on depressing

663
00:37:17,960 --> 00:37:20,120
Speaker 1: their turnout. He wrote in one of the groups that

664
00:37:20,160 --> 00:37:22,799
Speaker 1: was used to plan this content strategy. In the end,

665
00:37:22,880 --> 00:37:26,520
Speaker 1: this is kind of like a delicious little tidbit. It

666
00:37:26,640 --> 00:37:30,040
Speaker 1: was his own circle of idiots who turned against him,

667
00:37:30,560 --> 00:37:33,480
Speaker 1: The Verge reports. During the trial, some of Mackie's co

668
00:37:33,480 --> 00:37:36,840
Speaker 1: conspirators testified against him, revealing how the group's coordinated and

669
00:37:36,840 --> 00:37:39,760
Speaker 1: planned their posts and memes for maximum impact on Twitter

670
00:37:39,800 --> 00:37:42,879
Speaker 1: and elsewhere. Mackie, who testified in his own defense, said

671
00:37:42,920 --> 00:37:44,799
Speaker 1: that he was only one of many people in these

672
00:37:44,800 --> 00:37:47,520
Speaker 1: groups and that he was posting without much thought or consideration,

673
00:37:48,080 --> 00:37:50,920
Speaker 1: rather than as some part of some big grand scheme.

674
00:37:51,000 --> 00:37:52,319
Speaker 1: Like he talked about it like it was just a

675
00:37:52,400 --> 00:37:55,080
Speaker 1: joke or a prank, but that did not stop him

676
00:37:55,080 --> 00:37:58,920
Speaker 1: from being sentenced to real jail time. It might not

677
00:37:59,200 --> 00:38:02,480
Speaker 1: seem it, but this is kind of a big deal.

678
00:38:02,600 --> 00:38:04,760
Speaker 1: Like I don't want to say too much. But I

679
00:38:04,800 --> 00:38:08,600
Speaker 1: actually knew somebody who got popped for like a kind

680
00:38:08,640 --> 00:38:11,719
Speaker 1: of a similar ish thing. Somebody I worked with was

681
00:38:11,719 --> 00:38:14,680
Speaker 1: a volunteer on a campaign where he sent out a

682
00:38:14,880 --> 00:38:19,319
Speaker 1: mass email announcing that the Republican opponent was dropping out

683
00:38:19,320 --> 00:38:21,239
Speaker 1: of the race for a seat in the House, which

684
00:38:21,280 --> 00:38:24,600
Speaker 1: was not true, and the email made it look like

685
00:38:24,640 --> 00:38:27,080
Speaker 1: it was coming from the Republican opponent. It was like, Oh,

686
00:38:27,120 --> 00:38:29,920
Speaker 1: I'm dropping out because I want to spend more time

687
00:38:30,080 --> 00:38:32,759
Speaker 1: with my studies or something. And he said that this

688
00:38:32,880 --> 00:38:35,280
Speaker 1: was meant to be like a prank that he cooked

689
00:38:35,360 --> 00:38:38,040
Speaker 1: up after a few beers, which like was very on

690
00:38:38,160 --> 00:38:41,080
Speaker 1: brand for this person, I must say, But prank or not,

691
00:38:41,320 --> 00:38:45,040
Speaker 1: he was like arrested and indicted and charged with a

692
00:38:45,120 --> 00:38:48,600
Speaker 1: voter suppression. I think he ended up like pleading down

693
00:38:48,680 --> 00:38:50,640
Speaker 1: to avoid actual jail time, and maybe he had to

694
00:38:50,640 --> 00:38:53,360
Speaker 1: pay a fine or something. But it was pretty serious,

695
00:38:53,360 --> 00:38:56,440
Speaker 1: Like it was like a serious thing, So yeah, don't

696
00:38:56,480 --> 00:38:58,400
Speaker 1: do that. You might think it's a joke or a prank,

697
00:38:58,520 --> 00:38:59,560
Speaker 1: but don't do that.

698
00:39:00,840 --> 00:39:04,080
Speaker 4: Yeah, that's so stupid, Like that is such an obvious

699
00:39:05,440 --> 00:39:08,640
Speaker 4: and it always I mean, of course, it was this

700
00:39:08,760 --> 00:39:11,480
Speaker 4: guy's like buddies that turned against it. It is just it

701
00:39:11,520 --> 00:39:13,600
Speaker 4: just goes to show these people always end up being

702
00:39:13,840 --> 00:39:15,680
Speaker 4: such powers and such like.

703
00:39:16,080 --> 00:39:18,160
Speaker 3: You can't even own up to your own shit.

704
00:39:18,480 --> 00:39:24,240
Speaker 4: But oh man, I yeah, sad that's on him that

705
00:39:24,239 --> 00:39:26,320
Speaker 4: that was just a dumb move, honestly.

706
00:39:27,520 --> 00:39:31,960
Speaker 1: Okay, So speaking of stupid things, this is like I've

707
00:39:32,000 --> 00:39:35,319
Speaker 1: been like mulling this story over in my head since

708
00:39:35,320 --> 00:39:36,040
Speaker 1: I heard about it.

709
00:39:36,040 --> 00:39:37,399
Speaker 2: It's like the stupidest thing I've ever heard.

710
00:39:37,480 --> 00:39:39,640
Speaker 1: So if you're an elder millennial like me, you probably

711
00:39:39,760 --> 00:39:42,120
Speaker 1: know the music group the Fujis, and you might recall

712
00:39:42,560 --> 00:39:47,080
Speaker 1: that the rapper Praz from that group, The Fujis, has

713
00:39:47,120 --> 00:39:49,839
Speaker 1: been in some pretty.

714
00:39:48,800 --> 00:39:50,480
Speaker 2: Wild legal trouble lately.

715
00:39:50,920 --> 00:39:53,719
Speaker 1: Honestly, I really have a hard time like making heads

716
00:39:53,800 --> 00:39:55,960
Speaker 1: or tails of some of the legal claims against him,

717
00:39:56,160 --> 00:39:58,680
Speaker 1: But this is my understanding. Praz was a donor to

718
00:39:58,719 --> 00:40:01,279
Speaker 1: the Obama campaign back in twenty twelve and was part

719
00:40:01,280 --> 00:40:05,160
Speaker 1: of a criminal conspiracy along with a Malaysian financer, to

720
00:40:05,280 --> 00:40:08,080
Speaker 1: make a legal campaign contribution to the tune of almost

721
00:40:08,160 --> 00:40:12,360
Speaker 1: one million dollars to Obama's twenty twelve presidential campaign. Praz

722
00:40:12,560 --> 00:40:15,480
Speaker 1: was also charged by a federal grand jury for running

723
00:40:15,480 --> 00:40:18,600
Speaker 1: a back Channel campaign to get the Trump administration to

724
00:40:18,719 --> 00:40:23,000
Speaker 1: drop an investigation of a fugitive Malaysian financier and a

725
00:40:23,040 --> 00:40:26,040
Speaker 1: Malaysian investment company. He also it sounds like he was

726
00:40:26,080 --> 00:40:29,560
Speaker 1: maybe trying to like pay or maybe bribe question Mark,

727
00:40:29,640 --> 00:40:33,200
Speaker 1: a Republican Party fundraiser to aid in the release of

728
00:40:33,239 --> 00:40:37,920
Speaker 1: a Chinese dissident. This case featured testimony from Leonardo DiCaprio

729
00:40:38,440 --> 00:40:39,440
Speaker 1: and former US.

730
00:40:39,320 --> 00:40:40,760
Speaker 2: Attorney General Jeff Session.

731
00:40:40,840 --> 00:40:44,200
Speaker 1: So, like, I don't know, like I said, complicated and

732
00:40:44,320 --> 00:40:46,080
Speaker 1: very involved, But my point is, this is like a

733
00:40:46,239 --> 00:40:51,200
Speaker 1: very serious, like set of charges with like far reaching

734
00:40:51,360 --> 00:40:56,000
Speaker 1: implications that involve like national security and global domestic issues

735
00:40:56,040 --> 00:40:58,920
Speaker 1: and presidential candidates and blah blah blah. It's a it's

736
00:40:58,920 --> 00:41:02,040
Speaker 1: a it's a big bout of charges that have like real,

737
00:41:02,560 --> 00:41:04,479
Speaker 1: very serious potential jail time.

738
00:41:04,640 --> 00:41:07,719
Speaker 2: So if you were his attorney, you would probably be like, oh,

739
00:41:07,719 --> 00:41:09,000
Speaker 2: this is a very serious case.

740
00:41:09,120 --> 00:41:11,400
Speaker 1: I want to do a very good job, and maybe

741
00:41:11,480 --> 00:41:14,279
Speaker 1: you would not want to use an AI program to

742
00:41:14,320 --> 00:41:16,920
Speaker 1: write your final arguments, which is what his lead defense

743
00:41:17,000 --> 00:41:20,640
Speaker 1: lawyer did. Prose's lead defense attorney improperly relied on an

744
00:41:20,640 --> 00:41:24,520
Speaker 1: experimental generative AI program called Eye Level to draft his

745
00:41:24,640 --> 00:41:28,279
Speaker 1: closing argument in Prase's high profile criminal case. This is

746
00:41:28,320 --> 00:41:31,200
Speaker 1: all according to a newly filed brief demanding a retrial.

747
00:41:31,440 --> 00:41:34,800
Speaker 1: So Prose's new attorney said that the AI generated closing

748
00:41:34,880 --> 00:41:38,480
Speaker 1: argument by his previous lawyer, David Kenner, was just awful,

749
00:41:38,520 --> 00:41:40,839
Speaker 1: Like it just sounds like it was like didn't I mean,

750
00:41:40,880 --> 00:41:42,239
Speaker 1: it sounds like it was written by AI. Like this

751
00:41:42,239 --> 00:41:45,440
Speaker 1: doesn't sound like it made any sense, and that closing

752
00:41:45,520 --> 00:41:49,000
Speaker 1: argument bungled what was the most important part of the trial,

753
00:41:49,000 --> 00:41:52,480
Speaker 1: the closing argument. His new lawyer says, Kenner's closing argument

754
00:41:52,480 --> 00:41:57,120
Speaker 1: made frivolous arguments, misapprehended the required elements, conflated the schemes,

755
00:41:57,160 --> 00:42:00,560
Speaker 1: and ignored critical weaknesses in the government side. So as

756
00:42:00,600 --> 00:42:03,680
Speaker 1: bad as that is, here's where it gets really stupid.

757
00:42:04,040 --> 00:42:06,279
Speaker 2: As if that's not stupid enough, because.

758
00:42:06,040 --> 00:42:09,080
Speaker 1: They also accused Prose's legal team of having an undisclosed

759
00:42:09,160 --> 00:42:12,480
Speaker 1: financial interest in the AI company that they use to

760
00:42:12,520 --> 00:42:15,200
Speaker 1: write that final argument, and that his legal team regarded

761
00:42:15,239 --> 00:42:18,640
Speaker 1: Prose's trial as an opportunity to tout their AI company

762
00:42:18,640 --> 00:42:22,759
Speaker 1: to advance their own financial interests at Prose's expense. They

763
00:42:22,760 --> 00:42:25,440
Speaker 1: actually did put out a press release after the trial

764
00:42:25,640 --> 00:42:29,080
Speaker 1: hailing this as quote the first use of generative AI

765
00:42:29,160 --> 00:42:32,400
Speaker 1: and a federal trial. The press release included this like

766
00:42:33,000 --> 00:42:37,680
Speaker 1: very glowing comma kind of in retrospect embarrassing quote from

767
00:42:37,719 --> 00:42:40,680
Speaker 1: the lead attorney, who said that the AI program quote

768
00:42:40,920 --> 00:42:44,120
Speaker 1: turned hours and days of legal work into seconds, and

769
00:42:44,160 --> 00:42:46,440
Speaker 1: called his use of the program a look into the

770
00:42:46,480 --> 00:42:49,960
Speaker 1: future of how cases will be conducted. Yeah, conducted badly,

771
00:42:50,040 --> 00:42:52,440
Speaker 1: I think because he's asking for a new trial. I

772
00:42:52,440 --> 00:42:53,320
Speaker 1: mean he was convicted.

773
00:42:53,880 --> 00:42:55,440
Speaker 3: Yeah, that's.

774
00:42:57,160 --> 00:43:00,600
Speaker 1: It's just I mean, like it's almost there are no words, right,

775
00:43:00,719 --> 00:43:05,600
Speaker 1: Like it's so stupid and such a bad idea, And

776
00:43:05,760 --> 00:43:07,799
Speaker 1: I can't believe that anybody at this legal firm thought

777
00:43:07,840 --> 00:43:09,839
Speaker 1: this was a good idea and also like put out

778
00:43:09,840 --> 00:43:11,560
Speaker 1: press releases bragging about.

779
00:43:11,320 --> 00:43:15,759
Speaker 4: It exactly like you're you're taddling on yourself.

780
00:43:15,880 --> 00:43:16,600
Speaker 2: What like.

781
00:43:18,000 --> 00:43:20,759
Speaker 6: You're basically, first of all, you're already working with like

782
00:43:20,800 --> 00:43:26,239
Speaker 6: a high profile client, and you're just bragging about the

783
00:43:26,280 --> 00:43:29,960
Speaker 6: fact that you are bumbling his case so bad.

784
00:43:30,960 --> 00:43:36,000
Speaker 3: I that is crazy. That is I don't know what

785
00:43:36,080 --> 00:43:39,680
Speaker 3: to say. I just I have no response. That just

786
00:43:39,719 --> 00:43:42,240
Speaker 3: seems seems like a bad idea.

787
00:43:42,520 --> 00:43:44,520
Speaker 1: How mad would you be if like you're like, oh, yeah,

788
00:43:44,560 --> 00:43:46,239
Speaker 1: I might go to jail for like I might do

789
00:43:46,400 --> 00:43:49,680
Speaker 1: serious federal jail time on some like serious global like

790
00:43:50,080 --> 00:43:53,360
Speaker 1: charges like real charges, grown man charges, and you're using

791
00:43:53,440 --> 00:43:56,600
Speaker 1: like the legal version of chat GPT to come up

792
00:43:56,640 --> 00:43:58,440
Speaker 1: with the closing argument to defend me.

793
00:43:58,719 --> 00:43:59,960
Speaker 2: I'd be so mad.

794
00:43:59,840 --> 00:44:03,680
Speaker 1: I think it also just really reveals like how much

795
00:44:03,719 --> 00:44:06,480
Speaker 1: of this is a grift, like people who make money

796
00:44:06,520 --> 00:44:09,640
Speaker 1: from AI need us to be thinking that it is possible,

797
00:44:09,719 --> 00:44:12,520
Speaker 1: and also a good idea that AI will be defending

798
00:44:12,520 --> 00:44:15,040
Speaker 1: people on trial someday. It doesn't even matter if this

799
00:44:15,120 --> 00:44:18,400
Speaker 1: person gets a fair trial or not if their AI

800
00:44:18,640 --> 00:44:20,440
Speaker 1: technology you know, gets pressed.

801
00:44:20,960 --> 00:44:24,480
Speaker 4: Yeah, exactly, Like it just feels like another example of

802
00:44:24,520 --> 00:44:27,319
Speaker 4: how and I don't want to be like, oh see,

803
00:44:27,320 --> 00:44:30,120
Speaker 4: it just goes to show how domed this technology is.

804
00:44:30,160 --> 00:44:33,080
Speaker 4: But it clearly doesn't work right now, and like maybe

805
00:44:33,080 --> 00:44:35,319
Speaker 4: in the future it will and that will also be

806
00:44:35,400 --> 00:44:38,120
Speaker 4: its own problem to deal with, but like, clearly it's

807
00:44:38,160 --> 00:44:38,760
Speaker 4: not working.

808
00:44:39,440 --> 00:44:39,760
Speaker 2: Again.

809
00:44:40,480 --> 00:44:42,920
Speaker 4: I don't think I have seen a single example of

810
00:44:42,960 --> 00:44:45,719
Speaker 4: something written by an AI and any feel so far

811
00:44:45,840 --> 00:44:50,360
Speaker 4: that it has been well done, like maybe mediocre at best,

812
00:44:50,440 --> 00:44:53,600
Speaker 4: But it's also like, do you know this guy is

813
00:44:53,640 --> 00:44:57,440
Speaker 4: like making bank for that trial, Like lawyers make a

814
00:44:57,440 --> 00:44:58,040
Speaker 4: lot of money.

815
00:44:58,320 --> 00:45:01,719
Speaker 5: Yes, you're just letting the AI do like the work

816
00:45:01,920 --> 00:45:02,719
Speaker 5: that you're getting bad.

817
00:45:02,760 --> 00:45:03,440
Speaker 3: I don't know that.

818
00:45:03,960 --> 00:45:07,279
Speaker 4: Which again, I'm all for finding ways to not have

819
00:45:07,360 --> 00:45:10,520
Speaker 4: to do work. I'm all for being lazy, but like,

820
00:45:10,719 --> 00:45:13,080
Speaker 4: at this point, is somebody's.

821
00:45:12,600 --> 00:45:15,239
Speaker 3: Livelihood is on the line, it feels a little important.

822
00:45:15,680 --> 00:45:18,640
Speaker 2: Joey, It's one thing to be lazy. We're podcasters. Like,

823
00:45:18,760 --> 00:45:21,520
Speaker 2: nobody's gonna go to jail because of our laziness.

824
00:45:22,840 --> 00:45:26,680
Speaker 1: Somebody might have like an unpleasant commute, like, ah, I

825
00:45:26,719 --> 00:45:27,799
Speaker 1: was a waste of forty.

826
00:45:27,480 --> 00:45:30,479
Speaker 2: Five minutes, but I don't go to jail.

827
00:45:30,640 --> 00:45:36,160
Speaker 1: Angry comments, yeah, damn, And like I just think that,

828
00:45:36,320 --> 00:45:42,520
Speaker 1: like it's like prose should not nobody should be pras

829
00:45:42,640 --> 00:45:45,279
Speaker 1: or anybody should not be like a guinea pig to

830
00:45:45,719 --> 00:45:48,440
Speaker 1: have this tech to like be the test case for

831
00:45:48,440 --> 00:45:50,600
Speaker 1: whether this technology can be used in this way. It's

832
00:45:50,640 --> 00:45:54,319
Speaker 1: just like it's stupid and funny, but ultimately it's like

833
00:45:54,960 --> 00:45:59,640
Speaker 1: people should not meet guinea pigs for the efficacy of

834
00:45:59,680 --> 00:46:03,160
Speaker 1: this d of technology when, as you said, correctly, it's

835
00:46:03,200 --> 00:46:03,879
Speaker 1: not there yet.

836
00:46:04,040 --> 00:46:06,280
Speaker 2: Maybe it will be there, Maybe this is the future.

837
00:46:06,360 --> 00:46:09,040
Speaker 2: I don't know. I have my suspicions, but I don't know.

838
00:46:09,560 --> 00:46:10,520
Speaker 2: But it's not there yet.

839
00:46:10,640 --> 00:46:13,640
Speaker 1: So like letting Ai write your closing arguments and not

840
00:46:13,719 --> 00:46:18,239
Speaker 1: even doing a hard edit after the fact is just

841
00:46:18,239 --> 00:46:19,799
Speaker 1: not We're not but let's not do that.

842
00:46:19,800 --> 00:46:21,399
Speaker 2: If you're a lawyer, let's not do that.

843
00:46:25,280 --> 00:46:25,440
Speaker 4: More.

844
00:46:25,440 --> 00:46:38,600
Speaker 2: After a quick break, let's get right back into it.

845
00:46:43,440 --> 00:46:45,919
Speaker 4: Yeah, you know who, I really have not heard enough

846
00:46:45,960 --> 00:46:51,640
Speaker 4: about this week. Really really, I've been really wondering what

847
00:46:51,760 --> 00:46:54,920
Speaker 4: other weird stuff he's been up to on top of

848
00:46:56,040 --> 00:46:59,120
Speaker 4: all the usual bridget what did Elon do?

849
00:46:59,320 --> 00:46:59,640
Speaker 3: Now?

850
00:47:00,120 --> 00:47:01,880
Speaker 2: Well, I'm glad you asked, Joey.

851
00:47:01,960 --> 00:47:05,000
Speaker 1: Do you remember back when Elon Musk was like decided

852
00:47:05,080 --> 00:47:08,080
Speaker 1: that being tough on child sexual abuset material was like

853
00:47:08,120 --> 00:47:12,200
Speaker 1: his thing? He tweeted removing child exploitation as my number

854
00:47:12,239 --> 00:47:14,800
Speaker 1: one priority, and he just started sort of claiming without

855
00:47:14,840 --> 00:47:17,560
Speaker 1: evidence that he was cracking down on child sexual abust

856
00:47:17,600 --> 00:47:20,960
Speaker 1: material on Twitter more than the previous leadership of Twitter,

857
00:47:21,120 --> 00:47:22,600
Speaker 1: and a lot of people just kind of like bought

858
00:47:22,600 --> 00:47:24,040
Speaker 1: into it because he said it, and it's like, oh,

859
00:47:24,080 --> 00:47:26,040
Speaker 1: it must be true, even though that wasn't true.

860
00:47:26,120 --> 00:47:28,279
Speaker 3: Do you remember that, Yes, I do remember that.

861
00:47:28,560 --> 00:47:30,399
Speaker 4: I bet he did a great shot I bet he

862
00:47:30,440 --> 00:47:35,520
Speaker 4: was super successful and he there's actually no more child

863
00:47:35,600 --> 00:47:37,520
Speaker 4: sexual abuse ever in the world.

864
00:47:38,000 --> 00:47:40,000
Speaker 2: That cleaned it right up, got rid of it.

865
00:47:40,080 --> 00:47:42,279
Speaker 1: No no, no, wait, actually I'm seeing here that the

866
00:47:42,320 --> 00:47:46,399
Speaker 1: Australian watchdog e Safety Commission is actually fine Twitter three

867
00:47:46,480 --> 00:47:49,600
Speaker 1: hundred and fifty thousand dollars for failing to explain how

868
00:47:49,640 --> 00:47:52,600
Speaker 1: it is handling child sexual abust material on the platform.

869
00:47:52,880 --> 00:47:56,080
Speaker 1: The AP reports that the Commission issued legal transparency notices

870
00:47:56,120 --> 00:47:59,120
Speaker 1: earlier this year to Twitter and other platforms questioning what

871
00:47:59,120 --> 00:48:02,080
Speaker 1: they were doing to tap child sexual exploitation material on

872
00:48:02,080 --> 00:48:06,080
Speaker 1: their platforms, and that Twitter just did not sufficiently answer

873
00:48:06,400 --> 00:48:09,200
Speaker 1: and now they are getting this fine. Twitter apparently was

874
00:48:09,239 --> 00:48:12,040
Speaker 1: the worst defender. They provided no answers to some of

875
00:48:12,040 --> 00:48:15,520
Speaker 1: the questions, including questions like how many staff remained on

876
00:48:15,560 --> 00:48:17,719
Speaker 1: the Trust and Safety team that took on the work

877
00:48:17,800 --> 00:48:20,719
Speaker 1: preventing harmful and illegal contents it's must took over in

878
00:48:20,880 --> 00:48:24,000
Speaker 1: Monngrant from the Commission said, I think there's a degree

879
00:48:24,040 --> 00:48:26,959
Speaker 1: of defiance there, which like, yeah, I agree, elon Musk

880
00:48:27,040 --> 00:48:29,920
Speaker 1: being defiant of like something he has to do. Surprise surprise,

881
00:48:30,160 --> 00:48:33,520
Speaker 1: Grant says, if you've got basic human resources or payroll

882
00:48:33,880 --> 00:48:36,959
Speaker 1: you should know how many people are on each team. Yeah,

883
00:48:37,040 --> 00:48:39,440
Speaker 1: I agree, it seems pretty straightforward, doesn't seem like a

884
00:48:39,440 --> 00:48:40,400
Speaker 1: complicated question.

885
00:48:40,520 --> 00:48:42,000
Speaker 2: But Elon Muskriff used to.

886
00:48:41,960 --> 00:48:46,920
Speaker 4: Answer, I really do not understand how Twitter is still

887
00:48:46,960 --> 00:48:49,080
Speaker 4: like functioning as a website right now.

888
00:48:49,160 --> 00:48:50,640
Speaker 3: I feel like every.

889
00:48:51,880 --> 00:48:54,560
Speaker 4: Every week there's been another thing where they've been like, hey,

890
00:48:54,920 --> 00:48:56,839
Speaker 4: where are employees doing this thing?

891
00:48:56,880 --> 00:48:59,600
Speaker 3: And it's like, what you.

892
00:48:59,600 --> 00:49:02,359
Speaker 4: Mean those guys we fired a couple of months ago,

893
00:49:02,800 --> 00:49:06,839
Speaker 4: Like I somehow it's still up. So I'm sure they're

894
00:49:07,040 --> 00:49:10,839
Speaker 4: they have, but I wow, yeah, not surprised.

895
00:49:11,200 --> 00:49:14,279
Speaker 1: Not only is it still up, Joey, but Twitter is

896
00:49:14,440 --> 00:49:18,560
Speaker 1: rolling out a new program to combat bots in New

897
00:49:18,640 --> 00:49:21,200
Speaker 1: Zealand and the Philippines where you will have to pay

898
00:49:21,239 --> 00:49:24,879
Speaker 1: a dollar a year to make tweets. You can read

899
00:49:24,880 --> 00:49:26,880
Speaker 1: tweets for free, but you have to pay a dollar

900
00:49:27,000 --> 00:49:30,120
Speaker 1: a year to make tweets. Which my favorite response and

901
00:49:30,160 --> 00:49:32,040
Speaker 1: I saw about this on Twitter, was from one of

902
00:49:32,080 --> 00:49:35,360
Speaker 1: my favorite comedians, Vinnie Thomas. A dollar a year, brother,

903
00:49:35,480 --> 00:49:38,319
Speaker 1: I would not pay an acorn a decade.

904
00:49:40,160 --> 00:49:41,840
Speaker 3: Yeah, I'm sorry.

905
00:49:42,080 --> 00:49:44,920
Speaker 4: If not ever, it's up here in the US, like

906
00:49:44,960 --> 00:49:47,080
Speaker 4: that's it for me. That is officially when I'm deleted

907
00:49:47,080 --> 00:49:50,200
Speaker 4: by Twitter. I'm not giving Elon Musk a dollar. I mean,

908
00:49:50,239 --> 00:49:53,760
Speaker 4: I get no, like I would not give him a penny.

909
00:49:53,880 --> 00:49:55,440
Speaker 4: That is too much to tweet.

910
00:49:56,320 --> 00:49:57,040
Speaker 2: No.

911
00:49:57,040 --> 00:50:00,239
Speaker 1: No, but like I have such I mean, we'll your

912
00:50:00,280 --> 00:50:04,520
Speaker 1: all night. I have such big feelings about this. Fundamentally,

913
00:50:04,960 --> 00:50:07,400
Speaker 1: when you sign on to a social media platform, we

914
00:50:07,520 --> 00:50:11,400
Speaker 1: are the product our data, information about us that like

915
00:50:11,920 --> 00:50:16,080
Speaker 1: our eyeballs and ear holes, absorbing advertisement. That is the

916
00:50:16,600 --> 00:50:18,399
Speaker 1: whether we Whether I like it or not, I don't

917
00:50:18,480 --> 00:50:21,279
Speaker 1: like it, but that is the exchange that you that

918
00:50:21,640 --> 00:50:24,960
Speaker 1: gives you these platforms. I'm not gonna pay a dollar

919
00:50:25,640 --> 00:50:28,799
Speaker 1: a year or any amount of money to have you

920
00:50:29,239 --> 00:50:32,960
Speaker 1: then continue to extract all of my information, everything about

921
00:50:32,960 --> 00:50:34,080
Speaker 1: me to then make more money.

922
00:50:34,120 --> 00:50:34,400
Speaker 2: That's it.

923
00:50:34,400 --> 00:50:36,520
Speaker 1: I'm not paying that. That is a that is as

924
00:50:36,560 --> 00:50:37,520
Speaker 1: a bum deal.

925
00:50:37,800 --> 00:50:40,640
Speaker 4: I'm just imagining like paying to go see a movie

926
00:50:40,800 --> 00:50:42,719
Speaker 4: and you sit in the movie theater and you just

927
00:50:42,880 --> 00:50:48,120
Speaker 4: watch ads for take an hour, and somehow you're paying

928
00:50:48,160 --> 00:50:48,480
Speaker 4: for that.

929
00:50:49,800 --> 00:50:52,360
Speaker 3: It's no, yeah, no.

930
00:50:52,480 --> 00:50:56,520
Speaker 1: And like here's my thing is like I so like

931
00:50:56,640 --> 00:50:58,360
Speaker 1: Elon says, like I have to we have to do

932
00:50:58,400 --> 00:51:01,360
Speaker 1: this to combat bots. That is your job, homie. You

933
00:51:01,440 --> 00:51:03,839
Speaker 1: bought this platform. It is your job to figure that out?

934
00:51:03,840 --> 00:51:07,080
Speaker 1: What about I'm paying to make your plat like you're

935
00:51:07,520 --> 00:51:11,200
Speaker 1: you are paid like people are paid. I'm sure well

936
00:51:11,560 --> 00:51:14,520
Speaker 1: to figure out how to combat box on this platform.

937
00:51:14,640 --> 00:51:16,360
Speaker 2: Don't go in my pockets. I don't I didn't.

938
00:51:16,160 --> 00:51:18,359
Speaker 1: Fucking buy the platform. You did, like you figured this out.

939
00:51:18,360 --> 00:51:20,080
Speaker 1: It is not my job to figure this out for you.

940
00:51:20,080 --> 00:51:21,880
Speaker 1: It's not my job to give you a dollar a

941
00:51:21,960 --> 00:51:24,919
Speaker 1: year nor an acorn a decade to figure it out.

942
00:51:24,920 --> 00:51:26,080
Speaker 2: And I certainly won't.

943
00:51:25,800 --> 00:51:29,600
Speaker 1: Be And yeah, just the thing about him getting fined

944
00:51:29,800 --> 00:51:36,960
Speaker 1: for not complying with this transparency increy into child sexual

945
00:51:36,960 --> 00:51:39,280
Speaker 1: abast material and put it is not the only platform

946
00:51:39,280 --> 00:51:41,720
Speaker 1: that is that is being that is on notice. Google

947
00:51:41,760 --> 00:51:44,239
Speaker 1: also did not comply because they were plot They gave

948
00:51:44,560 --> 00:51:47,400
Speaker 1: generic responses to specific questions, which is like a classic

949
00:51:47,400 --> 00:51:49,640
Speaker 1: Google thing. So they actually had a formal warning, not

950
00:51:49,680 --> 00:51:53,560
Speaker 1: a fine, but Elon Musk kind of touting and puffing

951
00:51:53,600 --> 00:51:55,360
Speaker 1: up this chest and being like, I'm gonna be the

952
00:51:55,360 --> 00:51:58,760
Speaker 1: person who solves child exploitation on the platform. Something about

953
00:51:58,760 --> 00:52:00,719
Speaker 1: this really reminds me of the more panics that we've

954
00:52:00,719 --> 00:52:03,680
Speaker 1: seen around things like trafficking, where folks can just like

955
00:52:03,760 --> 00:52:07,000
Speaker 1: declare themselves the protector of children, like it's some kind

956
00:52:07,000 --> 00:52:09,600
Speaker 1: of self appointed title. So you get to say that

957
00:52:09,680 --> 00:52:13,080
Speaker 1: you're a self appointed protector of children and like do

958
00:52:13,520 --> 00:52:17,359
Speaker 1: nothing to actually protect children and just kind of go

959
00:52:17,440 --> 00:52:20,000
Speaker 1: with go on vibes. I guess I honestly think that

960
00:52:20,040 --> 00:52:23,680
Speaker 1: Elon Musk just decided to say this that he was

961
00:52:23,719 --> 00:52:28,120
Speaker 1: going to like be the person who combated sexual exploitation

962
00:52:28,160 --> 00:52:31,000
Speaker 1: material on the platform as a way to grandstand because

963
00:52:31,040 --> 00:52:32,800
Speaker 1: he knew people would run with it and the press

964
00:52:33,040 --> 00:52:35,080
Speaker 1: would publish it. I mean, they did publish it, and

965
00:52:35,480 --> 00:52:37,520
Speaker 1: then he just kind of dropped it, like he's certainly

966
00:52:37,520 --> 00:52:40,840
Speaker 1: not talking about combating the sexual explanation of children on

967
00:52:40,880 --> 00:52:43,279
Speaker 1: the platform right now. So I guess that's really how

968
00:52:43,360 --> 00:52:45,600
Speaker 1: much he cares about combating that, because he didn't even

969
00:52:45,880 --> 00:52:49,520
Speaker 1: bother to give accurate or even answers at all in

970
00:52:49,560 --> 00:52:51,560
Speaker 1: some cases to this inquiry into it.

971
00:52:52,080 --> 00:52:57,160
Speaker 4: Yeah, it's really a terrifying, depressing pattern of just I

972
00:52:57,200 --> 00:52:59,680
Speaker 4: read what our last big news cycle we were talking

973
00:52:59,680 --> 00:53:03,440
Speaker 4: about the whole Ashton Kutcher thing, and it's like, I

974
00:53:03,560 --> 00:53:07,799
Speaker 4: it's it's depressing, it's it really it's you know what,

975
00:53:07,840 --> 00:53:09,799
Speaker 4: it's good to see that at least he's facing some

976
00:53:09,880 --> 00:53:15,400
Speaker 4: consequences for this, and maybe that's the you know, little

977
00:53:15,400 --> 00:53:17,279
Speaker 4: bit of positivity we can pull out of this. But

978
00:53:17,320 --> 00:53:20,560
Speaker 4: it is and hopefully also, you know what, maybe another

979
00:53:20,600 --> 00:53:22,399
Speaker 4: part of this is, like it does feel like maybe

980
00:53:22,440 --> 00:53:25,360
Speaker 4: we're finally addressing the fact that people just simply saying

981
00:53:25,400 --> 00:53:28,279
Speaker 4: that they're protecting children doesn't necessarily mean they're doing that.

982
00:53:29,200 --> 00:53:34,640
Speaker 4: But yeah, it's it's not surprised that he is, uh,

983
00:53:35,160 --> 00:53:37,399
Speaker 4: that seems to be his emo, is saying he's gonna

984
00:53:37,440 --> 00:53:39,160
Speaker 4: do things and then not doing them.

985
00:53:40,160 --> 00:53:42,680
Speaker 3: So I guess this is on brand.

986
00:53:43,040 --> 00:53:43,920
Speaker 2: It's on brand.

987
00:53:44,520 --> 00:53:47,160
Speaker 1: That is such a positive silver lining, and I do

988
00:53:47,239 --> 00:53:50,000
Speaker 1: have one kind of positive story. I feel like today's

989
00:53:50,000 --> 00:53:53,200
Speaker 1: episode was very like we live in a techno enabled hellscape.

990
00:53:53,360 --> 00:53:55,600
Speaker 1: Like wow, Like I felt like it was like a

991
00:53:55,600 --> 00:53:58,640
Speaker 1: little you know, and it is how I'm feeling. Yeah,

992
00:53:59,360 --> 00:54:03,680
Speaker 1: it's been a u yeah, yeah, So I thought this

993
00:54:03,800 --> 00:54:07,040
Speaker 1: was pretty cool. Stanford is using virtual reality to help

994
00:54:07,080 --> 00:54:11,160
Speaker 1: people who have hoarding disorder practice organizing their spaces and

995
00:54:11,239 --> 00:54:14,520
Speaker 1: like letting things go. A pilot study by Stanford Medicine

996
00:54:14,520 --> 00:54:18,520
Speaker 1: researchers suggests that a virtual reality therapy might allow those

997
00:54:18,560 --> 00:54:21,680
Speaker 1: who have hoarding disorder to rehearse relinquishing possessions and a

998
00:54:21,760 --> 00:54:24,880
Speaker 1: simulation of their own home that could help them declutter

999
00:54:24,920 --> 00:54:28,279
Speaker 1: in real life. The simulations help patients practice organizational and

1000
00:54:28,320 --> 00:54:31,880
Speaker 1: decision making skills learned in cognitive behavioral therapy, currently the

1001
00:54:31,920 --> 00:54:34,759
Speaker 1: standard treatment for hoarding youth disorder, and to sensitize them

1002
00:54:34,800 --> 00:54:37,080
Speaker 1: to the stress that they might feel when discarding things.

1003
00:54:37,160 --> 00:54:39,200
Speaker 1: The results of this pilot program was published in the

1004
00:54:39,200 --> 00:54:42,520
Speaker 1: October issue of the Journal of Psychiatric Research. So hoarding

1005
00:54:42,560 --> 00:54:45,920
Speaker 1: disorder is a mental condition that effects about two point

1006
00:54:45,960 --> 00:54:48,160
Speaker 1: five percent of the United States, which I didn't know

1007
00:54:48,239 --> 00:54:50,600
Speaker 1: it was that high. I think it sounds like it's

1008
00:54:50,640 --> 00:54:53,680
Speaker 1: like kind of a tough issue because of things like

1009
00:54:53,840 --> 00:54:58,080
Speaker 1: shame and stigma, and because like the symptoms of it

1010
00:54:58,160 --> 00:55:00,279
Speaker 1: means that it can be hard to let people in,

1011
00:55:00,360 --> 00:55:03,560
Speaker 1: and so those people could involve first responders. So like,

1012
00:55:03,600 --> 00:55:05,359
Speaker 1: if you have an emergency in your home, it can

1013
00:55:05,400 --> 00:55:08,080
Speaker 1: be hard for first responders to get in, and that

1014
00:55:08,120 --> 00:55:10,920
Speaker 1: can be like specialists who are there to help you

1015
00:55:10,960 --> 00:55:13,839
Speaker 1: with hoarding disorder if those specialists are not able to

1016
00:55:13,840 --> 00:55:17,600
Speaker 1: like physically enter people's homes. Doctor Carolyn Rodriguez, Professor of

1017
00:55:17,640 --> 00:55:21,000
Speaker 1: psychiatry and behavioral sciences and senior author of the study

1018
00:55:21,160 --> 00:55:23,640
Speaker 1: said that some people are in such dire need, but

1019
00:55:23,719 --> 00:55:26,200
Speaker 1: we can't go into their homes. The clutter is stacked

1020
00:55:26,200 --> 00:55:27,920
Speaker 1: so high that it is dangerous for our team to

1021
00:55:27,920 --> 00:55:30,839
Speaker 1: go inside. Yet practicing letting go of items is such

1022
00:55:30,840 --> 00:55:32,920
Speaker 1: a useful skill that we wanted to create a virtual

1023
00:55:32,960 --> 00:55:35,760
Speaker 1: and safe environment. So here's how the pilot program worked.

1024
00:55:36,080 --> 00:55:39,120
Speaker 1: In the study, Rodriguez's team asked nine participants over the

1025
00:55:39,160 --> 00:55:41,920
Speaker 1: age of fifty five with diagnosed hoarding disorder to take

1026
00:55:41,960 --> 00:55:44,760
Speaker 1: photos and videos of the most cluttered room in their house,

1027
00:55:45,080 --> 00:55:47,719
Speaker 1: along with thirty possessions. With the help of a VR

1028
00:55:47,760 --> 00:55:51,520
Speaker 1: company and Stanford University engineering students, the photos and videos

1029
00:55:51,520 --> 00:55:54,960
Speaker 1: were then transformed into custom three D virtual environments. The

1030
00:55:55,000 --> 00:55:58,759
Speaker 1: participants navigated around their homes and manipulated their possessions using

1031
00:55:58,840 --> 00:56:02,960
Speaker 1: VR headsets and hands health controllers. The outcome well Seven

1032
00:56:03,000 --> 00:56:06,320
Speaker 1: of the nine participants improved in self reported hoarding symptoms,

1033
00:56:06,360 --> 00:56:08,759
Speaker 1: with an average decrease of twenty five percent. Eight of

1034
00:56:08,800 --> 00:56:11,360
Speaker 1: the nine participants also had less clutter in their homes

1035
00:56:11,400 --> 00:56:14,640
Speaker 1: based on visual assessments by clinicians, with an average decrease

1036
00:56:14,680 --> 00:56:18,399
Speaker 1: of fifteen percent. Now, these improvements are comparable to those

1037
00:56:18,400 --> 00:56:20,680
Speaker 1: that are found in group therapy alone, so it's not

1038
00:56:20,840 --> 00:56:25,799
Speaker 1: totally clear whether this VR therapy can add value. However, importantly,

1039
00:56:26,120 --> 00:56:29,360
Speaker 1: this small initial trial demonstrated that VR therapy for hoarding

1040
00:56:29,360 --> 00:56:33,200
Speaker 1: disorder is feasible and well tolerated, even in older patients.

1041
00:56:33,239 --> 00:56:35,759
Speaker 1: Like it sounds like they were worried that some of

1042
00:56:35,800 --> 00:56:39,200
Speaker 1: the older folks might be not so sure about trying

1043
00:56:39,239 --> 00:56:41,600
Speaker 1: this new technology with a headset, but in the end

1044
00:56:41,680 --> 00:56:44,560
Speaker 1: they actually ended up liking it. So all of this

1045
00:56:44,600 --> 00:56:48,280
Speaker 1: is to say that as grim as things might seem,

1046
00:56:48,360 --> 00:56:53,080
Speaker 1: sometime technology still can be and very much is used

1047
00:56:53,080 --> 00:56:58,280
Speaker 1: to help people design and architect healthier, happier, brighter, safer

1048
00:56:58,360 --> 00:57:01,640
Speaker 1: futures for themselves. And like, that's what I love about technology.

1049
00:57:02,239 --> 00:57:04,680
Speaker 1: That's the tech future. I think that we should all

1050
00:57:04,719 --> 00:57:07,560
Speaker 1: be looking toward. Yeah, it's not all bad.

1051
00:57:08,040 --> 00:57:08,480
Speaker 3: For sure.

1052
00:57:08,640 --> 00:57:12,400
Speaker 4: Yeah, Yeah, it's nice to hear a story where TECs

1053
00:57:12,440 --> 00:57:15,720
Speaker 4: being used for good and for helping people for once.

1054
00:57:16,880 --> 00:57:18,400
Speaker 3: But yeah, that is really great to hear.

1055
00:57:18,520 --> 00:57:21,520
Speaker 4: And it is like, you know, I don't know as

1056
00:57:21,600 --> 00:57:26,200
Speaker 4: much about like this particular disorder. I didn't realize it was, Yeah,

1057
00:57:26,280 --> 00:57:28,960
Speaker 4: that it affected two point five percent of the US population.

1058
00:57:30,640 --> 00:57:34,240
Speaker 3: But yeah, like all mental health stuff in general.

1059
00:57:34,240 --> 00:57:37,000
Speaker 4: Tends to be stigmatized, and it is like when I again,

1060
00:57:37,040 --> 00:57:39,000
Speaker 4: it's one of those things I wouldn't even really think about,

1061
00:57:39,280 --> 00:57:41,480
Speaker 4: you know, the stigmas behind it, but it is.

1062
00:57:41,600 --> 00:57:45,000
Speaker 3: It's great to hear. It's great to hear that that. Yeah,

1063
00:57:45,120 --> 00:57:47,800
Speaker 3: tech can be a really helpful.

1064
00:57:47,400 --> 00:57:50,200
Speaker 4: Thing and can be a really you know, useful tool,

1065
00:57:50,320 --> 00:57:53,920
Speaker 4: particularly when it comes to people's health and mental health.

1066
00:57:53,960 --> 00:57:57,880
Speaker 3: And yeah, hope to hear more stories like this going forward.

1067
00:57:58,600 --> 00:58:02,280
Speaker 1: Yes, more tech being used to help people build healthier,

1068
00:58:02,280 --> 00:58:06,560
Speaker 1: happier lives. Last tech being used to be awful. Please

1069
00:58:06,960 --> 00:58:11,400
Speaker 1: and thank you, Joey. This was a tough one. I

1070
00:58:11,440 --> 00:58:14,320
Speaker 1: really appreciate you being here. I really appreciate your perspective

1071
00:58:14,400 --> 00:58:17,240
Speaker 1: and you sharing so much of your full self. It's

1072
00:58:17,280 --> 00:58:20,520
Speaker 1: such an honor to be able to unpack all of

1073
00:58:20,560 --> 00:58:22,760
Speaker 1: these stories with you, So I just really appreciate it.

1074
00:58:23,120 --> 00:58:25,280
Speaker 3: Of course, Bridget happy to be on.

1075
00:58:25,360 --> 00:58:27,720
Speaker 4: It's always it's great got to talk about this stuf

1076
00:58:27,720 --> 00:58:28,320
Speaker 4: with you too.

1077
00:58:28,720 --> 00:58:31,040
Speaker 1: And listeners, Thanks so much for being here, Thanks so

1078
00:58:31,160 --> 00:58:34,120
Speaker 1: much for sticking with us. Be well and I will

1079
00:58:34,120 --> 00:58:40,480
Speaker 1: talk to you next week. If you're looking for ways

1080
00:58:40,480 --> 00:58:42,720
Speaker 1: to support the show, check out our March store at

1081
00:58:42,720 --> 00:58:43,720
Speaker 1: tangoti dot com.

1082
00:58:43,720 --> 00:58:44,360
Speaker 2: Slash store.

1083
00:58:45,600 --> 00:58:47,560
Speaker 1: Got a story about an interesting thing in tech? I

1084
00:58:47,680 --> 00:58:49,560
Speaker 1: just want to say Hi. You can reach us at

1085
00:58:49,560 --> 00:58:52,280
Speaker 1: Hello at tenggodi dot com. You can also find transcripts

1086
00:58:52,280 --> 00:58:54,760
Speaker 1: for today's episode at tengody dot com. There Are No

1087
00:58:54,800 --> 00:58:56,880
Speaker 1: Girls on the Internet was created by me Bridget Time.

1088
00:58:57,280 --> 00:59:00,480
Speaker 1: It's a production of iHeartRadio and Unboss Creative, edited by

1089
00:59:00,520 --> 00:59:04,560
Speaker 1: Joey pat Jonathan Strickland is our executive producer. Tary Harrison

1090
00:59:04,640 --> 00:59:07,400
Speaker 1: is our producer and sound engineer. Michael Amado is our

1091
00:59:07,440 --> 00:59:10,480
Speaker 1: contributing producer. I'm your host, Bridget Todd. If you want

1092
00:59:10,480 --> 00:59:12,920
Speaker 1: to help us grow, rate and review us on Apple Podcasts.

1093
00:59:13,680 --> 00:59:16,520
Speaker 1: For more podcasts from iHeartRadio, check out the iHeartRadio app,

1094
00:59:16,520 --> 00:59:22,280
Speaker 1: Apple Podcasts, or wherever you get your podcasts.