1
00:00:08,880 --> 00:00:12,799
Speaker 1: The heartbreaking videos and images from the ongoing fires in

2
00:00:12,840 --> 00:00:16,920
Speaker 1: Los Angeles are filling up social media. A number of

3
00:00:16,920 --> 00:00:20,600
Speaker 1: them are claiming to show the iconic Hollywood Sign on

4
00:00:20,760 --> 00:00:21,919
Speaker 1: fire last night.

5
00:00:22,320 --> 00:00:25,160
Speaker 2: Earlier this year, a bunch of videos went viral showing

6
00:00:25,200 --> 00:00:27,200
Speaker 2: the Hollywood Sign on fire.

7
00:00:27,320 --> 00:00:29,680
Speaker 3: Literally like the Hollywood Sign, it was burning, it was

8
00:00:29,720 --> 00:00:32,720
Speaker 3: burning yesterday, burning like what is going on?

9
00:00:32,840 --> 00:00:34,120
Speaker 4: It looked like the apocalypse.

10
00:00:35,120 --> 00:00:38,360
Speaker 2: They were posted in January when fires were raging across

11
00:00:38,560 --> 00:00:42,479
Speaker 2: LA where I live. This was a scary time and

12
00:00:42,560 --> 00:00:44,680
Speaker 2: those videos only made things worse.

13
00:00:45,360 --> 00:00:48,640
Speaker 4: These viral images that we see of the Hollywood Sign

14
00:00:48,720 --> 00:00:52,400
Speaker 4: on fire actually started to spread on social media as

15
00:00:52,479 --> 00:00:54,920
Speaker 4: Los Angeles in battles one of its worst fires in

16
00:00:55,000 --> 00:00:55,920
Speaker 4: all of its history.

17
00:00:56,160 --> 00:00:59,080
Speaker 2: There were different versions. Some of the videos just showed

18
00:00:59,120 --> 00:01:01,840
Speaker 2: fire on the hill low the letters, and in other

19
00:01:01,960 --> 00:01:03,960
Speaker 2: videos the letters themselves were burning.

20
00:01:04,319 --> 00:01:06,560
Speaker 3: When we saw the posts on Instagram, we were devastated.

21
00:01:06,600 --> 00:01:09,440
Speaker 3: We lived here all our lives and when we saw

22
00:01:09,480 --> 00:01:12,000
Speaker 3: that on Instagram, that broke our hearts. So we wanted

23
00:01:12,040 --> 00:01:15,080
Speaker 3: to come and see for as time, and we're really

24
00:01:15,080 --> 00:01:18,000
Speaker 3: shocked that the there's no fires, there's no fires, and

25
00:01:18,040 --> 00:01:19,959
Speaker 3: they're taking it basically.

26
00:01:20,520 --> 00:01:24,199
Speaker 2: So those videos were all fake. They were generated by AI.

27
00:01:24,720 --> 00:01:26,640
Speaker 2: If you saw these videos when they first came out,

28
00:01:26,959 --> 00:01:29,640
Speaker 2: maybe you already knew they were fake. But what you

29
00:01:29,720 --> 00:01:32,560
Speaker 2: might not know is how much money these videos can

30
00:01:32,600 --> 00:01:35,600
Speaker 2: make for their creators. And if the online course that

31
00:01:35,680 --> 00:01:38,000
Speaker 2: teaches you how to make these videos is to be believed,

32
00:01:38,520 --> 00:01:42,160
Speaker 2: you can make over five thousand dollars a month. Videos

33
00:01:42,240 --> 00:01:44,800
Speaker 2: like the Hollywood Sign burning are part of a bigger

34
00:01:44,840 --> 00:01:48,080
Speaker 2: phenomenon that is probably filling up your feed right now.

35
00:01:48,720 --> 00:01:50,840
Speaker 2: There's a word for this slap.

36
00:01:51,760 --> 00:01:55,040
Speaker 5: I actually don't know where it came from. Like I

37
00:01:55,080 --> 00:01:57,720
Speaker 5: had been calling it AI spam, I was writing about

38
00:01:57,720 --> 00:02:02,440
Speaker 5: it before it was called AI, and then someone on

39
00:02:02,480 --> 00:02:05,400
Speaker 5: Twitter I think, could just start calling it slop, and

40
00:02:05,440 --> 00:02:08,120
Speaker 5: I feel like slop is a better term for it.

41
00:02:08,520 --> 00:02:10,960
Speaker 5: There's a lot of different types of AI slop at

42
00:02:10,960 --> 00:02:14,240
Speaker 5: this point, but basically it is an AI generated image

43
00:02:14,600 --> 00:02:19,080
Speaker 5: or video that is designed to go viral on social media.

44
00:02:19,880 --> 00:02:22,959
Speaker 2: Jason Kevler is my friend and former colleague from back

45
00:02:23,000 --> 00:02:26,160
Speaker 2: when we both worked advice. Since then, he co founded

46
00:02:26,160 --> 00:02:28,720
Speaker 2: a site called four or for Media, and pretty much

47
00:02:28,800 --> 00:02:31,480
Speaker 2: right out the gate this stuff turned into one of

48
00:02:31,480 --> 00:02:34,280
Speaker 2: his beats. You're one of the first people who was

49
00:02:34,360 --> 00:02:38,880
Speaker 2: really documenting AI slap before it really truly blew up.

50
00:02:39,280 --> 00:02:41,560
Speaker 5: Yeah, I mean I'm obsessed with it. I've been obsessed

51
00:02:41,560 --> 00:02:44,160
Speaker 5: with it since the get go. I've just found it

52
00:02:44,240 --> 00:02:49,359
Speaker 5: to be like very fascinating to cover because I can

53
00:02:49,440 --> 00:02:54,040
Speaker 5: kind of like watch in real time as people lose

54
00:02:54,120 --> 00:02:56,239
Speaker 5: touch with reality. To be honest with you.

55
00:02:58,280 --> 00:03:00,160
Speaker 2: I don't know if I'm quite as obsessed with with

56
00:03:00,200 --> 00:03:03,240
Speaker 2: this stuff as Jason is. But then again, he was

57
00:03:03,240 --> 00:03:06,799
Speaker 2: looking at golden Jesus helicopters and I'm here looking at

58
00:03:06,880 --> 00:03:10,920
Speaker 2: fake fires. But when I started investigating, I realized that

59
00:03:10,960 --> 00:03:13,280
Speaker 2: the stuff that he was seeing and the stuff that

60
00:03:13,320 --> 00:03:16,000
Speaker 2: I was watching, we're all part of the same machine.

61
00:03:16,480 --> 00:03:18,520
Speaker 2: And I managed to talk to one of the people

62
00:03:18,600 --> 00:03:32,280
Speaker 2: behind it. I'm afraid from Kaleidoscope and iHeart podcasts. This

63
00:03:34,400 --> 00:03:39,240
Speaker 2: is kill Switch. I'm Dexter Thomas, I'm Chari.

64
00:04:02,720 --> 00:04:02,880
Speaker 6: Buy.

65
00:04:06,760 --> 00:04:09,200
Speaker 2: When did you start writing about AI slab?

66
00:04:10,280 --> 00:04:13,480
Speaker 5: Yeah, it was December twenty twenty three. One of our

67
00:04:13,520 --> 00:04:18,479
Speaker 5: readers posted this image of a guy in the United

68
00:04:18,600 --> 00:04:23,520
Speaker 5: Kingdom who carves dogs out of wood like with a chainsaw,

69
00:04:24,200 --> 00:04:28,240
Speaker 5: and this reader had noticed that there were all these

70
00:04:28,279 --> 00:04:35,160
Speaker 5: copycats of this one guy's dog wood carvings. Basically, there

71
00:04:35,160 --> 00:04:38,360
Speaker 5: were these Facebook pages that were posting dozens and dozens

72
00:04:38,400 --> 00:04:43,040
Speaker 5: of different versions of the original photos that he was uploading.

73
00:04:43,080 --> 00:04:46,040
Speaker 5: And so in some images it's like the guy would

74
00:04:46,040 --> 00:04:48,760
Speaker 5: be would have a goatee. In some images, the guy

75
00:04:48,800 --> 00:04:52,479
Speaker 5: would look Latino. In some images, the guy would be

76
00:04:52,520 --> 00:04:55,800
Speaker 5: a woman. In some images, the dog would be a

77
00:04:55,800 --> 00:04:58,640
Speaker 5: German shepherd instead of like, you know, a Golden Retriever.

78
00:04:59,480 --> 00:05:02,320
Speaker 5: And it was very obvious that they had been modified

79
00:05:02,320 --> 00:05:02,799
Speaker 5: by AI.

80
00:05:03,600 --> 00:05:06,720
Speaker 2: This stuff sounds pretty innocuous, and I guess it was.

81
00:05:07,240 --> 00:05:10,120
Speaker 2: Back in twenty twenty three. Image to image generators like

82
00:05:10,200 --> 00:05:14,159
Speaker 2: Dolly and Microsoft's Being Image Generator were still kind of novel,

83
00:05:14,640 --> 00:05:17,400
Speaker 2: and if someone wanted to use that to make variations

84
00:05:17,400 --> 00:05:21,000
Speaker 2: on existing images of chainsaw wood carvings, I mean, that's

85
00:05:21,120 --> 00:05:24,320
Speaker 2: not really my thing, but hey, if people are into it, whatever.

86
00:05:24,720 --> 00:05:27,000
Speaker 2: It was just kind of a.

87
00:05:26,920 --> 00:05:30,440
Speaker 5: Lot at first. This meant a lot of people were

88
00:05:30,560 --> 00:05:35,520
Speaker 5: using these aiimage generators and they were creating Facebook pages

89
00:05:35,880 --> 00:05:39,320
Speaker 5: and then posting I don't know, twenty thirty forty times

90
00:05:39,320 --> 00:05:42,960
Speaker 5: a day, and each page would have a theme. So

91
00:05:43,320 --> 00:05:46,960
Speaker 5: one of the themes would be like beautiful log cabins.

92
00:05:47,320 --> 00:05:51,480
Speaker 5: So a person would generate one hundred log cabins using

93
00:05:51,520 --> 00:05:54,840
Speaker 5: these aiimage generators and then they would post them on Facebook.

94
00:05:55,440 --> 00:05:58,479
Speaker 2: But his AI tools got better, and these Facebook pages

95
00:05:58,560 --> 00:06:04,960
Speaker 2: became more viral, the AI slap became more targeted and weirder.

96
00:06:06,120 --> 00:06:09,440
Speaker 5: The moment that this became really mainstream, in my opinion,

97
00:06:10,760 --> 00:06:16,840
Speaker 5: was this moment of shrimp Jesus and shrimp Jesus. Oh

98
00:06:16,880 --> 00:06:21,000
Speaker 5: we go right in Jesus, I mean, I think so.

99
00:06:21,000 --> 00:06:23,240
Speaker 5: So for a while, there were all of these images

100
00:06:23,240 --> 00:06:27,359
Speaker 5: of Jesus, this sort of stereotypical white Jesus, long hair,

101
00:06:28,080 --> 00:06:33,400
Speaker 5: and people were just posting hundreds of images of Jesus

102
00:06:33,440 --> 00:06:36,920
Speaker 5: in different situations and then the caption would say please

103
00:06:36,960 --> 00:06:39,320
Speaker 5: give me an amen. They would be asking people to

104
00:06:39,320 --> 00:06:41,880
Speaker 5: comment on this, which would boost in the algorithm, and

105
00:06:42,000 --> 00:06:43,960
Speaker 5: none of it was real. It was all AI generated.

106
00:06:44,400 --> 00:06:47,440
Speaker 5: There was a lot of images of Jesus sand sculptures,

107
00:06:47,680 --> 00:06:51,040
Speaker 5: and then the caption would be like only true believers

108
00:06:51,080 --> 00:06:54,320
Speaker 5: will love my art or something like that. And then

109
00:06:55,440 --> 00:07:02,520
Speaker 5: there was this one image where Jesus was floating above

110
00:07:02,600 --> 00:07:07,760
Speaker 5: the ocean and he had the face of Jesus but

111
00:07:07,880 --> 00:07:12,920
Speaker 5: the arms of shrimp. It was basically like an iracnid

112
00:07:13,160 --> 00:07:15,640
Speaker 5: Jesus with like six arms and they were all made

113
00:07:15,640 --> 00:07:18,680
Speaker 5: of shrimp. And it was just like obviously insane, like

114
00:07:18,720 --> 00:07:21,400
Speaker 5: an insane image, something that a human I don't think

115
00:07:21,440 --> 00:07:24,560
Speaker 5: would probably ever think up on their own. And this

116
00:07:24,640 --> 00:07:28,240
Speaker 5: image had millions of likes on Facebook, and there were

117
00:07:28,280 --> 00:07:30,680
Speaker 5: a bunch of different versions of it. It just went

118
00:07:30,840 --> 00:07:35,920
Speaker 5: incredibly viral and weirdly, like a lot of the comments

119
00:07:35,920 --> 00:07:39,720
Speaker 5: were not even about the fact that Jesus was a shrimp.

120
00:07:40,240 --> 00:07:44,200
Speaker 5: It was just like, amen, I love God, things like that,

121
00:07:44,480 --> 00:07:46,960
Speaker 5: and so, I mean, I don't think people thought it

122
00:07:47,040 --> 00:07:49,680
Speaker 5: was real, but it clearly didn't matter to a lot

123
00:07:49,720 --> 00:07:53,080
Speaker 5: of people that this was just like an absurd image.

124
00:07:53,640 --> 00:07:57,320
Speaker 2: It sounds like shrimp Jesus was kind of the turning

125
00:07:57,400 --> 00:08:02,160
Speaker 2: point for Ais. I don't want to say the genesis necessarily,

126
00:08:02,160 --> 00:08:04,040
Speaker 2: I don't want to get too biblical with this, but

127
00:08:04,680 --> 00:08:07,360
Speaker 2: when I read your article on shrimp Jesus, I think

128
00:08:07,400 --> 00:08:13,000
Speaker 2: that is when I really truly realized, Okay, something really

129
00:08:13,080 --> 00:08:14,600
Speaker 2: really strange is happening here.

130
00:08:15,480 --> 00:08:20,200
Speaker 5: Yeah, it was very interesting that this was happening on Facebook. First, like,

131
00:08:20,280 --> 00:08:23,880
Speaker 5: Facebook is a really old social network at this point,

132
00:08:24,320 --> 00:08:28,040
Speaker 5: it's not cool anymore. Like, I don't know a lot

133
00:08:28,080 --> 00:08:31,040
Speaker 5: of people who use Facebook in the same way that

134
00:08:31,080 --> 00:08:33,240
Speaker 5: they might have in like two thousand and eight, and

135
00:08:33,280 --> 00:08:36,280
Speaker 5: the people that I do know who use it are

136
00:08:36,360 --> 00:08:42,360
Speaker 5: generally older and therefore, I mean, perhaps more susceptible to

137
00:08:42,520 --> 00:08:46,720
Speaker 5: fake AI images. And then I wrote that article, and

138
00:08:46,760 --> 00:08:50,800
Speaker 5: there was also some different meme accounts on Instagram and

139
00:08:50,920 --> 00:08:56,760
Speaker 5: on Twitter who took screenshots of shrimp Jesus, and they

140
00:08:56,800 --> 00:09:00,960
Speaker 5: started saying Facebook is cooked. Facebook is became a meme

141
00:09:01,640 --> 00:09:05,440
Speaker 5: meaning look at what's happening over on Facebook. All the

142
00:09:05,480 --> 00:09:10,240
Speaker 5: old people are getting tricked into liking this absurd stuff.

143
00:09:11,120 --> 00:09:16,720
Speaker 5: And so that is a moment where AI slop escaped Facebook.

144
00:09:18,120 --> 00:09:21,040
Speaker 2: Shrimp Jesus went viral in April of twenty twenty four.

145
00:09:21,679 --> 00:09:24,200
Speaker 2: At the time, I remember thinking it was pretty funny.

146
00:09:24,320 --> 00:09:27,280
Speaker 2: I actually interviewed Jason about it and we basically spent

147
00:09:27,440 --> 00:09:31,679
Speaker 2: half an hour just laughing. But now, just a year later,

148
00:09:32,280 --> 00:09:36,800
Speaker 2: AI slap isn't only on Facebook tricking our parents. It's everywhere,

149
00:09:37,440 --> 00:09:40,640
Speaker 2: and it's not just bizarre or obviously fake stuff like

150
00:09:40,679 --> 00:09:44,480
Speaker 2: shrimp Jesus anymore. Some of those fake la fire videos

151
00:09:44,600 --> 00:09:48,160
Speaker 2: looked real, and they fooled a lot of people, so.

152
00:09:48,160 --> 00:09:50,240
Speaker 3: Which came right here just to check out the fires,

153
00:09:50,360 --> 00:09:53,520
Speaker 3: and there's nothing burnie in Hollywood.

154
00:09:53,559 --> 00:09:56,440
Speaker 5: The sign like you was shown on TV last night.

155
00:09:56,679 --> 00:10:00,280
Speaker 3: You guys should help each other out instead of trying

156
00:10:00,320 --> 00:10:05,280
Speaker 3: to create false narratives and trying to promote bus, you know,

157
00:10:06,160 --> 00:10:08,240
Speaker 3: help help each other out. It's not it's not it's

158
00:10:08,280 --> 00:10:08,640
Speaker 3: not right.

159
00:10:09,280 --> 00:10:13,520
Speaker 2: This is the latest iteration of AI content, more realistic,

160
00:10:14,000 --> 00:10:17,280
Speaker 2: more targeted, and tied to real world events.

161
00:10:17,880 --> 00:10:21,120
Speaker 5: That's the scary thing about it, right, is that when

162
00:10:21,120 --> 00:10:24,679
Speaker 5: I first started writing about this, there was almost nothing

163
00:10:25,880 --> 00:10:28,840
Speaker 5: that was political or tied to the news in any way.

164
00:10:29,400 --> 00:10:32,720
Speaker 5: It was almost all like, look at this crazy food,

165
00:10:33,320 --> 00:10:39,200
Speaker 5: look at this amazing futuristic sci fi scenescape, look at

166
00:10:39,280 --> 00:10:43,880
Speaker 5: shrimp Jesus, look at this sand sculpture. And then what

167
00:10:44,000 --> 00:10:48,920
Speaker 5: has happened is the people making this stuff have realized

168
00:10:48,960 --> 00:10:52,680
Speaker 5: that they can get more attention if they start tying

169
00:10:52,720 --> 00:10:54,320
Speaker 5: it to the news in some way.

170
00:10:56,160 --> 00:10:58,679
Speaker 2: So one night, as the fires were still burning in La,

171
00:10:58,920 --> 00:11:02,200
Speaker 2: I opened up Instagram, and this was kind of everyone's

172
00:11:02,200 --> 00:11:05,240
Speaker 2: way of communicating, and it was also kind of a lifeline.

173
00:11:05,679 --> 00:11:07,840
Speaker 2: When you look at someone's stories, you never knew if

174
00:11:07,880 --> 00:11:10,000
Speaker 2: it was going to be them saying, hey, I'm okay,

175
00:11:10,080 --> 00:11:12,040
Speaker 2: I'm safe, or if it was going to be them

176
00:11:12,320 --> 00:11:16,360
Speaker 2: showing their house burning down. So I'm scrolling through and

177
00:11:16,600 --> 00:11:18,680
Speaker 2: I see this video of animals that are in a

178
00:11:18,720 --> 00:11:23,400
Speaker 2: burning forest and there's firefighters saving the baby animals. There's

179
00:11:23,400 --> 00:11:27,160
Speaker 2: a firefighter holding these two baby bear cubs and carrying

180
00:11:27,160 --> 00:11:30,520
Speaker 2: them out of the flames. Pretty quickly, I realized, wait

181
00:11:30,520 --> 00:11:32,600
Speaker 2: a second, this is fake. And then I look at

182
00:11:32,600 --> 00:11:37,040
Speaker 2: the view count. It's in the millions and there's thousands

183
00:11:37,080 --> 00:11:40,920
Speaker 2: of comments. I get curious and I look at the

184
00:11:41,000 --> 00:11:46,480
Speaker 2: username future rider US. That's kind of weird. So I

185
00:11:46,520 --> 00:11:49,640
Speaker 2: look at the post history, and most of the posts

186
00:11:49,720 --> 00:11:54,439
Speaker 2: were of these AI motorcycles that were riding through futuristic landscapes,

187
00:11:55,200 --> 00:11:58,280
Speaker 2: so the name makes sense for those. But I scroll

188
00:11:58,400 --> 00:12:00,319
Speaker 2: up and I see that as soon who as the

189
00:12:00,360 --> 00:12:04,640
Speaker 2: fire started, they posted a fake Hollywood sign burning video

190
00:12:05,120 --> 00:12:07,800
Speaker 2: that got them a million views, and that was their

191
00:12:07,840 --> 00:12:11,560
Speaker 2: biggest success to that point, and they just kept posting

192
00:12:11,640 --> 00:12:12,800
Speaker 2: fire content after that.

193
00:12:14,440 --> 00:12:16,560
Speaker 5: The thing that's happened alongside of that is the AI

194
00:12:16,679 --> 00:12:18,760
Speaker 5: has gotten a lot better. The AI has gotten a

195
00:12:18,760 --> 00:12:19,800
Speaker 5: lot more convincing.

196
00:12:20,880 --> 00:12:22,560
Speaker 2: I said, I was able to tell this it's fake,

197
00:12:22,920 --> 00:12:26,079
Speaker 2: but it took me a second. And the comments are

198
00:12:26,160 --> 00:12:29,600
Speaker 2: kind of mixed. There's some people who are completely unaware

199
00:12:29,640 --> 00:12:32,000
Speaker 2: that this stuff is fake and saying things like, Wow,

200
00:12:32,040 --> 00:12:34,679
Speaker 2: look at these brave firefighters. I'm so glad they're helping

201
00:12:34,679 --> 00:12:38,800
Speaker 2: the animals. But there's other people who are posting angry

202
00:12:38,880 --> 00:12:42,640
Speaker 2: comments like how dare you make fake content about this disaster?

203
00:12:44,920 --> 00:12:46,600
Speaker 5: And so now you have a lot of people who

204
00:12:46,640 --> 00:12:50,680
Speaker 5: are making stuff that is designed to hit the news

205
00:12:50,720 --> 00:12:55,800
Speaker 5: cycle in some way, to upset people, to enrage people,

206
00:12:56,760 --> 00:13:00,280
Speaker 5: or to trick them. It's not just on face Book.

207
00:13:00,320 --> 00:13:03,440
Speaker 5: It's on YouTube, it's on TikTok, It's on Instagram. You know,

208
00:13:03,480 --> 00:13:06,880
Speaker 5: I've even seen it on Pinterest and LinkedIn. So it's

209
00:13:06,920 --> 00:13:09,839
Speaker 5: really become a strategy for people who want to make

210
00:13:09,880 --> 00:13:11,320
Speaker 5: money on the internet at this point.

211
00:13:12,520 --> 00:13:16,960
Speaker 2: Yeah, it's weird because it seemed like everything trickled down

212
00:13:17,040 --> 00:13:20,200
Speaker 2: to Facebook in the past few years. Good features from

213
00:13:20,200 --> 00:13:23,600
Speaker 2: somewhere else eventually make it over to Facebook. Information that

214
00:13:23,679 --> 00:13:27,000
Speaker 2: first happens on Twitter, because it's really real time, eventually

215
00:13:27,000 --> 00:13:30,240
Speaker 2: makes it over to Facebook. It's not like this really

216
00:13:30,280 --> 00:13:34,120
Speaker 2: weird thing that has started on Facebook is spread out

217
00:13:34,520 --> 00:13:35,480
Speaker 2: to the rest of the world.

218
00:13:35,559 --> 00:13:38,720
Speaker 5: It's the first time Facebook's irrelevant in like a decade.

219
00:13:40,200 --> 00:13:42,960
Speaker 2: This is the innovation that's happening on Facebook. No joke.

220
00:13:43,160 --> 00:13:47,080
Speaker 2: Yeah is aislab. But when was it that you first

221
00:13:47,160 --> 00:13:51,800
Speaker 2: started seeing stuff that was realistic and was directly tied

222
00:13:51,840 --> 00:13:54,520
Speaker 2: to actual events that were happening in the real world.

223
00:13:55,720 --> 00:14:00,520
Speaker 5: There was this moment where in Israel's invasion of Gaza,

224
00:14:01,800 --> 00:14:05,480
Speaker 5: there was that moment where they went into Rafa and

225
00:14:06,440 --> 00:14:10,320
Speaker 5: there was an AI generated image called all Eyes on Rafa.

226
00:14:11,000 --> 00:14:12,120
Speaker 2: Can you describe the image?

227
00:14:12,240 --> 00:14:16,560
Speaker 5: Yeah, So it was huge font and it said all

228
00:14:16,600 --> 00:14:21,760
Speaker 5: eyes on Rafa. There was like a bunch of tents

229
00:14:22,240 --> 00:14:25,600
Speaker 5: and what looked to be like a refugee camp. And

230
00:14:27,520 --> 00:14:33,400
Speaker 5: this was shared like tens of millions of times on Instagram.

231
00:14:33,560 --> 00:14:35,680
Speaker 5: A lot of celebrities shared it. There was a bunch

232
00:14:35,720 --> 00:14:39,040
Speaker 5: of people writing about it. So I started looking for

233
00:14:39,080 --> 00:14:43,640
Speaker 5: where it came from, and I found this group on

234
00:14:43,720 --> 00:14:50,320
Speaker 5: Facebook for AI creators in Malaysia and they were testing

235
00:14:50,480 --> 00:14:55,080
Speaker 5: all of these different versions of AI generated images about

236
00:14:55,200 --> 00:14:59,280
Speaker 5: the war in Gaza, and the all Eyes on Rafa

237
00:15:00,080 --> 00:15:03,840
Speaker 5: image came from that Facebook group. So that was the

238
00:15:03,840 --> 00:15:08,320
Speaker 5: first time that I ever saw AI spam intersect directly

239
00:15:08,440 --> 00:15:11,760
Speaker 5: with the news, and it was interesting because in that

240
00:15:11,840 --> 00:15:14,600
Speaker 5: group they were talking about the all eyes on Rafa

241
00:15:15,000 --> 00:15:19,480
Speaker 5: image and how viral it went, and we're like, maybe

242
00:15:19,560 --> 00:15:22,320
Speaker 5: we can reverse engineer this, maybe we can do this

243
00:15:22,880 --> 00:15:26,040
Speaker 5: over and over and over again. A month after that,

244
00:15:26,080 --> 00:15:29,640
Speaker 5: I figured out how people were making money with these

245
00:15:29,640 --> 00:15:32,680
Speaker 5: images and why and the whole strategy behind it.

246
00:15:33,760 --> 00:15:36,480
Speaker 2: Who's behind these posts and how do they make money.

247
00:15:37,120 --> 00:15:50,480
Speaker 2: We'll get into that after the break. One of the

248
00:15:50,520 --> 00:15:53,720
Speaker 2: disconnects that I've been seeing just in my own reporting

249
00:15:54,520 --> 00:15:59,560
Speaker 2: is that I think there is an awareness growing among

250
00:15:59,680 --> 00:16:04,040
Speaker 2: some people that AI generated images are a thing, and

251
00:16:04,360 --> 00:16:08,880
Speaker 2: that it's not always obvious if something is AI. But

252
00:16:10,040 --> 00:16:12,880
Speaker 2: I think a lot of people don't necessarily realize why

253
00:16:12,920 --> 00:16:15,880
Speaker 2: this is being made, what motivation there might be.

254
00:16:16,040 --> 00:16:20,160
Speaker 5: For a very long time. I and also the experts

255
00:16:20,200 --> 00:16:22,440
Speaker 5: that I spoke to, One thing that we couldn't figure

256
00:16:22,440 --> 00:16:25,120
Speaker 5: out was like, why are they doing this? Like what

257
00:16:25,320 --> 00:16:29,040
Speaker 5: is the scam here? Because there was no obvious way

258
00:16:29,040 --> 00:16:32,400
Speaker 5: that it was being monetized. For months, I thought that

259
00:16:32,440 --> 00:16:35,760
Speaker 5: people were doing this and trying to make money off

260
00:16:36,120 --> 00:16:38,360
Speaker 5: of Facebook's platform in some way. I thought they were

261
00:16:38,400 --> 00:16:40,360
Speaker 5: trying to hack people I thought they were trying to

262
00:16:40,400 --> 00:16:43,400
Speaker 5: push them off the website to steal their credit card

263
00:16:43,480 --> 00:16:47,000
Speaker 5: information or something like that. But all along they were

264
00:16:47,040 --> 00:16:51,480
Speaker 5: just getting paid directly by Facebook because these images were

265
00:16:51,480 --> 00:16:52,240
Speaker 5: going viral.

266
00:16:54,000 --> 00:16:57,680
Speaker 2: These creators don't need to scam anybody. Having a viral

267
00:16:57,800 --> 00:17:00,200
Speaker 2: video is enough to make a lot of money.

268
00:17:00,560 --> 00:17:05,400
Speaker 5: Facebook has this thing called the Creator Bonus Program, and

269
00:17:06,200 --> 00:17:10,679
Speaker 5: it basically pays people a sliver of ad revenue for

270
00:17:11,440 --> 00:17:12,840
Speaker 5: posts that get engagement.

271
00:17:14,240 --> 00:17:18,080
Speaker 2: How much money can you make? Meta doesn't publish those numbers,

272
00:17:18,480 --> 00:17:21,560
Speaker 2: but I asked a few influencers and recently the rate

273
00:17:21,600 --> 00:17:23,639
Speaker 2: seemed to be around one hundred to one hundred and

274
00:17:23,640 --> 00:17:25,200
Speaker 2: twenty dollars per million views.

275
00:17:25,800 --> 00:17:28,399
Speaker 5: It's become a job to be totally honest with you.

276
00:17:28,600 --> 00:17:32,480
Speaker 5: It's pretty crazy because there's there's like this one example

277
00:17:33,880 --> 00:17:39,080
Speaker 5: of a guy who quit his job in India. He

278
00:17:39,200 --> 00:17:41,560
Speaker 5: was like working in the medical industry and he wasn't

279
00:17:41,560 --> 00:17:43,760
Speaker 5: making a lot of money and he was supporting his

280
00:17:43,800 --> 00:17:46,399
Speaker 5: family and he was like, I used to work like

281
00:17:47,040 --> 00:17:51,440
Speaker 5: sixteen hour days and then I learned about spamming Facebook.

282
00:17:52,400 --> 00:17:56,280
Speaker 5: And he posted this one image that was a train

283
00:17:56,640 --> 00:17:59,920
Speaker 5: made out of leaves. It's like just to passenger train,

284
00:18:00,240 --> 00:18:02,679
Speaker 5: but the train was made entirely out of leaves. It

285
00:18:02,720 --> 00:18:05,639
Speaker 5: was an AI image and he made four hundred dollars

286
00:18:05,840 --> 00:18:10,000
Speaker 5: from that image. And he was like, I was only

287
00:18:10,040 --> 00:18:14,560
Speaker 5: making two hundred dollars a month at my other job. Wow,

288
00:18:15,000 --> 00:18:17,119
Speaker 5: And so I just do this now.

289
00:18:17,560 --> 00:18:22,280
Speaker 2: Wow. And there's the incentive. You can make pretty serious

290
00:18:22,320 --> 00:18:25,760
Speaker 2: money here, which brings us back to future writer us.

291
00:18:26,400 --> 00:18:29,400
Speaker 2: It's not really possible to know exactly how much money

292
00:18:29,400 --> 00:18:32,040
Speaker 2: they're making, but if we go back to that estimate

293
00:18:32,119 --> 00:18:35,119
Speaker 2: of about one hundred bucks per million views, let's compare

294
00:18:35,200 --> 00:18:38,639
Speaker 2: that to their most successful day. In a roughly twenty

295
00:18:38,680 --> 00:18:42,240
Speaker 2: four hour stretch, starting on January tenth, they posted seven

296
00:18:42,320 --> 00:18:47,560
Speaker 2: videos which collectively got about ninety four million views. Theoretically,

297
00:18:48,000 --> 00:18:51,760
Speaker 2: that could work out to nine thousand, four hundred dollars

298
00:18:51,760 --> 00:18:54,679
Speaker 2: in one day. And that's not the only way the

299
00:18:54,680 --> 00:18:57,719
Speaker 2: account makes money. They also sell a guide so that

300
00:18:57,760 --> 00:19:00,960
Speaker 2: you yourself can start your own AI slaw business for

301
00:19:01,160 --> 00:19:02,440
Speaker 2: just nineteen ninety nine.

302
00:19:02,720 --> 00:19:07,280
Speaker 6: Want to grow your Instagram TikTok YouTube fast, get thousands

303
00:19:07,320 --> 00:19:11,760
Speaker 6: of followers, create viral reels, and earn five thousand dollars

304
00:19:11,800 --> 00:19:15,800
Speaker 6: plus every month with the Viral Reels Guide it's easier

305
00:19:15,800 --> 00:19:20,480
Speaker 6: than ever. Step by step instructions, proven strategies, the perfect

306
00:19:20,520 --> 00:19:24,199
Speaker 6: for beginners, no experience needed, Ready to start. Grab the

307
00:19:24,200 --> 00:19:28,000
Speaker 6: guide today for just nineteen dollars and ninety nine cents.

308
00:19:28,760 --> 00:19:32,280
Speaker 2: This is a key part of the new AI slop economy.

309
00:19:32,800 --> 00:19:37,920
Speaker 5: So there is this entire network of influencers. Almost all

310
00:19:37,960 --> 00:19:44,199
Speaker 5: of them are in India, Vietnam, Pakistan, a couple in

311
00:19:44,400 --> 00:19:48,040
Speaker 5: a few African countries and Central America, but for the

312
00:19:48,119 --> 00:19:52,879
Speaker 5: most part they are in developing countries who have YouTube channels,

313
00:19:53,119 --> 00:19:56,800
Speaker 5: who are like, here is how you can make AI spam,

314
00:19:57,160 --> 00:19:59,520
Speaker 5: and here's how to put it on Facebook, and here's

315
00:19:59,560 --> 00:20:00,640
Speaker 5: how to mind to ties it.

316
00:20:01,359 --> 00:20:04,240
Speaker 2: So as I went further down this Future writer us

317
00:20:04,359 --> 00:20:07,479
Speaker 2: rabbit hole, I got so curious that I realized I

318
00:20:07,560 --> 00:20:09,560
Speaker 2: needed to know what was in this course they were selling,

319
00:20:10,400 --> 00:20:15,000
Speaker 2: So for journalism's sake, I bought it. It's a ZIP

320
00:20:15,040 --> 00:20:18,880
Speaker 2: file with two files. The first one is this really

321
00:20:18,960 --> 00:20:22,960
Speaker 2: short PDF which is pretty clearly chat GBT generated, and

322
00:20:23,640 --> 00:20:26,640
Speaker 2: the summary of it is it basically gives you these instructions.

323
00:20:27,080 --> 00:20:30,679
Speaker 2: First look online for what's already trending at the moment. Second,

324
00:20:31,000 --> 00:20:33,720
Speaker 2: type that into Sora dot Ai to generate a video

325
00:20:33,760 --> 00:20:37,840
Speaker 2: about that thing, add some music, and three posts a

326
00:20:37,920 --> 00:20:41,080
Speaker 2: video online. Then just repeat that multiple times a day.

327
00:20:41,760 --> 00:20:44,720
Speaker 2: The second file is just a seven minute iPhone screen

328
00:20:44,760 --> 00:20:48,560
Speaker 2: recording of them generating a prompt and then uploading that online.

329
00:20:49,119 --> 00:20:52,680
Speaker 5: It's like almost like a pyramid scheme where it's like, well, well,

330
00:20:52,680 --> 00:20:54,840
Speaker 5: this one person made a lot of money and here's

331
00:20:54,840 --> 00:20:57,280
Speaker 5: a guide to doing it, so I'm gonna try as well.

332
00:20:58,160 --> 00:21:00,280
Speaker 5: You just have like tens of thousands of people who

333
00:21:00,320 --> 00:21:03,359
Speaker 5: are trying this, and the end result is the entire

334
00:21:03,400 --> 00:21:04,560
Speaker 5: platform gets spammed.

335
00:21:05,680 --> 00:21:08,520
Speaker 2: So who's the audience for this stuff?

336
00:21:09,080 --> 00:21:12,600
Speaker 5: I mean, there's definitely some strategic thinking about will people

337
00:21:12,600 --> 00:21:16,120
Speaker 5: in the United States, the United Kingdom or Canada care

338
00:21:16,200 --> 00:21:18,960
Speaker 5: about this stuff? That's the strategy. And I know that's

339
00:21:18,960 --> 00:21:21,360
Speaker 5: the strategy because a lot of the videos about how

340
00:21:21,359 --> 00:21:24,920
Speaker 5: to make this stuff talk about here's what people in

341
00:21:24,960 --> 00:21:27,320
Speaker 5: the United States care about. Like I watched one video

342
00:21:27,920 --> 00:21:31,680
Speaker 5: that basically was like Americans love babies and they love pets,

343
00:21:32,040 --> 00:21:35,960
Speaker 5: and so make AI images about babies and pets. I've

344
00:21:35,960 --> 00:21:39,320
Speaker 5: seen guides that are like, here's what you need to

345
00:21:39,320 --> 00:21:43,119
Speaker 5: know about Jesus because you may be Hindu and you

346
00:21:43,680 --> 00:21:47,240
Speaker 5: don't know so like, if you're making AI spam about Jesus,

347
00:21:47,359 --> 00:21:49,880
Speaker 5: here are words to type in that will get you Jesus.

348
00:21:49,920 --> 00:21:54,800
Speaker 5: Because a lot of Americans are Christian. You want people

349
00:21:54,840 --> 00:21:56,960
Speaker 5: in the United States and Canada to look at these

350
00:21:57,040 --> 00:22:00,439
Speaker 5: because the way that online advertising works is if you

351
00:22:00,520 --> 00:22:05,600
Speaker 5: are in a richer country, the ad rates are higher,

352
00:22:06,160 --> 00:22:10,000
Speaker 5: page views from developed countries.

353
00:22:09,680 --> 00:22:11,359
Speaker 7: Are worth more.

354
00:22:11,920 --> 00:22:16,679
Speaker 5: Yeah, but I think the audience is an algorithm. I

355
00:22:16,680 --> 00:22:21,280
Speaker 5: think that the audience is like what what works well

356
00:22:21,440 --> 00:22:27,440
Speaker 5: in the algorithm, because the goal is not to create

357
00:22:28,080 --> 00:22:32,800
Speaker 5: an amazing image or an amazing video that people are

358
00:22:32,800 --> 00:22:36,760
Speaker 5: going to resonate with. The goal is to make people

359
00:22:36,880 --> 00:22:41,399
Speaker 5: linger on any given image or video long enough to

360
00:22:41,480 --> 00:22:44,920
Speaker 5: send a signal to the algorithm that this is something

361
00:22:44,960 --> 00:22:48,000
Speaker 5: that a human being spent time looking at, spend time

362
00:22:48,000 --> 00:22:51,880
Speaker 5: engaging with. You know, if it's something totally absurd, you're

363
00:22:51,880 --> 00:22:54,280
Speaker 5: going to get people in the comment saying, hey, this

364
00:22:54,359 --> 00:22:56,680
Speaker 5: isn't real, and then you're going to have fights back

365
00:22:56,680 --> 00:22:59,560
Speaker 5: and forth, and all of those signals send to the

366
00:22:59,600 --> 00:23:03,639
Speaker 5: algorithm that this is something that's worth surfacing in someone

367
00:23:03,640 --> 00:23:07,560
Speaker 5: else's feed. And so I really don't think that the

368
00:23:07,640 --> 00:23:11,040
Speaker 5: audience for this is real human beings.

369
00:23:13,200 --> 00:23:14,960
Speaker 2: You might have heard that last bit and thought of

370
00:23:15,000 --> 00:23:18,560
Speaker 2: something called the dead Internet theory. It's well, you could

371
00:23:18,640 --> 00:23:21,560
Speaker 2: kind of call it a conspiracy theory, but basically it

372
00:23:21,600 --> 00:23:24,280
Speaker 2: refers to the idea that the Internet has so many

373
00:23:24,320 --> 00:23:29,280
Speaker 2: bots and algorithmically generated content that human interaction is actually

374
00:23:29,280 --> 00:23:33,200
Speaker 2: a minority of the traffic online. The majority of traffic

375
00:23:33,400 --> 00:23:35,879
Speaker 2: is just bots spamming each other back and forth.

376
00:23:36,320 --> 00:23:38,240
Speaker 5: And the way that you would apply this to say,

377
00:23:38,840 --> 00:23:44,159
Speaker 5: shrimp Jesus, for example, is like, well, there's a bot

378
00:23:44,280 --> 00:23:48,320
Speaker 5: that posted this AI image, and then maybe all the

379
00:23:48,359 --> 00:23:50,600
Speaker 5: people liking at our bots, and maybe all the people

380
00:23:50,600 --> 00:23:54,879
Speaker 5: commenting on it our bots, and therefore none of it

381
00:23:54,920 --> 00:23:55,320
Speaker 5: is real.

382
00:23:56,119 --> 00:23:58,879
Speaker 2: But Jason has a slightly different theory.

383
00:23:58,960 --> 00:24:02,160
Speaker 5: I think that's too reductive. I just I don't think

384
00:24:02,200 --> 00:24:05,240
Speaker 5: that that's what's happening, and I know that's not what's happening,

385
00:24:05,359 --> 00:24:10,200
Speaker 5: because there are human beings in the loop. I'm certain

386
00:24:10,240 --> 00:24:14,480
Speaker 5: of it. Like they're human beings who are prompting these

387
00:24:14,800 --> 00:24:18,119
Speaker 5: AI images and are posting them. They may not be

388
00:24:18,240 --> 00:24:21,600
Speaker 5: monitoring the accounts very closely, but they're making it and

389
00:24:21,600 --> 00:24:25,920
Speaker 5: they're posting these images. And then there are definitely bots

390
00:24:26,720 --> 00:24:31,560
Speaker 5: who are liking and commenting on some of these images.

391
00:24:32,400 --> 00:24:36,280
Speaker 5: But these images and these photos and these you know,

392
00:24:36,440 --> 00:24:40,320
Speaker 5: videos are showing up in people's feeds. So I've called

393
00:24:40,400 --> 00:24:43,359
Speaker 5: the zombie Internet, where it's like a mix of human

394
00:24:43,400 --> 00:24:47,080
Speaker 5: beings and bots, where you have human beings arguing in

395
00:24:47,119 --> 00:24:49,240
Speaker 5: the comments with bots. You have human beings in the

396
00:24:49,240 --> 00:24:51,879
Speaker 5: comments arguing with other human beings. You have bots in

397
00:24:51,920 --> 00:24:54,960
Speaker 5: the comments arguing with other bots. And it's to me,

398
00:24:55,080 --> 00:24:58,760
Speaker 5: that's even worse than dead Internet, where everyone is a bot,

399
00:24:59,320 --> 00:25:04,840
Speaker 5: because you have all of these real humans who can't

400
00:25:04,880 --> 00:25:09,760
Speaker 5: tell that they're commenting on an AI generated image and

401
00:25:09,800 --> 00:25:15,159
Speaker 5: they're arguing about it, and they're spending tons of time,

402
00:25:15,480 --> 00:25:19,520
Speaker 5: like tons of like you know, human hours, engaging with it.

403
00:25:20,160 --> 00:25:23,719
Speaker 2: Yeah, like we're humans are moving amongst the dead, and

404
00:25:23,800 --> 00:25:26,040
Speaker 2: you end up with something that's only kind of half

405
00:25:26,119 --> 00:25:28,919
Speaker 2: alive and half dead and somewhere in the middle there. So,

406
00:25:29,119 --> 00:25:31,840
Speaker 2: while humans might not be the target audience for these

407
00:25:31,840 --> 00:25:35,840
Speaker 2: images and videos, real people are being fed this content

408
00:25:36,560 --> 00:25:39,080
Speaker 2: and you'd think that that would piss them off, but

409
00:25:39,359 --> 00:25:42,440
Speaker 2: we're starting to find out that that's not necessarily the case.

410
00:25:43,280 --> 00:25:46,159
Speaker 5: So there was a Hurricane Helene that hit you know,

411
00:25:46,320 --> 00:25:51,919
Speaker 5: North Carolina, Georgia the southeast and in the aftermath that

412
00:25:52,000 --> 00:25:55,240
Speaker 5: there were a lot of horrible images coming out of it,

413
00:25:55,240 --> 00:25:59,399
Speaker 5: has come out of any natural disaster, and there was

414
00:25:59,440 --> 00:26:02,840
Speaker 5: an AI generated image of a three year old girl

415
00:26:03,080 --> 00:26:05,800
Speaker 5: crying and I think she was like sitting on a

416
00:26:05,880 --> 00:26:08,400
Speaker 5: raft or you know, there was like a flood around her.

417
00:26:09,320 --> 00:26:14,159
Speaker 5: And this image is very clearly AI generated, but it

418
00:26:14,240 --> 00:26:17,800
Speaker 5: went really viral and it was shared by a few

419
00:26:17,880 --> 00:26:22,080
Speaker 5: Republican politicians and they were sort of talking about how

420
00:26:23,680 --> 00:26:27,679
Speaker 5: this is what FEMA and Joe Biden's poor response to

421
00:26:27,720 --> 00:26:31,359
Speaker 5: the hurricane has done to people, right and there was

422
00:26:31,359 --> 00:26:34,640
Speaker 5: a moment where everyone was like, this is fake, You're stupid,

423
00:26:35,000 --> 00:26:38,960
Speaker 5: And the response from the politicians were like, I don't

424
00:26:39,000 --> 00:26:42,000
Speaker 5: care if it's real or not. Something like this is

425
00:26:42,040 --> 00:26:42,800
Speaker 5: happening there.

426
00:26:43,520 --> 00:26:45,520
Speaker 2: Yeah, I mean, I'll even read it here. This is

427
00:26:45,560 --> 00:26:49,879
Speaker 2: Amy Kramer, the National Committee woman for the Republican National Convention, said,

428
00:26:50,000 --> 00:26:53,440
Speaker 2: I'm reading this verbatim. There are people going through much

429
00:26:53,480 --> 00:26:56,080
Speaker 2: worse than what is shown in this pic. So I'm

430
00:26:56,119 --> 00:26:58,719
Speaker 2: leaving it because it is emblematic of the trauma and

431
00:26:58,800 --> 00:27:03,840
Speaker 2: pain people are living through right now. That is something

432
00:27:03,880 --> 00:27:06,280
Speaker 2: that I've seen a lot when I look at the

433
00:27:06,359 --> 00:27:11,280
Speaker 2: comment sections of fake AI generated images that are related

434
00:27:11,280 --> 00:27:13,320
Speaker 2: to something that's actually happening in the real world, you'll

435
00:27:13,320 --> 00:27:16,280
Speaker 2: see people in the comments who were, I think, in

436
00:27:16,359 --> 00:27:19,240
Speaker 2: their own way, trying to make the Internet a better

437
00:27:19,280 --> 00:27:21,760
Speaker 2: place by telling people, hey, this is fake and trying

438
00:27:21,760 --> 00:27:25,440
Speaker 2: to educate people. And then some of those responses though,

439
00:27:25,560 --> 00:27:28,320
Speaker 2: are well, I don't care if this is fake. It

440
00:27:28,320 --> 00:27:32,360
Speaker 2: doesn't matter because I'm sure something like this is happening.

441
00:27:33,119 --> 00:27:37,560
Speaker 2: This is just a depiction of it. Yeah, that I

442
00:27:37,600 --> 00:27:38,720
Speaker 2: find really interesting.

443
00:27:39,520 --> 00:27:44,960
Speaker 5: It's really interesting, and I'll tell you like I used

444
00:27:45,000 --> 00:27:50,679
Speaker 5: to be more optimistic that social media can be fixed

445
00:27:50,720 --> 00:27:53,560
Speaker 5: and like her information ecosystems can be fixed and things

446
00:27:53,640 --> 00:27:57,920
Speaker 5: like that, and a lot of my first articles about

447
00:27:57,920 --> 00:28:01,920
Speaker 5: this were about people can't tell that they're not real,

448
00:28:02,560 --> 00:28:04,960
Speaker 5: and therefore it's bad that people can't tell that it's

449
00:28:05,000 --> 00:28:07,960
Speaker 5: not real. And now it's a mix of people not

450
00:28:08,040 --> 00:28:10,080
Speaker 5: being able to tell that these things are not real

451
00:28:10,320 --> 00:28:15,320
Speaker 5: and people not caring that they're not real. And the

452
00:28:15,359 --> 00:28:19,320
Speaker 5: second one is almost worse, where you know it's fake,

453
00:28:19,359 --> 00:28:21,440
Speaker 5: but you share it anyway because it captures some sort

454
00:28:21,480 --> 00:28:26,320
Speaker 5: of vibe, like if it verifies their worldview, then it's

455
00:28:26,800 --> 00:28:30,160
Speaker 5: useful to them in some way. Making it very unclear

456
00:28:30,240 --> 00:28:32,040
Speaker 5: what is real and what is fake is part of

457
00:28:32,080 --> 00:28:36,960
Speaker 5: the point of that entire project, where the truth is unknowable.

458
00:28:39,640 --> 00:28:42,680
Speaker 2: What are social media platforms doing about this? And is

459
00:28:42,720 --> 00:28:45,480
Speaker 2: there anything that we can do about it? That's after

460
00:28:45,480 --> 00:28:59,400
Speaker 2: the break, So this is where I have to ask

461
00:28:59,480 --> 00:29:02,240
Speaker 2: about what the platforms are doing, because this sounds like

462
00:29:03,520 --> 00:29:07,600
Speaker 2: it would make the experience really not fun. You get

463
00:29:07,640 --> 00:29:10,960
Speaker 2: on Facebook, you get on Instagram, you get on TikTok,

464
00:29:11,400 --> 00:29:15,080
Speaker 2: and everything is fake. Platforms can't possibly want this. So

465
00:29:15,320 --> 00:29:19,320
Speaker 2: you've talked to platforms, what's been the responsive places, especially

466
00:29:19,400 --> 00:29:20,440
Speaker 2: like Facebook.

467
00:29:21,160 --> 00:29:29,080
Speaker 5: Yeah, they don't care, like they like it, and I

468
00:29:29,120 --> 00:29:31,360
Speaker 5: know that they like it because Mark Zuckerberg has talked

469
00:29:31,360 --> 00:29:35,040
Speaker 5: about it in quarterly earnings reports Q three of last year.

470
00:29:35,720 --> 00:29:37,960
Speaker 7: Another part that I haven't talked about quite as much

471
00:29:38,040 --> 00:29:43,960
Speaker 7: yet is the opportunity for AI to help people create content.

472
00:29:44,600 --> 00:29:46,480
Speaker 7: And I think we're going to add a whole new

473
00:29:47,000 --> 00:29:52,400
Speaker 7: category of content, which is AI generated or AI summarized content.

474
00:29:52,920 --> 00:29:55,480
Speaker 7: And I think that that's going to be just very

475
00:29:55,480 --> 00:30:01,120
Speaker 7: exciting for the for Facebook and Instagram and maybe threads

476
00:30:01,160 --> 00:30:04,120
Speaker 7: or other kind of feed experiences over time, and.

477
00:30:04,040 --> 00:30:07,440
Speaker 5: I've also talked to Facebook comms people and said, like,

478
00:30:08,320 --> 00:30:10,520
Speaker 5: do you want this type of stuff on your platform?

479
00:30:10,520 --> 00:30:13,720
Speaker 5: Are you going to delete it? And you know, they

480
00:30:13,760 --> 00:30:16,719
Speaker 5: will delete some of the really grotesque things if it

481
00:30:16,840 --> 00:30:21,000
Speaker 5: violates other parts of their content policies, but they will

482
00:30:21,040 --> 00:30:25,320
Speaker 5: not delete anything just because it is AI generated or

483
00:30:25,360 --> 00:30:30,160
Speaker 5: because it's spam. And at the same time, Meta is

484
00:30:31,120 --> 00:30:35,880
Speaker 5: developing its own artificial intelligence. You can make AI slop

485
00:30:36,080 --> 00:30:40,120
Speaker 5: for lack of a better term, using Meta's own tools

486
00:30:40,160 --> 00:30:43,880
Speaker 5: and then post it to Facebook. And then most recently

487
00:30:43,960 --> 00:30:47,840
Speaker 5: that they said, you know, we're going to hopefully create

488
00:30:47,920 --> 00:30:51,680
Speaker 5: tools that will allow users to make their own AI

489
00:30:51,840 --> 00:30:56,920
Speaker 5: generated profiles of fake people. And we imagine a future

490
00:30:56,960 --> 00:30:59,960
Speaker 5: where like a lot of the content on these platforms

491
00:31:00,200 --> 00:31:02,120
Speaker 5: is generated by AI.

492
00:31:03,040 --> 00:31:07,200
Speaker 2: Jason, why like this seems like a bad All this

493
00:31:07,200 --> 00:31:08,000
Speaker 2: stuff seems bad.

494
00:31:08,480 --> 00:31:11,360
Speaker 5: Yeah, I've tried to figure out exactly why this is happening,

495
00:31:11,440 --> 00:31:14,520
Speaker 5: Like I've tried to put myself in Mark Zuckerberg's shoes

496
00:31:14,600 --> 00:31:18,200
Speaker 5: and be like, Okay, what is like the bullish argument here?

497
00:31:18,400 --> 00:31:21,240
Speaker 5: And so one, it's like they're spending billions and billions

498
00:31:21,240 --> 00:31:24,320
Speaker 5: of dollars on AI data centers, so they need to

499
00:31:24,400 --> 00:31:27,800
Speaker 5: push this on people because they think that artificial intelligence

500
00:31:27,840 --> 00:31:30,959
Speaker 5: is the future of work, it's the future of the Internet,

501
00:31:31,000 --> 00:31:34,880
Speaker 5: it's the future of humanity, and so they are desperate

502
00:31:34,920 --> 00:31:38,840
Speaker 5: to find use cases for this in some way. The

503
00:31:39,000 --> 00:31:42,840
Speaker 5: other thing that I've been thinking about is that the

504
00:31:42,880 --> 00:31:46,040
Speaker 5: way that all of Meta's platforms work is it tries

505
00:31:46,080 --> 00:31:48,880
Speaker 5: to learn as much about you as possible so that

506
00:31:48,960 --> 00:31:51,760
Speaker 5: you stay on their platforms as long as possible so

507
00:31:51,800 --> 00:31:56,240
Speaker 5: that they can deliver targeted ads to you. And right

508
00:31:56,280 --> 00:31:59,720
Speaker 5: now they have billions of people posting on their platforms

509
00:32:00,040 --> 00:32:02,440
Speaker 5: all sorts of different types of content, and then they

510
00:32:02,480 --> 00:32:06,760
Speaker 5: need to rely on their algorithm to categorize that content

511
00:32:06,840 --> 00:32:09,120
Speaker 5: in some way and deliver it to people who they

512
00:32:09,160 --> 00:32:12,760
Speaker 5: think will like it. And what I think is happening

513
00:32:12,800 --> 00:32:18,920
Speaker 5: here is they want to use artificial intelligence to create

514
00:32:19,440 --> 00:32:24,120
Speaker 5: hyper specific types of content so that you get on

515
00:32:24,160 --> 00:32:27,920
Speaker 5: their platforms and you don't stop scrolling. It's like, if

516
00:32:27,960 --> 00:32:30,920
Speaker 5: you are really into, like a specific type of sports

517
00:32:30,960 --> 00:32:34,840
Speaker 5: car and you only want to see like amazing videos

518
00:32:34,880 --> 00:32:38,400
Speaker 5: of that sports car driving around, there might not be

519
00:32:38,760 --> 00:32:42,400
Speaker 5: human beings creating enough of that content to like satisfy

520
00:32:42,440 --> 00:32:46,000
Speaker 5: you and keep you on that platform. Long enough, Whereas

521
00:32:46,080 --> 00:32:49,760
Speaker 5: with artificial intelligence, they can just make millions of different

522
00:32:49,920 --> 00:32:53,640
Speaker 5: variations of the specific thing that you're into, feed it

523
00:32:53,720 --> 00:32:55,880
Speaker 5: to you over and over and over again, and then

524
00:32:56,520 --> 00:32:59,880
Speaker 5: you know, target you even more close to with ads

525
00:33:00,040 --> 00:33:03,240
Speaker 5: and keep you on the platform longer. They want to

526
00:33:03,320 --> 00:33:09,000
Speaker 5: trap people into like even more specific algorithmic silos where

527
00:33:09,120 --> 00:33:14,480
Speaker 5: hyper specific, artificially intelligent content is fed to you endlessly.

528
00:33:14,760 --> 00:33:17,560
Speaker 2: Which brings us back to our guy or gal. I

529
00:33:17,600 --> 00:33:21,680
Speaker 2: actually don't know, future writer us. I'd seen all these

530
00:33:21,720 --> 00:33:24,680
Speaker 2: angry comments in their posts, and I decided I just

531
00:33:24,800 --> 00:33:27,640
Speaker 2: needed to see what the person behind the account was thinking,

532
00:33:28,240 --> 00:33:31,080
Speaker 2: so I DM them. They told me they were Russian,

533
00:33:31,440 --> 00:33:33,960
Speaker 2: and at first they were mostly bragging about how many

534
00:33:34,040 --> 00:33:36,840
Speaker 2: views they were getting. But when I pointed out that

535
00:33:36,920 --> 00:33:39,240
Speaker 2: a lot of people were either angry about their posts

536
00:33:39,400 --> 00:33:42,120
Speaker 2: or had no idea that it was fake, they started

537
00:33:42,120 --> 00:33:45,360
Speaker 2: getting defensive. Future writer us said that they didn't see

538
00:33:45,400 --> 00:33:49,080
Speaker 2: the problem because they'd added an AI tag to their videos,

539
00:33:49,640 --> 00:33:53,240
Speaker 2: and well, they have a point. Instagram does have a

540
00:33:53,240 --> 00:33:56,920
Speaker 2: feature that allows uploaders to voluntarily tag their posts as

541
00:33:56,920 --> 00:34:00,880
Speaker 2: AI generated. The trouble is that this label doesn't show

542
00:34:00,960 --> 00:34:03,840
Speaker 2: up when you're watching the video Normally, you only see

543
00:34:03,880 --> 00:34:05,680
Speaker 2: it if you look at the bottom and there's a

544
00:34:05,680 --> 00:34:09,000
Speaker 2: C more tag and you tap that, and even then

545
00:34:09,360 --> 00:34:12,799
Speaker 2: space is prioritized for the song title, so sometimes that

546
00:34:12,880 --> 00:34:16,240
Speaker 2: tag is pushed off the screen and all it says

547
00:34:16,400 --> 00:34:19,359
Speaker 2: is AI info in small text in the bottom right,

548
00:34:19,880 --> 00:34:22,040
Speaker 2: and if you tap that, it shows you some more

549
00:34:22,080 --> 00:34:28,480
Speaker 2: information AI info, not AI warning, not AI caution, just

550
00:34:28,760 --> 00:34:34,279
Speaker 2: AI info. Why would you ever tap that? Meta has

551
00:34:34,320 --> 00:34:36,439
Speaker 2: a page on their site that makes a big deal

552
00:34:36,440 --> 00:34:39,799
Speaker 2: about the introduction of this tag, and they primarily show

553
00:34:39,840 --> 00:34:43,320
Speaker 2: what it looks like in the grid view. The issue

554
00:34:43,440 --> 00:34:46,800
Speaker 2: is that it's even more imperceptible there. So when you

555
00:34:46,840 --> 00:34:48,839
Speaker 2: first look at a post and the grid, you see

556
00:34:48,880 --> 00:34:52,279
Speaker 2: the location tag, then you see the music title, and

557
00:34:52,320 --> 00:34:55,200
Speaker 2: that scrolls in a view for a few moments. Only

558
00:34:55,360 --> 00:34:59,800
Speaker 2: after that does the text AI info appear. By that

559
00:35:00,280 --> 00:35:02,760
Speaker 2: you're watching the video, you're not looking at tiny text

560
00:35:02,960 --> 00:35:05,759
Speaker 2: rolls in the upper corner of your screen. And also,

561
00:35:06,040 --> 00:35:09,439
Speaker 2: Meta never notified users that they were rolling this feature out.

562
00:35:10,000 --> 00:35:13,600
Speaker 2: Why would anyone know that this exists? And by the way,

563
00:35:13,719 --> 00:35:15,680
Speaker 2: I did reach out to Meta when I was first

564
00:35:15,680 --> 00:35:18,480
Speaker 2: reporting on this, and I asked them about their policy

565
00:35:18,520 --> 00:35:22,120
Speaker 2: on AI on their platform, specifically, if there's any obligation

566
00:35:22,239 --> 00:35:24,680
Speaker 2: for a user to more clearly label a post as

567
00:35:24,760 --> 00:35:28,280
Speaker 2: AI other than that small badge, or why the desktop

568
00:35:28,360 --> 00:35:32,080
Speaker 2: doesn't show the badge at all. They never responded, and

569
00:35:32,120 --> 00:35:34,440
Speaker 2: this is where I have to kind of agree with

570
00:35:34,520 --> 00:35:37,840
Speaker 2: Future writer us. They said that if people don't notice

571
00:35:37,840 --> 00:35:42,640
Speaker 2: the interfaces AI tag, it's not the poster's fault, it's Instagram's,

572
00:35:43,160 --> 00:35:46,640
Speaker 2: and it's the platform's responsibility to make those tags bigger

573
00:35:46,880 --> 00:35:50,680
Speaker 2: or more noticeable. That doesn't seem to be happening, and

574
00:35:50,800 --> 00:35:53,839
Speaker 2: since both the AI slot posters and the platforms are

575
00:35:53,840 --> 00:35:57,200
Speaker 2: making money, there's no real incentive for anyone to stop.

576
00:35:58,080 --> 00:36:01,080
Speaker 2: But it does get weird when this stuff is happening

577
00:36:01,239 --> 00:36:05,279
Speaker 2: in a place that you live. You've been reporting on

578
00:36:05,360 --> 00:36:08,279
Speaker 2: AI slap a lot, and I'm sure that when you

579
00:36:08,360 --> 00:36:12,120
Speaker 2: saw the Hollywood sign thing on fire, youknew exactly what

580
00:36:12,239 --> 00:36:17,399
Speaker 2: that was. Was there anything about the AI generated slap

581
00:36:17,480 --> 00:36:20,480
Speaker 2: that was coming from the LA fires that was surprising

582
00:36:20,560 --> 00:36:20,719
Speaker 2: to you?

583
00:36:21,520 --> 00:36:24,640
Speaker 5: I wasn't surprised that it happened, like I wasn't surprised

584
00:36:24,640 --> 00:36:28,200
Speaker 5: that people were making slop about it. I was surprised

585
00:36:29,400 --> 00:36:32,759
Speaker 5: that it upset me, like I was surprised, as someone

586
00:36:32,800 --> 00:36:35,840
Speaker 5: who lives in Los Angeles, who knows people who lost

587
00:36:35,880 --> 00:36:39,080
Speaker 5: their homes, who saw the fires like you know, the

588
00:36:39,560 --> 00:36:43,759
Speaker 5: first day as they were growing. I was surprised that

589
00:36:44,239 --> 00:36:46,479
Speaker 5: I was upset that this was happening and that people

590
00:36:46,560 --> 00:36:50,520
Speaker 5: were making money off of it. And I think I

591
00:36:50,640 --> 00:36:55,080
Speaker 5: was also upset because there were some really brave journalists

592
00:36:55,160 --> 00:36:57,319
Speaker 5: from the LA Times, New York Times, a lot of

593
00:36:57,360 --> 00:37:01,759
Speaker 5: local spots who were going there take photos, taking videos,

594
00:37:02,360 --> 00:37:08,319
Speaker 5: risking their lives to share this stuff. And then many

595
00:37:08,360 --> 00:37:11,080
Speaker 5: of the images and videos that were going really viral

596
00:37:11,120 --> 00:37:14,279
Speaker 5: were just like the Hollywood Sign is on fire. And

597
00:37:14,360 --> 00:37:16,479
Speaker 5: I was surprised because it was like the first time

598
00:37:16,520 --> 00:37:21,600
Speaker 5: that aislop had impacted anything that had any personal meaning

599
00:37:21,640 --> 00:37:24,320
Speaker 5: to me, and I found it to be like pretty upsetting.

600
00:37:24,960 --> 00:37:27,640
Speaker 2: It's interesting that you say that about people risking their

601
00:37:27,640 --> 00:37:32,319
Speaker 2: lives because the creator, when people started calling them out

602
00:37:32,680 --> 00:37:36,920
Speaker 2: a lot on their most viral reel, they posted a

603
00:37:36,920 --> 00:37:40,640
Speaker 2: response and they say, I'm Marita here. In this video,

604
00:37:40,719 --> 00:37:43,240
Speaker 2: I aimed to shed light on the reality of what's happening.

605
00:37:43,640 --> 00:37:47,400
Speaker 2: The problems are very real. Animals are dying, homes are

606
00:37:47,440 --> 00:37:51,280
Speaker 2: being destroyed, and firefighters are risking their lives to save others.

607
00:37:51,680 --> 00:37:54,799
Speaker 2: They don't have the time to produce visually stunning and

608
00:37:54,840 --> 00:37:58,359
Speaker 2: powerful footage to raise awareness about these issues. That's why

609
00:37:58,360 --> 00:38:00,400
Speaker 2: I took the initiative to create something that could help

610
00:38:00,440 --> 00:38:04,320
Speaker 2: people see and truly think about these tragedies. So basically,

611
00:38:04,600 --> 00:38:06,400
Speaker 2: people are risking their lives, they don't have time to

612
00:38:06,440 --> 00:38:09,120
Speaker 2: make these really well produced things, so I made this

613
00:38:09,320 --> 00:38:13,120
Speaker 2: for you. Which, of course, this all breaks down when

614
00:38:13,239 --> 00:38:15,479
Speaker 2: right after the fires stop being in the news as much,

615
00:38:15,880 --> 00:38:21,120
Speaker 2: they go on to making completely other unrelated AI generated content.

616
00:38:21,600 --> 00:38:23,919
Speaker 5: I find it to be offensive more or less. It's

617
00:38:23,960 --> 00:38:26,920
Speaker 5: just like it's I think it's kind of tasteless. I

618
00:38:26,960 --> 00:38:31,919
Speaker 5: don't think that that matters anymore on the Internet. But

619
00:38:32,000 --> 00:38:34,319
Speaker 5: you know, there were plenty of images coming out of

620
00:38:35,800 --> 00:38:41,840
Speaker 5: the La Fires, and we don't need an unlimited, infinite

621
00:38:42,360 --> 00:38:45,799
Speaker 5: visual gallery of everything that is happening. And I think

622
00:38:45,880 --> 00:38:51,240
Speaker 5: that's one of the biggest problems with AI slot more generally,

623
00:38:51,440 --> 00:38:55,239
Speaker 5: is that you can find any news that you want,

624
00:38:55,719 --> 00:39:01,000
Speaker 5: anything that confirms your worldview because of and because of

625
00:39:01,040 --> 00:39:04,000
Speaker 5: social media. So it's like, if you think that the

626
00:39:04,160 --> 00:39:07,640
Speaker 5: La fires was an act of God punishing gay people

627
00:39:07,800 --> 00:39:12,319
Speaker 5: in Los Angeles, which I've seen AI videos where that's

628
00:39:12,880 --> 00:39:16,720
Speaker 5: what they're about, Like God is striking back against Hollywood's

629
00:39:16,760 --> 00:39:19,560
Speaker 5: gay people. There's a video for you. If you think

630
00:39:19,600 --> 00:39:22,280
Speaker 5: that it was like a space laser, there's a video

631
00:39:22,400 --> 00:39:24,640
Speaker 5: for you. Like if you think that it was just

632
00:39:24,760 --> 00:39:27,719
Speaker 5: like climate change, there's a video for you. If you

633
00:39:27,800 --> 00:39:30,920
Speaker 5: only care about the animals that lost their homes, like,

634
00:39:30,960 --> 00:39:31,880
Speaker 5: there's a video for you.

635
00:39:32,520 --> 00:39:35,080
Speaker 2: Yeah, it just feels like something we're gonna see more

636
00:39:35,440 --> 00:39:38,400
Speaker 2: and more. You know, every time there's some new advancement

637
00:39:38,480 --> 00:39:41,080
Speaker 2: or some new engine has dropped, some new you know,

638
00:39:41,120 --> 00:39:45,120
Speaker 2: AI technology is dropped, people look at it, and the

639
00:39:45,680 --> 00:39:47,799
Speaker 2: really excited people will post, oh my gosh, look at

640
00:39:47,800 --> 00:39:52,280
Speaker 2: this and just think we're able to accomplish this today.

641
00:39:52,360 --> 00:39:55,439
Speaker 2: But this is the worst it'll ever be. What does

642
00:39:55,560 --> 00:40:00,040
Speaker 2: that mean for the future of AI slop and the

643
00:40:00,040 --> 00:40:03,960
Speaker 2: future of how we're going to experience reality on the internet.

644
00:40:05,160 --> 00:40:08,440
Speaker 5: Yeah, So two things. One that's absolutely correct. It's like

645
00:40:08,760 --> 00:40:12,720
Speaker 5: I've watched this stuff evolve in real time, and AI

646
00:40:12,760 --> 00:40:16,520
Speaker 5: generated videos especially have gotten far more realistic in the

647
00:40:16,600 --> 00:40:20,520
Speaker 5: last month and way way way better than they were

648
00:40:20,520 --> 00:40:24,440
Speaker 5: a year ago. And two the people were saying, like

649
00:40:25,120 --> 00:40:31,160
Speaker 5: we can use artificial intelligence to improve special effects for Hollywood,

650
00:40:31,280 --> 00:40:36,520
Speaker 5: to improve productivity for you know, writers or whatever like that.

651
00:40:36,600 --> 00:40:38,839
Speaker 5: All the productivity gains that are going to happen in

652
00:40:38,920 --> 00:40:42,400
Speaker 5: sort of like a best case use of artificial intelligence,

653
00:40:43,520 --> 00:40:47,120
Speaker 5: that very well might be true. But alongside of that,

654
00:40:47,960 --> 00:40:50,520
Speaker 5: you're going to have so many more people using these

655
00:40:50,520 --> 00:40:55,279
Speaker 5: tools to spam the Internet, to abuse people, to make

656
00:40:55,320 --> 00:40:59,799
Speaker 5: deep fakes of you know, celebrities and people that they

657
00:40:59,840 --> 00:41:02,879
Speaker 5: know in high school and things like that. And when

658
00:41:03,000 --> 00:41:05,840
Speaker 5: you're just like using the Internet as a consumer like that,

659
00:41:05,840 --> 00:41:08,360
Speaker 5: that's a lot of what you're going to experience because

660
00:41:09,360 --> 00:41:12,319
Speaker 5: there's a lot more people trying to make a few

661
00:41:12,360 --> 00:41:15,520
Speaker 5: bucks on Facebook than there are Hollywood studios that are

662
00:41:15,560 --> 00:41:18,400
Speaker 5: trying to make like a triple A film.

663
00:41:19,880 --> 00:41:22,680
Speaker 2: So one last thing before I let Jason go, I

664
00:41:22,680 --> 00:41:25,439
Speaker 2: asked if he could read me this one paragraph from

665
00:41:25,440 --> 00:41:29,080
Speaker 2: his shrimp Jesus article, and hopefully it'll make sense why I.

666
00:41:29,040 --> 00:41:34,040
Speaker 5: Asked, there are AI generated pages full of AI deformed women,

667
00:41:34,120 --> 00:41:38,480
Speaker 5: breastfeeding tiny cows, celebrities with amputations that they do not

668
00:41:38,600 --> 00:41:41,480
Speaker 5: have in real life. Jesus as a shrimp, Jesus as

669
00:41:41,480 --> 00:41:45,640
Speaker 5: a collection of Phanto bottles, Jesus as sand sculpture, Jesus

670
00:41:45,719 --> 00:41:49,000
Speaker 5: as a series of ramen noodles, Jesus as a shrimp

671
00:41:49,080 --> 00:41:52,400
Speaker 5: mixed with sprite bottles and ramen noodles. Jesus made a

672
00:41:52,480 --> 00:41:56,920
Speaker 5: plastic bottles and posing with large breasted AI generated female soldiers.

673
00:41:57,480 --> 00:42:00,800
Speaker 5: Jesus on a plane with AI generated sexy fe flight attendants,

674
00:42:01,440 --> 00:42:06,640
Speaker 5: giant gold Jesus being evacuated from a river, golden helicopter,

675
00:42:06,800 --> 00:42:11,439
Speaker 5: Jesus banana, Jesus coffee, Jesus goldfish, Jesus rice Jesus, any

676
00:42:11,520 --> 00:42:14,719
Speaker 5: number of AI generated female soldiers on a page called

677
00:42:14,880 --> 00:42:19,320
Speaker 5: beautiful Military, a page called everything skull, which is exactly

678
00:42:19,320 --> 00:42:24,920
Speaker 5: what it sounds like. Malnourished dogs, indigenous identity pages, beautiful landscapes,

679
00:42:25,080 --> 00:42:31,080
Speaker 5: flower arrangements, weird cakes, et cetera. I should write like

680
00:42:31,120 --> 00:42:33,680
Speaker 5: that more often, where it's just like, here's a bunch

681
00:42:33,680 --> 00:42:34,439
Speaker 5: of shit I saw.

682
00:42:36,600 --> 00:42:44,000
Speaker 2: I mean, just the breadth and the absolute unhinged quality

683
00:42:44,080 --> 00:42:49,319
Speaker 2: of it. I think it gives. It's a wild snapshot

684
00:42:49,400 --> 00:42:52,120
Speaker 2: of where we were. What is this last year? That

685
00:42:52,560 --> 00:42:56,000
Speaker 2: was the state of Ai back then was slop, was

686
00:42:56,120 --> 00:43:00,920
Speaker 2: kind of funny, and now not that long long after this,

687
00:43:01,080 --> 00:43:05,840
Speaker 2: we're now in the zone where aislop is being used

688
00:43:06,000 --> 00:43:10,360
Speaker 2: to make people afraid. It's being used to make people

689
00:43:10,480 --> 00:43:13,360
Speaker 2: think the things that are happening that are obviously not happening.

690
00:43:13,400 --> 00:43:16,359
Speaker 2: And this is affecting people who otherwise think that they're

691
00:43:16,440 --> 00:43:20,440
Speaker 2: very smart and informed and engaged and knowledgeable about the world.

692
00:43:20,640 --> 00:43:25,080
Speaker 2: So we've made a jump, a really quick jump from Hahaha,

693
00:43:25,120 --> 00:43:27,560
Speaker 2: isn't this funny all of us smart nerds on the

694
00:43:27,560 --> 00:43:31,400
Speaker 2: internet get to laugh at our parents' generation to wait

695
00:43:31,400 --> 00:43:35,520
Speaker 2: a second, this is affecting stuff that's affecting our perception

696
00:43:35,719 --> 00:43:39,400
Speaker 2: of a literal natural disaster that happened where you and

697
00:43:39,440 --> 00:43:39,799
Speaker 2: I live.

698
00:43:43,960 --> 00:43:47,800
Speaker 5: Yeah, I mean almost everything is trying to scare people.

699
00:43:48,400 --> 00:43:51,400
Speaker 5: It's trying to talk about the news, it's trying to

700
00:43:51,480 --> 00:43:56,319
Speaker 5: confuse people. And yeah, there's definitely a part of me

701
00:43:56,360 --> 00:43:59,239
Speaker 5: where I'm like, can we go back to Jesus with

702
00:43:59,280 --> 00:44:02,720
Speaker 5: the hot flight tence? Like what are we doing here?

703
00:44:03,920 --> 00:44:04,520
Speaker 2: And here we are?

704
00:44:05,320 --> 00:44:08,360
Speaker 5: Yeah, And like I feel like I can still generally

705
00:44:08,400 --> 00:44:11,560
Speaker 5: tell what's AI generated and what's not, but I'm using

706
00:44:11,600 --> 00:44:14,279
Speaker 5: like way more of my brain power like to try

707
00:44:14,320 --> 00:44:16,920
Speaker 5: to decipher what's real and what's not because it is

708
00:44:16,960 --> 00:44:17,840
Speaker 5: getting way better.

709
00:44:21,960 --> 00:44:24,440
Speaker 2: Thank you so much for listening to kill Switch and

710
00:44:24,719 --> 00:44:26,600
Speaker 2: let us know what you think. If there's something we

711
00:44:26,680 --> 00:44:29,040
Speaker 2: want us to cover, let us know that too. You

712
00:44:29,080 --> 00:44:32,400
Speaker 2: can hit us at kill Switch at Kaleidoscope dot NYC,

713
00:44:32,960 --> 00:44:35,080
Speaker 2: or you can find me at dex Digi on the

714
00:44:35,160 --> 00:44:39,880
Speaker 2: Gram or Blue Sky if that's more your flavor. And

715
00:44:40,040 --> 00:44:42,160
Speaker 2: also if you can leave us a review, it helps

716
00:44:42,200 --> 00:44:44,560
Speaker 2: other people find the show, which helps us keep doing

717
00:44:44,600 --> 00:44:48,560
Speaker 2: our thing. This show is hosted by me Dexter Thomas.

718
00:44:49,960 --> 00:44:54,160
Speaker 2: It's produced by Seno Ozaki, Darluk Potts, and Kate Osborne.

719
00:44:54,440 --> 00:44:57,120
Speaker 2: The theme song is by Kyle Murdoch, who also mixed

720
00:44:57,160 --> 00:45:01,160
Speaker 2: the show from Kaleidoscope Or execut Native producers are Oz

721
00:45:01,239 --> 00:45:05,360
Speaker 2: Valascian on Guest, Kaki Kadur, and Kate Osbourne from iHeart

722
00:45:05,480 --> 00:45:09,719
Speaker 2: Our Executive producers are Katrina Norbl and Nikki E. Tor See.

723
00:45:09,760 --> 00:45:12,840
Speaker 2: All in the next one h