1 00:00:05,600 --> 00:00:07,320 Speaker 1: There Are No Girls on the Internet. As a production 2 00:00:07,360 --> 00:00:14,880 Speaker 1: of iHeartRadio and Unbossed Creative, I'm Bridget Toad and this 3 00:00:14,960 --> 00:00:19,800 Speaker 1: is there are No Girls on the Internet. So this 4 00:00:19,840 --> 00:00:21,800 Speaker 1: is going to be a little bit different of an 5 00:00:21,800 --> 00:00:24,240 Speaker 1: episode than the one that we initially had planned for today, 6 00:00:24,640 --> 00:00:27,639 Speaker 1: and that is because I have found myself personally in 7 00:00:27,680 --> 00:00:30,920 Speaker 1: a situation that I think really speaks to this specific 8 00:00:30,960 --> 00:00:35,240 Speaker 1: moment in technology, media, the Internet and where we're going 9 00:00:35,240 --> 00:00:39,200 Speaker 1: in the future. And as we're exploring this present future 10 00:00:39,240 --> 00:00:42,160 Speaker 1: of ours, we are probably going to find ourselves having 11 00:00:42,200 --> 00:00:44,880 Speaker 1: more and more moments like this one. So I wanted 12 00:00:44,880 --> 00:00:47,360 Speaker 1: to bring all of you along on this ride with me. 13 00:00:48,320 --> 00:00:50,959 Speaker 1: I am here with my producer, Mike. Mike, it is 14 00:00:51,000 --> 00:00:54,360 Speaker 1: not often that we are talking about drama. Drama might 15 00:00:54,360 --> 00:00:58,600 Speaker 1: be a little bit strong drama discourse dialogue that I 16 00:00:58,640 --> 00:01:00,800 Speaker 1: am at the center of. For something that I said 17 00:01:00,880 --> 00:01:03,240 Speaker 1: on the podcast a few weeks ago, thank you for 18 00:01:03,360 --> 00:01:06,000 Speaker 1: bravely being here to walk us through this journey. 19 00:01:06,080 --> 00:01:08,760 Speaker 2: Yeah, thanks for having me along. I'm excited to have 20 00:01:08,840 --> 00:01:12,000 Speaker 2: a front row seat. Don't sell yourself short. It is 21 00:01:12,280 --> 00:01:14,800 Speaker 2: legit internet drama that you are involved in. 22 00:01:15,360 --> 00:01:17,640 Speaker 1: I know. It's so much better to have internet low 23 00:01:17,680 --> 00:01:20,679 Speaker 1: stakes Internet drama when you're not involved in it. So 24 00:01:21,040 --> 00:01:22,560 Speaker 1: I kind of feel like I'm on the other end 25 00:01:22,560 --> 00:01:25,480 Speaker 1: of what I've enjoyed rubbernecking at when so many other 26 00:01:25,520 --> 00:01:27,440 Speaker 1: people are on the other end. So here's what's going down. 27 00:01:27,760 --> 00:01:29,680 Speaker 1: If you follow me on Instagram, you might have seen 28 00:01:29,720 --> 00:01:31,600 Speaker 1: that we had a little bit of drama about something 29 00:01:31,600 --> 00:01:33,160 Speaker 1: that we said on the podcast a few weeks ago. 30 00:01:33,680 --> 00:01:36,280 Speaker 1: In our newscast from May nineteenth, I was talking about 31 00:01:36,280 --> 00:01:40,880 Speaker 1: this very weirdly worded Facebook post that Essence Magazine published 32 00:01:40,920 --> 00:01:43,600 Speaker 1: on their Facebook page. Basically was a picture of actor 33 00:01:43,680 --> 00:01:48,520 Speaker 1: Viola Davis at the Can Film Festival looking beautiful. Side note, 34 00:01:48,560 --> 00:01:52,240 Speaker 1: I also might have mispronounced Can in that episode. I 35 00:01:52,280 --> 00:01:55,960 Speaker 1: have always said Con. I thought I was saying it correctly. 36 00:01:56,240 --> 00:01:58,120 Speaker 1: It's how I have said it my whole life. I 37 00:01:58,160 --> 00:02:00,880 Speaker 1: got some feedback that perhaps that it has pronounced can. I 38 00:02:00,920 --> 00:02:04,440 Speaker 1: looked it up and I saw both iterations of the pronunciation. 39 00:02:04,600 --> 00:02:08,600 Speaker 1: So Con, if you are French, if you are affiliated 40 00:02:08,639 --> 00:02:12,840 Speaker 1: with that festival, let me know if I'm saying it incorrectly. Can. 41 00:02:12,880 --> 00:02:14,800 Speaker 1: This is how I'm going to say it right now. 42 00:02:14,960 --> 00:02:19,640 Speaker 1: But any event, Essence was basically complimenting Viola Davis how 43 00:02:19,680 --> 00:02:21,840 Speaker 1: she looked in this picture. She looks amazing. She's wearing 44 00:02:21,880 --> 00:02:24,400 Speaker 1: all white. They put out a Facebook post and I'm 45 00:02:24,400 --> 00:02:28,280 Speaker 1: going to read word for word. We give credit when 46 00:02:28,320 --> 00:02:34,000 Speaker 1: credit is due, and Villa Davis misspelling theirs is looking 47 00:02:34,080 --> 00:02:37,000 Speaker 1: like an eight point fifty. Everyone at can can now 48 00:02:37,080 --> 00:02:39,960 Speaker 1: pack your bags and return home. This is a eight. 49 00:02:40,440 --> 00:02:44,640 Speaker 1: This is an eight. This is supper. God, damn, the 50 00:02:44,760 --> 00:02:48,359 Speaker 1: damn is broken and the flood of goodness has overflowed. 51 00:02:48,600 --> 00:02:53,320 Speaker 1: Can out of ten hashtag essens. So I speculated that 52 00:02:53,440 --> 00:02:55,840 Speaker 1: this post was not written by a human, It was 53 00:02:55,880 --> 00:03:00,720 Speaker 1: in fact written by AI. I believe that somebody specifically 54 00:03:00,760 --> 00:03:06,400 Speaker 1: asked an AI program to compliment someone's outfit and do 55 00:03:06,560 --> 00:03:08,880 Speaker 1: so in the voice of a black woman. That is 56 00:03:08,919 --> 00:03:11,440 Speaker 1: what I believe. That is my opinion. In the episode, 57 00:03:11,480 --> 00:03:13,160 Speaker 1: when we were talking about it, I think I made 58 00:03:13,200 --> 00:03:15,239 Speaker 1: it very clear. I said, I don't have any proof, 59 00:03:15,720 --> 00:03:17,560 Speaker 1: but no one will ever be able to convince me 60 00:03:18,080 --> 00:03:20,679 Speaker 1: that this was not written by AI. Just something about it. 61 00:03:20,760 --> 00:03:23,920 Speaker 1: I believe it was written by AI. That just seemed 62 00:03:23,960 --> 00:03:27,960 Speaker 1: like the most likely explanation to me, given how weird 63 00:03:28,200 --> 00:03:33,040 Speaker 1: that text was. I posted a clip from that episode 64 00:03:33,040 --> 00:03:36,360 Speaker 1: of a podcast talking about this to my Instagram page 65 00:03:36,440 --> 00:03:40,880 Speaker 1: and Essence Magazine Surprise Surprise replied, So when I woke 66 00:03:40,960 --> 00:03:44,360 Speaker 1: up on Saturday and saw that they were in my comments, 67 00:03:45,080 --> 00:03:47,560 Speaker 1: at first I was like pretty happy. I was like, wow, 68 00:03:47,600 --> 00:03:50,360 Speaker 1: I can't believe that this post made it all the 69 00:03:50,360 --> 00:03:55,400 Speaker 1: way to Essence. So their reply said busted call us 70 00:03:55,560 --> 00:03:58,120 Speaker 1: I Carly, and then a little robot emoji, which is 71 00:03:58,160 --> 00:04:00,800 Speaker 1: a reference to a Disney Channel show about two kind 72 00:04:00,840 --> 00:04:04,080 Speaker 1: of techy girls who run a website and a show online. 73 00:04:04,160 --> 00:04:09,400 Speaker 1: So I took that to mean they are playfully acknowledging Yep, 74 00:04:09,440 --> 00:04:13,040 Speaker 1: we're busted. We used AI to make this comment. That's 75 00:04:13,040 --> 00:04:15,480 Speaker 1: why it was so weird, No big deal. Didn't think 76 00:04:15,520 --> 00:04:17,679 Speaker 1: anything of it. In fact, I thought like, oh wow, 77 00:04:17,800 --> 00:04:22,680 Speaker 1: I am happy to see them playfully taking ownership of 78 00:04:22,760 --> 00:04:25,279 Speaker 1: being called out for using kind of a like a 79 00:04:25,360 --> 00:04:29,480 Speaker 1: janky AI voice. So then I replied, ah, love you guys, 80 00:04:29,880 --> 00:04:33,280 Speaker 1: hard emoji crying laughing emoji, because I was legitimately tickled 81 00:04:33,279 --> 00:04:36,560 Speaker 1: by this, right, and the whole clip was sort of 82 00:04:36,600 --> 00:04:40,479 Speaker 1: meant in jest, right, Like I wasn't dragging Essence Magazine. 83 00:04:40,520 --> 00:04:42,719 Speaker 1: I like Essence Magazine, and I think they do good reporting. 84 00:04:43,160 --> 00:04:47,400 Speaker 1: It was more about the pitfalls and fall and like 85 00:04:47,560 --> 00:04:51,400 Speaker 1: drawbacks of experimenting with ai voice in media. It really 86 00:04:51,440 --> 00:04:53,520 Speaker 1: could have been any brand that was not meant to 87 00:04:53,560 --> 00:04:55,159 Speaker 1: be an attack on essence. I did not feel it 88 00:04:55,200 --> 00:04:59,839 Speaker 1: that way. People listening to the episode, it's very jovial, 89 00:05:00,680 --> 00:05:05,880 Speaker 1: lighthearted with me. Okay, So they replied to my comment 90 00:05:05,920 --> 00:05:08,720 Speaker 1: that's like I love you guys, They say, we love 91 00:05:08,760 --> 00:05:12,359 Speaker 1: you too, but let's be more responsible with the reporting 92 00:05:12,640 --> 00:05:17,520 Speaker 1: of misinformation. So that you're right to guess that is 93 00:05:17,560 --> 00:05:21,760 Speaker 1: the appropriate response. What are your thoughts on that as 94 00:05:21,760 --> 00:05:23,600 Speaker 1: the producer of this podcast. 95 00:05:23,560 --> 00:05:27,680 Speaker 2: Well, it does not feel good to be accused of 96 00:05:27,760 --> 00:05:32,240 Speaker 2: misinf spreading misinformation, right, Like, we go out of our 97 00:05:32,279 --> 00:05:37,839 Speaker 2: way to counter misinformation, and so that doesn't feel good. 98 00:05:38,720 --> 00:05:41,920 Speaker 2: And I can imagine that you know it being on 99 00:05:41,960 --> 00:05:46,240 Speaker 2: your personal Instagram felt extra not good. But it's also 100 00:05:46,279 --> 00:05:49,760 Speaker 2: a weird sequence of posts, right Like the first post 101 00:05:49,920 --> 00:05:54,440 Speaker 2: said busted, as if they were busted doing the thing 102 00:05:54,480 --> 00:05:55,599 Speaker 2: they were accused of doing. 103 00:05:55,800 --> 00:05:58,240 Speaker 1: Who says busted when they're not busted, Like busted has 104 00:05:58,279 --> 00:06:01,240 Speaker 1: a very specific unless they were kind of trying to 105 00:06:01,560 --> 00:06:04,880 Speaker 1: play with it or something. But like busted, means oh no. 106 00:06:05,000 --> 00:06:09,080 Speaker 2: Cause yeah, yeah, like I have been caught. I'm busted. 107 00:06:10,440 --> 00:06:13,680 Speaker 2: So it's weird to know what to make of it, 108 00:06:14,120 --> 00:06:17,080 Speaker 2: Like if they're if they are busted, then what was 109 00:06:17,120 --> 00:06:17,920 Speaker 2: the misinformation? 110 00:06:18,320 --> 00:06:22,400 Speaker 1: Great question? So the misinformation comment I just could not 111 00:06:22,520 --> 00:06:26,599 Speaker 1: let stand. I fought that was a pretty strong way 112 00:06:26,640 --> 00:06:28,680 Speaker 1: to phrase something that I went out of my way 113 00:06:28,720 --> 00:06:31,800 Speaker 1: to say. I have no proof, this is my opinion. 114 00:06:31,920 --> 00:06:35,720 Speaker 1: I'm just saying what I think. I did also include 115 00:06:35,760 --> 00:06:39,599 Speaker 1: that someone at Essence did edit that post so that 116 00:06:39,680 --> 00:06:42,400 Speaker 1: it looked more It was more polished and didn't read 117 00:06:42,520 --> 00:06:45,160 Speaker 1: quite as wed. I still think it's weird in my opinion, 118 00:06:45,240 --> 00:06:48,760 Speaker 1: but somebody went in and edited it, so clearly we're 119 00:06:48,800 --> 00:06:51,640 Speaker 1: both on the same page that post something was up 120 00:06:51,680 --> 00:06:53,279 Speaker 1: with it, because why else would they edit it. So 121 00:06:53,760 --> 00:06:56,359 Speaker 1: to their misinformation comment, I reiterated that this was just 122 00:06:56,360 --> 00:06:59,680 Speaker 1: my opinion about how such a weird post wound up 123 00:06:59,680 --> 00:07:02,239 Speaker 1: on their pay I asked, like, if it wasn't Ai, 124 00:07:03,360 --> 00:07:05,719 Speaker 1: was it like a sloppy human? You didn't even spell 125 00:07:05,800 --> 00:07:08,560 Speaker 1: Viola Davis's name, right. I would think that any person 126 00:07:08,600 --> 00:07:12,080 Speaker 1: working at Essence, writing about entertainment especially would know how 127 00:07:12,120 --> 00:07:14,480 Speaker 1: to spell her name and so I said, if I 128 00:07:14,520 --> 00:07:17,320 Speaker 1: got it wrong, I am more than happy to correct 129 00:07:17,320 --> 00:07:19,000 Speaker 1: the record, and that still stands. I would love to 130 00:07:19,040 --> 00:07:22,160 Speaker 1: correct the record, but I need to know what happened. 131 00:07:22,200 --> 00:07:23,880 Speaker 1: Was it a human was it not AI? Like, what 132 00:07:23,960 --> 00:07:28,880 Speaker 1: are you disputing specifically? And then they went silent. So 133 00:07:28,960 --> 00:07:31,920 Speaker 1: this is a little bit of a personal thing with me. 134 00:07:32,400 --> 00:07:35,679 Speaker 1: I really have an issue when somebody is very loud, 135 00:07:35,720 --> 00:07:39,000 Speaker 1: the accusation is very loud, but then when you're like, okay, 136 00:07:39,000 --> 00:07:40,480 Speaker 1: well then what did I get wrong? When you're asked 137 00:07:40,480 --> 00:07:44,000 Speaker 1: for clarifying information, silent cannot I cannot stand that. It's 138 00:07:44,040 --> 00:07:46,920 Speaker 1: like a throw a rock and hide your hands kind 139 00:07:46,920 --> 00:07:49,960 Speaker 1: of thing, Like you were so loud accusing me of 140 00:07:50,120 --> 00:07:54,840 Speaker 1: misreporting misinformation about your publication, but you're unwilling to give 141 00:07:54,880 --> 00:07:57,320 Speaker 1: me any information about what exactly I got wrong and 142 00:07:57,400 --> 00:07:59,920 Speaker 1: how I got it wrong. I want to provide accurate 143 00:08:00,040 --> 00:08:03,520 Speaker 1: information to my listenership and my readership and use my 144 00:08:03,560 --> 00:08:06,920 Speaker 1: platform to do that, obviously, but it's telling to me 145 00:08:08,320 --> 00:08:12,800 Speaker 1: that they just went silent. So I don't engage in 146 00:08:12,840 --> 00:08:16,400 Speaker 1: a lot of drama. I'm a drama appreciate her. I'm 147 00:08:16,440 --> 00:08:19,840 Speaker 1: a drama connoisseur. This is a podcast but I'm wearing 148 00:08:19,880 --> 00:08:23,520 Speaker 1: a hat currently as we were recording that references my 149 00:08:23,680 --> 00:08:26,720 Speaker 1: love of petty drama. It's a hat that says I 150 00:08:26,760 --> 00:08:28,760 Speaker 1: don't know her, and it's a hat from my one 151 00:08:28,760 --> 00:08:31,400 Speaker 1: of my favorite podcasts, two Weekly. It's a reference to 152 00:08:31,440 --> 00:08:35,040 Speaker 1: Mariah Carey always when asked about her, one of her 153 00:08:35,080 --> 00:08:39,199 Speaker 1: nemesis is Nemesi j Lo. She always coolly responds with 154 00:08:39,679 --> 00:08:41,839 Speaker 1: I don't know her, which I think is a great 155 00:08:41,880 --> 00:08:46,120 Speaker 1: way to respond to drama without really engaging in it, but 156 00:08:46,160 --> 00:08:49,360 Speaker 1: still engaging in it. Love her. But here's the thing 157 00:08:49,400 --> 00:08:52,560 Speaker 1: about me. I am kind of a petty person. I 158 00:08:52,600 --> 00:08:56,360 Speaker 1: host a podcast called Beef that is about pettiness and 159 00:08:56,480 --> 00:08:59,880 Speaker 1: rivalries and why it's so important. So obviously I wasn't 160 00:09:00,080 --> 00:09:03,000 Speaker 1: going to let this go telling me that I'm misreporting 161 00:09:03,040 --> 00:09:06,120 Speaker 1: things and reporting misinformation, I'm not going to let that go. 162 00:09:06,200 --> 00:09:09,199 Speaker 1: I'm sorry. So this happened on a weekend and I 163 00:09:09,240 --> 00:09:10,760 Speaker 1: happened to have a lot of time on my hands. 164 00:09:11,080 --> 00:09:13,720 Speaker 1: So I made another comment and I was like, essence, 165 00:09:13,800 --> 00:09:15,960 Speaker 1: what is the truth? Didn't hear back? I made a 166 00:09:16,000 --> 00:09:20,200 Speaker 1: story with the with a screenshot of their initial post, 167 00:09:20,320 --> 00:09:24,280 Speaker 1: and I said essence in my Instagram comments has implied 168 00:09:24,400 --> 00:09:26,320 Speaker 1: that they did not use AI to write this post. 169 00:09:26,920 --> 00:09:28,480 Speaker 1: I asked them, I said, I will be happy to 170 00:09:28,480 --> 00:09:30,560 Speaker 1: correct the record if they give me some follow up 171 00:09:30,559 --> 00:09:33,520 Speaker 1: about what did happen? Was it a human error? You 172 00:09:33,559 --> 00:09:36,600 Speaker 1: know what happened here? Happy to correct, but need some information. 173 00:09:36,840 --> 00:09:40,040 Speaker 1: Still nothing. So that is why I am taking it 174 00:09:40,320 --> 00:09:42,360 Speaker 1: to the podcast. I feel like I need to talk 175 00:09:42,360 --> 00:09:44,960 Speaker 1: about it. I'm not intending the unletting it go until 176 00:09:44,960 --> 00:09:47,120 Speaker 1: I hear back from Essence and so if anyone knows 177 00:09:47,240 --> 00:09:49,600 Speaker 1: Essence or has a connection to them, I would love 178 00:09:49,600 --> 00:09:52,240 Speaker 1: to hear you have an invite to come on the show. 179 00:09:52,320 --> 00:09:53,720 Speaker 1: I actually able to think that would be great. 180 00:09:54,040 --> 00:09:57,480 Speaker 2: So bridget what about this post made you think it 181 00:09:57,520 --> 00:09:58,319 Speaker 2: was written by AI? 182 00:09:58,640 --> 00:10:02,320 Speaker 1: Great question. Again, this is my opinion. I have no proof. 183 00:10:02,360 --> 00:10:06,520 Speaker 1: I have no insight into Essence Magazine's editorial room. I 184 00:10:06,559 --> 00:10:08,800 Speaker 1: put out a poll on Instagram to say, like, do 185 00:10:08,840 --> 00:10:11,560 Speaker 1: people think this is AI or not? Overwhelmingly most people 186 00:10:11,600 --> 00:10:13,800 Speaker 1: think it's AI. Not that it's a scientific poll, but 187 00:10:13,840 --> 00:10:15,680 Speaker 1: one person said that they believe that it was written 188 00:10:15,679 --> 00:10:19,640 Speaker 1: by a human who was trying to do this like youthful, 189 00:10:19,840 --> 00:10:24,679 Speaker 1: voicy TikTok voice and just falling short reasonable. Right, Here's 190 00:10:24,720 --> 00:10:27,400 Speaker 1: why I think it was AI. I spend a lot 191 00:10:27,440 --> 00:10:32,080 Speaker 1: of time analyzing AI generated content, both visual content and 192 00:10:32,120 --> 00:10:34,560 Speaker 1: written content. And one thing that when it comes to 193 00:10:34,600 --> 00:10:39,760 Speaker 1: written text is AI can sometimes be a bit repetitive. 194 00:10:40,200 --> 00:10:47,000 Speaker 1: And so the fact that this essence post reiterated this 195 00:10:47,160 --> 00:10:50,840 Speaker 1: eight bit a few times that seemed a little AI 196 00:10:51,080 --> 00:10:54,200 Speaker 1: like to me, like this eight this is a eight, 197 00:10:54,280 --> 00:10:58,679 Speaker 1: this is a eight. I don't It's not something I 198 00:10:58,800 --> 00:11:01,959 Speaker 1: get that they are going for, like a very specific 199 00:11:02,160 --> 00:11:05,560 Speaker 1: black women you know slang, I say that you know 200 00:11:05,679 --> 00:11:08,480 Speaker 1: she ate that ate ni left no crumbs all the time, 201 00:11:09,040 --> 00:11:12,240 Speaker 1: that would be those are phrases that I've heard before 202 00:11:12,640 --> 00:11:15,840 Speaker 1: in the vernacular. The way that they put it in 203 00:11:15,840 --> 00:11:18,280 Speaker 1: that repetitive way, have never heard that before. And the 204 00:11:18,320 --> 00:11:22,760 Speaker 1: fact that it's repeating similar words I'm sorry, that is 205 00:11:22,800 --> 00:11:25,320 Speaker 1: something that AI it kind of does when you're looking 206 00:11:25,360 --> 00:11:27,839 Speaker 1: at AI generated text is repetition. So that was the 207 00:11:27,880 --> 00:11:29,520 Speaker 1: first thing that kind of made me think less is AI. 208 00:11:30,120 --> 00:11:34,080 Speaker 1: The second thing is a little bit harder to describe, 209 00:11:34,720 --> 00:11:37,400 Speaker 1: but you know it when you see it. It's just 210 00:11:37,480 --> 00:11:41,240 Speaker 1: that AI generated text just doesn't sound right the same 211 00:11:41,280 --> 00:11:43,920 Speaker 1: way that when you see an AI generated image sometimes 212 00:11:44,000 --> 00:11:46,720 Speaker 1: it just has a quality to it that's hard to define, 213 00:11:46,720 --> 00:11:48,720 Speaker 1: but you know it when you see it that tells 214 00:11:48,760 --> 00:11:51,800 Speaker 1: you this, this isn't quite right. Like, Mike, do you 215 00:11:51,840 --> 00:11:55,000 Speaker 1: remember a couple of years ago when people would be 216 00:11:55,040 --> 00:11:57,880 Speaker 1: playing with AI and be like, oh, we trained an 217 00:11:57,880 --> 00:12:01,120 Speaker 1: AI on watching fifty Hallmark Christmas movies and here's what 218 00:12:01,200 --> 00:12:03,679 Speaker 1: it generated. And it's the joke that the reason why 219 00:12:03,720 --> 00:12:07,560 Speaker 1: those things were funny was that, like they were almost right, 220 00:12:07,840 --> 00:12:10,000 Speaker 1: but something about them just was off. So you could 221 00:12:10,040 --> 00:12:12,320 Speaker 1: just tell, like, this is not a normal Christmas movie. 222 00:12:12,360 --> 00:12:15,599 Speaker 1: There's some detail or quality to it that makes it 223 00:12:15,720 --> 00:12:17,720 Speaker 1: just sound off. Do you know what I'm saying. 224 00:12:18,000 --> 00:12:22,280 Speaker 2: Yeah, it'll it'll be like ninety ninety five percent of 225 00:12:22,320 --> 00:12:25,600 Speaker 2: the way they're just like nailing all the common tropes 226 00:12:25,640 --> 00:12:29,439 Speaker 2: and patterns from its training corpus, but that last five 227 00:12:29,559 --> 00:12:32,440 Speaker 2: or ten percent will just be like off the wall 228 00:12:32,800 --> 00:12:35,800 Speaker 2: and like stand out like a sort of thumb exactly. 229 00:12:35,840 --> 00:12:37,439 Speaker 1: So that's that's what I think is going on here. 230 00:12:37,440 --> 00:12:40,120 Speaker 1: That's what this sounds like to me. Also, the fact 231 00:12:40,200 --> 00:12:44,440 Speaker 1: the post relies on two different metaphors. One is like 232 00:12:44,720 --> 00:12:46,560 Speaker 1: she ate. If you're not familiar with that, it's like 233 00:12:47,040 --> 00:12:49,320 Speaker 1: if somebody ate. It means that they whatever they're doing, 234 00:12:49,360 --> 00:12:50,840 Speaker 1: they're doing a good job of it, right, They ate 235 00:12:50,880 --> 00:12:52,600 Speaker 1: and left no crumb. She thought she ate that all 236 00:12:52,600 --> 00:12:56,640 Speaker 1: of that one and then two we give credit where 237 00:12:56,679 --> 00:12:58,760 Speaker 1: credit is due, And this is looking like an eight 238 00:12:58,760 --> 00:13:01,480 Speaker 1: P fifty a reference to credit scores, money you know 239 00:13:01,559 --> 00:13:06,160 Speaker 1: in your bag. To us, those two metaphors seem very 240 00:13:06,200 --> 00:13:10,120 Speaker 1: distinct to me. It's curious to me that someone would 241 00:13:10,160 --> 00:13:13,360 Speaker 1: put them in the same post. It just it just 242 00:13:13,360 --> 00:13:15,800 Speaker 1: seems so desparate that I have to question it, Like 243 00:13:15,880 --> 00:13:19,720 Speaker 1: it just sounds like somebody was trying to pack way 244 00:13:19,800 --> 00:13:24,880 Speaker 1: too many aave metaphors and slang terms into one sentence, 245 00:13:24,960 --> 00:13:28,280 Speaker 1: even metaphors that don't really relate to each other. And 246 00:13:28,280 --> 00:13:31,600 Speaker 1: that is something that we know that AI does. When 247 00:13:31,640 --> 00:13:34,280 Speaker 1: you ask AI to write something that's one of the 248 00:13:34,360 --> 00:13:37,040 Speaker 1: kind of giveaways that it might not be a human 249 00:13:37,320 --> 00:13:39,559 Speaker 1: and in fact it is AI, is that it's giving 250 00:13:39,600 --> 00:13:42,400 Speaker 1: you way too much. It's like a little bit over 251 00:13:42,440 --> 00:13:44,520 Speaker 1: the top in a way that makes it that much 252 00:13:44,559 --> 00:13:46,640 Speaker 1: more obvious that it's not a human. And I want 253 00:13:46,679 --> 00:13:49,000 Speaker 1: to get into a little bit more why I feel 254 00:13:49,000 --> 00:13:51,959 Speaker 1: like this post reads like AI to me. After a 255 00:13:52,040 --> 00:14:08,800 Speaker 1: quick break at our back. So another thing that just 256 00:14:08,880 --> 00:14:14,120 Speaker 1: strikes me as potentially one of the reasons why this 257 00:14:14,160 --> 00:14:17,360 Speaker 1: feels like AI to me, in my opinion, is that 258 00:14:17,400 --> 00:14:21,440 Speaker 1: it was part of a series of posts just breaking 259 00:14:21,480 --> 00:14:25,240 Speaker 1: down different celebrities outfits, and so it's you know, it's 260 00:14:25,240 --> 00:14:28,160 Speaker 1: gonna be like it's not like one post, it's gonna 261 00:14:28,200 --> 00:14:32,480 Speaker 1: be multiple posts as people walk the carpet at the festival. 262 00:14:32,760 --> 00:14:36,600 Speaker 1: And so I just having worked in social media before, 263 00:14:36,960 --> 00:14:39,880 Speaker 1: I've run social media for big news companies that you've 264 00:14:39,880 --> 00:14:43,080 Speaker 1: definitely heard of. I know that when you are in 265 00:14:43,120 --> 00:14:45,760 Speaker 1: a situation where you're like live live tweeting, or like 266 00:14:46,040 --> 00:14:50,280 Speaker 1: you're gonna be posting ten pictures and coming up with 267 00:14:50,320 --> 00:14:52,840 Speaker 1: posts and captions for like ten or twenty pictures in 268 00:14:52,880 --> 00:14:55,360 Speaker 1: an hour, that's a lot. I was doing this work 269 00:14:55,360 --> 00:14:58,520 Speaker 1: before AI was so commonplace in media. It would not 270 00:14:58,600 --> 00:15:03,080 Speaker 1: be surprising to me if a brand like Essence or 271 00:15:03,120 --> 00:15:05,440 Speaker 1: to be like, listen, we're gonna have one hundred images 272 00:15:05,480 --> 00:15:07,960 Speaker 1: of celebrities. We get the caption from this festival, let's 273 00:15:08,000 --> 00:15:09,480 Speaker 1: just run it in just let's just run it into 274 00:15:09,520 --> 00:15:11,680 Speaker 1: chat GPT and pull from there to make this quick. 275 00:15:11,760 --> 00:15:14,880 Speaker 1: That would that surprise me at all? And again, no shade. 276 00:15:14,880 --> 00:15:18,160 Speaker 1: That would not be any different than I'm sure any 277 00:15:18,160 --> 00:15:20,520 Speaker 1: other media company is doing right now. That is not 278 00:15:20,560 --> 00:15:23,080 Speaker 1: anything that is to be ashamed of. That's something bad. 279 00:15:23,120 --> 00:15:25,160 Speaker 1: I'm not even calling them out. It just like is 280 00:15:25,200 --> 00:15:29,960 Speaker 1: a reality of how brands and media companies are likely 281 00:15:30,040 --> 00:15:34,040 Speaker 1: right now already using AI, if not experimenting with it, 282 00:15:34,280 --> 00:15:36,720 Speaker 1: and certainly how they're going to be using it going forward, 283 00:15:36,800 --> 00:15:40,680 Speaker 1: I'm pretty sure. And because you know, media companies and 284 00:15:40,760 --> 00:15:44,680 Speaker 1: brands are already using this technology to communicate with us 285 00:15:44,800 --> 00:15:47,520 Speaker 1: the public, I wanted to play a little game, do 286 00:15:47,600 --> 00:15:51,280 Speaker 1: a little experiment that I think will just be another 287 00:15:51,440 --> 00:15:55,320 Speaker 1: bit of evidence as to why I feel so strongly 288 00:15:55,400 --> 00:15:58,840 Speaker 1: that this post was generated by AI. So I went 289 00:15:58,880 --> 00:16:02,560 Speaker 1: over to chat GPT and I asked Chatgypt to come 290 00:16:02,640 --> 00:16:06,320 Speaker 1: up with a short social media post about Viola Davis 291 00:16:06,560 --> 00:16:09,920 Speaker 1: her outfit at can. So first, when I put it in, 292 00:16:10,000 --> 00:16:12,560 Speaker 1: I said, make a post about how good Viola Davis's 293 00:16:12,600 --> 00:16:16,440 Speaker 1: outfit looked at can as a black woman. The first 294 00:16:16,440 --> 00:16:19,440 Speaker 1: thing that they gave me was very kind of formal. 295 00:16:19,480 --> 00:16:21,440 Speaker 1: It was like, let's take a moment to appreciate the 296 00:16:22,040 --> 00:16:25,720 Speaker 1: incomparable Viola Davis a true embodiment of elegance and beauty 297 00:16:25,960 --> 00:16:27,880 Speaker 1: who raised the red cart. But at this year's Can 298 00:16:27,920 --> 00:16:30,880 Speaker 1: Film Festival as a fellow black woman, I couldn't help 299 00:16:30,920 --> 00:16:33,840 Speaker 1: it be in all of her captivating presence and radiant charm. 300 00:16:34,080 --> 00:16:35,920 Speaker 1: So this when I just said do it as a 301 00:16:35,960 --> 00:16:40,360 Speaker 1: black woman, it was giving me you know, still pretty 302 00:16:40,400 --> 00:16:43,920 Speaker 1: polished like standard English. It was just the speaker is 303 00:16:44,000 --> 00:16:47,760 Speaker 1: just referencing that they are a black woman, which obviously 304 00:16:47,880 --> 00:16:49,840 Speaker 1: is not what this post sounds like. So then I 305 00:16:49,880 --> 00:16:53,120 Speaker 1: was like, ah, same thing, but give it to me 306 00:16:53,400 --> 00:16:58,840 Speaker 1: an aave African American vernacular English or like slang. Listen 307 00:16:58,880 --> 00:17:02,320 Speaker 1: to the difference in this in what they gave me. 308 00:17:02,880 --> 00:17:05,600 Speaker 2: So this you're gonna read what chat GPT gave you. 309 00:17:05,640 --> 00:17:07,040 Speaker 2: In response to that prompt. 310 00:17:07,119 --> 00:17:11,920 Speaker 1: That's right slaying the Can scene. Viola Davis looking snatched 311 00:17:12,200 --> 00:17:16,000 Speaker 1: hands emoji, fingernail painting emoji. Y'all, let's take a hot 312 00:17:16,040 --> 00:17:18,719 Speaker 1: minute to give some major props to our girl, Viola 313 00:17:18,800 --> 00:17:22,640 Speaker 1: Davis straight killing it at the Can Film Festival. Fire emoji. 314 00:17:22,960 --> 00:17:25,560 Speaker 1: She came through dripping with all that melon and magic 315 00:17:25,880 --> 00:17:29,560 Speaker 1: servant looks. That got a shouting Yes, Queen Viola was 316 00:17:29,560 --> 00:17:32,880 Speaker 1: straight up flawless, rocking that red carpet like nobody's business. 317 00:17:33,040 --> 00:17:35,720 Speaker 1: She had a swooning and a jaw dropping gown that 318 00:17:35,840 --> 00:17:38,320 Speaker 1: hugged all of her curves just right. And can we 319 00:17:38,359 --> 00:17:41,040 Speaker 1: talk about that melon and glow? Her skin was popping 320 00:17:41,119 --> 00:17:43,880 Speaker 1: like a summer sunset. Viola's talent is on a whole 321 00:17:44,040 --> 00:17:48,600 Speaker 1: nother level and another is like apostrophe than nt h 322 00:17:48,640 --> 00:17:51,560 Speaker 1: e er a whole another level. And she ain't afraid 323 00:17:51,560 --> 00:17:54,280 Speaker 1: to speak truth to power. She's using her platform to 324 00:17:54,320 --> 00:17:56,800 Speaker 1: shine a light on important issues and make a difference. 325 00:17:57,119 --> 00:18:00,560 Speaker 1: That's what we call a real boss lady. Y'all ain't 326 00:18:00,600 --> 00:18:03,560 Speaker 1: ready for the slag age that Viola David's brought to Can. 327 00:18:03,760 --> 00:18:06,760 Speaker 1: Her outfit had us all shook melon and poppin confidence 328 00:18:06,800 --> 00:18:10,960 Speaker 1: on bleak hashtag Viola Davis hashtag Can Film Festival hashtag 329 00:18:11,160 --> 00:18:15,440 Speaker 1: slaying it. So, I don't think I need to tell 330 00:18:15,560 --> 00:18:18,520 Speaker 1: you that. I feel like there's a lot going on 331 00:18:19,000 --> 00:18:22,159 Speaker 1: in what chat GPT gave us. But well, do you 332 00:18:22,160 --> 00:18:23,640 Speaker 1: have a reaction to it? Like what do you think? 333 00:18:23,680 --> 00:18:24,800 Speaker 1: What are your thoughts? 334 00:18:25,400 --> 00:18:31,439 Speaker 2: It's a lot. Uh yeah, it really sounded kind of 335 00:18:31,480 --> 00:18:34,560 Speaker 2: similar to the post we were talking about. 336 00:18:35,160 --> 00:18:35,320 Speaker 1: Uh. 337 00:18:36,000 --> 00:18:42,440 Speaker 2: It referenced Melanin' three times repetition, right, Okay, it's generous. 338 00:18:42,480 --> 00:18:44,480 Speaker 1: Something that jumps out at me that I think is 339 00:18:44,600 --> 00:18:48,679 Speaker 1: very similar to the Essence magazine Facebook post that I 340 00:18:48,720 --> 00:18:51,679 Speaker 1: believe was generated by AI was that it takes things 341 00:18:51,680 --> 00:18:54,720 Speaker 1: that are I wouldn't say disparate, but it just it 342 00:18:55,280 --> 00:19:00,359 Speaker 1: adds a lot in like it's like, it's not I 343 00:19:00,400 --> 00:19:04,439 Speaker 1: don't know that someone would say in a if they 344 00:19:04,440 --> 00:19:07,240 Speaker 1: were making a social media post. I would be surprised 345 00:19:07,320 --> 00:19:12,280 Speaker 1: if someone was using this many slang words, like if 346 00:19:12,320 --> 00:19:17,359 Speaker 1: you're saying yes queen, adding something that is on fleek 347 00:19:17,880 --> 00:19:19,959 Speaker 1: that's like a hat on a hat. Like it's just like, 348 00:19:20,280 --> 00:19:22,960 Speaker 1: I don't know a person who would speak that way. 349 00:19:23,440 --> 00:19:26,160 Speaker 1: And I think I see a lot of the similar 350 00:19:26,800 --> 00:19:29,440 Speaker 1: repetition of things that we got on that Essence post 351 00:19:29,640 --> 00:19:31,879 Speaker 1: to what I've what I've just generated from chat GPT. 352 00:19:32,000 --> 00:19:34,399 Speaker 1: I think it just it just seems very similar to me. 353 00:19:35,200 --> 00:19:39,600 Speaker 1: It seems similar in the ways of like making little 354 00:19:41,160 --> 00:19:45,639 Speaker 1: like references to things that are not totally slang, like 355 00:19:46,119 --> 00:19:48,080 Speaker 1: they kind of sound like slang, and if you read 356 00:19:48,080 --> 00:19:51,199 Speaker 1: it quickly, you know, you might be like, oh, that 357 00:19:51,280 --> 00:19:54,040 Speaker 1: sounds like how you know you would expect But then 358 00:19:54,040 --> 00:19:56,480 Speaker 1: when you actually person you're like, well, do I actually 359 00:19:56,520 --> 00:19:58,720 Speaker 1: know anybody who speaks like this? Is this what a 360 00:19:58,800 --> 00:20:02,720 Speaker 1: human would actually say? Or is this what AI pulling from? 361 00:20:03,240 --> 00:20:06,280 Speaker 1: Parts of the culture, parts of like everything that's out 362 00:20:06,320 --> 00:20:09,159 Speaker 1: there about what is the perception of what it sounds 363 00:20:09,160 --> 00:20:11,600 Speaker 1: like to be a black woman speaking in aave about 364 00:20:11,600 --> 00:20:14,399 Speaker 1: something that she likes. It just just feels like someone 365 00:20:14,880 --> 00:20:21,160 Speaker 1: doing a bad impression of black women and the way 366 00:20:21,160 --> 00:20:23,159 Speaker 1: that we talk online. It really reminds me a lot 367 00:20:23,200 --> 00:20:26,840 Speaker 1: of what Shafika Hudson described in our episode about and 368 00:20:27,040 --> 00:20:32,240 Speaker 1: Father's Day, as she describes it as obviously racist word salad, Like, 369 00:20:32,520 --> 00:20:36,600 Speaker 1: there's something about this that chat GPTs, the content that 370 00:20:36,720 --> 00:20:40,439 Speaker 1: chat GPT spit out that just reads like a black 371 00:20:40,560 --> 00:20:44,480 Speaker 1: woman impersonation word salad Like it makes all of the 372 00:20:44,520 --> 00:20:48,879 Speaker 1: things on their own makes sense. But when you zoom 373 00:20:49,000 --> 00:20:51,199 Speaker 1: out and you're like, well, is that really what someone 374 00:20:51,200 --> 00:20:53,600 Speaker 1: would string together if they were trying to create a 375 00:20:53,640 --> 00:20:57,240 Speaker 1: social post? In my opinion, probably. 376 00:20:56,840 --> 00:21:00,320 Speaker 2: Not, Yeah, that's really a student. I think you that 377 00:21:00,359 --> 00:21:02,760 Speaker 2: it's like a hat on a hat, like it just 378 00:21:02,800 --> 00:21:09,679 Speaker 2: goes on and on with multiple metaphors, multiple things that 379 00:21:09,880 --> 00:21:15,640 Speaker 2: sound like they could be slang, but maybe aren't. Yeah, 380 00:21:15,680 --> 00:21:21,240 Speaker 2: it's and when you zoom out, it looks like what 381 00:21:22,119 --> 00:21:27,480 Speaker 2: a large language model trained on a corpus of perceptions 382 00:21:27,560 --> 00:21:30,240 Speaker 2: of what black women might sound like. 383 00:21:30,680 --> 00:21:34,199 Speaker 1: And again, as cringey as all of this sounds, and 384 00:21:34,240 --> 00:21:37,680 Speaker 1: I know it sounds very cringey, I'm not even necessarily 385 00:21:37,760 --> 00:21:40,560 Speaker 1: pointing all of this out to call out Essence or 386 00:21:40,600 --> 00:21:44,160 Speaker 1: any media company, because again, Essence is not doing anything 387 00:21:44,240 --> 00:21:46,880 Speaker 1: that I don't think any other media company out there 388 00:21:47,000 --> 00:21:49,479 Speaker 1: is doing. I think this is commonplace. I think there 389 00:21:49,480 --> 00:21:51,680 Speaker 1: are times when it seems more when it is more 390 00:21:51,720 --> 00:21:56,399 Speaker 1: obvious than others. But I think this is something that 391 00:21:56,440 --> 00:22:01,720 Speaker 1: we're going to have to train ourselves to be aware 392 00:22:01,800 --> 00:22:05,960 Speaker 1: of and critical of, and be you know, thinking about 393 00:22:06,000 --> 00:22:09,200 Speaker 1: as we consume media as we go forward in this 394 00:22:09,240 --> 00:22:12,040 Speaker 1: particular moment in our tech our shared tech world. 395 00:22:12,680 --> 00:22:16,760 Speaker 2: Yeah, you know, I keep thinking about the like, what 396 00:22:16,760 --> 00:22:18,880 Speaker 2: does it mean that it packed all of those different 397 00:22:19,200 --> 00:22:25,520 Speaker 2: metaphors and illusions and idioms in there, And like, maybe 398 00:22:25,560 --> 00:22:28,960 Speaker 2: that's what it looks like when part of the prompt 399 00:22:29,040 --> 00:22:31,720 Speaker 2: to chat GPT or one of these large language models 400 00:22:31,880 --> 00:22:36,000 Speaker 2: is to try to sound like a particular group, Is 401 00:22:36,560 --> 00:22:39,439 Speaker 2: that it just really hyper focuses on that part of 402 00:22:39,480 --> 00:22:43,439 Speaker 2: the assignment, and so it just keeps like hammering on 403 00:22:43,560 --> 00:22:47,440 Speaker 2: it over and over again in a really unnaturalistic way. 404 00:22:49,960 --> 00:22:56,080 Speaker 1: And I also think that, you know, it's particularly salient 405 00:22:56,200 --> 00:22:59,960 Speaker 1: when you're talking about the way that marginalized groups communicate 406 00:23:00,119 --> 00:23:03,240 Speaker 1: with each other. You know, if you ask chat GBT 407 00:23:03,359 --> 00:23:08,280 Speaker 1: to say something in a stereotypical you know, like give 408 00:23:08,320 --> 00:23:10,240 Speaker 1: it to me an aave, or give it to me 409 00:23:11,200 --> 00:23:15,480 Speaker 1: as a gay person, or I just think that it's 410 00:23:15,560 --> 00:23:19,639 Speaker 1: easy to recognize when someone is being a caricature of 411 00:23:19,680 --> 00:23:22,000 Speaker 1: a marginalized person when we're seeing on television or in 412 00:23:22,040 --> 00:23:26,040 Speaker 1: a movie. I don't know that it's easy to recognize 413 00:23:26,080 --> 00:23:31,359 Speaker 1: it in text that is generated by AI. But I 414 00:23:31,400 --> 00:23:35,000 Speaker 1: think that the same way that we are thinking about 415 00:23:35,000 --> 00:23:37,840 Speaker 1: it when we consume movies and television, we should be 416 00:23:37,880 --> 00:23:40,520 Speaker 1: thinking about it, I guess, or now we should be. 417 00:23:40,640 --> 00:23:42,640 Speaker 1: We're going to have to be thinking about it as 418 00:23:42,640 --> 00:23:46,720 Speaker 1: we just consume content out in the world in this 419 00:23:46,800 --> 00:23:47,840 Speaker 1: era going forward. 420 00:23:48,480 --> 00:23:51,359 Speaker 2: Yeah, I think we've all been seeing headlines for the 421 00:23:51,400 --> 00:23:54,840 Speaker 2: past I don't know, five or six months now ever 422 00:23:54,920 --> 00:23:59,160 Speaker 2: since AI really just like exploded into the public discourse 423 00:23:59,200 --> 00:24:03,160 Speaker 2: with these publicly available tools you know, we've all heard 424 00:24:03,240 --> 00:24:06,520 Speaker 2: the messaging that we need to start using AI and 425 00:24:06,560 --> 00:24:09,680 Speaker 2: figure out how to work AI into our professional workflows 426 00:24:09,720 --> 00:24:12,480 Speaker 2: so that we can be using it more and be 427 00:24:12,520 --> 00:24:16,639 Speaker 2: that much more efficient and effective and productive than people 428 00:24:16,640 --> 00:24:19,720 Speaker 2: who aren't using it, who are going to fall away 429 00:24:20,080 --> 00:24:24,760 Speaker 2: like dinosaurs and relics. And you know, I think a 430 00:24:24,760 --> 00:24:28,199 Speaker 2: lot of people are kind of questioning how true is 431 00:24:28,240 --> 00:24:31,480 Speaker 2: that and what does that even mean? But yeah, you 432 00:24:31,520 --> 00:24:37,119 Speaker 2: can't blame Essence for experimenting with it and you know, 433 00:24:37,200 --> 00:24:40,560 Speaker 2: trying to put AI to work for them if that's 434 00:24:40,600 --> 00:24:42,840 Speaker 2: what they were doing, which you know, like you said, 435 00:24:42,880 --> 00:24:45,840 Speaker 2: it seems like they probably were, so yeah, it's not 436 00:24:46,160 --> 00:24:50,080 Speaker 2: so shameful. It's probably a little embarrassing that they published 437 00:24:50,080 --> 00:24:51,880 Speaker 2: something that they then had to go back and edit, 438 00:24:51,960 --> 00:24:54,960 Speaker 2: but like you know, people do embarrassing stuff all the time. 439 00:24:55,080 --> 00:24:58,159 Speaker 1: So I should also say that the idea like that 440 00:24:58,560 --> 00:25:02,040 Speaker 1: post this is not even really coming from me. As 441 00:25:02,040 --> 00:25:04,879 Speaker 1: I said, I'm a former social media editor and so 442 00:25:04,960 --> 00:25:07,200 Speaker 1: I'm still in a lot of these big, like online 443 00:25:07,200 --> 00:25:11,280 Speaker 1: professional groups dedicated to social media management and like best 444 00:25:11,320 --> 00:25:13,920 Speaker 1: practices and all of that. That is where I first 445 00:25:13,960 --> 00:25:15,959 Speaker 1: saw this post. That is where it first came on 446 00:25:15,960 --> 00:25:20,399 Speaker 1: my radar. Somebody not me posted a screenshot of the 447 00:25:20,440 --> 00:25:23,880 Speaker 1: original Essence magazine Facebook post put it in the group 448 00:25:23,920 --> 00:25:26,320 Speaker 1: and they were like, yo is Essence in here? Like 449 00:25:26,359 --> 00:25:31,439 Speaker 1: this is a really weird post, and so everybody was 450 00:25:31,560 --> 00:25:34,800 Speaker 1: roasting it, so certainly it wasn't just me, and the 451 00:25:34,920 --> 00:25:39,240 Speaker 1: consensus of social media industry professionals was that it was 452 00:25:39,240 --> 00:25:41,960 Speaker 1: written by Ai. So I can't even take credit for 453 00:25:42,600 --> 00:25:46,200 Speaker 1: that as an idea. I wish I could. I definitely 454 00:25:46,200 --> 00:25:48,600 Speaker 1: would have seen that in thought something's up. But the 455 00:25:48,800 --> 00:25:52,480 Speaker 1: reality is is that a large group of social media 456 00:25:52,520 --> 00:25:55,080 Speaker 1: professionals were roasting it and said it was Ai. I 457 00:25:55,119 --> 00:25:57,159 Speaker 1: happened to be one of them. But this is not 458 00:25:57,320 --> 00:25:59,960 Speaker 1: just coming from me. This was like a like an 459 00:26:00,119 --> 00:26:04,440 Speaker 1: online consensus of the space. So I'm sorry. I'm sure 460 00:26:04,480 --> 00:26:06,560 Speaker 1: that if you like for Essence Magazine, I'm sure that 461 00:26:06,680 --> 00:26:08,680 Speaker 1: is like difficult to hear. Nobody wants to hear that 462 00:26:08,680 --> 00:26:12,520 Speaker 1: their post was being roasted by a bunch of their peers. 463 00:26:12,920 --> 00:26:14,720 Speaker 1: But I hate to break it to you that is 464 00:26:14,720 --> 00:26:15,320 Speaker 1: what was going on. 465 00:26:15,440 --> 00:26:17,760 Speaker 2: I'm suddenly concerned that it might have actually been written 466 00:26:17,760 --> 00:26:21,000 Speaker 2: by a human who is now like devastated that everyone 467 00:26:21,000 --> 00:26:23,919 Speaker 2: thinks they're a robot, and perhaps they're questioning themselves. 468 00:26:24,200 --> 00:26:26,800 Speaker 1: You know, they should be taking one of those catch 469 00:26:26,920 --> 00:26:29,640 Speaker 1: but tests that are supposed to see if you're a robot. 470 00:26:29,680 --> 00:26:31,320 Speaker 1: It's like, oh d you dream of the electric sheep, 471 00:26:31,480 --> 00:26:35,919 Speaker 1: Like it's so hard you always fail though. This is 472 00:26:35,960 --> 00:26:38,960 Speaker 1: like I'm I sometimes think that you might be a 473 00:26:39,040 --> 00:26:42,879 Speaker 1: robot because I know when you have those tests, you're like, 474 00:26:42,920 --> 00:26:44,760 Speaker 1: I can't I guess I can't go to this website. 475 00:26:44,920 --> 00:26:47,960 Speaker 2: Yeah, they're the worst because I feel like, yeah, I 476 00:26:48,080 --> 00:26:50,360 Speaker 2: marked all of the tiles that have bridges in them, 477 00:26:50,720 --> 00:26:53,639 Speaker 2: but like somehow I still fail. I don't know. It 478 00:26:53,680 --> 00:26:54,480 Speaker 2: seems unfair. 479 00:26:57,520 --> 00:27:12,280 Speaker 1: More after a quick break, let's get right back into it. Okay, 480 00:27:12,320 --> 00:27:15,119 Speaker 1: So this is a little bit more than just my 481 00:27:15,560 --> 00:27:19,800 Speaker 1: personal petty beef with Essence Magazine, because I think we're 482 00:27:19,800 --> 00:27:22,080 Speaker 1: going to be seeing more and more media companies and 483 00:27:22,200 --> 00:27:27,480 Speaker 1: brands using AI to communicate with their audiences. Again, I 484 00:27:27,520 --> 00:27:30,760 Speaker 1: don't believe that there's anything inherently in and of itself 485 00:27:30,840 --> 00:27:34,080 Speaker 1: wrong with that. In fact, I was kind of hoping, 486 00:27:34,160 --> 00:27:35,920 Speaker 1: you know, when we talked about this on the podcast, 487 00:27:36,280 --> 00:27:39,080 Speaker 1: that this could be a moment of media transparency, which 488 00:27:39,119 --> 00:27:41,720 Speaker 1: is always a good thing. Everybody everywhere right now is 489 00:27:41,720 --> 00:27:43,080 Speaker 1: talking about how we're all going to need to be 490 00:27:43,160 --> 00:27:45,639 Speaker 1: using AI in our work more. You know, we need 491 00:27:45,680 --> 00:27:47,800 Speaker 1: to get behind it. I can't tell you how many 492 00:27:47,800 --> 00:27:49,520 Speaker 1: times that is like what I have heard, like prepare 493 00:27:49,560 --> 00:27:52,600 Speaker 1: yourself for the AI revolution, blah blah blah. It would 494 00:27:52,680 --> 00:27:55,400 Speaker 1: not surprise me if people at Essence are like, oh, 495 00:27:55,400 --> 00:27:58,520 Speaker 1: we need to be experimenting with how we are using 496 00:27:58,560 --> 00:28:00,640 Speaker 1: AI in our work. Maybe it can make our work 497 00:28:00,680 --> 00:28:03,879 Speaker 1: more efficient, effective whatever. I did not bring it up 498 00:28:03,880 --> 00:28:06,120 Speaker 1: because I thought it was some huge scandal. I did 499 00:28:06,119 --> 00:28:08,399 Speaker 1: not bring it up because I wanted to embarrass Essence 500 00:28:08,440 --> 00:28:12,040 Speaker 1: maybe a little bit. But you know, publishing on social 501 00:28:12,119 --> 00:28:16,800 Speaker 1: media is inherently ridiculous and embarrassing, right Like, I think 502 00:28:16,960 --> 00:28:21,600 Speaker 1: if you are posting on public social media accounts, there's 503 00:28:21,600 --> 00:28:24,119 Speaker 1: always going to be that slip up, that thing of 504 00:28:24,119 --> 00:28:26,359 Speaker 1: like that sounded really cringey. That is part of the 505 00:28:26,400 --> 00:28:29,720 Speaker 1: process pointing that out, pointing out the messiness in cringiness 506 00:28:29,720 --> 00:28:32,520 Speaker 1: that is inherent in posting on social media is not 507 00:28:33,160 --> 00:28:36,280 Speaker 1: a bad thing. In fact, I think that transparency would 508 00:28:36,280 --> 00:28:39,320 Speaker 1: actually help us have a better understanding of this moment 509 00:28:39,400 --> 00:28:41,080 Speaker 1: that we are in when it comes to tech and 510 00:28:41,120 --> 00:28:43,560 Speaker 1: how it is going to shape how media companies and 511 00:28:43,600 --> 00:28:46,560 Speaker 1: brands engage with their audiences. I think for me, it 512 00:28:46,640 --> 00:28:51,320 Speaker 1: is really about transparency. You know. I was hopeful, like 513 00:28:51,360 --> 00:28:54,560 Speaker 1: when I saw that oh busted comment that Essence left 514 00:28:54,600 --> 00:28:56,440 Speaker 1: on my Instagram, I was hopeful that we were going 515 00:28:56,480 --> 00:29:00,200 Speaker 1: to be getting a moment of transparency. But then they 516 00:29:00,240 --> 00:29:06,680 Speaker 1: accuse me bridget of misreporting and spreading misinformation, and so 517 00:29:07,040 --> 00:29:09,120 Speaker 1: I just can't ignore that, not just because I'm a 518 00:29:09,120 --> 00:29:12,520 Speaker 1: petty bitch, which I am, but because I didn't say 519 00:29:12,600 --> 00:29:16,040 Speaker 1: that it was definitely one hundred percent, definitively written by AI. 520 00:29:16,520 --> 00:29:18,720 Speaker 1: I just said that I thought, in my opinion that 521 00:29:18,760 --> 00:29:21,800 Speaker 1: it seemed like it was written by AI, and it does. 522 00:29:21,880 --> 00:29:24,800 Speaker 1: It still does to me. That's still my opinion. But 523 00:29:24,840 --> 00:29:28,480 Speaker 1: they accused me of something that I take pretty seriously, 524 00:29:28,800 --> 00:29:31,280 Speaker 1: and like I was saying before, when we're talking about 525 00:29:31,280 --> 00:29:34,800 Speaker 1: marginalized communities especially, I do think that there is a 526 00:29:34,920 --> 00:29:38,880 Speaker 1: level of trust that you have with your community that 527 00:29:38,920 --> 00:29:41,680 Speaker 1: you're speaking to that is just important to honor. You know, 528 00:29:41,840 --> 00:29:44,240 Speaker 1: no one wants to feel like AI is being used 529 00:29:44,240 --> 00:29:47,920 Speaker 1: to mimic them, or to mock them, or to create 530 00:29:47,960 --> 00:29:52,520 Speaker 1: a kind of cruel, hollow stereotype about how the world 531 00:29:52,600 --> 00:29:55,120 Speaker 1: sees them. You know that a piece of technology is 532 00:29:55,160 --> 00:29:59,280 Speaker 1: just spitting out what they think the world thinks about 533 00:29:59,320 --> 00:30:02,800 Speaker 1: how we sound. You know that's not an authentic version 534 00:30:02,840 --> 00:30:05,760 Speaker 1: of who I am. That is just a fun house 535 00:30:05,920 --> 00:30:09,640 Speaker 1: mirror image of how the world sees me. And we 536 00:30:09,760 --> 00:30:13,360 Speaker 1: know our society is so full of biases. I don't 537 00:30:13,440 --> 00:30:20,400 Speaker 1: want to be kind of tricked into connecting with a hollow, 538 00:30:20,600 --> 00:30:25,480 Speaker 1: false depiction that is simply recreating what our bias society 539 00:30:25,880 --> 00:30:28,440 Speaker 1: already thinks about how I sound as a black woman. 540 00:30:28,800 --> 00:30:30,560 Speaker 1: For the sake of argument, to be clear, I am 541 00:30:30,600 --> 00:30:32,760 Speaker 1: not saying that this is what happened, But let's just say, 542 00:30:32,800 --> 00:30:35,640 Speaker 1: for the sake of argument, that they were hiring white 543 00:30:35,640 --> 00:30:40,080 Speaker 1: male social media editors who were then using AI to 544 00:30:40,200 --> 00:30:43,840 Speaker 1: mimic how they thought black women smoke and black women's 545 00:30:43,840 --> 00:30:47,760 Speaker 1: speech patterns. I probably would not be the only person who, like, 546 00:30:48,520 --> 00:30:51,560 Speaker 1: wasn't super comfortable with that dynamic, right. I don't like 547 00:30:51,600 --> 00:30:55,440 Speaker 1: the idea of, you know, being a black woman navigating 548 00:30:55,560 --> 00:31:01,360 Speaker 1: the Internet and then engaging with or identify with a 549 00:31:01,440 --> 00:31:04,280 Speaker 1: speaker who I assume is also a black woman like me, 550 00:31:04,720 --> 00:31:08,760 Speaker 1: but is actually AI right like that, that's not something 551 00:31:08,760 --> 00:31:11,520 Speaker 1: that sits well with me. That's not something that makes 552 00:31:11,520 --> 00:31:14,400 Speaker 1: me feel seen or comfortable. So I think, especially when 553 00:31:14,400 --> 00:31:20,080 Speaker 1: it's brands where their whole thing is about making a 554 00:31:20,160 --> 00:31:25,320 Speaker 1: marginalized community feel seen and feel supported and heard and amplified, 555 00:31:25,920 --> 00:31:27,320 Speaker 1: I do think there needs to be a little bit 556 00:31:27,360 --> 00:31:30,239 Speaker 1: of transparency around the use of AI there, if that 557 00:31:30,320 --> 00:31:32,880 Speaker 1: is what's going on. And so all of that is 558 00:31:32,920 --> 00:31:38,320 Speaker 1: to say, essence, you tell me, was that weird post 559 00:31:38,360 --> 00:31:42,280 Speaker 1: written by AI or was it published by a human editor? 560 00:31:42,880 --> 00:31:45,000 Speaker 1: And that's how I got on Facebook. I just want 561 00:31:45,040 --> 00:31:49,320 Speaker 1: to know you accused me of misreporting something. I would 562 00:31:49,320 --> 00:31:53,680 Speaker 1: be so pleased to come on here and say, looks 563 00:31:53,680 --> 00:31:56,400 Speaker 1: like I got it wrong. This is the human who 564 00:31:56,440 --> 00:31:59,600 Speaker 1: wrote that they were having a weird night, they misspelled 565 00:31:59,640 --> 00:32:02,760 Speaker 1: her name whatever. I've been there. Part of the reason 566 00:32:02,760 --> 00:32:04,240 Speaker 1: why I want to know is because I've been there, 567 00:32:04,280 --> 00:32:06,800 Speaker 1: like I. If you like, if you want to hear 568 00:32:06,840 --> 00:32:10,320 Speaker 1: some stories about like epic work fuck ups on the 569 00:32:10,400 --> 00:32:13,160 Speaker 1: social media account, talk to my old boss at MSNBC. 570 00:32:13,400 --> 00:32:15,800 Speaker 1: She will have some stories for you. Because I've been there, 571 00:32:15,840 --> 00:32:18,720 Speaker 1: I've done it. So if that's what's going on, totally 572 00:32:18,760 --> 00:32:22,880 Speaker 1: willing to correct the record, and even that is like 573 00:32:23,720 --> 00:32:27,600 Speaker 1: a transparency thing, like I'll never forget. My second favorite 574 00:32:27,840 --> 00:32:30,600 Speaker 1: social media mess up was a tweet from I think 575 00:32:30,600 --> 00:32:33,160 Speaker 1: it was the Boston Globe where they were using They 576 00:32:33,160 --> 00:32:37,560 Speaker 1: wanted to say their authorities are investigating, but for some 577 00:32:37,600 --> 00:32:41,960 Speaker 1: reason they've tweeted investigating and they had to come back 578 00:32:42,000 --> 00:32:45,480 Speaker 1: on and be like, we're not deleting the tweet. Like 579 00:32:45,600 --> 00:32:48,440 Speaker 1: we saw the tweet it was. It was incorrect, but 580 00:32:48,600 --> 00:32:52,120 Speaker 1: we're not deleting it because it's already been retweeted so 581 00:32:52,160 --> 00:32:55,080 Speaker 1: many times and it would be pointless. So yeah, we're 582 00:32:55,120 --> 00:32:56,520 Speaker 1: just leaving it up. And then that's it up. And 583 00:32:56,560 --> 00:32:59,520 Speaker 1: I respected it because a little transparency. Oh do you 584 00:32:59,520 --> 00:33:01,440 Speaker 1: need them just to be like, oh, yeah, we got 585 00:33:01,440 --> 00:33:04,800 Speaker 1: that's wrong, here's what happened, our bad and move forward. 586 00:33:04,960 --> 00:33:07,520 Speaker 1: That is the point of social media, not to get 587 00:33:07,600 --> 00:33:13,520 Speaker 1: so defensive and then so cagey when things don't come 588 00:33:13,520 --> 00:33:17,080 Speaker 1: off right. Social media is one big test kitchen of 589 00:33:17,160 --> 00:33:19,200 Speaker 1: trying things and seeing it they land, and they don't 590 00:33:19,200 --> 00:33:21,000 Speaker 1: always land, so just just acknowledge that. 591 00:33:21,400 --> 00:33:25,040 Speaker 2: So bridget. What was your first favorite social media fuck up? 592 00:33:25,480 --> 00:33:29,720 Speaker 1: Oh my god, it was the greatest day in social 593 00:33:29,800 --> 00:33:34,960 Speaker 1: media history. It was when Yahoo News was reporting about 594 00:33:34,960 --> 00:33:41,360 Speaker 1: the Trump administration trying to have a bigger navy, but 595 00:33:41,440 --> 00:33:43,880 Speaker 1: instead of the B in the word bigger, they used 596 00:33:43,880 --> 00:33:47,320 Speaker 1: an N and they tweeted it. And when I tell 597 00:33:47,400 --> 00:33:50,800 Speaker 1: you that, like even here here we go. When I 598 00:33:50,800 --> 00:33:53,440 Speaker 1: google it, one of the first things that comes up 599 00:33:53,480 --> 00:33:56,320 Speaker 1: is an Essence magazine article. So Essence, you're out there 600 00:33:56,360 --> 00:33:59,320 Speaker 1: doing the good reporting on social media. Like, yup, we're 601 00:33:59,360 --> 00:34:03,960 Speaker 1: still laughing at black Twitter's jokes following Yahoo finances navy tweet, right, 602 00:34:04,680 --> 00:34:06,520 Speaker 1: that was when I tell you, like, that was like 603 00:34:06,520 --> 00:34:08,040 Speaker 1: one of those Twitter moments where you just had to 604 00:34:08,040 --> 00:34:10,600 Speaker 1: be there. You really just had to like be there 605 00:34:11,280 --> 00:34:14,000 Speaker 1: in twenty seventeen when that happened, I'll tell you this, 606 00:34:14,040 --> 00:34:18,040 Speaker 1: I got no work done. Is too busy reading those 607 00:34:18,080 --> 00:34:19,480 Speaker 1: tweets because they were too funny. 608 00:34:19,719 --> 00:34:21,680 Speaker 2: Uh, that was a pretty special moment. 609 00:34:21,719 --> 00:34:24,720 Speaker 1: I think that was a pretty special moment. And you know, again, 610 00:34:24,960 --> 00:34:28,240 Speaker 1: I like Essence. I think they do good work. Sometimes 611 00:34:28,280 --> 00:34:30,480 Speaker 1: I've heard some rumors that sometimes they don't always pay 612 00:34:30,520 --> 00:34:32,560 Speaker 1: for that work, But that's not me saying that. That's 613 00:34:32,600 --> 00:34:34,839 Speaker 1: the interest saying that, look it up yourself. That's what 614 00:34:34,840 --> 00:34:39,400 Speaker 1: the streets say not me. But ultimately I think that 615 00:34:39,560 --> 00:34:43,239 Speaker 1: in this moment in the intersection of media and technology, 616 00:34:43,640 --> 00:34:48,040 Speaker 1: audiences deserve transparency, and audiences are smart enough to know 617 00:34:48,080 --> 00:34:51,440 Speaker 1: when something's up. All of those social media professionals, nobody 618 00:34:51,480 --> 00:34:54,000 Speaker 1: told them that this was AI. We were smart enough 619 00:34:54,040 --> 00:34:58,120 Speaker 1: as savvy audiences to say, this doesn't sound right. Your audiences, 620 00:34:58,200 --> 00:35:00,320 Speaker 1: you've got to trust them, and you've got to trust 621 00:35:00,440 --> 00:35:04,319 Speaker 1: that they are critical, savvy people. And so I think 622 00:35:04,360 --> 00:35:07,720 Speaker 1: in this moment where AI and all of this weird 623 00:35:08,280 --> 00:35:12,160 Speaker 1: new stuff is happening with technology, it is imperative that 624 00:35:12,200 --> 00:35:16,040 Speaker 1: media companies really trust their audiences and respect their audiences 625 00:35:16,280 --> 00:35:18,480 Speaker 1: and give us a little bit of transparency. And I 626 00:35:18,480 --> 00:35:21,439 Speaker 1: don't think it bodes well for how we move forward. 627 00:35:21,480 --> 00:35:23,120 Speaker 1: If a little Dog and a Pony show, that is 628 00:35:23,160 --> 00:35:28,560 Speaker 1: this podcast gently ribs Essence Magazine about maybe using AI 629 00:35:28,719 --> 00:35:30,960 Speaker 1: and like, oh, it didn't sound good. If how they 630 00:35:31,040 --> 00:35:36,720 Speaker 1: respond is to get super defensive, accuse me of spreading misinformation, 631 00:35:36,840 --> 00:35:40,440 Speaker 1: which I did not do, and then just like go silent. 632 00:35:40,960 --> 00:35:43,200 Speaker 1: I want this to be a dialogue. If Essence Magazine 633 00:35:43,200 --> 00:35:46,640 Speaker 1: can totally come on the show, but I have to 634 00:35:46,680 --> 00:35:52,319 Speaker 1: say until I get some information, some clarifying information from them. 635 00:35:52,920 --> 00:35:55,560 Speaker 1: I will go to my grave believing this is written 636 00:35:55,560 --> 00:35:58,160 Speaker 1: by AI. I am sorry, like it is my opinion. 637 00:35:58,280 --> 00:36:00,000 Speaker 1: I don't know. As I said, I have no proof, 638 00:36:00,360 --> 00:36:02,560 Speaker 1: but that I think that we would both be in 639 00:36:02,600 --> 00:36:06,280 Speaker 1: agreement that that post didn't sound right they edited it. Yeah, 640 00:36:06,320 --> 00:36:08,960 Speaker 1: So I guess that's really the bottom line. Like, this 641 00:36:09,080 --> 00:36:12,200 Speaker 1: is not just about my petty beef with them. It 642 00:36:12,280 --> 00:36:16,240 Speaker 1: is about what we could expect from brands, what transparency 643 00:36:16,280 --> 00:36:19,040 Speaker 1: we could expect, And I think early on we should 644 00:36:19,040 --> 00:36:22,919 Speaker 1: be established in some norms about about that transparency, right, 645 00:36:23,000 --> 00:36:26,560 Speaker 1: Like I do, I personally do think that media companies 646 00:36:26,880 --> 00:36:29,120 Speaker 1: should come up with some kind of an understanding of 647 00:36:29,120 --> 00:36:31,560 Speaker 1: how they will communicate when something has been generated by 648 00:36:31,560 --> 00:36:34,040 Speaker 1: AI to their audiences. The same thing that we were 649 00:36:34,040 --> 00:36:36,960 Speaker 1: talking about on the newscast last week about whether or 650 00:36:37,040 --> 00:36:41,319 Speaker 1: not platforms should include a watermark when an image is 651 00:36:42,000 --> 00:36:42,960 Speaker 1: AI generated. 652 00:36:43,040 --> 00:36:45,520 Speaker 2: You believe that they should, Yeah, I absolutely do. I 653 00:36:45,560 --> 00:36:47,600 Speaker 2: was thinking about that. You know, It's like when you 654 00:36:47,640 --> 00:36:51,440 Speaker 2: have an AI generated image like there was that one, 655 00:36:51,840 --> 00:36:55,720 Speaker 2: uh we talked about last week of DeSantis, the Dasantus 656 00:36:55,760 --> 00:36:59,760 Speaker 2: campaign posting those images of Trump like hugging and kissing Fauci. 657 00:37:00,800 --> 00:37:04,680 Speaker 2: There should be a watermark indicating that, like that they're 658 00:37:04,840 --> 00:37:09,560 Speaker 2: fake images, right, And it shouldn't just fall on the 659 00:37:09,760 --> 00:37:12,880 Speaker 2: end user in the public to figure out what is 660 00:37:12,960 --> 00:37:17,040 Speaker 2: real and what is fake. That's but unfortunately, I guess 661 00:37:17,040 --> 00:37:18,600 Speaker 2: that's kind of where we're at, right. That's like one 662 00:37:18,640 --> 00:37:24,439 Speaker 2: of the key skills of literacy in twenty twenty three 663 00:37:24,760 --> 00:37:27,799 Speaker 2: is distinguishing what's real, what's fake, what was written by 664 00:37:27,840 --> 00:37:28,920 Speaker 2: a robot, what wasn't. 665 00:37:29,160 --> 00:37:32,040 Speaker 1: I would argue that it shouldn't be Media literacy is important, 666 00:37:32,040 --> 00:37:33,560 Speaker 1: but it shouldn't be up to your average person to 667 00:37:33,600 --> 00:37:38,200 Speaker 1: be so critically engaged with the media that they mindlessly consume. 668 00:37:38,400 --> 00:37:40,880 Speaker 1: That's not how media consumption always works. You'll always have 669 00:37:40,920 --> 00:37:43,360 Speaker 1: that moment when you're on the toilet or just in 670 00:37:43,400 --> 00:37:46,000 Speaker 1: the checkout line, or don't haven't had your coffee where 671 00:37:46,040 --> 00:37:48,640 Speaker 1: you see something quickly and you're like, wait what. It 672 00:37:48,680 --> 00:37:51,920 Speaker 1: should not be up to individuals to have to parse that. 673 00:37:52,320 --> 00:37:54,799 Speaker 1: And I think that we need to start establishing some 674 00:37:54,960 --> 00:37:59,200 Speaker 1: guardrails and some guidelines for how brands and platforms are 675 00:37:59,239 --> 00:38:04,560 Speaker 1: going to ethically and responsibly use AI going forward, and 676 00:38:04,600 --> 00:38:06,279 Speaker 1: we got to do it soon. I think that's what 677 00:38:06,360 --> 00:38:12,560 Speaker 1: this whole kerfuffle with me an essence really comes down to, 678 00:38:12,920 --> 00:38:15,240 Speaker 1: you know, if I have to be the poster person 679 00:38:15,480 --> 00:38:19,799 Speaker 1: for those guardrails, so be it. I'll do it. 680 00:38:20,239 --> 00:38:23,879 Speaker 2: Well, good luck to you. We need it. It's hard. 681 00:38:23,920 --> 00:38:26,759 Speaker 2: It's hard to know we need some guardrails, and so 682 00:38:27,880 --> 00:38:32,200 Speaker 2: Todd versus Essence. Here we go, the Ultimate Beef. 683 00:38:32,320 --> 00:38:36,160 Speaker 1: The Ultimate Beef. Tune into season two of Beef. It'llills 684 00:38:36,239 --> 00:38:39,680 Speaker 1: be a like a slow Burn style breakdown between me 685 00:38:40,200 --> 00:38:42,759 Speaker 1: and my beef with Essence magazine. But listen, No but 686 00:38:42,840 --> 00:38:44,799 Speaker 1: in all series says, I want to know what folks think. 687 00:38:45,080 --> 00:38:48,440 Speaker 1: I'll put a copy of the original post in the Patreon. 688 00:38:48,840 --> 00:38:51,080 Speaker 1: Take a look. I'll do a poll. You do not 689 00:38:51,320 --> 00:38:54,319 Speaker 1: have to subscribe or be a paying member to see this. 690 00:38:54,400 --> 00:38:56,719 Speaker 1: It'll be a public post. That's how much I want 691 00:38:56,719 --> 00:38:58,879 Speaker 1: to know what y'all think. You can find the link 692 00:38:58,920 --> 00:39:00,920 Speaker 1: to the Patreon to vote, and through the post and 693 00:39:00,960 --> 00:39:03,640 Speaker 1: the description for this episode. Do you think it was 694 00:39:03,680 --> 00:39:06,200 Speaker 1: AI generated or do you not? I cannot be the 695 00:39:06,239 --> 00:39:08,680 Speaker 1: only one who sinks this, But if you really think 696 00:39:08,680 --> 00:39:10,080 Speaker 1: it was just a sloppy human, I want to know 697 00:39:10,160 --> 00:39:12,400 Speaker 1: that too. Let's get to the bottom of this together. 698 00:39:12,840 --> 00:39:19,400 Speaker 1: An essence, call me, got a story about an interesting 699 00:39:19,400 --> 00:39:21,440 Speaker 1: thing in tech, or just want to say hi. You 700 00:39:21,440 --> 00:39:23,759 Speaker 1: can reach us at Hello at tangody dot com. You 701 00:39:23,760 --> 00:39:26,800 Speaker 1: can also find transcripts for today's episode at tengody dot com. 702 00:39:27,000 --> 00:39:28,640 Speaker 1: There Are No Girls on the Internet was created by 703 00:39:28,680 --> 00:39:32,040 Speaker 1: me bridget Toad. It's a production of iHeartRadio, an unbossed creative. 704 00:39:32,440 --> 00:39:35,440 Speaker 1: Jonathan Strickland is our executive producer. Tari Harrison is our 705 00:39:35,440 --> 00:39:38,960 Speaker 1: producer and sound engineer. Michael Amado is our contributing producer. 706 00:39:39,239 --> 00:39:41,879 Speaker 1: I'm your host, bridget Tod. If you want to help 707 00:39:41,960 --> 00:39:44,960 Speaker 1: us grow, rate and review us on Apple Podcasts. For 708 00:39:45,040 --> 00:39:48,360 Speaker 1: more podcasts from iHeartRadio, check out the iHeartRadio app, Apple podcast, 709 00:39:48,480 --> 00:40:01,879 Speaker 1: or wherever you get your podcasts.