1 00:00:04,160 --> 00:00:05,880 Speaker 1: There Are No Girls on the Internet as a production 2 00:00:05,920 --> 00:00:13,000 Speaker 1: of I Heart Radio and Unboss Creative. I'm Bridget Todd 3 00:00:13,160 --> 00:00:14,840 Speaker 1: and this is There Are No Girls on the Internet. 4 00:00:17,320 --> 00:00:19,600 Speaker 1: If you don't know Sadete Harry, she is one of 5 00:00:19,640 --> 00:00:22,119 Speaker 1: my heroes, and a piece that she wrote for Wired 6 00:00:22,200 --> 00:00:25,840 Speaker 1: magazine interrogating the way that technology sees black women is 7 00:00:25,880 --> 00:00:29,720 Speaker 1: actually one of the biggest inspirations for this podcast. Sadet 8 00:00:29,960 --> 00:00:33,080 Speaker 1: is constantly speaking truth to power and technology, and I 9 00:00:33,159 --> 00:00:34,960 Speaker 1: was lucky enough to sit down with her for a 10 00:00:35,040 --> 00:00:37,159 Speaker 1: live taping of There Are No Girls on the Internet 11 00:00:37,440 --> 00:00:42,000 Speaker 1: in New York City during Unfinished Live, a festival celebrating technology, 12 00:00:42,120 --> 00:00:45,920 Speaker 1: culture and the arts, where Sadek got really real about 13 00:00:45,920 --> 00:00:49,240 Speaker 1: power and technology. And if you want to hear Sudet again, 14 00:00:49,520 --> 00:00:52,120 Speaker 1: you are in luck. She'll be back at Unfinished Live 15 00:00:53,159 --> 00:00:57,160 Speaker 1: September one, both I r L from New York City 16 00:00:57,200 --> 00:00:59,640 Speaker 1: and streaming online. She'll be joined by some of the 17 00:00:59,680 --> 00:01:03,640 Speaker 1: most interesting people in technology and culture like Dr Sophia Noble, 18 00:01:03,680 --> 00:01:08,080 Speaker 1: Denis Duncan, Bartender Thurston, and the founding member of Pussy Riot. 19 00:01:08,360 --> 00:01:10,800 Speaker 1: You might even see me there, so if you do, 20 00:01:10,959 --> 00:01:13,560 Speaker 1: be sure to come say hi. Go to Live dot 21 00:01:13,640 --> 00:01:16,479 Speaker 1: Unfinished dot com for tickets, and please enjoy this live 22 00:01:16,520 --> 00:01:18,840 Speaker 1: episode of There Are No Girls on the Internet from 23 00:01:18,920 --> 00:01:23,720 Speaker 1: Unfinished Live last year. Hello everyone, Thank you so much 24 00:01:23,760 --> 00:01:29,960 Speaker 1: for being here. How's everybody feeling? Yeah? Uh, my name 25 00:01:30,040 --> 00:01:32,360 Speaker 1: is Bridget Todd. I am the creator and host of 26 00:01:32,360 --> 00:01:34,679 Speaker 1: the podcast There Are No Girls on the Internet. Um, 27 00:01:34,840 --> 00:01:37,920 Speaker 1: this is my first ever live show, So thank you 28 00:01:37,959 --> 00:01:40,399 Speaker 1: so much for being here. It means so much to me. 29 00:01:43,000 --> 00:01:44,760 Speaker 1: I'm so thrilled to be here with my guest, the 30 00:01:45,040 --> 00:01:50,560 Speaker 1: brilliant Sidette Harry give it up for Todette. Hello. So 31 00:01:50,600 --> 00:01:52,760 Speaker 1: a little bit about my podcast For folks who don't know, 32 00:01:52,840 --> 00:01:55,200 Speaker 1: it's called There Are No Girls on the Internet. And 33 00:01:55,360 --> 00:01:58,120 Speaker 1: one of the first questions I often get is what's 34 00:01:58,120 --> 00:02:00,400 Speaker 1: with that name? What do you mean there are no 35 00:02:00,480 --> 00:02:03,640 Speaker 1: girls on the Internet. Well, there's an old saying that 36 00:02:03,680 --> 00:02:06,360 Speaker 1: everybody on the Internet is a guy, and if they 37 00:02:06,400 --> 00:02:09,079 Speaker 1: say they're a woman, they're just pretending they're not actually 38 00:02:09,080 --> 00:02:12,520 Speaker 1: a woman. Or if they are a woman online, that 39 00:02:12,680 --> 00:02:15,640 Speaker 1: identity doesn't actually matter. You know, we're all the same 40 00:02:15,680 --> 00:02:19,600 Speaker 1: on the internet, and so that exactly so that identity 41 00:02:19,680 --> 00:02:22,799 Speaker 1: and all of the issues that come along with that identity, 42 00:02:23,000 --> 00:02:25,880 Speaker 1: there's this misconception that we just leave it at the door, 43 00:02:26,160 --> 00:02:30,040 Speaker 1: And I actually truly believed both of these things for 44 00:02:30,080 --> 00:02:32,840 Speaker 1: a very long time. I believe that black queer women 45 00:02:32,919 --> 00:02:35,840 Speaker 1: like me were outliers and technology and the internet, and 46 00:02:35,880 --> 00:02:37,959 Speaker 1: I believe if we did show up in these places, 47 00:02:38,120 --> 00:02:40,799 Speaker 1: our identities and all of the issues connected with those 48 00:02:40,800 --> 00:02:43,800 Speaker 1: identities well just didn't matter. You know, we left them 49 00:02:43,800 --> 00:02:46,440 Speaker 1: on the door when we've logged in. But that is 50 00:02:46,440 --> 00:02:50,280 Speaker 1: not true. Women, black folks, people of color, queer folks, 51 00:02:50,440 --> 00:02:53,600 Speaker 1: people who have all been traditionally marginalized. We've been showing 52 00:02:53,639 --> 00:02:57,200 Speaker 1: up online to make it better, safer, more fun, more inclusive. 53 00:02:57,639 --> 00:03:00,919 Speaker 1: And we've been there from the very beginning. I mean, 54 00:03:01,160 --> 00:03:04,120 Speaker 1: think about it. What would the internet be like without 55 00:03:04,360 --> 00:03:09,320 Speaker 1: black folks, queer folks, trans folks. It would be so boring, y'all. 56 00:03:09,320 --> 00:03:13,480 Speaker 1: It would just be journalists making boring jokes and having 57 00:03:13,520 --> 00:03:16,920 Speaker 1: boring opinions about baseball. Right. We couldn't even have that 58 00:03:17,120 --> 00:03:19,639 Speaker 1: without black people because a lot of journalists boring jokes 59 00:03:19,639 --> 00:03:23,560 Speaker 1: are stolen from black interactions, thank you, thank you. What 60 00:03:23,560 --> 00:03:26,840 Speaker 1: would they report about if it wasn't watching us exactly exactly. 61 00:03:26,880 --> 00:03:29,560 Speaker 1: It would be a nightmare without us. But because people 62 00:03:29,600 --> 00:03:32,480 Speaker 1: from traditionally marginalized backgrounds. We've always been there since the 63 00:03:32,600 --> 00:03:36,600 Speaker 1: very beginning, and we often are the ones doing the unpaid, difficult, 64 00:03:36,880 --> 00:03:41,000 Speaker 1: sometimes dangerous, and personal personally costly work of making Internet 65 00:03:41,040 --> 00:03:45,200 Speaker 1: spaces safer, better, more inclusive, and better. And when we 66 00:03:45,280 --> 00:03:47,960 Speaker 1: do this work, it's not just for us as marginalized people. 67 00:03:48,280 --> 00:03:51,680 Speaker 1: This work makes spaces better and safer for everyone. Um, 68 00:03:51,720 --> 00:03:53,200 Speaker 1: and so I want to give you a little pop 69 00:03:53,280 --> 00:03:56,440 Speaker 1: quiz to sort of illustrate what I mean. So, which 70 00:03:56,480 --> 00:03:58,560 Speaker 1: of the following and I know that you know answers? 71 00:03:59,000 --> 00:04:01,640 Speaker 1: Which of the following is something that we know about 72 00:04:01,640 --> 00:04:05,560 Speaker 1: the Internet. Ahead of the election, an army of fake 73 00:04:05,640 --> 00:04:09,000 Speaker 1: social media accounts targeted black voters in an attempt to 74 00:04:09,080 --> 00:04:15,800 Speaker 1: destabilize our election process. Two, Facebook's moderation practices disproportionately removed 75 00:04:15,800 --> 00:04:20,719 Speaker 1: posts from black people talking about our experiences with racism. Lastly, 76 00:04:21,360 --> 00:04:25,880 Speaker 1: on TikTok, white supremacist groups create extremist content using TikTok's 77 00:04:25,920 --> 00:04:29,000 Speaker 1: own features, not just to avoid detection, but to even 78 00:04:29,080 --> 00:04:32,200 Speaker 1: have their content surface on users for you page. So, 79 00:04:32,320 --> 00:04:34,080 Speaker 1: which one of those three things is the thing that 80 00:04:34,120 --> 00:04:36,160 Speaker 1: we know about the internet? Raisor hand you think it's 81 00:04:36,200 --> 00:04:42,760 Speaker 1: one raisor hand you think it's too how about three? Okay, 82 00:04:42,760 --> 00:04:45,600 Speaker 1: so if you said all of the above, good job, 83 00:04:45,760 --> 00:04:48,719 Speaker 1: you get a name. Here's another question. Of all of 84 00:04:48,720 --> 00:04:51,960 Speaker 1: those things I just said, which of those things are 85 00:04:52,000 --> 00:04:55,760 Speaker 1: things that black organizers, black social media users, black cultural 86 00:04:55,800 --> 00:04:58,960 Speaker 1: critics have been vocally raising the alarm about for a 87 00:04:59,080 --> 00:05:03,800 Speaker 1: very long time? And he guesses all of the above, 88 00:05:04,000 --> 00:05:06,800 Speaker 1: you guys are all getting it perfectly. She said, all 89 00:05:06,800 --> 00:05:09,120 Speaker 1: of the above, you would be right. And a piece 90 00:05:09,160 --> 00:05:11,760 Speaker 1: for Wired called listening to Black Women the innovation that 91 00:05:11,800 --> 00:05:14,600 Speaker 1: tech can't quite figure out. My guest today, the brilliant 92 00:05:14,600 --> 00:05:17,840 Speaker 1: cultural critic and all around tech troublemaker Sedet argues that 93 00:05:17,880 --> 00:05:20,320 Speaker 1: when black women speak up about the abuses and harms 94 00:05:20,360 --> 00:05:23,320 Speaker 1: that we face online, people with power just don't listen. 95 00:05:23,640 --> 00:05:26,320 Speaker 1: That is, until that harm is experienced by other users. 96 00:05:26,800 --> 00:05:30,080 Speaker 1: She writes, harmful behavior towards black women isn't enough to 97 00:05:30,120 --> 00:05:33,320 Speaker 1: inspire change until others are harmed. But the original harms 98 00:05:33,320 --> 00:05:36,640 Speaker 1: are often lost by journalists task with covering tech. The 99 00:05:36,720 --> 00:05:40,400 Speaker 1: power and rhetoric that went unchecked becomes common, and tactics 100 00:05:40,480 --> 00:05:43,680 Speaker 1: used to gets black women for lulls become weapons used 101 00:05:43,680 --> 00:05:47,080 Speaker 1: in conspiracies destabilizing the very nature of truth, from the 102 00:05:47,120 --> 00:05:50,000 Speaker 1: swarming of victims to posing as black women to destabilize 103 00:05:50,000 --> 00:05:54,200 Speaker 1: communities or even countries. Defining the systemic abuse becomes a 104 00:05:54,240 --> 00:05:57,880 Speaker 1: frustrating exercise of describing an empty space that no one 105 00:05:57,960 --> 00:06:02,279 Speaker 1: believes is there. If we can fall, surveil, and automate everyone, 106 00:06:02,720 --> 00:06:05,360 Speaker 1: how could we miss anything important? And if that and 107 00:06:05,760 --> 00:06:08,400 Speaker 1: if and if it isn't important, it is only important 108 00:06:08,400 --> 00:06:11,880 Speaker 1: for how it changes the mythical standard user, no matter 109 00:06:11,920 --> 00:06:14,920 Speaker 1: how many people were hurt before. So so that when 110 00:06:14,960 --> 00:06:17,080 Speaker 1: I heard those words, I have to tell you it 111 00:06:17,160 --> 00:06:20,080 Speaker 1: was the impetus for me creating my podcast at all 112 00:06:20,440 --> 00:06:24,560 Speaker 1: in general, because it made me feel so sane as 113 00:06:24,600 --> 00:06:28,520 Speaker 1: a black woman showing up online. I think people often 114 00:06:28,680 --> 00:06:32,360 Speaker 1: miss our issues, and you spoke to it so beautifully 115 00:06:32,400 --> 00:06:34,159 Speaker 1: in that piece. And so I'm so excited to talk 116 00:06:34,160 --> 00:06:37,560 Speaker 1: to you today about that harm, what accountability looks like 117 00:06:37,600 --> 00:06:40,599 Speaker 1: for folks who have ignored that harm, enabled that harm, 118 00:06:40,640 --> 00:06:42,960 Speaker 1: and in some cases profited from that harm, And how 119 00:06:43,000 --> 00:06:45,800 Speaker 1: we move forward to an Internet that meaningfully listens to 120 00:06:45,839 --> 00:06:49,400 Speaker 1: black women. Oh my gosh, you never told me that before. 121 00:06:49,960 --> 00:06:55,159 Speaker 1: It's true. First and foremost, I want to do the 122 00:06:55,160 --> 00:06:58,200 Speaker 1: thing where we name the fact that this is my 123 00:06:58,480 --> 00:07:02,480 Speaker 1: second kind of public thing without a face mask. Then 124 00:07:02,720 --> 00:07:06,680 Speaker 1: that doesn't involve like family members, so im fidgety um. 125 00:07:06,880 --> 00:07:09,000 Speaker 1: These are all things, and it's like, let's be honest 126 00:07:09,040 --> 00:07:11,360 Speaker 1: about the place we are in and the level of 127 00:07:11,360 --> 00:07:14,120 Speaker 1: comfort we are feeling, because part of the work is 128 00:07:14,200 --> 00:07:18,440 Speaker 1: just we like high tech solutions, we like the things 129 00:07:18,440 --> 00:07:21,720 Speaker 1: that are shining and sexy, but we are ultimately all 130 00:07:21,840 --> 00:07:24,280 Speaker 1: using the web for our lives. We need to use 131 00:07:24,320 --> 00:07:25,880 Speaker 1: the web to connect to each other. We need to 132 00:07:25,960 --> 00:07:29,160 Speaker 1: use the web at this point to get groceries, get vaccines, 133 00:07:29,320 --> 00:07:35,480 Speaker 1: to do our jobs. And the issue with what I've 134 00:07:35,480 --> 00:07:39,600 Speaker 1: seen and what I've experienced with specifically that piece that 135 00:07:39,680 --> 00:07:45,680 Speaker 1: led to the writing of that piece, is that there's 136 00:07:45,760 --> 00:07:49,280 Speaker 1: no way around when you have certain marginalizations or even 137 00:07:49,480 --> 00:07:52,000 Speaker 1: in the current world, for you not to be online. 138 00:07:52,360 --> 00:07:54,600 Speaker 1: There's no way for you not to bring your whole 139 00:07:54,600 --> 00:07:58,280 Speaker 1: self to the work you do online the way you 140 00:07:58,320 --> 00:08:01,200 Speaker 1: are online. What usually happen is that you package it 141 00:08:01,400 --> 00:08:04,160 Speaker 1: so that whoever you're dealing with at the time feels comfortable, 142 00:08:04,240 --> 00:08:07,160 Speaker 1: but you're still your whole self. You're still having all 143 00:08:07,200 --> 00:08:08,680 Speaker 1: of these issues and with some of the things that 144 00:08:08,720 --> 00:08:12,680 Speaker 1: we talked about. I wrote that in January. I've never 145 00:08:12,680 --> 00:08:16,560 Speaker 1: told the story about that article, but I am. And 146 00:08:16,600 --> 00:08:18,600 Speaker 1: it's kind of indicative to the way I've been online 147 00:08:18,760 --> 00:08:22,080 Speaker 1: most of my life. But what happened was it was 148 00:08:22,800 --> 00:08:26,920 Speaker 1: Brianna Taylor, Rest in Peace, Rest and power. The protests 149 00:08:26,920 --> 00:08:31,600 Speaker 1: started for Brianna Taylor, and there was a uproar of 150 00:08:31,640 --> 00:08:35,079 Speaker 1: how could we have known? And what is going on? 151 00:08:35,400 --> 00:08:37,960 Speaker 1: And we're well, how do we do this? And a 152 00:08:38,000 --> 00:08:41,000 Speaker 1: lot of this was also in post George Floyd. But 153 00:08:41,080 --> 00:08:44,000 Speaker 1: one of the things that happened is people were just like, 154 00:08:44,160 --> 00:08:46,440 Speaker 1: how do we really describe this? Where is this thing? 155 00:08:47,000 --> 00:08:49,840 Speaker 1: And I had written the art and article for Model 156 00:08:49,920 --> 00:08:55,240 Speaker 1: View Culture about people posing as black women in in 157 00:08:55,480 --> 00:09:01,640 Speaker 1: two um kind of dry the web wed ridden feminism 158 00:09:01,679 --> 00:09:05,440 Speaker 1: in twenty fourteen. It had been a and phenomenon we 159 00:09:05,480 --> 00:09:09,480 Speaker 1: had been explosing in twenty thirteen. And if we're talking 160 00:09:09,520 --> 00:09:14,439 Speaker 1: about last year, so how many years ago is that? 161 00:09:14,800 --> 00:09:19,120 Speaker 1: How many years passed? Seven? Now we work in tech, 162 00:09:19,200 --> 00:09:22,520 Speaker 1: we are in social media. You certainly become sexy and hot. 163 00:09:22,640 --> 00:09:27,680 Speaker 1: Usually it moves within minutes or months the metaverse and 164 00:09:27,800 --> 00:09:30,520 Speaker 1: f t s those blow up and go in months, 165 00:09:30,600 --> 00:09:33,080 Speaker 1: but suddenly to talk to black women take seven months. 166 00:09:33,520 --> 00:09:37,400 Speaker 1: And the editor of Wire at the time said something, 167 00:09:37,400 --> 00:09:39,880 Speaker 1: and I was like, pay me to write this. I 168 00:09:39,920 --> 00:09:41,800 Speaker 1: just said, maybe if you just paid me to write this, 169 00:09:41,920 --> 00:09:43,760 Speaker 1: and a lot of things went back and forth, and 170 00:09:43,800 --> 00:09:47,440 Speaker 1: then pandemic was happening. I said that in June. The 171 00:09:47,480 --> 00:09:51,320 Speaker 1: article got published in January, so that still took an 172 00:09:51,320 --> 00:09:54,560 Speaker 1: additional seven months. And that is a common theme for 173 00:09:54,760 --> 00:09:57,080 Speaker 1: things that have to do with women, I think often 174 00:09:57,080 --> 00:10:01,040 Speaker 1: in general, specifically women of color. And once I finished 175 00:10:01,040 --> 00:10:04,679 Speaker 1: writing the article, Facebook whatever, what have you? What has 176 00:10:04,760 --> 00:10:06,760 Speaker 1: dropped within the past couple of weeks we are getting 177 00:10:06,880 --> 00:10:10,439 Speaker 1: which is a really great piece of journalism, the Facebook reports, 178 00:10:10,440 --> 00:10:13,160 Speaker 1: but they're in Wall Street Journal. They've been the Facebook 179 00:10:13,200 --> 00:10:16,120 Speaker 1: podcast and one of the reports and this was really 180 00:10:16,160 --> 00:10:18,880 Speaker 1: done in depth for the m I T Technology Review 181 00:10:19,320 --> 00:10:22,640 Speaker 1: points out that something like five of the top ten 182 00:10:24,480 --> 00:10:28,640 Speaker 1: revenue slash groups may for centered on black people, and 183 00:10:28,679 --> 00:10:31,319 Speaker 1: like three of the ten for indigenous people are fake 184 00:10:32,559 --> 00:10:35,760 Speaker 1: and are known to be fake pretending to be black people. 185 00:10:36,520 --> 00:10:38,760 Speaker 1: I wrote this. I wrote my article in Model View 186 00:10:38,800 --> 00:10:44,720 Speaker 1: Culture in twenty fourteen. I wrote an article for Wired 187 00:10:44,760 --> 00:10:47,800 Speaker 1: in twenty twenty there was a report that went to 188 00:10:47,960 --> 00:10:51,560 Speaker 1: the Senate from Oxford. So this is not a small 189 00:10:51,840 --> 00:10:54,959 Speaker 1: independent report. It was an Oxford And we also have 190 00:10:55,000 --> 00:10:58,000 Speaker 1: Sherne Mitchell and the Audience who wrote who wrote a 191 00:10:58,000 --> 00:11:01,880 Speaker 1: report about this in I think also seventeen and at 192 00:11:01,960 --> 00:11:05,760 Speaker 1: various points. So we had all of this, but suddenly 193 00:11:05,760 --> 00:11:09,480 Speaker 1: it becomes a thing when Wall Street General writes about 194 00:11:09,520 --> 00:11:12,560 Speaker 1: it. It It becomes a thing like even Oxford couldn't get 195 00:11:12,640 --> 00:11:15,679 Speaker 1: these people off. It wasn't the Senate hearing. Like one 196 00:11:15,679 --> 00:11:17,520 Speaker 1: of the things that I say is like bam. This 197 00:11:17,600 --> 00:11:20,720 Speaker 1: was also in the Amnesty International report, and that was 198 00:11:20,720 --> 00:11:23,640 Speaker 1: an interesting thing because I was interviewed for that report 199 00:11:23,720 --> 00:11:26,400 Speaker 1: and I've made some very specific comments on race and 200 00:11:26,559 --> 00:11:29,520 Speaker 1: got told in the way that women who are multiply 201 00:11:29,559 --> 00:11:33,160 Speaker 1: marginalized are often told, it's divisive what you said, so 202 00:11:33,200 --> 00:11:36,440 Speaker 1: we're pulling it out. And what I said was the 203 00:11:36,600 --> 00:11:40,280 Speaker 1: first targets of these issues are usually black women. We 204 00:11:40,320 --> 00:11:43,600 Speaker 1: don't pay attention, and in fact, we incentivize not paying 205 00:11:43,600 --> 00:11:46,480 Speaker 1: attention because it makes great leaders and people get very 206 00:11:46,480 --> 00:11:50,160 Speaker 1: good at talking about misinformation or harm online by making 207 00:11:50,160 --> 00:11:54,400 Speaker 1: those people usually singly marginalized white women. But it was 208 00:11:54,440 --> 00:11:58,800 Speaker 1: divisive and that I think four of those Facebook groups 209 00:11:58,880 --> 00:12:02,840 Speaker 1: have been mentioned in the study by Oxford after which 210 00:12:02,880 --> 00:12:04,760 Speaker 1: was still done after the studies and the observations of 211 00:12:04,760 --> 00:12:07,680 Speaker 1: black women, and once they were mentored in the Wall 212 00:12:07,679 --> 00:12:10,640 Speaker 1: Street Journal article and the reports, how long do you 213 00:12:10,679 --> 00:12:12,920 Speaker 1: think it took them to take it off the internet? 214 00:12:16,440 --> 00:12:20,439 Speaker 1: Not seven years, twenty four hours? Oh, y'all are so 215 00:12:20,800 --> 00:12:26,040 Speaker 1: y'all are so helpful, twelve twelve by the time one 216 00:12:26,120 --> 00:12:29,800 Speaker 1: of and some of them are just so openly offensive, 217 00:12:29,920 --> 00:12:32,240 Speaker 1: like the one the number one was my Baby Daddy 218 00:12:32,280 --> 00:12:35,640 Speaker 1: Ain't Ship because that's how they think black people took online. 219 00:12:36,840 --> 00:12:38,680 Speaker 1: So they thought that that was a real article, that 220 00:12:38,760 --> 00:12:41,560 Speaker 1: was a real group when it made it wasn't And 221 00:12:42,720 --> 00:12:44,600 Speaker 1: that came down in twelve hours as long as the 222 00:12:44,600 --> 00:12:48,480 Speaker 1: person reporting it wasn't black. And that has been a 223 00:12:48,559 --> 00:12:51,000 Speaker 1: common theme in so many things that I've found for 224 00:12:51,200 --> 00:12:54,120 Speaker 1: multiply marginalized people, but specifically for how black women are 225 00:12:54,200 --> 00:12:58,560 Speaker 1: interacted with them line now, usually for things like this, 226 00:12:58,640 --> 00:13:03,080 Speaker 1: we are asked when we had these discussions the issue 227 00:13:03,480 --> 00:13:06,480 Speaker 1: and part of what I wrote the article for and 228 00:13:06,559 --> 00:13:11,600 Speaker 1: hearing about your podcast is I really like being black? 229 00:13:13,480 --> 00:13:19,040 Speaker 1: I like being what and it's not in and I 230 00:13:19,120 --> 00:13:21,760 Speaker 1: like doing tech work and I like analyzing things, and 231 00:13:21,800 --> 00:13:26,960 Speaker 1: I don't feel that I should have to answer everything 232 00:13:26,960 --> 00:13:29,040 Speaker 1: through a lens of how do I make it diverse 233 00:13:29,080 --> 00:13:32,240 Speaker 1: and inclusive or how do we answer our problems with 234 00:13:33,160 --> 00:13:36,640 Speaker 1: the lack of representation, because it's not an our problem, 235 00:13:36,679 --> 00:13:40,920 Speaker 1: that's a you problem. I am this person everywhere I go. Also, 236 00:13:41,679 --> 00:13:44,199 Speaker 1: when I'm thinking about tech issues, and why I wrote 237 00:13:44,200 --> 00:13:48,280 Speaker 1: that article was I like to think about tech issues. 238 00:13:48,679 --> 00:13:51,320 Speaker 1: I like to think about things like q A. I 239 00:13:51,400 --> 00:13:53,360 Speaker 1: like to think about things about I like to think 240 00:13:53,400 --> 00:13:55,520 Speaker 1: about So what does the gith hub repo is? Why 241 00:13:55,520 --> 00:13:58,360 Speaker 1: does get hub design like that? My primary thing right 242 00:13:58,360 --> 00:14:01,439 Speaker 1: now is community and calms. So if you've actually worked 243 00:14:01,440 --> 00:14:03,080 Speaker 1: in product design, you know if you do anything that 244 00:14:03,120 --> 00:14:06,680 Speaker 1: involves community, comms copy everybody's working in get hub, you 245 00:14:06,720 --> 00:14:10,920 Speaker 1: are usually reporting tickets. But we don't talk about those things, 246 00:14:10,920 --> 00:14:13,960 Speaker 1: and we often don't ask people who do work to 247 00:14:14,080 --> 00:14:17,240 Speaker 1: talk about things. There is a separation between the social 248 00:14:17,640 --> 00:14:21,560 Speaker 1: and the technical and the problem. And the thing that 249 00:14:21,600 --> 00:14:25,400 Speaker 1: I want constantly trying to push is that those divisions 250 00:14:25,760 --> 00:14:28,080 Speaker 1: are built into the Internet. So the first even the 251 00:14:28,120 --> 00:14:30,680 Speaker 1: start of the World Wide Web, Unfinished Live is about 252 00:14:30,720 --> 00:14:33,840 Speaker 1: decentralized protocols, and you will look at these things and 253 00:14:33,840 --> 00:14:36,400 Speaker 1: you'll see that the original meetings with tim Berners, Lee 254 00:14:36,520 --> 00:14:38,800 Speaker 1: and all of these people were divided like this is 255 00:14:38,800 --> 00:14:41,760 Speaker 1: a technical protocol, this is a social protocol. That's a 256 00:14:41,880 --> 00:14:43,880 Speaker 1: big problem. And that is a huge problem that we 257 00:14:43,920 --> 00:14:47,440 Speaker 1: have carried through the web since its inception of separating 258 00:14:47,440 --> 00:14:49,920 Speaker 1: those things, except they influence each other. If you don't 259 00:14:49,920 --> 00:14:53,320 Speaker 1: have social represent asation, you don't design well. If you 260 00:14:53,400 --> 00:14:56,520 Speaker 1: don't have a good analysis of technical work, you don't 261 00:14:56,560 --> 00:14:59,600 Speaker 1: make good choices for what happens in social And it's 262 00:14:59,640 --> 00:15:04,040 Speaker 1: an artificial separation, and it's also socially influenced by where 263 00:15:04,040 --> 00:15:08,040 Speaker 1: people think you are. Because the other part about the 264 00:15:08,120 --> 00:15:10,680 Speaker 1: thing of like let's listen to black women is that 265 00:15:10,680 --> 00:15:13,880 Speaker 1: when I get pulled into things or sometimes where things 266 00:15:13,960 --> 00:15:16,360 Speaker 1: like people want you to be Oh, we want to 267 00:15:16,480 --> 00:15:19,320 Speaker 1: we want to hear what you have to say, can 268 00:15:19,360 --> 00:15:23,040 Speaker 1: you can you talk about that? And they really want 269 00:15:23,080 --> 00:15:25,240 Speaker 1: me to sing the ballad of how terrible it is 270 00:15:25,280 --> 00:15:28,160 Speaker 1: to be black and why they should be nice to me? 271 00:15:28,920 --> 00:15:31,600 Speaker 1: And when you want to sing the song of joy 272 00:15:31,640 --> 00:15:34,360 Speaker 1: of I love being black, but your your product design 273 00:15:34,480 --> 00:15:36,720 Speaker 1: is bad and the fact that me being black means 274 00:15:36,720 --> 00:15:39,000 Speaker 1: your product doesn't work? Is you problem? I need you 275 00:15:39,040 --> 00:15:41,560 Speaker 1: to get better on that. COOBU. They suddenly don't want 276 00:15:41,560 --> 00:15:45,360 Speaker 1: to have the conversation. People love to have diversity conversations, 277 00:15:45,360 --> 00:15:48,320 Speaker 1: but I'm like, okay, public, please do me a favor 278 00:15:48,320 --> 00:15:50,320 Speaker 1: of someone who works in products, who looks at these tickets. 279 00:15:50,520 --> 00:15:52,640 Speaker 1: Publish all your diversity numbers. Don't tell me you're gonna 280 00:15:52,640 --> 00:15:54,520 Speaker 1: do better. I want to see all of those numbers 281 00:15:54,560 --> 00:15:56,960 Speaker 1: in an easily accessible place that I can pull up 282 00:15:57,040 --> 00:16:04,280 Speaker 1: everything time. My backgrounds are libraries, so don't don't. You 283 00:16:04,320 --> 00:16:06,200 Speaker 1: don't have to tell me anything you don't I don't 284 00:16:06,240 --> 00:16:08,120 Speaker 1: need to part and part of the joy of being 285 00:16:08,160 --> 00:16:10,080 Speaker 1: black is I don't have to be the singular black person. 286 00:16:10,120 --> 00:16:13,920 Speaker 1: I don't want to be a spokesperson. I like librarians. 287 00:16:13,960 --> 00:16:16,920 Speaker 1: I like library stuff, like thinking and reading. I like 288 00:16:17,440 --> 00:16:19,520 Speaker 1: creating and coding and all of that. I don't need 289 00:16:19,560 --> 00:16:21,120 Speaker 1: to be the singular black person. There are people who 290 00:16:21,160 --> 00:16:24,080 Speaker 1: are often much better served than this. But I want 291 00:16:24,120 --> 00:16:26,280 Speaker 1: my work to be done well. I wanted to be 292 00:16:26,440 --> 00:16:29,120 Speaker 1: well compensated for the things I do. I want you 293 00:16:29,160 --> 00:16:30,760 Speaker 1: to credit me, and I want you to credit mine, 294 00:16:30,800 --> 00:16:34,320 Speaker 1: and I want you to have good practices. I happen 295 00:16:34,400 --> 00:16:37,560 Speaker 1: to be black while asking for these things, but that 296 00:16:37,600 --> 00:16:40,440 Speaker 1: doesn't make it a social justice request. It makes it 297 00:16:40,480 --> 00:16:44,280 Speaker 1: a request for good systems. And the problem with these 298 00:16:44,280 --> 00:16:46,040 Speaker 1: things is that people will treat this like, oh, you 299 00:16:46,080 --> 00:16:50,200 Speaker 1: want to do diversity because you're talking about how the 300 00:16:50,240 --> 00:16:54,760 Speaker 1: link the neural linguistic program pro programming penalizes black people 301 00:16:54,800 --> 00:16:56,640 Speaker 1: more than it penalizes people who pretend to be black. 302 00:16:56,680 --> 00:16:58,720 Speaker 1: So you're talking about diversitly. I'm like, I'm talking about 303 00:16:58,760 --> 00:17:02,320 Speaker 1: your your your machine learning set doesn't work, and then 304 00:17:02,360 --> 00:17:04,560 Speaker 1: when it stops, and then when it hits somebody actually 305 00:17:04,600 --> 00:17:07,080 Speaker 1: care about, It's like, what is our problem with AI? 306 00:17:07,160 --> 00:17:09,159 Speaker 1: There might be a math problem. So it's not a 307 00:17:09,160 --> 00:17:11,600 Speaker 1: math problem when it's penalizing me or picking me out 308 00:17:11,720 --> 00:17:14,960 Speaker 1: or penalizing black people, but it's a math problem when 309 00:17:15,000 --> 00:17:18,720 Speaker 1: it stops white people. Are we using two different kinds 310 00:17:18,760 --> 00:17:22,200 Speaker 1: of math? Which if we are, it's fine, but let's 311 00:17:22,280 --> 00:17:26,960 Speaker 1: lean into that reality and the danger becomes it's like, 312 00:17:27,000 --> 00:17:29,920 Speaker 1: you will listen to me, Bemoan. Being black, you will 313 00:17:29,960 --> 00:17:31,840 Speaker 1: not list You will not listen to me and have 314 00:17:31,920 --> 00:17:36,040 Speaker 1: effectual steps for us to do this work better and 315 00:17:37,000 --> 00:17:40,880 Speaker 1: that is an issue that keeps coming up, and we're 316 00:17:40,920 --> 00:17:42,520 Speaker 1: going to see more of it with the idea of 317 00:17:42,520 --> 00:17:45,800 Speaker 1: the now content creator economy, where everybody's response when a 318 00:17:45,840 --> 00:17:47,760 Speaker 1: black person has a problem, it's like, are you a 319 00:17:47,800 --> 00:17:50,400 Speaker 1: content creator because we really want to boost your profile. 320 00:17:50,760 --> 00:17:52,920 Speaker 1: I don't want you to boost my profile. I want 321 00:17:52,960 --> 00:17:56,600 Speaker 1: you to fix this. I don't need I like making podcasts. 322 00:17:56,600 --> 00:17:59,800 Speaker 1: I love your podcast, but I don't need to make 323 00:17:59,840 --> 00:18:02,720 Speaker 1: a podcast to get you to fix the AI that 324 00:18:02,720 --> 00:18:05,280 Speaker 1: would make both of us guerrillas. And I especially don't 325 00:18:05,320 --> 00:18:07,480 Speaker 1: need to make a podcast for this three or four 326 00:18:07,560 --> 00:18:11,120 Speaker 1: times every single gut damn year when somebody pointed out 327 00:18:11,119 --> 00:18:14,560 Speaker 1: in and you can't provide me a change log for 328 00:18:14,720 --> 00:18:18,520 Speaker 1: what actual interventions and reports and white papers you published 329 00:18:18,560 --> 00:18:21,720 Speaker 1: and synthesize to make it stop happening. I don't need 330 00:18:21,720 --> 00:18:25,800 Speaker 1: a podcast, I need a paper trail. But they don't 331 00:18:26,000 --> 00:18:28,959 Speaker 1: believe that we should have those things or it's right 332 00:18:29,000 --> 00:18:30,960 Speaker 1: for us to ask for those things, And that I 333 00:18:31,000 --> 00:18:34,639 Speaker 1: think is what is really especially as we are and 334 00:18:34,640 --> 00:18:37,920 Speaker 1: then times it's really is getting stressful because we are 335 00:18:38,000 --> 00:18:42,479 Speaker 1: asking for changes and responses to these herculeans. One sin 336 00:18:42,560 --> 00:18:47,200 Speaker 1: a lifetime, one sin of millennia occurrences. But the thing 337 00:18:47,240 --> 00:18:50,200 Speaker 1: about change and innovation is that you don't just innovate 338 00:18:50,240 --> 00:18:53,160 Speaker 1: a product. You don't just change the technical things. You've 339 00:18:53,200 --> 00:18:56,199 Speaker 1: got to change society. And what is very I think 340 00:18:56,240 --> 00:18:58,120 Speaker 1: it's most uncomfortable for a lot of the people who 341 00:18:58,440 --> 00:19:00,880 Speaker 1: don't want to listen or things like that, and sometimes 342 00:19:00,880 --> 00:19:03,720 Speaker 1: even for me, is that I have to change myself. 343 00:19:04,280 --> 00:19:06,640 Speaker 1: So I when you tell me how do we deal 344 00:19:06,680 --> 00:19:11,200 Speaker 1: with diversity? First of all, who But the second question 345 00:19:11,359 --> 00:19:15,040 Speaker 1: is why why are we talking about diversity? Why are 346 00:19:15,040 --> 00:19:17,320 Speaker 1: we talking about it being a fundamental part of what's 347 00:19:17,359 --> 00:19:20,280 Speaker 1: not functioning? Well? Why aren't we talking about it be 348 00:19:20,280 --> 00:19:24,440 Speaker 1: a fundamental part of the reason we're here. I do 349 00:19:24,520 --> 00:19:27,439 Speaker 1: not like models that constantly asked me to be supplicant 350 00:19:27,520 --> 00:19:30,040 Speaker 1: to deal with racism when you've already set it up 351 00:19:30,040 --> 00:19:32,720 Speaker 1: in such a racist way that I'm constantly requesting things. 352 00:19:33,040 --> 00:19:34,600 Speaker 1: And there are times when I feel you have more 353 00:19:34,640 --> 00:19:36,160 Speaker 1: of a problem with the fact that when I tell 354 00:19:36,200 --> 00:19:39,320 Speaker 1: you no or this is wrong and it sticks and 355 00:19:39,359 --> 00:19:41,200 Speaker 1: you can't shut us down or you have us out 356 00:19:41,240 --> 00:19:43,399 Speaker 1: that we're at that place in some ways, then you 357 00:19:43,480 --> 00:19:44,920 Speaker 1: have a problem with the fact that the thing don't 358 00:19:44,920 --> 00:20:02,600 Speaker 1: work let's take a quick break at our back. You 359 00:20:02,640 --> 00:20:06,560 Speaker 1: said earlier how we are often having to to scream 360 00:20:06,600 --> 00:20:08,600 Speaker 1: at the top of our lungs for someone to hear 361 00:20:08,680 --> 00:20:11,600 Speaker 1: us to fix things right, and that everybody wants to say, oh, 362 00:20:11,640 --> 00:20:14,080 Speaker 1: listen to black women, amplify black women, We support black 363 00:20:14,080 --> 00:20:18,000 Speaker 1: women until we're pointing out these problems that cause us harm. 364 00:20:18,200 --> 00:20:20,480 Speaker 1: And if we're not singing this sad song about how 365 00:20:20,520 --> 00:20:23,840 Speaker 1: hard it is and we're actually saying no, your product, 366 00:20:23,920 --> 00:20:26,880 Speaker 1: your platform is creating this harm. Um you shouted out. 367 00:20:26,920 --> 00:20:29,200 Speaker 1: One of my kind of tech hero Sharene mitchell I. 368 00:20:29,240 --> 00:20:31,400 Speaker 1: Don't want to put you on the spot, but founder 369 00:20:31,520 --> 00:20:34,119 Speaker 1: of Stop Online Valance against Women, who really did a 370 00:20:34,119 --> 00:20:36,320 Speaker 1: lot of the reporting early on about the way that 371 00:20:36,400 --> 00:20:39,560 Speaker 1: black women experience harm online. So one of my questions 372 00:20:39,560 --> 00:20:42,399 Speaker 1: for you is, like, what if you're someone who just 373 00:20:42,520 --> 00:20:45,679 Speaker 1: wants to use social media to talk about real housewives 374 00:20:45,840 --> 00:20:47,920 Speaker 1: or do your job, and you didn't really sign up 375 00:20:47,920 --> 00:20:51,119 Speaker 1: to be this unpaid sort of person who is always 376 00:20:51,119 --> 00:20:54,200 Speaker 1: flagging these issues to make these products function the way 377 00:20:54,240 --> 00:20:57,879 Speaker 1: they should, Like, what like, how do we exist online 378 00:20:58,440 --> 00:21:02,480 Speaker 1: if we want to not have this extra unpaid burden 379 00:21:02,480 --> 00:21:04,880 Speaker 1: that we really shouldn't have. Just to show up. Well, 380 00:21:04,920 --> 00:21:06,760 Speaker 1: for me, it's not a one if I got started 381 00:21:06,760 --> 00:21:10,360 Speaker 1: online because I'm a sci fi geek, like but that's 382 00:21:10,359 --> 00:21:14,080 Speaker 1: where a lot of these problems happen. Fandom nerd them. Recently, 383 00:21:14,119 --> 00:21:17,320 Speaker 1: Twitch had was having hate raids where they basically, we're 384 00:21:17,359 --> 00:21:23,840 Speaker 1: flooding the thing, flooding people's Uh. They were flooding people 385 00:21:23,920 --> 00:21:30,439 Speaker 1: streams because of this, and the response is there is 386 00:21:30,440 --> 00:21:32,800 Speaker 1: as there for me, there's a two pronged response. The 387 00:21:32,840 --> 00:21:35,400 Speaker 1: response that I would give you, as someone who cares 388 00:21:35,440 --> 00:21:38,679 Speaker 1: about your mental energy and your face, is like, curate 389 00:21:38,720 --> 00:21:42,840 Speaker 1: your fee list, do this, do that, etcetera. You have 390 00:21:43,000 --> 00:21:45,280 Speaker 1: to kind of approach it because that's the only way 391 00:21:45,280 --> 00:21:49,800 Speaker 1: you will be able to operate cleanly online. The other 392 00:21:49,960 --> 00:21:53,200 Speaker 1: part about it is in the way that I feel, 393 00:21:53,240 --> 00:21:56,320 Speaker 1: as a person who makes these things, someone who looks 394 00:21:56,359 --> 00:21:59,000 Speaker 1: at the features and such, that it's that it's not 395 00:21:59,280 --> 00:22:03,280 Speaker 1: your response stability. This is no longer a question to me. 396 00:22:03,359 --> 00:22:06,480 Speaker 1: And that might be a responsively annoyed and tide of 397 00:22:06,520 --> 00:22:09,680 Speaker 1: the pandemic and how we haven't addressed racism and sexism 398 00:22:09,680 --> 00:22:12,359 Speaker 1: and everything to the point we are now worried about 399 00:22:12,359 --> 00:22:16,200 Speaker 1: going outside because of what's happening. It is the point. 400 00:22:16,280 --> 00:22:18,399 Speaker 1: It is the It is the need and the necessity 401 00:22:18,400 --> 00:22:22,080 Speaker 1: of the people to fix it. I I don't I 402 00:22:22,119 --> 00:22:24,959 Speaker 1: don't want to have another unpaid conversation. Can you do 403 00:22:25,119 --> 00:22:28,400 Speaker 1: freak q A research? Can you do free design research 404 00:22:28,440 --> 00:22:31,800 Speaker 1: and free you user interviews? Because you don't believe me 405 00:22:31,840 --> 00:22:34,360 Speaker 1: when I say I have a different experience. So I've 406 00:22:34,400 --> 00:22:36,240 Speaker 1: got to cut and paste and do a whole report. 407 00:22:36,680 --> 00:22:39,800 Speaker 1: But you're paying somebody within your organization who's usually not 408 00:22:40,119 --> 00:22:43,240 Speaker 1: black and doesn't use the platform six figures to do it. 409 00:22:43,680 --> 00:22:45,680 Speaker 1: At this point, get that person to do their job, 410 00:22:46,119 --> 00:22:49,840 Speaker 1: or respect the or design it so that I can 411 00:22:49,880 --> 00:22:51,840 Speaker 1: report for free. Because the other side of this is 412 00:22:51,960 --> 00:22:54,360 Speaker 1: as someone who looks at community, as someone who looks 413 00:22:54,359 --> 00:22:56,800 Speaker 1: at use your feedback. Most of the time, when we 414 00:22:56,840 --> 00:22:59,120 Speaker 1: are experiencing things like that, we want to tell someone 415 00:22:59,280 --> 00:23:02,040 Speaker 1: because we wanted to stop. So we'll intrinsically go hey, 416 00:23:02,040 --> 00:23:04,880 Speaker 1: And some of it is cars telling a home model, 417 00:23:04,880 --> 00:23:06,400 Speaker 1: but we'll turn to somebody and be like, Hi, I'm 418 00:23:06,440 --> 00:23:09,560 Speaker 1: experiencing these things. I think one of the things that 419 00:23:09,680 --> 00:23:13,880 Speaker 1: is most enraging to me about the content creator distinction 420 00:23:13,920 --> 00:23:20,680 Speaker 1: specifically is watching TikTok users and watching TikTok creators. There is, yes, 421 00:23:20,720 --> 00:23:23,880 Speaker 1: the power black storytelling, the power black art and culture. 422 00:23:23,920 --> 00:23:27,240 Speaker 1: But if you are a young person of color, but 423 00:23:27,359 --> 00:23:32,480 Speaker 1: specifically black, I am in all of you. You are 424 00:23:32,560 --> 00:23:36,679 Speaker 1: learning high level video editing and algorithmic justice and machine learning, 425 00:23:36,840 --> 00:23:39,040 Speaker 1: and you are putting it into a medium on the 426 00:23:39,080 --> 00:23:42,920 Speaker 1: medium that is that is marginalizing you, and you are 427 00:23:43,040 --> 00:23:45,760 Speaker 1: quick and good about it. Because how quickly does TikTok 428 00:23:45,840 --> 00:23:49,520 Speaker 1: respond when somebody publishes and goes, hey, you're surfacing unnatural material, 429 00:23:50,000 --> 00:23:53,399 Speaker 1: which means these and I say, young kids to me, 430 00:23:53,440 --> 00:23:56,760 Speaker 1: I'm right now, anybody under twenty five. I don't mean, 431 00:23:57,119 --> 00:24:00,320 Speaker 1: I don't mean to infantilize, but anyone who's under two five. 432 00:24:00,440 --> 00:24:02,200 Speaker 1: So these are people who, if they had gone to 433 00:24:02,359 --> 00:24:05,320 Speaker 1: school for this, would not be finished with the pH d. 434 00:24:06,560 --> 00:24:10,080 Speaker 1: But they are already quick and recognizing these patterns, recognizing 435 00:24:10,119 --> 00:24:14,480 Speaker 1: the tech, reporting it. They are doing that work already, 436 00:24:14,880 --> 00:24:17,240 Speaker 1: and they're working as scientists, they're working as observers, they're 437 00:24:17,240 --> 00:24:20,800 Speaker 1: working as researchers, they're working as organizers making no, not 438 00:24:20,880 --> 00:24:24,800 Speaker 1: making dances. And we're saying to them, all you're doing 439 00:24:24,880 --> 00:24:27,320 Speaker 1: is content creation being But the honest truth is they 440 00:24:27,400 --> 00:24:30,959 Speaker 1: have to run a small think tank for every single 441 00:24:31,040 --> 00:24:36,840 Speaker 1: account to respond to to curate because we have done 442 00:24:37,040 --> 00:24:40,679 Speaker 1: so poorly in actually building the product and building the 443 00:24:40,720 --> 00:24:44,320 Speaker 1: processes for harm reduction and harm read mitigation, or just 444 00:24:44,400 --> 00:24:48,480 Speaker 1: moderating our content. That's that I I one of the 445 00:24:48,480 --> 00:24:50,119 Speaker 1: things that I'm starting to find with the frame and 446 00:24:50,200 --> 00:24:54,399 Speaker 1: it's often confrontational. I'll be confrontation a little bit. Is 447 00:24:54,680 --> 00:24:58,040 Speaker 1: I'm no longer accepting the framing of So let's hear 448 00:24:58,080 --> 00:25:00,880 Speaker 1: more about my problem. Okay, where we are, We're gonna 449 00:25:00,920 --> 00:25:03,320 Speaker 1: start there. Tell me how you got to two thousand 450 00:25:03,320 --> 00:25:06,080 Speaker 1: and twenty one and didn't know this was a problem. 451 00:25:06,080 --> 00:25:08,280 Speaker 1: Tell me how you got to two thousand and twenty 452 00:25:08,320 --> 00:25:10,840 Speaker 1: one and you didn't know that marginalized people have a 453 00:25:10,880 --> 00:25:13,919 Speaker 1: hard time online. Tell me how you are in a 454 00:25:14,000 --> 00:25:16,920 Speaker 1: sink tank, in a nonprofit, in a job when you 455 00:25:17,000 --> 00:25:18,800 Speaker 1: didn't If you don't know this, when I can pull 456 00:25:18,920 --> 00:25:24,040 Speaker 1: reports now from Harvard, Oxford, Yale, at one point, Clemson University, 457 00:25:24,200 --> 00:25:28,960 Speaker 1: Amnesty International, myself. All of this is open publication. These 458 00:25:28,960 --> 00:25:31,200 Speaker 1: are the publications you mix. So why are you talking 459 00:25:31,200 --> 00:25:33,320 Speaker 1: to me like I don't know what's going on? And 460 00:25:33,480 --> 00:25:37,240 Speaker 1: number two, don't tell me about my tone. If the fact, 461 00:25:37,320 --> 00:25:40,920 Speaker 1: then I'm angry. We've seen what these people do unchecked. 462 00:25:41,600 --> 00:25:45,120 Speaker 1: I have been getting death threats since I was twenty two. 463 00:25:46,160 --> 00:25:49,040 Speaker 1: I'm gonna let people don't a secret. I'm thirty seven. 464 00:25:50,240 --> 00:25:54,200 Speaker 1: I've been getting death threats for fifteen smooth straight years. 465 00:25:55,960 --> 00:25:59,359 Speaker 1: I'm not I'm not here to babysit you. I'm not 466 00:25:59,440 --> 00:26:01,639 Speaker 1: here to make you feel good about the dereliction of 467 00:26:01,680 --> 00:26:04,719 Speaker 1: your duty. I'm here to fix this problem, and if 468 00:26:04,720 --> 00:26:06,160 Speaker 1: I can't fix it for me, I'm here to fix 469 00:26:06,200 --> 00:26:07,959 Speaker 1: it for the people behind me. Now, we can do 470 00:26:07,960 --> 00:26:09,600 Speaker 1: that with some social things, but we also can do 471 00:26:09,640 --> 00:26:12,880 Speaker 1: that by you just doing your job. Don't automatically turn 472 00:26:12,920 --> 00:26:15,479 Speaker 1: on contents. Don't use an AI that recognizes me as 473 00:26:15,480 --> 00:26:18,600 Speaker 1: a gorilla. Don't do it. We don't have to have 474 00:26:18,640 --> 00:26:20,679 Speaker 1: a discussion. You don't have to hear my thoughts. I'm 475 00:26:20,720 --> 00:26:24,760 Speaker 1: not a small child. Just fix it. Start making products 476 00:26:24,760 --> 00:26:27,520 Speaker 1: that help people tell you what they need, and then 477 00:26:27,520 --> 00:26:30,359 Speaker 1: when they tell you them, don't try and finance it 478 00:26:30,400 --> 00:26:32,880 Speaker 1: so you do something different because you're not comfortable you've 479 00:26:32,920 --> 00:26:36,159 Speaker 1: been told what is needed. Either do it or be 480 00:26:36,200 --> 00:26:38,720 Speaker 1: honest about the fact of why you're not doing it 481 00:26:39,240 --> 00:26:42,320 Speaker 1: and also allows and start allowing us to have those 482 00:26:42,359 --> 00:26:45,920 Speaker 1: discussions where we just get to do our job, coders 483 00:26:45,920 --> 00:26:49,040 Speaker 1: and creators and thinkers and writers, and we want to 484 00:26:49,080 --> 00:26:50,800 Speaker 1: go in and write a good bit of code. We 485 00:26:50,800 --> 00:26:52,680 Speaker 1: want to write some good copy. We want to build 486 00:26:52,680 --> 00:26:56,120 Speaker 1: these communities, make it so I can do that. I 487 00:26:56,440 --> 00:26:59,280 Speaker 1: My part of my job to district shouldn't be how 488 00:26:59,359 --> 00:27:03,960 Speaker 1: do I help you solve racism? No, We're gonna do 489 00:27:04,000 --> 00:27:07,879 Speaker 1: it together Grey, But I would just really like to 490 00:27:07,960 --> 00:27:10,359 Speaker 1: build the code that I'm building. I'm working on a 491 00:27:10,359 --> 00:27:17,280 Speaker 1: product now m with Mozilla Rally, so we are specifically 492 00:27:17,320 --> 00:27:26,160 Speaker 1: trying to build ways of tracking data tracking everything from 493 00:27:26,400 --> 00:27:29,000 Speaker 1: doom scrolling so how which was coined by a woman 494 00:27:29,040 --> 00:27:32,240 Speaker 1: of color, Karen Huff about how you are online to 495 00:27:32,520 --> 00:27:34,760 Speaker 1: how ads are targeted to you without having to go 496 00:27:34,800 --> 00:27:38,800 Speaker 1: through platforms. It's built through web extension. So and it's 497 00:27:38,840 --> 00:27:41,359 Speaker 1: great because right after that was it Facebook shut that 498 00:27:41,480 --> 00:27:44,000 Speaker 1: Facebook observer. We found out that all the data everybody 499 00:27:44,040 --> 00:27:50,840 Speaker 1: was getting wasn't true. And that is it takes everything 500 00:27:50,840 --> 00:27:52,680 Speaker 1: in me not to start with so I told you so, 501 00:27:52,840 --> 00:27:54,879 Speaker 1: and everything in me is not good enough. So I 502 00:27:54,960 --> 00:28:00,240 Speaker 1: told you so that there is there are so many 503 00:28:00,280 --> 00:28:03,520 Speaker 1: people who told these people this. One of the jokes 504 00:28:03,560 --> 00:28:05,639 Speaker 1: I have is that there are people who have formed 505 00:28:05,640 --> 00:28:07,800 Speaker 1: a coalition of oh my god, don't do that when 506 00:28:07,840 --> 00:28:10,720 Speaker 1: it comes to social media who don't agree on anything else. 507 00:28:11,720 --> 00:28:14,679 Speaker 1: I don't agree on anything else, but you've found it 508 00:28:14,680 --> 00:28:22,240 Speaker 1: from sex workers x X, religious conservatives, abortion rights activists, 509 00:28:22,280 --> 00:28:25,240 Speaker 1: black women, tech people, all of us have come together 510 00:28:25,280 --> 00:28:27,520 Speaker 1: and be like, I need you to think about this. 511 00:28:27,720 --> 00:28:30,879 Speaker 1: Why would you trust Facebook? Why would you organize anything 512 00:28:30,920 --> 00:28:34,199 Speaker 1: to make you trust Facebook as a tactical decision, not 513 00:28:34,320 --> 00:28:37,800 Speaker 1: as a whatever decision. And that comes not from our 514 00:28:37,840 --> 00:28:39,600 Speaker 1: notice because we're not on the inside. We've been the 515 00:28:39,600 --> 00:28:41,800 Speaker 1: people these attacks. I don't mean, I need to know 516 00:28:41,840 --> 00:28:43,320 Speaker 1: why you don't trust them, and I need you to 517 00:28:43,320 --> 00:28:47,160 Speaker 1: build in better arts. And if there's like no, no, no, 518 00:28:47,200 --> 00:28:50,120 Speaker 1: you don't understand how we work in Silicon Valley. We're friends, 519 00:28:50,120 --> 00:28:53,000 Speaker 1: blah blah blah. Now you get this that most of 520 00:28:53,040 --> 00:28:55,840 Speaker 1: this data is not good. How many people's PhDs just 521 00:28:56,000 --> 00:29:01,479 Speaker 1: got screwed because that data isn'tviable. But nobody wanted to 522 00:29:01,560 --> 00:29:04,840 Speaker 1: even think in terms of teaching, Let's be prepared for 523 00:29:04,880 --> 00:29:08,560 Speaker 1: the if we're hostile, You and I and other marginalized 524 00:29:08,600 --> 00:29:12,520 Speaker 1: people have no other option but to think what happens 525 00:29:12,520 --> 00:29:15,320 Speaker 1: if this goes left? And that is a reality in 526 00:29:15,320 --> 00:29:18,000 Speaker 1: the world, and they have been watching it for years, 527 00:29:18,200 --> 00:29:24,000 Speaker 1: so why aren't they prepared? And it's and if you 528 00:29:24,120 --> 00:29:26,600 Speaker 1: if you feel uncomfortable about giving me an answer that 529 00:29:26,680 --> 00:29:29,920 Speaker 1: feels like a thing you need to work out, right 530 00:29:31,240 --> 00:29:33,959 Speaker 1: when you have a jail break or something like that, 531 00:29:34,000 --> 00:29:37,040 Speaker 1: you fix that immediately. What is it about our issues? 532 00:29:37,360 --> 00:29:40,000 Speaker 1: What is it about the issues of people represented that 533 00:29:40,160 --> 00:29:42,360 Speaker 1: you can take so long? And I think the point 534 00:29:42,400 --> 00:29:44,200 Speaker 1: that we really need to move from now if we 535 00:29:44,280 --> 00:29:46,760 Speaker 1: want to get better, is that we're not going to 536 00:29:46,840 --> 00:29:50,160 Speaker 1: get past this until we do that. Why are certain 537 00:29:50,160 --> 00:29:53,960 Speaker 1: people's issues, Why are certain responses always secondary? That's not 538 00:29:54,440 --> 00:29:56,360 Speaker 1: We keep dancing around this, and we're gonna keep up 539 00:29:56,360 --> 00:29:58,320 Speaker 1: coming up with funny terms we're more concerned with. But 540 00:29:58,400 --> 00:30:02,200 Speaker 1: we're not getting past that. Unto will we answer it? 541 00:30:02,480 --> 00:30:04,960 Speaker 1: And it's super uncomfortable And I am a human, so 542 00:30:05,000 --> 00:30:07,640 Speaker 1: I understand why you don't want to. But we're now 543 00:30:07,680 --> 00:30:10,880 Speaker 1: in a pandemic that is going into its second, possibly 544 00:30:10,960 --> 00:30:15,600 Speaker 1: third year because we don't have we can't understand basic 545 00:30:15,720 --> 00:30:19,560 Speaker 1: kind of empathetics social reactions. There was a run up 546 00:30:19,600 --> 00:30:24,320 Speaker 1: on the capital of racists who were trying to kill people. 547 00:30:24,520 --> 00:30:26,400 Speaker 1: You don't hang a noose on the front of the 548 00:30:26,480 --> 00:30:30,120 Speaker 1: capital justice symbolical jester in the United States of America. 549 00:30:30,320 --> 00:30:33,080 Speaker 1: Do not tell that black lie to my black face. 550 00:30:33,560 --> 00:30:35,440 Speaker 1: I know what my people have been through. You put 551 00:30:35,480 --> 00:30:37,640 Speaker 1: a noose on a you put a new somewhere. You're 552 00:30:37,640 --> 00:30:40,760 Speaker 1: trying to hang some people. They did that on the Capitol. 553 00:30:41,360 --> 00:30:44,160 Speaker 1: They still haven't had a real full hearing. We've had 554 00:30:44,200 --> 00:30:48,120 Speaker 1: all of this happened, and we're still just listening. Why 555 00:30:48,160 --> 00:30:50,880 Speaker 1: aren't we acting? And until we get to this point, 556 00:30:50,960 --> 00:30:54,000 Speaker 1: we're gonna keep having spurs up and flirts up and 557 00:30:54,000 --> 00:30:56,520 Speaker 1: goes up and goes down until we answer that question 558 00:30:56,520 --> 00:31:02,000 Speaker 1: of why aren't we moving more. After a quick break, 559 00:31:13,560 --> 00:31:16,320 Speaker 1: let's get right back into it. One of the things 560 00:31:16,320 --> 00:31:18,560 Speaker 1: that I feel so frustrated about, as someone who has 561 00:31:18,600 --> 00:31:21,400 Speaker 1: worked in the disinformation and online extremism space for a while, 562 00:31:21,920 --> 00:31:24,320 Speaker 1: is this idea that we had to combat for so 563 00:31:24,400 --> 00:31:27,000 Speaker 1: long that it's just jokes and people will make these 564 00:31:27,040 --> 00:31:31,200 Speaker 1: comments online it's not serious. It didn't take a rocket 565 00:31:31,240 --> 00:31:35,960 Speaker 1: scientist to see that online commentary doesn't just stay online 566 00:31:36,040 --> 00:31:39,080 Speaker 1: and that what we saw on January six is directly related. 567 00:31:39,320 --> 00:31:42,960 Speaker 1: But talk about like lying to my face. How often 568 00:31:43,280 --> 00:31:46,480 Speaker 1: I would be in meetings with tech leadership and they 569 00:31:46,480 --> 00:31:49,239 Speaker 1: would say, oh, well, it's about speech. You know, this 570 00:31:49,320 --> 00:31:51,280 Speaker 1: is not about like we're not trying to you know, 571 00:31:51,320 --> 00:31:52,959 Speaker 1: this is not going to be related to like in 572 00:31:53,040 --> 00:31:56,560 Speaker 1: real life actions. We know things that start online don't 573 00:31:56,600 --> 00:31:59,080 Speaker 1: stay online, and so what we I mean, I live 574 00:31:59,120 --> 00:32:01,200 Speaker 1: in d C. What I saw in my own backyard 575 00:32:01,240 --> 00:32:04,240 Speaker 1: in January six, I saw it as a direct reaction 576 00:32:04,560 --> 00:32:08,440 Speaker 1: to the inaction that you just described to all of 577 00:32:08,440 --> 00:32:11,080 Speaker 1: these different little cutesy names for what we can all 578 00:32:11,080 --> 00:32:17,640 Speaker 1: plainly see. It's like extremism, house, boxy, woman, get get spicy. 579 00:32:18,360 --> 00:32:22,920 Speaker 1: I have a hard time believing that spaces and confederations 580 00:32:22,960 --> 00:32:25,440 Speaker 1: that are wider than the racists and the Proud Boys 581 00:32:25,960 --> 00:32:31,480 Speaker 1: are well versed in protecting me. If you do a 582 00:32:31,520 --> 00:32:38,960 Speaker 1: misinformation panel and everybody's white, I've stopped listening at this point. 583 00:32:38,960 --> 00:32:42,480 Speaker 1: If you can't grab somebody to be hey, let's talk, 584 00:32:42,800 --> 00:32:46,760 Speaker 1: just stand there and talk. That's a baxt level of 585 00:32:46,800 --> 00:32:49,520 Speaker 1: work that you're not willing to do that. I now 586 00:32:49,600 --> 00:32:52,760 Speaker 1: know that I can't trust anything else. I'll really, I'll 587 00:32:52,760 --> 00:32:57,680 Speaker 1: really come up because there is you've had time. And 588 00:32:57,760 --> 00:33:02,200 Speaker 1: the reason it's a joking is because it's a to them. 589 00:33:02,240 --> 00:33:05,480 Speaker 1: It is jokes in speech to them. And I'm actually 590 00:33:05,680 --> 00:33:07,800 Speaker 1: before this, I worked with the Choral Project, So I 591 00:33:07,880 --> 00:33:10,440 Speaker 1: was the community research leads for the Choral Project and 592 00:33:10,520 --> 00:33:13,600 Speaker 1: that it was about comment moderation. So we worked on 593 00:33:13,640 --> 00:33:18,880 Speaker 1: building things to moderate comments. And there are times depending 594 00:33:19,040 --> 00:33:20,360 Speaker 1: and like there's a whole type of things like you 595 00:33:20,360 --> 00:33:22,600 Speaker 1: have to set what you'll except, etcetera, etcetera. There are 596 00:33:22,640 --> 00:33:24,840 Speaker 1: times where I would moderate something or look at something 597 00:33:24,920 --> 00:33:27,160 Speaker 1: and this is something that I would punch someone in 598 00:33:27,200 --> 00:33:29,600 Speaker 1: the faith for if they were standing right in front 599 00:33:29,600 --> 00:33:33,600 Speaker 1: of me. But as a content moderate moderator, based on 600 00:33:33,800 --> 00:33:38,240 Speaker 1: what we had defined our parameters were, I had to 601 00:33:38,320 --> 00:33:40,600 Speaker 1: let it go. I might not like it, but I 602 00:33:40,600 --> 00:33:44,360 Speaker 1: would let let it go. The thing that is very 603 00:33:44,360 --> 00:33:47,760 Speaker 1: that is often grounded in a lot of these decisions 604 00:33:48,040 --> 00:33:52,600 Speaker 1: is that often we are not asking them to do 605 00:33:52,640 --> 00:33:54,840 Speaker 1: anything they have not set out in their own rules 606 00:33:55,000 --> 00:33:58,920 Speaker 1: or bylines or anything like that. We are asking them 607 00:33:58,960 --> 00:34:02,440 Speaker 1: to merely infor worced them for marginalized people the way 608 00:34:02,440 --> 00:34:04,800 Speaker 1: they bled they enforced them for people who might matter. 609 00:34:05,160 --> 00:34:07,280 Speaker 1: That's literally the only thing I'm asking you to do. 610 00:34:09,040 --> 00:34:13,920 Speaker 1: I actually had an experience with Twitter last year. I 611 00:34:13,920 --> 00:34:15,640 Speaker 1: think it was last year. Time means nothing right now, 612 00:34:15,960 --> 00:34:23,000 Speaker 1: but there is a congress person where um who said 613 00:34:23,040 --> 00:34:28,759 Speaker 1: something so violently anti Asian and sinophobic. I don't want 614 00:34:28,760 --> 00:34:34,479 Speaker 1: to repeat it, but it was congresswoman that a little 615 00:34:34,680 --> 00:34:39,240 Speaker 1: that speech warning, I just went, you racist, raggedy bitch. 616 00:34:41,200 --> 00:34:43,239 Speaker 1: This is not something my mom's gonna be proud of. 617 00:34:43,280 --> 00:34:45,359 Speaker 1: That's not necessarily I'm necessarily proud of at that moment, 618 00:34:45,400 --> 00:34:47,560 Speaker 1: because it was just such a gut reaction of what 619 00:34:48,680 --> 00:34:52,920 Speaker 1: and there was and I knew I was in good 620 00:34:52,920 --> 00:34:55,200 Speaker 1: company because that was not I wasn't the only person 621 00:34:55,320 --> 00:34:58,320 Speaker 1: who said that. It was me. It was a reporter 622 00:34:58,560 --> 00:35:00,799 Speaker 1: from I think the South Chida Poe was it was 623 00:35:00,840 --> 00:35:02,920 Speaker 1: I think there was a white mom in Texas who 624 00:35:03,040 --> 00:35:05,839 Speaker 1: was like, oh my god, you were racist, Stitch. I 625 00:35:05,920 --> 00:35:09,360 Speaker 1: was the only person who was blocked. I'm a verified 626 00:35:09,400 --> 00:35:12,560 Speaker 1: account for whatever that means, but I was blocked. They 627 00:35:13,120 --> 00:35:14,759 Speaker 1: were a whole bunch of things, and there was no 628 00:35:14,800 --> 00:35:17,160 Speaker 1: way for me to appeal that. I actually had to 629 00:35:17,200 --> 00:35:24,279 Speaker 1: contact someone separately, and that for for moderation. As a 630 00:35:24,320 --> 00:35:28,480 Speaker 1: person who has moderation experience. That's a really bad model 631 00:35:29,080 --> 00:35:31,279 Speaker 1: if you're worried about things like that, and especially for 632 00:35:31,800 --> 00:35:35,719 Speaker 1: targeted congresswoman, you actually should be more concerned about that 633 00:35:35,840 --> 00:35:38,760 Speaker 1: language because she's a congresswoman. So I actually was not 634 00:35:39,160 --> 00:35:41,480 Speaker 1: against the fact that I was blocked, because you actually 635 00:35:41,480 --> 00:35:44,080 Speaker 1: have to worry about that because again, the one of 636 00:35:44,120 --> 00:35:48,880 Speaker 1: the most targeted people online for racism and has been 637 00:35:49,200 --> 00:35:54,520 Speaker 1: for about ten years is Diane Abbott, the MP in London. 638 00:35:54,920 --> 00:35:58,560 Speaker 1: The most targeted person in the anglophil in world is 639 00:35:58,600 --> 00:36:02,520 Speaker 1: a black woman, black MP for labor in London. That's 640 00:36:02,560 --> 00:36:05,879 Speaker 1: almost never mentioned. She's targeted more than anyone you could 641 00:36:05,880 --> 00:36:07,239 Speaker 1: think of. I think at a certain point she was 642 00:36:07,280 --> 00:36:11,560 Speaker 1: targeted more than Michelle Obama, but we don't talk about 643 00:36:11,560 --> 00:36:15,799 Speaker 1: that because of her specific status. But when the problem came, 644 00:36:16,200 --> 00:36:20,440 Speaker 1: the hammer came down on me. The hammer did not 645 00:36:20,520 --> 00:36:23,200 Speaker 1: come down on other folks. And there is no way 646 00:36:23,239 --> 00:36:27,000 Speaker 1: to aggregate these these decisions. And I had a another 647 00:36:27,120 --> 00:36:32,080 Speaker 1: friend who had become friendly with who experienced a similar 648 00:36:32,160 --> 00:36:35,719 Speaker 1: a similar thing, and had someone say, well, we're not 649 00:36:35,800 --> 00:36:43,560 Speaker 1: sure that happens to black women, and you're lying or 650 00:36:43,600 --> 00:36:52,360 Speaker 1: you're bad at your job, But also how much do 651 00:36:52,400 --> 00:36:54,520 Speaker 1: you want us to do? How do you get us 652 00:36:54,520 --> 00:36:56,399 Speaker 1: through if you're going to gaslight us at every turn, 653 00:36:56,760 --> 00:36:58,799 Speaker 1: if it always is something you kicked down the road 654 00:36:58,840 --> 00:37:00,960 Speaker 1: will get to what we'll get to it. And what 655 00:37:01,000 --> 00:37:03,239 Speaker 1: we're getting to is that black women are leaving these platforms. 656 00:37:03,960 --> 00:37:06,840 Speaker 1: Didn't Twitter. Twitter just had to pay eight hundred million 657 00:37:06,880 --> 00:37:10,279 Speaker 1: dollars to somebody, I think its own board because engagement 658 00:37:10,360 --> 00:37:13,520 Speaker 1: numbers were fludged, And I have a slightly more than 659 00:37:14,600 --> 00:37:16,560 Speaker 1: hunch that some of that has to do with how 660 00:37:16,640 --> 00:37:21,480 Speaker 1: badly they've moderated these racists and bots accounts versus the 661 00:37:21,480 --> 00:37:27,600 Speaker 1: actual content those people create. And you've gotta be you've 662 00:37:27,680 --> 00:37:30,360 Speaker 1: got to be willing to get better at the work. 663 00:37:31,560 --> 00:37:35,120 Speaker 1: And what I think is often the issue for some 664 00:37:35,239 --> 00:37:38,600 Speaker 1: things is that some people do not want to change. 665 00:37:38,760 --> 00:37:41,480 Speaker 1: They don't want to change. It is not to them. 666 00:37:41,560 --> 00:37:43,799 Speaker 1: Even with the Nazis in the streets, the fascist running 667 00:37:43,880 --> 00:37:47,040 Speaker 1: up and down, the planet on fire and a's still 668 00:37:47,120 --> 00:37:50,239 Speaker 1: in the middle of a pandemic, it's not serious enough 669 00:37:50,280 --> 00:37:53,040 Speaker 1: for them yet to change the way they do things. 670 00:37:55,960 --> 00:37:57,839 Speaker 1: And that is a hard thing to say, and it's 671 00:37:57,840 --> 00:38:02,880 Speaker 1: a hard thing to hear. But until there's an actual change, 672 00:38:03,080 --> 00:38:07,279 Speaker 1: I don't know that we can say anything different. And 673 00:38:07,400 --> 00:38:10,000 Speaker 1: for someone who if I was going back to the 674 00:38:10,120 --> 00:38:11,799 Speaker 1: loop de loop, I started with, but if I am 675 00:38:11,840 --> 00:38:15,680 Speaker 1: going to be a talk to a black woman I 676 00:38:15,719 --> 00:38:18,360 Speaker 1: care about online, the first thing I would tell you 677 00:38:18,520 --> 00:38:24,280 Speaker 1: is they have yet to make steps that are clear 678 00:38:24,360 --> 00:38:27,360 Speaker 1: for your protection. That's them problem, that's not you problem. 679 00:38:27,400 --> 00:38:31,480 Speaker 1: But I want to make sure that you are aware 680 00:38:31,520 --> 00:38:33,719 Speaker 1: of that. And that would be the thing, because my 681 00:38:33,719 --> 00:38:36,080 Speaker 1: first concern is going to be how you are doing, 682 00:38:36,280 --> 00:38:39,359 Speaker 1: not how the tech is doing in terms of like 683 00:38:39,400 --> 00:38:41,480 Speaker 1: what do I see before? One of the things I 684 00:38:41,600 --> 00:38:44,920 Speaker 1: really like about my job right now and the project 685 00:38:44,960 --> 00:38:48,760 Speaker 1: we're doing with Mozilla rally is it's starting to address 686 00:38:48,800 --> 00:38:51,120 Speaker 1: what I think is always the fundamental problem with these 687 00:38:51,120 --> 00:38:53,759 Speaker 1: things is how do you start getting information that people 688 00:38:53,760 --> 00:38:58,319 Speaker 1: can independently uh corroborate. How do you start getting that 689 00:38:58,480 --> 00:39:02,080 Speaker 1: kind of raw data that these platforms have been siloing 690 00:39:02,080 --> 00:39:04,719 Speaker 1: and keeping to themselves. How do you get people who 691 00:39:04,760 --> 00:39:07,359 Speaker 1: honestly want to have a good experience and will then 692 00:39:07,400 --> 00:39:10,240 Speaker 1: tell you that to be able to get some real contexts? 693 00:39:10,239 --> 00:39:12,279 Speaker 1: So when you tell me when you because some of 694 00:39:12,280 --> 00:39:15,000 Speaker 1: these studies we're working with we're working with Princeton, We're 695 00:39:15,000 --> 00:39:18,160 Speaker 1: working with Stanford, and we are going to be working 696 00:39:18,160 --> 00:39:19,839 Speaker 1: with the Markup and I'm very excited about that because 697 00:39:19,880 --> 00:39:24,640 Speaker 1: they do great work. But couple the data with talking 698 00:39:24,680 --> 00:39:27,480 Speaker 1: to people and asking, hey, how did you feel what 699 00:39:27,520 --> 00:39:29,960 Speaker 1: was going on when you saw this? And it's going 700 00:39:30,000 --> 00:39:32,640 Speaker 1: to be done with respect, It's going to be done 701 00:39:32,640 --> 00:39:35,880 Speaker 1: with transparency, and it's going to be done in ways 702 00:39:35,920 --> 00:39:39,320 Speaker 1: that are not directly under the people who have taken 703 00:39:39,360 --> 00:39:41,200 Speaker 1: so long to do right by you and still fail. 704 00:39:41,960 --> 00:39:45,680 Speaker 1: And I think that is what I am hoping more 705 00:39:46,719 --> 00:39:48,919 Speaker 1: works through, is that that we stopped making the idea 706 00:39:48,960 --> 00:39:52,399 Speaker 1: of people and things secondary at work, and we start 707 00:39:52,480 --> 00:39:56,440 Speaker 1: moving into the no. It is important to us that 708 00:39:56,520 --> 00:40:00,040 Speaker 1: we think about how people experience things. You know, I 709 00:40:01,560 --> 00:40:03,960 Speaker 1: love all of this. I one of the reasons why 710 00:40:04,000 --> 00:40:06,960 Speaker 1: I'm so interested in these conversations about how these online 711 00:40:06,960 --> 00:40:09,520 Speaker 1: spaces are moderated is because, you know, you talk about 712 00:40:09,560 --> 00:40:12,960 Speaker 1: women who are essentially pushed out of these spaces because 713 00:40:12,960 --> 00:40:15,680 Speaker 1: of this kind of harassment that just you don't see 714 00:40:15,719 --> 00:40:17,879 Speaker 1: it ever ending. And I was one of those women. 715 00:40:17,960 --> 00:40:20,040 Speaker 1: There was time in my life where I was a 716 00:40:20,200 --> 00:40:23,160 Speaker 1: very very avid redditor. I would like wake up, and 717 00:40:23,200 --> 00:40:26,920 Speaker 1: I was unpaid moderating all of these different spaces, and 718 00:40:27,760 --> 00:40:30,080 Speaker 1: you know, it was a big part of who I was. 719 00:40:30,120 --> 00:40:32,399 Speaker 1: It was a big part of like what made me me. 720 00:40:32,880 --> 00:40:35,320 Speaker 1: And if you've ever been on Reddit, you know sometimes 721 00:40:35,320 --> 00:40:37,920 Speaker 1: it's a place where you are going to be harassed. 722 00:40:38,120 --> 00:40:40,120 Speaker 1: Not just the black Ladies Subpreddit was one of the 723 00:40:40,160 --> 00:40:44,400 Speaker 1: most targeted reddits online up until like two thousand eighteen exactly. 724 00:40:44,880 --> 00:40:48,000 Speaker 1: And you know, I don't remember thinking so when it 725 00:40:48,080 --> 00:40:50,880 Speaker 1: was harassment. That wasn't just like they're saying I mean 726 00:40:50,960 --> 00:40:52,960 Speaker 1: things to me. It was like, I know where you live, 727 00:40:53,040 --> 00:40:54,719 Speaker 1: and it sounds like this person maybe doesn't know where 728 00:40:54,719 --> 00:40:57,839 Speaker 1: I live. I remember thinking, like, I've given so much 729 00:40:57,920 --> 00:41:01,080 Speaker 1: of my time and my energy and myself to this platform. 730 00:41:01,120 --> 00:41:03,560 Speaker 1: Certainly someone is going to hear me. Certainly when I 731 00:41:03,600 --> 00:41:06,720 Speaker 1: speak up, I will be listened to. I will be heard. 732 00:41:07,120 --> 00:41:09,520 Speaker 1: And when I realized that there was no one to 733 00:41:09,600 --> 00:41:11,560 Speaker 1: hear what I had to say, there was nowhere to 734 00:41:11,600 --> 00:41:14,839 Speaker 1: turn to, I realized it just wasn't worth it, and 735 00:41:14,880 --> 00:41:18,959 Speaker 1: so I checked out. I just I just logged off. 736 00:41:19,000 --> 00:41:21,719 Speaker 1: And so I think back to like how much that 737 00:41:21,800 --> 00:41:23,920 Speaker 1: how much those communities meant to me, How much those 738 00:41:23,920 --> 00:41:26,319 Speaker 1: spaces meant to me, and I just let them go 739 00:41:26,719 --> 00:41:30,520 Speaker 1: because every time I raised what I was experiencing that 740 00:41:30,560 --> 00:41:33,680 Speaker 1: some of this stuff was really scary, no one listened. 741 00:41:33,880 --> 00:41:35,480 Speaker 1: It was like I was shouting and to avoid. And 742 00:41:35,520 --> 00:41:37,960 Speaker 1: so I always think about all the women what it 743 00:41:38,000 --> 00:41:40,040 Speaker 1: feels like to go through this, what it feels like 744 00:41:40,120 --> 00:41:41,719 Speaker 1: to be on the other side of it, and what 745 00:41:41,800 --> 00:41:43,919 Speaker 1: it feels like to finally be like enough, this enough. 746 00:41:43,960 --> 00:41:46,360 Speaker 1: So I'm so happy that you talk about the actual 747 00:41:46,880 --> 00:41:50,239 Speaker 1: emotional experience of going through it, not just like as 748 00:41:50,280 --> 00:41:53,239 Speaker 1: a user, but as a person who experiences things. So 749 00:41:53,239 --> 00:41:56,480 Speaker 1: I'm gonna tell you something that I want to tell everybody, 750 00:41:56,680 --> 00:41:59,200 Speaker 1: and this is something that I have not learned, but 751 00:41:59,480 --> 00:42:03,759 Speaker 1: there would be helps. It is not your responsibility to 752 00:42:03,800 --> 00:42:06,959 Speaker 1: set yourself on fire so other people have warmth and heat. 753 00:42:11,000 --> 00:42:14,600 Speaker 1: You didn't just let it go, and don't like that 754 00:42:15,480 --> 00:42:19,799 Speaker 1: you were exposed to a level of abused, non response 755 00:42:20,160 --> 00:42:24,320 Speaker 1: and trauma because the things we are called and said 756 00:42:24,600 --> 00:42:29,560 Speaker 1: to us online are traumatic that ended up not being 757 00:42:29,680 --> 00:42:33,280 Speaker 1: worth the effort you put in. There is I don't 758 00:42:33,320 --> 00:42:36,080 Speaker 1: know why there there becomes like they feel like there's 759 00:42:36,120 --> 00:42:40,800 Speaker 1: often a belief that hard work must be terrorizing that 760 00:42:41,000 --> 00:42:42,800 Speaker 1: do not like because sometimes hard work starts. You just 761 00:42:42,800 --> 00:42:44,040 Speaker 1: gotta do the thing. You gotta do the rep, you 762 00:42:44,080 --> 00:42:46,640 Speaker 1: gotta do the you gotta do the project. But you 763 00:42:47,040 --> 00:42:52,719 Speaker 1: shouldn't have to be hazed to talk about your hair. 764 00:42:53,080 --> 00:42:55,120 Speaker 1: You shouldn't have to be hazed to talk about yourself 765 00:42:55,160 --> 00:42:58,440 Speaker 1: in a movie. And if you are, and it's against 766 00:42:58,480 --> 00:43:02,840 Speaker 1: their guidelines, there's someone's job for this to be done. 767 00:43:03,040 --> 00:43:05,280 Speaker 1: And it's also that the things to talk about moderation 768 00:43:05,360 --> 00:43:08,000 Speaker 1: is that even when moderation is done, most constant moderation 769 00:43:08,040 --> 00:43:12,080 Speaker 1: farms are formed off to usually women in the Philippines. 770 00:43:12,280 --> 00:43:14,440 Speaker 1: So we are hurting women of color coming and going 771 00:43:14,480 --> 00:43:17,000 Speaker 1: because not only are they reading our trauma, they're also 772 00:43:17,040 --> 00:43:20,120 Speaker 1: seeing the things we never see, which are assault videos 773 00:43:20,200 --> 00:43:24,600 Speaker 1: and um sorry, Chmale wrote about this, I think for 774 00:43:24,760 --> 00:43:29,000 Speaker 1: Vergin again five years ago, but we're getting all of 775 00:43:29,000 --> 00:43:32,360 Speaker 1: that and it's just like tapping out for what doesn't 776 00:43:32,440 --> 00:43:37,640 Speaker 1: serve you is a completely a normal human response, and 777 00:43:37,760 --> 00:43:42,080 Speaker 1: you're a human. And I remember specifically around Reddit because 778 00:43:42,760 --> 00:43:45,680 Speaker 1: like a gat sometimes spicy, but Alexis Ohani is like, 779 00:43:45,800 --> 00:43:48,839 Speaker 1: I don't understand what's this house is happening? Why are 780 00:43:48,840 --> 00:43:52,440 Speaker 1: people getting like this online. Sir, you were the president 781 00:43:52,640 --> 00:43:58,520 Speaker 1: and CEO of Reddit. Sir, I'm gonna need you to 782 00:43:58,600 --> 00:44:02,080 Speaker 1: give me more than a tweet. I'm going to need 783 00:44:02,280 --> 00:44:05,080 Speaker 1: to give you more me more than a wonderfully edit 784 00:44:05,120 --> 00:44:10,960 Speaker 1: podcast with the Rising Music. If you really want to 785 00:44:11,000 --> 00:44:13,920 Speaker 1: know how we got here, you're going to sit there. 786 00:44:14,000 --> 00:44:16,919 Speaker 1: You're going to sit down with some people and they're 787 00:44:16,960 --> 00:44:19,000 Speaker 1: not going to just be content creators. They're going to 788 00:44:19,040 --> 00:44:21,359 Speaker 1: be black designers. They're going to be black PhDs. They're 789 00:44:21,360 --> 00:44:23,480 Speaker 1: going to be black users, and they're going to be 790 00:44:24,280 --> 00:44:26,640 Speaker 1: queer users, and they're gonna be Asian users, and they're 791 00:44:26,640 --> 00:44:30,080 Speaker 1: gonna be Latin name users. And we're going to sit 792 00:44:30,120 --> 00:44:32,480 Speaker 1: down and actually go back, and we're going to make 793 00:44:32,520 --> 00:44:35,279 Speaker 1: some hard lines in the sand, and if we're not 794 00:44:35,320 --> 00:44:38,239 Speaker 1: going to back it up, what you're actually telling me 795 00:44:38,320 --> 00:44:41,759 Speaker 1: is you don't want to do this. And honestly, my 796 00:44:41,840 --> 00:44:44,440 Speaker 1: shocking opinion, it is fine that you don't want to 797 00:44:44,440 --> 00:44:47,160 Speaker 1: do this, But every moment you play in my face, 798 00:44:47,280 --> 00:44:49,520 Speaker 1: every moment you make a big decoration, every moment you 799 00:44:49,520 --> 00:44:52,160 Speaker 1: don't follow through, every moment we really want to meet 800 00:44:52,200 --> 00:44:54,560 Speaker 1: with you and dodge that call or you say that 801 00:44:54,600 --> 00:44:58,120 Speaker 1: you're doing a fellowship and it's thirty dollars less than 802 00:44:58,160 --> 00:45:01,400 Speaker 1: you pay the lowest paid person and who gets a job. 803 00:45:02,880 --> 00:45:06,920 Speaker 1: Every single time you do that, you sap energy from people. 804 00:45:07,360 --> 00:45:10,640 Speaker 1: You sap energy from movements, you sap people's and you 805 00:45:10,719 --> 00:45:13,880 Speaker 1: sap the energy for people to have good communities online. 806 00:45:14,320 --> 00:45:17,840 Speaker 1: And you don't have to do it to me personal, 807 00:45:18,320 --> 00:45:20,440 Speaker 1: even though it's been done to me personal for it 808 00:45:20,520 --> 00:45:23,680 Speaker 1: to matter to me, And if you don't want to change, 809 00:45:23,719 --> 00:45:26,760 Speaker 1: that's fine. But do not be surprised when you're connection 810 00:45:26,840 --> 00:45:28,960 Speaker 1: numbers go down. Don't be surprised when people find new 811 00:45:28,960 --> 00:45:31,799 Speaker 1: ways to do this, and don't be shocked when as 812 00:45:31,960 --> 00:45:35,120 Speaker 1: people who are against you. The thing that I cannot 813 00:45:35,239 --> 00:45:37,600 Speaker 1: buy buy is for all of these people who are 814 00:45:37,680 --> 00:45:40,960 Speaker 1: listening and pretending and caring but do not actually do 815 00:45:41,120 --> 00:45:43,960 Speaker 1: the work. At the end of the day, your user. 816 00:45:44,600 --> 00:45:46,879 Speaker 1: Those people want to have you to have a good 817 00:45:46,880 --> 00:45:48,919 Speaker 1: experience because they want to have a safe place to be. 818 00:45:49,080 --> 00:45:51,640 Speaker 1: The people who are the racist, the nazis, all of them. 819 00:45:51,800 --> 00:45:54,319 Speaker 1: They fundamentally don't want your platform to work. They don't 820 00:45:54,320 --> 00:45:56,120 Speaker 1: want your product to work, They don't want people to 821 00:45:56,160 --> 00:45:58,520 Speaker 1: be able to use it. They want you to fail. 822 00:45:59,320 --> 00:46:01,640 Speaker 1: Why are you focus on the people who want you 823 00:46:01,680 --> 00:46:03,279 Speaker 1: to fail more than you are focused on the people 824 00:46:03,280 --> 00:46:07,719 Speaker 1: who want you to win. And what social cues and 825 00:46:07,760 --> 00:46:11,000 Speaker 1: what social biases do you have that make this something 826 00:46:11,040 --> 00:46:15,480 Speaker 1: that you keep doing? Are you if you're and again, 827 00:46:15,520 --> 00:46:17,640 Speaker 1: we're not going to get past if you don't answer 828 00:46:17,680 --> 00:46:22,560 Speaker 1: that question. So I have a final question for you. 829 00:46:24,080 --> 00:46:26,680 Speaker 1: This is the question I usually end every interview with. 830 00:46:27,640 --> 00:46:30,280 Speaker 1: So we said all of this all of a sudden, 831 00:46:30,960 --> 00:46:33,319 Speaker 1: are you hopeful about the state of the internet and 832 00:46:33,360 --> 00:46:35,680 Speaker 1: technology when you look at where we are? Are you 833 00:46:35,760 --> 00:46:37,879 Speaker 1: hopeful for what's on the horizon? Do you think it's 834 00:46:37,920 --> 00:46:41,040 Speaker 1: better than where we are now or worse? I think 835 00:46:41,040 --> 00:46:46,279 Speaker 1: it's different, and I am I'm built to be hopeful. No, 836 00:46:47,040 --> 00:46:49,480 Speaker 1: my my mother, my mother used to sometimes says about me, 837 00:46:49,520 --> 00:46:51,800 Speaker 1: and I'm very very brilliant. I not sometimes very smart. 838 00:46:52,480 --> 00:46:57,800 Speaker 1: I've got more hope than sense. But I am hopeful 839 00:46:57,920 --> 00:47:01,839 Speaker 1: about technology because I'm hopeful of about people. That's part 840 00:47:01,840 --> 00:47:03,200 Speaker 1: of the reason why I'm drawn to the work I do. 841 00:47:03,239 --> 00:47:07,880 Speaker 1: I'm hopeful about people. Again, I say the analysis and 842 00:47:07,960 --> 00:47:11,680 Speaker 1: the things I see the young folks on TikTok to you, 843 00:47:12,080 --> 00:47:15,040 Speaker 1: Oh my god, I can't imagine I'm being hopeful when 844 00:47:15,040 --> 00:47:19,320 Speaker 1: you see someone reviving an ancient indigenous practice of throat 845 00:47:19,360 --> 00:47:22,040 Speaker 1: singing with their mother. How can you not be hopeful 846 00:47:23,000 --> 00:47:28,200 Speaker 1: when you see young queer kids be able to get help? 847 00:47:28,280 --> 00:47:31,279 Speaker 1: How how can you not be How can you not 848 00:47:31,440 --> 00:47:34,600 Speaker 1: be hopeful when someone teaches you how to magically get 849 00:47:34,640 --> 00:47:39,320 Speaker 1: curry stains out of a type of ware part. I'm Guyanese. 850 00:47:40,120 --> 00:47:42,080 Speaker 1: Actually I'm a hat, but I'm Guyanese. And you know 851 00:47:42,120 --> 00:47:44,319 Speaker 1: that that that's a mystical, magical thing. And you see 852 00:47:44,360 --> 00:47:48,760 Speaker 1: that someone can do that, you are I'm inexplicably hopeful 853 00:47:49,160 --> 00:47:51,160 Speaker 1: that you can see that in the streets. But I 854 00:47:51,200 --> 00:47:55,000 Speaker 1: also think that hope is not enough. I don't think 855 00:47:55,040 --> 00:47:58,359 Speaker 1: that there's I'm not excited by far away things. I'm 856 00:47:58,360 --> 00:48:00,960 Speaker 1: excited by the work that's being on and so many 857 00:48:00,960 --> 00:48:03,520 Speaker 1: people are showing up to do that work. But I 858 00:48:03,520 --> 00:48:08,080 Speaker 1: am also very very frightened because since that is common 859 00:48:08,120 --> 00:48:10,799 Speaker 1: with something that was given to me. Is how much 860 00:48:10,880 --> 00:48:14,319 Speaker 1: longer people will have the energy and the resources to 861 00:48:14,360 --> 00:48:18,040 Speaker 1: do that work is what scares me. And how committed 862 00:48:18,080 --> 00:48:23,000 Speaker 1: people are to actually redistributing, redistributing or revolutionizing so that 863 00:48:23,040 --> 00:48:25,239 Speaker 1: they can do the work, That's what scares me. But 864 00:48:25,360 --> 00:48:27,439 Speaker 1: what it comes down to, do I feel hope at all? 865 00:48:27,480 --> 00:48:30,160 Speaker 1: Of course, I get up and I got if. I 866 00:48:30,200 --> 00:48:32,200 Speaker 1: get up and I have something to do, and somebody 867 00:48:32,280 --> 00:48:34,799 Speaker 1: is saying that they are thinking about a thing, or 868 00:48:34,840 --> 00:48:37,200 Speaker 1: they've noticed a thing, and they still committed to making 869 00:48:37,200 --> 00:48:41,120 Speaker 1: a piece of art or making a piece of media, 870 00:48:41,280 --> 00:48:43,560 Speaker 1: or even a tweet that says this is important to me. 871 00:48:43,600 --> 00:48:45,760 Speaker 1: And I want the world to be slightly better. God, 872 00:48:45,800 --> 00:48:56,000 Speaker 1: I'm hopeful. I'm hopeful every day so that, Harry, we 873 00:48:56,120 --> 00:48:58,359 Speaker 1: are just about out of time. I have to thank 874 00:48:58,520 --> 00:49:00,239 Speaker 1: each and every one of you for being here. You 875 00:49:00,280 --> 00:49:01,879 Speaker 1: have no idea how much this means to me. Thank 876 00:49:01,920 --> 00:49:04,360 Speaker 1: you so much for leaning into this conversation. Thank you 877 00:49:04,400 --> 00:49:06,560 Speaker 1: again to Debt for being here. If you want to 878 00:49:06,560 --> 00:49:09,280 Speaker 1: hear more conversations like this, please tune into my podcast. 879 00:49:09,320 --> 00:49:10,920 Speaker 1: There are no girls on the internet. We would love 880 00:49:10,960 --> 00:49:14,320 Speaker 1: to have you. Um yes, thank you so much for coming. 881 00:49:15,160 --> 00:49:31,040 Speaker 1: Thank you so you're so good. Got a story about 882 00:49:31,040 --> 00:49:33,080 Speaker 1: an interesting thing in tech, or just want to say hi. 883 00:49:33,520 --> 00:49:35,800 Speaker 1: You can have me us at hello at tangdi dot com. 884 00:49:35,840 --> 00:49:38,240 Speaker 1: You can also find transcripts for today's episode at tangdi 885 00:49:38,320 --> 00:49:40,360 Speaker 1: dot com. There are no Girls on the Internet was 886 00:49:40,360 --> 00:49:42,759 Speaker 1: created by me bridget Todd. It's a production of I 887 00:49:42,800 --> 00:49:46,400 Speaker 1: heart Radio and Unboss creative Jonathan Strickland as our executive producer. 888 00:49:46,760 --> 00:49:50,080 Speaker 1: Ary Harrison is our producer and sound engineer. Michaelmato is 889 00:49:50,080 --> 00:49:53,640 Speaker 1: our contributing producer. I'm your host, bridget Todd. If you 890 00:49:53,640 --> 00:49:55,360 Speaker 1: want to help us grow, rate and review us on 891 00:49:55,400 --> 00:49:58,799 Speaker 1: Apple Podcasts. For more podcasts from I heart Radio, check 892 00:49:58,840 --> 00:50:01,000 Speaker 1: out the iHeart Radio app, Apple podcast or wherever you 893 00:50:01,040 --> 00:50:14,799 Speaker 1: get your podcasts. H m hm