1 00:00:00,400 --> 00:00:05,760 Speaker 1: People get fired up. You know, people are very you know, passionate. 2 00:00:06,080 --> 00:00:09,119 Speaker 1: When it comes to race, it matters race. So of 3 00:00:09,160 --> 00:00:13,400 Speaker 1: course if you see like people being denied access to buses, 4 00:00:13,840 --> 00:00:15,920 Speaker 1: you're like, you know, your first instant is like, what 5 00:00:16,000 --> 00:00:24,119 Speaker 1: the heck is going on? There are no girls on 6 00:00:24,120 --> 00:00:26,200 Speaker 1: the Internet. As a production of I Heart Radio and 7 00:00:26,280 --> 00:00:33,120 Speaker 1: Unbossed Creative, I'm Bridget Todd and this is there are 8 00:00:33,120 --> 00:00:38,640 Speaker 1: no girls on the Internet. At least sixties hundred thousand 9 00:00:38,640 --> 00:00:41,760 Speaker 1: people have fled Ukraine in the days following Russia's invasion, 10 00:00:42,000 --> 00:00:45,080 Speaker 1: according to The New York Times. Some of these include students, 11 00:00:45,120 --> 00:00:49,360 Speaker 1: are migrant workers from Africa, Asia or other regions. People 12 00:00:49,400 --> 00:00:53,000 Speaker 1: of color in Ukraine reported racist mistreatment as they tried 13 00:00:53,040 --> 00:00:56,240 Speaker 1: to leave the country. The United Nations has acknowledged that 14 00:00:56,320 --> 00:00:59,960 Speaker 1: non white refugees have faced racism while attempting to leave 15 00:01:00,040 --> 00:01:04,320 Speaker 1: the country. Videos flooded social media of people of color 16 00:01:04,360 --> 00:01:07,240 Speaker 1: being taken off buses, being shoved the back of lines 17 00:01:07,280 --> 00:01:11,080 Speaker 1: in favor of white Ukrainians, and being harassed by extremists 18 00:01:12,000 --> 00:01:15,240 Speaker 1: and in this moment a very real crisis and very 19 00:01:15,319 --> 00:01:19,880 Speaker 1: real fear. Bad actors are also exploiting their stories and 20 00:01:20,120 --> 00:01:24,759 Speaker 1: social media platforms to further cause chaos, confusion, and distrust. 21 00:01:25,720 --> 00:01:28,679 Speaker 1: It is a lot to unbraid. So I turned to 22 00:01:28,720 --> 00:01:32,960 Speaker 1: Christopher Boozy, CEO of BT Sentinel, a tool that helps 23 00:01:32,959 --> 00:01:38,000 Speaker 1: determine real people on Twitter from inauthentic accounts. So, you know, 24 00:01:38,200 --> 00:01:40,320 Speaker 1: I was reading a little bit about your background, about 25 00:01:40,360 --> 00:01:43,440 Speaker 1: how you initially fell in love with technology and computers. 26 00:01:43,680 --> 00:01:45,440 Speaker 1: Take me back, how did you How did you first 27 00:01:45,440 --> 00:01:48,200 Speaker 1: get involved with this kind of stuff. Oh it's simple. 28 00:01:48,320 --> 00:01:54,800 Speaker 1: My mother. Um, she she used to work for telephone company. Um, 29 00:01:54,840 --> 00:01:56,840 Speaker 1: you know, it's a rising now, but back then it 30 00:01:57,000 --> 00:01:59,520 Speaker 1: was I think nine Next or New York Tells, something 31 00:01:59,560 --> 00:02:02,880 Speaker 1: like that. And she worked with computers, so she knew 32 00:02:02,960 --> 00:02:06,480 Speaker 1: where computers were going before a lot of people, especially 33 00:02:06,480 --> 00:02:10,840 Speaker 1: in our community, UM, knew where computers were going. Um. 34 00:02:10,880 --> 00:02:15,840 Speaker 1: So for Christmas, she purchased me in a Mattel Aquarious computer. 35 00:02:16,880 --> 00:02:18,720 Speaker 1: You know, it was considered kind of like a toy, 36 00:02:18,800 --> 00:02:21,640 Speaker 1: but it was it was a computer, you know. Um, 37 00:02:21,680 --> 00:02:26,919 Speaker 1: it was basic and actually the language basic. And Um, 38 00:02:26,919 --> 00:02:29,880 Speaker 1: this this journey that I've been on, I tell people 39 00:02:29,919 --> 00:02:32,280 Speaker 1: all the time, it's really easy to say it started 40 00:02:32,320 --> 00:02:36,160 Speaker 1: with my mom. So Christopher's work determining bats from authentic 41 00:02:36,160 --> 00:02:40,600 Speaker 1: real accounts really came into sharper focus around the presidential election. 42 00:02:43,760 --> 00:02:46,440 Speaker 1: Presidential election in the United States was a really weird 43 00:02:46,480 --> 00:02:50,280 Speaker 1: time online. Bad actors use social media to create chaos 44 00:02:50,360 --> 00:02:54,040 Speaker 1: and confusion, and a Senate inquiry found that no group 45 00:02:54,120 --> 00:02:57,280 Speaker 1: was targeted for this kind of disinformation more than black folks. 46 00:02:58,040 --> 00:03:01,640 Speaker 1: Bad actors what you social media accounts pretending often times 47 00:03:01,680 --> 00:03:04,600 Speaker 1: pretty badly to be black. If you listen to our 48 00:03:04,639 --> 00:03:07,720 Speaker 1: episode last season most Saffiica Hudson, you know exactly what 49 00:03:07,760 --> 00:03:10,440 Speaker 1: I'm talking about. It just created a lot of distrust 50 00:03:10,560 --> 00:03:14,640 Speaker 1: and confusion, which ultimately was the entire point. This is 51 00:03:14,639 --> 00:03:17,240 Speaker 1: around the time when Christopher really started to see the 52 00:03:17,240 --> 00:03:20,400 Speaker 1: impact that these kinds of disinformation tactics had on our 53 00:03:20,440 --> 00:03:25,120 Speaker 1: ability to meaningfully connect online, especially for black folks. After 54 00:03:25,160 --> 00:03:30,760 Speaker 1: the election, we realized like, hey, there were these fake accounts, 55 00:03:31,480 --> 00:03:35,960 Speaker 1: uh that were influencing conversations that you know, we're also 56 00:03:36,080 --> 00:03:39,000 Speaker 1: being used to target people of color to try to 57 00:03:39,040 --> 00:03:44,280 Speaker 1: swathe them away from Hillary Clayton and the Democrats. Um yeah, 58 00:03:44,320 --> 00:03:47,400 Speaker 1: I realized like, hey, there's a huge problem here. And 59 00:03:47,440 --> 00:03:51,560 Speaker 1: then we started having people who were calling each other 60 00:03:51,640 --> 00:03:54,600 Speaker 1: bots like if they didn't agree with each other. So 61 00:03:54,920 --> 00:03:56,760 Speaker 1: you know, if you came to my you know, my 62 00:03:56,840 --> 00:04:00,880 Speaker 1: Twitter feed and you're like, you know, hey something whatever, 63 00:04:01,000 --> 00:04:02,440 Speaker 1: and then I'm just like, I don't agree with you. 64 00:04:02,520 --> 00:04:04,360 Speaker 1: Then someone jumps in, you know that this person is 65 00:04:04,400 --> 00:04:06,160 Speaker 1: a bot or that person is a bot, and I 66 00:04:06,200 --> 00:04:10,640 Speaker 1: just thought it wasn't productive and it was counter I 67 00:04:10,680 --> 00:04:14,160 Speaker 1: mean it just for what social media is and what 68 00:04:14,240 --> 00:04:16,520 Speaker 1: we are supposed to use it for. I just thought 69 00:04:16,640 --> 00:04:20,000 Speaker 1: by everyone calling each other about because we did not agree, 70 00:04:20,360 --> 00:04:23,320 Speaker 1: that that just was adding to the problem. So, you know, 71 00:04:23,360 --> 00:04:26,039 Speaker 1: I set out to try to create a platform to 72 00:04:26,080 --> 00:04:30,800 Speaker 1: allow people to be able to identify the real accounts 73 00:04:30,839 --> 00:04:32,920 Speaker 1: from the fake accounts, you know, because I really don't 74 00:04:32,960 --> 00:04:34,679 Speaker 1: even though the name of the company is bought Sineal, 75 00:04:34,800 --> 00:04:37,920 Speaker 1: I don't like using the term bot that much because 76 00:04:38,000 --> 00:04:41,919 Speaker 1: it has morphed over time. Um And a lot of 77 00:04:41,960 --> 00:04:45,480 Speaker 1: the accounts now that we see are not really bots 78 00:04:45,560 --> 00:04:49,240 Speaker 1: per se. They are more human controlled accounts. Um. So 79 00:04:49,320 --> 00:04:52,039 Speaker 1: we like to say in authentic accounts. So how do 80 00:04:52,080 --> 00:04:55,039 Speaker 1: you actually use machine learning to distinguish an authentic accounts 81 00:04:55,040 --> 00:05:00,200 Speaker 1: from authentic accounts? Back in twenty seventeen, started work being 82 00:05:00,200 --> 00:05:04,520 Speaker 1: on the platform, really started doing the research, and you know, 83 00:05:04,560 --> 00:05:06,960 Speaker 1: in the beginning hit a roadblock because it's like, okay, 84 00:05:07,560 --> 00:05:10,440 Speaker 1: you know when you when you create these models, these 85 00:05:10,640 --> 00:05:13,400 Speaker 1: machine learning models, you have to train it and you 86 00:05:13,520 --> 00:05:17,160 Speaker 1: have to give an examples of quote unquote what's a 87 00:05:17,200 --> 00:05:20,840 Speaker 1: good account versus a bad account. So you know, my 88 00:05:20,960 --> 00:05:23,960 Speaker 1: opinion of a good account may be different from your 89 00:05:23,960 --> 00:05:25,920 Speaker 1: your opinion, and you know, my opinion of a bad 90 00:05:25,960 --> 00:05:28,479 Speaker 1: account might be different from yours and so forth. So 91 00:05:28,640 --> 00:05:31,560 Speaker 1: what I consider good may not be with other people 92 00:05:31,720 --> 00:05:35,400 Speaker 1: consider good or bad. Uh So, what I ended up 93 00:05:35,440 --> 00:05:41,000 Speaker 1: doing was using Twitter's UM terms of service there there 94 00:05:41,040 --> 00:05:45,800 Speaker 1: there you know, rules, and that was the guide like 95 00:05:45,960 --> 00:05:49,719 Speaker 1: whatever they considered what's breaking the rules and you know whatever, 96 00:05:50,160 --> 00:05:53,440 Speaker 1: that's what I would use as the you know, the 97 00:05:53,520 --> 00:05:58,000 Speaker 1: roadmap or the map whatever UM. So then started looking 98 00:05:58,000 --> 00:06:00,400 Speaker 1: for accounts that were considered good and consider bad and 99 00:06:00,480 --> 00:06:02,800 Speaker 1: trained the model and and did this over time and 100 00:06:03,160 --> 00:06:05,520 Speaker 1: at the same time building out the platform, and then 101 00:06:05,560 --> 00:06:10,160 Speaker 1: in launched it UM And I mean, I don't want 102 00:06:10,200 --> 00:06:13,000 Speaker 1: to say it was an overnight success, but people, you know, 103 00:06:13,760 --> 00:06:16,680 Speaker 1: pretty much flocked to it because it was something that 104 00:06:16,760 --> 00:06:19,880 Speaker 1: people were really dying for, because they really wanted to 105 00:06:19,920 --> 00:06:23,000 Speaker 1: know who they were interacting with. So there were already 106 00:06:23,000 --> 00:06:25,679 Speaker 1: a few tools out there to determine if an account 107 00:06:25,680 --> 00:06:29,279 Speaker 1: online as a BOT or not, but Christopher wanted to 108 00:06:29,320 --> 00:06:32,480 Speaker 1: go further. There were a couple of other, um, you know, 109 00:06:32,600 --> 00:06:36,400 Speaker 1: platforms or similar products out there there, but you know, 110 00:06:36,560 --> 00:06:38,440 Speaker 1: the way that they were designed, they were designed to 111 00:06:38,480 --> 00:06:41,000 Speaker 1: pretty much say like bot or not, you know, kind 112 00:06:41,000 --> 00:06:43,640 Speaker 1: of like old days hot or not, bot or not. Yeah, 113 00:06:44,200 --> 00:06:47,240 Speaker 1: you know, And I thought that was bad because it's 114 00:06:47,279 --> 00:06:51,600 Speaker 1: it's it's not black and white, it really isn't. And 115 00:06:51,640 --> 00:06:54,479 Speaker 1: so my system was more like a credit you know, 116 00:06:54,640 --> 00:06:58,560 Speaker 1: score system, where you have accounts that are rated normal, 117 00:06:59,400 --> 00:07:04,520 Speaker 1: satisfied three, disruptive, and problematic, obviously problematic being the worst, 118 00:07:04,560 --> 00:07:07,520 Speaker 1: you know, obviously like the lease worst or whatever. And 119 00:07:07,560 --> 00:07:10,760 Speaker 1: so people understood that right away. So they were able 120 00:07:10,800 --> 00:07:14,000 Speaker 1: to look at those reports that are generating when you 121 00:07:14,000 --> 00:07:17,920 Speaker 1: analyze an account and they're like, okay, I get this, 122 00:07:18,120 --> 00:07:20,640 Speaker 1: understand it. So it's not just you know, bot or not. 123 00:07:21,120 --> 00:07:24,320 Speaker 1: You know, we have a range of different scores. I 124 00:07:24,320 --> 00:07:26,880 Speaker 1: have been called a bot before if I've said something 125 00:07:26,920 --> 00:07:29,040 Speaker 1: that people a lot of people didn't agree with. Um 126 00:07:29,040 --> 00:07:30,800 Speaker 1: it's one of the reasons I have my camera on 127 00:07:30,840 --> 00:07:32,280 Speaker 1: for this interview. I was like, I just want to 128 00:07:32,280 --> 00:07:34,320 Speaker 1: make sure that he knows that he's talking to it 129 00:07:34,520 --> 00:07:37,440 Speaker 1: an actual black human who exists in the world. Do 130 00:07:37,520 --> 00:07:40,600 Speaker 1: you just see somebody on Twitter who is just not 131 00:07:40,840 --> 00:07:44,520 Speaker 1: using the language correctly? Like obviously at your Twitter feed 132 00:07:44,560 --> 00:07:48,200 Speaker 1: today and someone said someone had a tweet that said, 133 00:07:48,640 --> 00:07:52,120 Speaker 1: any time a black goes against what they're supposed to 134 00:07:52,120 --> 00:07:55,240 Speaker 1: be doing or doesn't doesn't support the Democrats, y'all say 135 00:07:55,240 --> 00:07:59,080 Speaker 1: it's a bot. And I'm thinking, I don't know any 136 00:07:59,080 --> 00:08:02,360 Speaker 1: other black people who would refer to another black person 137 00:08:02,440 --> 00:08:04,800 Speaker 1: as a black That doesn't sound right to me. And 138 00:08:04,840 --> 00:08:08,280 Speaker 1: so it's interesting how before we just had these sort 139 00:08:08,280 --> 00:08:11,600 Speaker 1: of cultural cues or language cues to help us understand 140 00:08:11,600 --> 00:08:14,440 Speaker 1: if this person is actually, you know, the black human 141 00:08:14,480 --> 00:08:16,760 Speaker 1: that they're purport purporting to be, And now we have 142 00:08:16,880 --> 00:08:18,520 Speaker 1: this tool that can really put a little bit of 143 00:08:18,720 --> 00:08:22,760 Speaker 1: of of data behind it. This is actually a persistent 144 00:08:22,760 --> 00:08:25,920 Speaker 1: problem on social media people pretending to be someone they're not. 145 00:08:25,960 --> 00:08:30,640 Speaker 1: Online journalist Wanna Thompson popularized the term black fishing, when 146 00:08:30,680 --> 00:08:33,280 Speaker 1: someone who isn't really black pretends to be black on 147 00:08:33,320 --> 00:08:36,000 Speaker 1: social media. And it doesn't just stop at race. It 148 00:08:36,000 --> 00:08:38,840 Speaker 1: can be all kinds of things. For instance, people pretending 149 00:08:38,840 --> 00:08:42,760 Speaker 1: to be medical professionals or doctors to spread vaccine misinformation. 150 00:08:43,280 --> 00:08:46,600 Speaker 1: And this person that you're talking about, we called it 151 00:08:46,640 --> 00:08:52,600 Speaker 1: black fishing, when someone pretends to be black, creates an account, 152 00:08:53,440 --> 00:08:58,560 Speaker 1: uses a black photo, and they try to persuade other people, 153 00:08:58,800 --> 00:09:02,000 Speaker 1: you know, in the community to do things by saying 154 00:09:02,000 --> 00:09:04,840 Speaker 1: certain things. So they would say, for example, I don't 155 00:09:04,880 --> 00:09:07,720 Speaker 1: like Joe Biden. You know, he's not he hasn't done 156 00:09:07,760 --> 00:09:11,000 Speaker 1: anything for the black community. You know, me being a black, 157 00:09:15,800 --> 00:09:20,400 Speaker 1: I don't find him to you know, have my values 158 00:09:20,520 --> 00:09:24,360 Speaker 1: or whatever. Um. So anyone reading that will say, wait, 159 00:09:24,559 --> 00:09:27,959 Speaker 1: you know, is that a typeo you know? Or did 160 00:09:27,960 --> 00:09:31,720 Speaker 1: this person actually get it raw? Um? And that applies 161 00:09:31,760 --> 00:09:33,960 Speaker 1: to a lot of different things. That that applies to 162 00:09:34,080 --> 00:09:37,880 Speaker 1: people who are pretending to be doctors who are telling 163 00:09:37,920 --> 00:09:41,840 Speaker 1: people not to take the vaccine, and another doctor reading 164 00:09:42,000 --> 00:09:44,880 Speaker 1: some of what they're tweeting would say, this makes absolutely 165 00:09:44,920 --> 00:09:47,720 Speaker 1: no sense. So so maybe to you and I, uh, 166 00:09:47,920 --> 00:09:50,720 Speaker 1: not being doctors, who may not spot that right away, 167 00:09:51,160 --> 00:09:54,960 Speaker 1: but a professional you know that does this for a living, 168 00:09:55,000 --> 00:09:57,680 Speaker 1: would say, hey, what you said just makes absolutely no sense. 169 00:09:57,720 --> 00:10:01,160 Speaker 1: There's no way you're a doctor. So you know, so 170 00:10:01,240 --> 00:10:03,240 Speaker 1: the same applies to like you said, when you know, 171 00:10:03,760 --> 00:10:06,200 Speaker 1: unfortunately someone is trying to pretend like they're black, Black 172 00:10:06,240 --> 00:10:10,280 Speaker 1: fools can usually spot that right away. Yeah, and I 173 00:10:10,320 --> 00:10:14,839 Speaker 1: also think I completely agree, And I think you gave 174 00:10:14,840 --> 00:10:17,960 Speaker 1: people a way to have just better conversations on social 175 00:10:18,000 --> 00:10:20,719 Speaker 1: media because we probably all had that experience of your 176 00:10:20,720 --> 00:10:24,160 Speaker 1: talking to somebody on Twitter and eventually you're like, this 177 00:10:24,200 --> 00:10:26,200 Speaker 1: person is not worth my time, This person is not 178 00:10:26,240 --> 00:10:28,840 Speaker 1: worth having a conversation with. This person is not interested 179 00:10:28,880 --> 00:10:33,199 Speaker 1: in having a thoughtful conversation. And I think you're to 180 00:10:33,480 --> 00:10:37,640 Speaker 1: you what you've done has given people a better framework 181 00:10:37,679 --> 00:10:39,559 Speaker 1: for when it's like this person is not worth engaging. 182 00:10:39,600 --> 00:10:42,800 Speaker 1: This person is misrepresenting themselves. This person is misrepresenting the 183 00:10:42,880 --> 00:10:45,160 Speaker 1: situation that they're that they're claiming to be an expert 184 00:10:45,200 --> 00:10:47,760 Speaker 1: on or claiming to have experience with. You know, not 185 00:10:47,800 --> 00:10:50,600 Speaker 1: every not every person on social media is worth your 186 00:10:50,640 --> 00:10:52,480 Speaker 1: time or like the person that you should be trying 187 00:10:52,520 --> 00:10:56,560 Speaker 1: to have a real conversation with. Ultimately, Christopher wants to 188 00:10:56,600 --> 00:11:00,760 Speaker 1: help create better social media experiences, one where people, especially 189 00:11:00,760 --> 00:11:03,120 Speaker 1: women of color, who we know are so often targeted, 190 00:11:03,559 --> 00:11:06,680 Speaker 1: don't have to be subjected to constant harassment just to 191 00:11:06,720 --> 00:11:10,600 Speaker 1: show up online. But what's happened on Twitter. There's also 192 00:11:10,720 --> 00:11:15,280 Speaker 1: the targeted harassment side of things, where a lot of 193 00:11:15,320 --> 00:11:20,160 Speaker 1: these in authentic accounts, UM, they purposely go after people 194 00:11:20,240 --> 00:11:24,679 Speaker 1: that are either you know, supporting an individual or you know, 195 00:11:24,760 --> 00:11:27,760 Speaker 1: they're talking about climate change or you know, whatever the 196 00:11:27,800 --> 00:11:31,520 Speaker 1: issue may be. And we see that a lot with women, 197 00:11:32,200 --> 00:11:37,000 Speaker 1: especially women of color. UM. You know, we're doing a 198 00:11:37,080 --> 00:11:41,599 Speaker 1: study now, research now on Kamala Harris. UM. We previously 199 00:11:41,679 --> 00:11:47,600 Speaker 1: did something on Megan Markle, and women of color are 200 00:11:47,800 --> 00:11:49,960 Speaker 1: seemed to be like the prime target for a lot 201 00:11:50,000 --> 00:11:54,120 Speaker 1: of these accounts. So we started building out too to 202 00:11:54,160 --> 00:11:56,640 Speaker 1: help with that. You know, we have an order blocker 203 00:11:56,760 --> 00:12:00,520 Speaker 1: that blocks accounts not only based on the Bosom rating, 204 00:12:00,880 --> 00:12:05,560 Speaker 1: but also it could be tailored to the individual. Let's 205 00:12:05,600 --> 00:12:07,880 Speaker 1: just say there's an emoji that a lot of these 206 00:12:07,880 --> 00:12:11,000 Speaker 1: accounts are using. I can't think of something right this second, 207 00:12:11,000 --> 00:12:14,120 Speaker 1: but uh, if if you want, you can block accounts 208 00:12:14,120 --> 00:12:17,640 Speaker 1: that are using that specific emoji or even specific keywords 209 00:12:17,679 --> 00:12:20,600 Speaker 1: if you wanted to. UM, you can block accounts that 210 00:12:20,640 --> 00:12:23,920 Speaker 1: are just recently created because, as you know, a lot 211 00:12:23,960 --> 00:12:26,360 Speaker 1: of times when they're doing the swarming when they're attacking, 212 00:12:26,400 --> 00:12:28,760 Speaker 1: they will just go and create a bunch of accounts 213 00:12:28,800 --> 00:12:31,800 Speaker 1: like right away and then spam you and attack you 214 00:12:31,840 --> 00:12:35,520 Speaker 1: with that. So you can actually auto block accounts that 215 00:12:35,559 --> 00:12:38,320 Speaker 1: were just recently created or don't have a lot of 216 00:12:38,360 --> 00:12:40,439 Speaker 1: followers or not, you know whatever. I mean, it can 217 00:12:40,480 --> 00:12:44,360 Speaker 1: be literally tailored to your taste. Um, so we thought 218 00:12:44,440 --> 00:12:46,760 Speaker 1: that was a lot better than just people using generic 219 00:12:46,800 --> 00:12:50,520 Speaker 1: blocklists or you know, using other products that just block 220 00:12:50,720 --> 00:12:53,920 Speaker 1: based on a list. You know you're blocking it, so 221 00:12:54,000 --> 00:12:56,800 Speaker 1: I should you know, that doesn't really work. I mean, 222 00:12:57,040 --> 00:13:00,680 Speaker 1: we are trying to make the platform form a place 223 00:13:01,360 --> 00:13:03,920 Speaker 1: where people can feel safe, you know, that they can 224 00:13:04,000 --> 00:13:06,960 Speaker 1: use our tools to I don't know, have a better 225 00:13:07,040 --> 00:13:10,360 Speaker 1: experience on Twitter and then hopefully on other platforms as 226 00:13:10,440 --> 00:13:27,520 Speaker 1: following the future. Let's a quick break ut her back. 227 00:13:29,040 --> 00:13:32,600 Speaker 1: I was baking though, Fisher literally looked me my eye 228 00:13:32,600 --> 00:13:37,320 Speaker 1: and said, in his language only Ukrainians, that's all that 229 00:13:37,480 --> 00:13:42,640 Speaker 1: if you're black, you should walk. That's Jessica Arecpo, a 230 00:13:42,720 --> 00:13:46,640 Speaker 1: Nigerian medical student and one of the estimated sixteen thousand 231 00:13:46,679 --> 00:13:51,120 Speaker 1: African students living in Ukraine. Around twenty Indian students also 232 00:13:51,200 --> 00:13:54,800 Speaker 1: live in the country. As the invasion of Ukraine intensified 233 00:13:55,360 --> 00:13:58,880 Speaker 1: we solve reports of non white people in Ukraine struggling 234 00:13:58,880 --> 00:14:01,880 Speaker 1: to get out of the country. The hashtag Africans in 235 00:14:02,000 --> 00:14:05,200 Speaker 1: Ukraine was used to amplify stories of Africans being pulled 236 00:14:05,240 --> 00:14:08,200 Speaker 1: off trains and busses not being allowed to flee in 237 00:14:08,280 --> 00:14:13,160 Speaker 1: favor of white Ukrainians by Ukrainian authorities. Doctor Imbagwu, a 238 00:14:13,200 --> 00:14:15,920 Speaker 1: twenty four year old doctor from Nigeria who lived in 239 00:14:15,960 --> 00:14:19,240 Speaker 1: western Ukraine, told The New York Times the Ukrainian border 240 00:14:19,280 --> 00:14:21,920 Speaker 1: guards were not letting us through. They were beating people 241 00:14:22,000 --> 00:14:24,480 Speaker 1: up with sticks and tearing off their jackets. They would 242 00:14:24,480 --> 00:14:26,360 Speaker 1: slap them, they would beat them, they would push them 243 00:14:26,360 --> 00:14:28,760 Speaker 1: to the end of the queue. It was awful. So 244 00:14:28,840 --> 00:14:32,120 Speaker 1: I need to make this really clear. It is absolutely 245 00:14:32,160 --> 00:14:34,200 Speaker 1: true that the people of color in Ukraine are being 246 00:14:34,240 --> 00:14:37,960 Speaker 1: mistreated during an active invasion because of racism, and it's disgusting. 247 00:14:38,520 --> 00:14:41,560 Speaker 1: The High Commissioner for Refugees from the United Nations confirmed 248 00:14:41,600 --> 00:14:44,440 Speaker 1: this in a statement. And really, you don't even need 249 00:14:44,520 --> 00:14:46,600 Speaker 1: to look to stories from folks on the ground to 250 00:14:46,640 --> 00:14:48,840 Speaker 1: see the way that racism against non white people in 251 00:14:48,960 --> 00:14:52,160 Speaker 1: Ukraine is playing out. This isn't a place with all 252 00:14:52,240 --> 00:14:54,920 Speaker 1: due respect, you know, like at Rock or Afghanistan, it 253 00:14:55,000 --> 00:14:59,479 Speaker 1: has seen conflict raging for decades. This is a relatively 254 00:14:59,520 --> 00:15:02,920 Speaker 1: civiliz relatively European I have to choose those words carefully, 255 00:15:02,960 --> 00:15:05,480 Speaker 1: to city where you wouldn't expect that or hope that 256 00:15:05,560 --> 00:15:09,520 Speaker 1: it's going to happen. But this clear racism also reveals 257 00:15:09,520 --> 00:15:13,280 Speaker 1: a really important, yet difficult to contend with reality about 258 00:15:13,280 --> 00:15:17,600 Speaker 1: how disinformation works, That it's often rooted in actual truth, 259 00:15:18,840 --> 00:15:23,040 Speaker 1: and bad actors inflame legitimate tensions during already tense moments 260 00:15:23,080 --> 00:15:26,080 Speaker 1: like this to create chaos and confusion at a climate 261 00:15:26,120 --> 00:15:29,240 Speaker 1: where nobody knows what to believe. So, while it is 262 00:15:29,280 --> 00:15:32,440 Speaker 1: absolutely true that non white refugees in Ukraine are facing 263 00:15:32,440 --> 00:15:35,720 Speaker 1: disgusting racism as they try to flee, it's also true 264 00:15:35,760 --> 00:15:39,640 Speaker 1: that inauthentic accounts and bad actors are cruelly using their 265 00:15:39,680 --> 00:15:44,440 Speaker 1: stories to inflame racial tensions and deepen existing divisions. And 266 00:15:44,480 --> 00:15:46,680 Speaker 1: what's even more disgusting is that we have a digital 267 00:15:46,680 --> 00:15:49,280 Speaker 1: media landscape that makes it really easy for them to 268 00:15:49,320 --> 00:15:52,040 Speaker 1: do this. So what are you seeing in terms of 269 00:15:52,040 --> 00:15:55,760 Speaker 1: a conversation online with regard to black people in Ukraine. First, 270 00:15:55,800 --> 00:16:00,520 Speaker 1: I would like to say that yes, there were of 271 00:16:00,800 --> 00:16:02,720 Speaker 1: you know, of color, not just black people, know they 272 00:16:02,760 --> 00:16:06,840 Speaker 1: were there were you know, Indian people, Brazilians as well 273 00:16:07,560 --> 00:16:12,840 Speaker 1: who did Um, who did face some discrimination, I guess 274 00:16:12,920 --> 00:16:15,120 Speaker 1: is how you would say it, because they were not 275 00:16:15,200 --> 00:16:21,280 Speaker 1: allowed to board busses. Now, the the pushback to that was, well, 276 00:16:21,640 --> 00:16:26,000 Speaker 1: you know where they were going, Um, they were not 277 00:16:26,120 --> 00:16:28,520 Speaker 1: allowed to enter that they had to go into like 278 00:16:28,560 --> 00:16:31,800 Speaker 1: another country or something like that. UM. So like if 279 00:16:31,800 --> 00:16:34,360 Speaker 1: they were going trying to go into Poland, for example, 280 00:16:34,880 --> 00:16:38,800 Speaker 1: there were black folks who were denied access. So that's true. 281 00:16:39,440 --> 00:16:42,680 Speaker 1: And there were people that were not allowed on buses 282 00:16:42,760 --> 00:16:46,920 Speaker 1: or pulled off buses and stuff like that. UM. Now 283 00:16:47,200 --> 00:16:51,760 Speaker 1: you have accounts that are popping up all of a sudden, 284 00:16:52,280 --> 00:16:56,240 Speaker 1: newly created accounts claiming to be black that were saying 285 00:16:56,320 --> 00:17:00,720 Speaker 1: things that we could not verify. You know that videos 286 00:17:00,760 --> 00:17:03,960 Speaker 1: that were not even from Ukraine that people started you know, 287 00:17:04,000 --> 00:17:07,679 Speaker 1: sharing that stuff. And we can clearly see that a 288 00:17:07,720 --> 00:17:10,760 Speaker 1: lot of these accounts were fake, they were inauthentic, you know, 289 00:17:10,880 --> 00:17:15,600 Speaker 1: using our technology, UM looking at you know what exactly 290 00:17:15,640 --> 00:17:19,359 Speaker 1: these accounts are saying. Because some of these accounts were 291 00:17:19,480 --> 00:17:22,040 Speaker 1: just spamming the same thing over and over and over. 292 00:17:22,080 --> 00:17:25,600 Speaker 1: And over again, and that's a clear sign of platform manipulation. 293 00:17:27,080 --> 00:17:29,520 Speaker 1: It's so awful for so many reasons, but a big 294 00:17:29,520 --> 00:17:31,800 Speaker 1: one is that it creates a climate where the actual 295 00:17:31,880 --> 00:17:34,840 Speaker 1: people of color fleeing for their lives have to work 296 00:17:34,960 --> 00:17:37,960 Speaker 1: that much harder to amplify their stories in a media 297 00:17:38,080 --> 00:17:42,320 Speaker 1: landscape awash with confusion and in authentic discourse. Students sharing 298 00:17:42,440 --> 00:17:45,520 Speaker 1: videos about their experiences in Ukraine on social media began 299 00:17:45,640 --> 00:17:49,560 Speaker 1: timestamping their videos and adding exact location codes to demonstrate 300 00:17:49,560 --> 00:17:52,560 Speaker 1: that they were actually real and authentic, and the fact 301 00:17:52,600 --> 00:17:55,000 Speaker 1: that they would even need to do this just to 302 00:17:55,040 --> 00:17:59,119 Speaker 1: be heard demonstrates how badly tech platforms have failed to 303 00:17:59,160 --> 00:18:02,679 Speaker 1: create a landscape that people can meaningfully turn to for 304 00:18:02,760 --> 00:18:06,520 Speaker 1: sharing and receiving information during a time of real crisis, 305 00:18:06,560 --> 00:18:09,120 Speaker 1: because they have to compete with inauthentic accounts and bad 306 00:18:09,119 --> 00:18:13,440 Speaker 1: actors who are using their very real trauma to manipulate people. 307 00:18:14,640 --> 00:18:18,240 Speaker 1: It's a complex situation. And then pointing it out, Christopher 308 00:18:18,280 --> 00:18:21,959 Speaker 1: face criticism that he was invalidating the reality of racism 309 00:18:22,040 --> 00:18:25,480 Speaker 1: actually fased by non white people in Ukraine. But even 310 00:18:25,520 --> 00:18:29,520 Speaker 1: that reveals a tough point about combating disinformation. Bad actors 311 00:18:29,520 --> 00:18:33,400 Speaker 1: will seiz on, moments of crisis, intention to inflame legitimate 312 00:18:33,400 --> 00:18:36,800 Speaker 1: pressure points that already exist in our communities, the kinds 313 00:18:36,840 --> 00:18:39,680 Speaker 1: of sensitive or highly charged topics that can be difficult 314 00:18:39,720 --> 00:18:43,800 Speaker 1: to discuss. So you know, it's our job to report 315 00:18:43,840 --> 00:18:46,760 Speaker 1: the truth, you know, published the truth, whether it defends 316 00:18:46,800 --> 00:18:49,679 Speaker 1: someone or not. And that's what we did. And of 317 00:18:49,720 --> 00:18:51,919 Speaker 1: course there were people that were just like, oh, you know, 318 00:18:51,960 --> 00:18:54,960 Speaker 1: you're perpetrating this thing. Is if it's just propaganda, you know, 319 00:18:55,000 --> 00:18:57,760 Speaker 1: our people are being left to die, And you're like, no, 320 00:18:58,119 --> 00:19:00,919 Speaker 1: that's not what we're doing at all. We're not saying 321 00:19:00,960 --> 00:19:03,680 Speaker 1: that this is not actually happening on the ground. But 322 00:19:03,760 --> 00:19:07,280 Speaker 1: when you have accounts that are trying to sow division, 323 00:19:07,280 --> 00:19:09,720 Speaker 1: who start trying to sow discord, excuse me, who are 324 00:19:09,760 --> 00:19:12,720 Speaker 1: trying to divide people, who are trying to make you know, 325 00:19:12,760 --> 00:19:17,000 Speaker 1: people of color not supportive of a country because of 326 00:19:17,080 --> 00:19:20,840 Speaker 1: some incidents that happened. Um, I mean, look, let's let's 327 00:19:21,040 --> 00:19:24,160 Speaker 1: let's be honestly, let's be real. There's racism everywhere. There's 328 00:19:24,200 --> 00:19:26,959 Speaker 1: racism here in the United States. You know. Unfortunately, I 329 00:19:27,000 --> 00:19:29,439 Speaker 1: can walk down the street and get stopped by a 330 00:19:29,480 --> 00:19:31,720 Speaker 1: car and got bid. I can get shot just because 331 00:19:32,280 --> 00:19:36,159 Speaker 1: of the color of my skin. But going back to 332 00:19:36,200 --> 00:19:40,920 Speaker 1: the actual fake accounts, they were clearly trying to manipulate 333 00:19:41,560 --> 00:19:47,199 Speaker 1: and we see this all the time unfortunately on social media, 334 00:19:47,320 --> 00:19:52,959 Speaker 1: black folks or targeted a lot um because you know, 335 00:19:53,080 --> 00:19:56,840 Speaker 1: whether it's Black Lives Matter, whether it's elections, you know, 336 00:19:57,400 --> 00:20:01,119 Speaker 1: they feel as if we're easily manipulated because you know, 337 00:20:01,359 --> 00:20:05,680 Speaker 1: matters of race. People get fired up. You know, people 338 00:20:06,359 --> 00:20:10,280 Speaker 1: are very you know, passionate when it comes to race. 339 00:20:10,600 --> 00:20:13,280 Speaker 1: It matters of race. So of course if you see 340 00:20:13,320 --> 00:20:18,600 Speaker 1: like people being denied access to buses, you're like, you know, 341 00:20:18,640 --> 00:20:20,719 Speaker 1: your first instinct is like, what the heck is going on? 342 00:20:20,880 --> 00:20:23,080 Speaker 1: Like I'm supporting this country and now you're treating my 343 00:20:23,160 --> 00:20:27,040 Speaker 1: people like like garbage, like what's happening? And then it 344 00:20:27,080 --> 00:20:31,040 Speaker 1: goes viral And that's what state actors want. They want 345 00:20:31,080 --> 00:20:33,840 Speaker 1: that they want to muddy up the waters. You know, 346 00:20:33,920 --> 00:20:38,120 Speaker 1: they want you to not support this country, not support Ukraine, 347 00:20:38,760 --> 00:20:42,239 Speaker 1: so they will take a little snippet of truth and 348 00:20:42,280 --> 00:20:45,040 Speaker 1: make it seem like a whole entire country is filled 349 00:20:45,080 --> 00:20:48,520 Speaker 1: with Nazis and people who hate black folks, and that's 350 00:20:48,520 --> 00:20:51,760 Speaker 1: just not true. Are their races in Ukraine of course 351 00:20:51,800 --> 00:20:55,399 Speaker 1: there there are. I mean, I'm they're like I said, 352 00:20:55,800 --> 00:20:57,800 Speaker 1: I'm from the United States. They're they're a bunch of 353 00:20:57,840 --> 00:20:59,399 Speaker 1: races here, and they're a bunch of races in the 354 00:20:59,520 --> 00:21:02,439 Speaker 1: UK and there are a bunch of racists everywhere. But 355 00:21:02,520 --> 00:21:05,719 Speaker 1: that doesn't mean that the whole entire country is racist. 356 00:21:05,920 --> 00:21:08,560 Speaker 1: That doesn't mean that because these people were not allowed 357 00:21:08,560 --> 00:21:11,120 Speaker 1: on the you know, the buses are not allowed entry 358 00:21:11,119 --> 00:21:13,720 Speaker 1: into a country, that that was the policy of the 359 00:21:13,800 --> 00:21:17,159 Speaker 1: actual country itself. Um, And that's what we were just 360 00:21:17,200 --> 00:21:20,720 Speaker 1: trying to, uh, you know, to to to convey to 361 00:21:20,760 --> 00:21:24,360 Speaker 1: people that, hey, look, be really careful about what you're sharing. 362 00:21:24,960 --> 00:21:27,800 Speaker 1: You can be upset about what's happening in Ukraine, you 363 00:21:27,800 --> 00:21:30,560 Speaker 1: could be upset about people not being acts allowed access 364 00:21:30,560 --> 00:21:32,320 Speaker 1: to buses and stuff like that, but you can also 365 00:21:32,359 --> 00:21:37,520 Speaker 1: be vigilant and not help, you know, escalate this situation 366 00:21:37,560 --> 00:21:41,080 Speaker 1: on social media. Yeah, and I think that that really 367 00:21:41,119 --> 00:21:46,880 Speaker 1: exposes a truth about disinformation and bad actors that I 368 00:21:46,920 --> 00:21:48,679 Speaker 1: say a lot, but this was a time where I 369 00:21:48,720 --> 00:21:53,120 Speaker 1: really felt it. You know, bad actors they exploit our 370 00:21:53,240 --> 00:21:57,360 Speaker 1: legitimate tensions and traumas and triggers to manipulate us. And 371 00:21:57,440 --> 00:21:59,480 Speaker 1: I know that when I saw these videos of black 372 00:21:59,520 --> 00:22:02,560 Speaker 1: folks and other folks of color, you know, not being 373 00:22:02,640 --> 00:22:06,720 Speaker 1: let on busses and all of this chaos, it triggered 374 00:22:06,760 --> 00:22:08,560 Speaker 1: something in me like that is that is a tension 375 00:22:08,600 --> 00:22:12,800 Speaker 1: point within me personally. Disinformation tends to be rooted in 376 00:22:12,880 --> 00:22:16,600 Speaker 1: some kind of legitimate truth, right, and that bad actors 377 00:22:16,640 --> 00:22:20,480 Speaker 1: they exploit that, those tensions, those pressure points, They exploit 378 00:22:20,560 --> 00:22:23,199 Speaker 1: that within people to manipulate us. And I definitely felt it. 379 00:22:23,240 --> 00:22:27,240 Speaker 1: I had to stop myself from you know, quickly retweeting 380 00:22:27,240 --> 00:22:30,560 Speaker 1: and and amplifying videos just because they had caused a 381 00:22:30,880 --> 00:22:33,800 Speaker 1: kind of emotional response from me. And I think that's 382 00:22:33,800 --> 00:22:36,679 Speaker 1: something that we need to really be super clear on 383 00:22:36,840 --> 00:22:39,760 Speaker 1: that bad actors they're very savvy. They know how to 384 00:22:39,840 --> 00:22:43,080 Speaker 1: manipulate issues that get people fired up, and they they 385 00:22:43,080 --> 00:22:46,480 Speaker 1: definitely found my issue, and you know, I think that 386 00:22:47,040 --> 00:22:49,760 Speaker 1: being really aware of that is key, and then also 387 00:22:49,800 --> 00:22:53,440 Speaker 1: really knowing the historical precedent, because you're absolutely right. I 388 00:22:53,520 --> 00:22:55,320 Speaker 1: think that a lot of bad actors and people who 389 00:22:55,320 --> 00:22:59,320 Speaker 1: are pushing disinformation just see black the black community in 390 00:22:59,320 --> 00:23:02,960 Speaker 1: the United States as easy fodder for manipulation. You know, 391 00:23:03,040 --> 00:23:06,080 Speaker 1: we know that in the election, there was no group 392 00:23:06,200 --> 00:23:11,680 Speaker 1: targeted for Russian interference on social media to medal in 393 00:23:11,720 --> 00:23:14,080 Speaker 1: the election more than black folks in the United States. 394 00:23:14,080 --> 00:23:16,080 Speaker 1: We know that a Senate inquiry confirmed that, and so 395 00:23:16,280 --> 00:23:18,720 Speaker 1: we've got to keep in mind there is a historical 396 00:23:18,760 --> 00:23:23,080 Speaker 1: precedent for you know, people seeing us as easy targets 397 00:23:23,080 --> 00:23:25,920 Speaker 1: for manipulation along the basis of race, and that that 398 00:23:26,240 --> 00:23:30,280 Speaker 1: bad actors are going to exploit things that are legitimate concerns, 399 00:23:30,280 --> 00:23:33,840 Speaker 1: like there are is legitimate anti blackness and racism happening 400 00:23:33,840 --> 00:23:37,399 Speaker 1: in Ukraine. I am sure of it. However, it's not 401 00:23:37,560 --> 00:23:41,640 Speaker 1: negating that to also keep in mind, and bad actors 402 00:23:41,640 --> 00:23:47,360 Speaker 1: are going to exploit that truth to try to manipulate us. Absolutely. 403 00:23:48,000 --> 00:23:51,000 Speaker 1: I mean, you're preaching to the choir here, um. And 404 00:23:51,040 --> 00:23:53,760 Speaker 1: that's what we try to We try to educate not 405 00:23:53,920 --> 00:23:58,280 Speaker 1: only know the black community, but we also try to educate, 406 00:23:58,320 --> 00:24:00,320 Speaker 1: you know, the white community as well, to let them 407 00:24:00,400 --> 00:24:04,080 Speaker 1: understand what's happening. Because still people don't realize even I 408 00:24:04,119 --> 00:24:08,080 Speaker 1: mean it's been several years now, don't realize just how 409 00:24:08,200 --> 00:24:12,600 Speaker 1: much platform manipulation is happening. They don't realize how much 410 00:24:12,640 --> 00:24:16,480 Speaker 1: targeted harassment is happening. Um. So that's why I try 411 00:24:16,520 --> 00:24:20,680 Speaker 1: to use my Twitter account as a teaching tool. UM. 412 00:24:21,400 --> 00:24:24,359 Speaker 1: And you know, whether it's you know, a celebrity that's 413 00:24:24,440 --> 00:24:27,520 Speaker 1: being attacked or an organization that's being attacked, you know, 414 00:24:27,720 --> 00:24:32,280 Speaker 1: I try to kind of rip the scab off and 415 00:24:32,280 --> 00:24:35,560 Speaker 1: and and and let people see because sometimes, you know, 416 00:24:35,760 --> 00:24:38,360 Speaker 1: I would have people ask like why are you amplifying this? 417 00:24:38,480 --> 00:24:42,200 Speaker 1: You know, and it's like the only way we're gonna 418 00:24:42,320 --> 00:24:44,520 Speaker 1: educate people, and and and the only way we're gonna 419 00:24:44,560 --> 00:24:48,520 Speaker 1: fix this is by educating people is showing them and 420 00:24:48,560 --> 00:24:52,000 Speaker 1: giving them a window into what's happening. Because a lot 421 00:24:52,040 --> 00:24:55,399 Speaker 1: of a lot of the researchers UM in my field 422 00:24:55,400 --> 00:24:57,440 Speaker 1: that do this, like a lot of times if they 423 00:24:57,480 --> 00:25:00,480 Speaker 1: publish a report, they don't even know publish the list 424 00:25:00,520 --> 00:25:04,800 Speaker 1: of accounts. We don't do that. We publish everything because 425 00:25:04,840 --> 00:25:09,800 Speaker 1: we want people to understand what's happening. So whether you know, 426 00:25:09,840 --> 00:25:13,639 Speaker 1: we are showing you know, pages of tweets, you know, 427 00:25:13,760 --> 00:25:18,520 Speaker 1: the accounts themselves. UM, we want people to be educated. 428 00:25:19,119 --> 00:25:21,320 Speaker 1: And you know, I'm asked all the time like how 429 00:25:21,320 --> 00:25:23,119 Speaker 1: are we going to fix this problem? And I'm like, 430 00:25:23,119 --> 00:25:29,520 Speaker 1: critical thinking is key here, UM, rethinking how we teach 431 00:25:29,600 --> 00:25:33,960 Speaker 1: our kids about you know, social media and and and 432 00:25:34,000 --> 00:25:38,120 Speaker 1: looking for you know, like, for example, if someone posts 433 00:25:38,119 --> 00:25:42,919 Speaker 1: something um and you're not you're not sure it's it's legitimate, 434 00:25:43,520 --> 00:25:46,400 Speaker 1: teaching our kids to research and find out if that's 435 00:25:46,440 --> 00:25:49,280 Speaker 1: you know, legitimate, taking just five minutes and trying to 436 00:25:49,320 --> 00:25:54,080 Speaker 1: find you know, other sources for this particular story. And 437 00:25:54,080 --> 00:25:55,760 Speaker 1: and I'm I'm gonna tell you right now, I have 438 00:25:55,880 --> 00:26:02,160 Speaker 1: seen journalists. These are professionals who retweet stories that are 439 00:26:02,200 --> 00:26:05,560 Speaker 1: completely fake. And I still, you know, it happened a 440 00:26:05,600 --> 00:26:11,720 Speaker 1: lot in and it's still happening in. Yeah. I mean 441 00:26:11,920 --> 00:26:15,320 Speaker 1: I have been guilty of it. I have to admit, 442 00:26:15,440 --> 00:26:18,200 Speaker 1: and and and I've been guilty of it before I 443 00:26:18,280 --> 00:26:20,720 Speaker 1: knew a lot about how this stuff works. Now, when 444 00:26:20,760 --> 00:26:23,359 Speaker 1: I see a story, I kind of have my bullshit 445 00:26:23,400 --> 00:26:24,920 Speaker 1: detect her up. There are a couple of things where 446 00:26:24,920 --> 00:26:26,840 Speaker 1: I'm like, oh, I don't know, a story that just 447 00:26:26,880 --> 00:26:32,760 Speaker 1: seems a little like a little too I kind of 448 00:26:32,800 --> 00:26:36,160 Speaker 1: put this. When I see a story that seems taylor 449 00:26:36,280 --> 00:26:38,800 Speaker 1: made for someone like me to share it, it almost 450 00:26:38,800 --> 00:26:43,399 Speaker 1: seems like it was crafted specifically for virality, my bullshit 451 00:26:43,440 --> 00:26:44,840 Speaker 1: detector goes up. Or I'm like, oh, this is just 452 00:26:44,880 --> 00:26:48,800 Speaker 1: a little too convenient that everything that that would prompt 453 00:26:48,840 --> 00:26:51,960 Speaker 1: someone like me to share is there. And so I 454 00:26:53,000 --> 00:26:55,840 Speaker 1: have gotten a lot smarter about that kind of thing now. 455 00:26:56,080 --> 00:26:58,040 Speaker 1: But a few years ago, I don't think we were 456 00:26:58,080 --> 00:27:01,639 Speaker 1: having conversations about, like, it's good to check you know, 457 00:27:01,800 --> 00:27:04,560 Speaker 1: your sources, check your sources. It's good to like verify 458 00:27:04,840 --> 00:27:07,679 Speaker 1: if something seems a little fishy to you, maybe google it. 459 00:27:07,880 --> 00:27:10,000 Speaker 1: You know, I don't think we were having conversations about 460 00:27:10,040 --> 00:27:12,760 Speaker 1: the importance of that kind of literacy online even just 461 00:27:12,800 --> 00:27:16,520 Speaker 1: a few years ago. We were not. We were and 462 00:27:16,520 --> 00:27:18,880 Speaker 1: and and it's good to see that we are having 463 00:27:18,880 --> 00:27:25,119 Speaker 1: those conversations. Um. You know, I look, one company can't 464 00:27:25,160 --> 00:27:26,880 Speaker 1: do it all, you know, I would love to see 465 00:27:26,880 --> 00:27:29,800 Speaker 1: more companies come into this space and be public about it, 466 00:27:29,800 --> 00:27:33,119 Speaker 1: because there are there are some companies that work for 467 00:27:33,160 --> 00:27:36,359 Speaker 1: like campaigns, UM and they do things behind the scenes, 468 00:27:37,040 --> 00:27:40,879 Speaker 1: and that's not helping. It really isn't. Because yes, you know, 469 00:27:40,960 --> 00:27:43,840 Speaker 1: it's good to like, if there's a campaign and there's 470 00:27:43,840 --> 00:27:49,000 Speaker 1: someone putting out disinformation, someone is helping to mitigate that disinformation. 471 00:27:49,359 --> 00:27:52,679 Speaker 1: But we need we need more people doing this publicly. 472 00:27:53,200 --> 00:27:56,320 Speaker 1: You know, we need workshops, We need people to understand, 473 00:27:56,520 --> 00:27:59,439 Speaker 1: like you said like, hey, check other sources. Um, we 474 00:27:59,600 --> 00:28:03,040 Speaker 1: wasn't have that conversation a few years ago. Hey, you know, 475 00:28:04,280 --> 00:28:07,480 Speaker 1: look at who you're engaging with, Look at who you're amplifying. 476 00:28:07,680 --> 00:28:10,679 Speaker 1: Is this person a state actor? Because there are there 477 00:28:10,720 --> 00:28:15,240 Speaker 1: are accounts that you know, fly under the wire for months, 478 00:28:15,240 --> 00:28:19,840 Speaker 1: sometimes years that are you know, they are fake and 479 00:28:19,880 --> 00:28:23,760 Speaker 1: they are state sponsored accounts, and they're just helping to 480 00:28:24,560 --> 00:28:27,200 Speaker 1: you know, whatever it may be, you know, whether it's 481 00:28:27,240 --> 00:28:30,520 Speaker 1: trying to help Republicans or trying to you know, pretend 482 00:28:30,560 --> 00:28:33,120 Speaker 1: like they are Democrats in the beginning and then kind 483 00:28:33,119 --> 00:28:35,080 Speaker 1: of switch up and say, oh, you know, I'm no 484 00:28:35,160 --> 00:28:38,920 Speaker 1: longer supporting the Democrats because of X, Y and c um. 485 00:28:38,960 --> 00:28:41,960 Speaker 1: You know, we see that a lot. So, you know, 486 00:28:42,080 --> 00:28:45,160 Speaker 1: I just think, I just think that as a society, 487 00:28:44,880 --> 00:28:53,920 Speaker 1: we need to start having these conversations more. After a break, 488 00:29:04,120 --> 00:29:07,880 Speaker 1: let's get right back into it. You really reveal something 489 00:29:07,920 --> 00:29:11,840 Speaker 1: about why I get so fired up about things like 490 00:29:11,920 --> 00:29:15,360 Speaker 1: in authentic accounts and disinformation is because we're not really 491 00:29:15,400 --> 00:29:18,960 Speaker 1: able to have we're not really able to view social 492 00:29:19,000 --> 00:29:23,960 Speaker 1: media to have the authentic, thoughtful, accurate, substitutive conversations that 493 00:29:24,000 --> 00:29:26,360 Speaker 1: we need to be happy and so I'm a black person. 494 00:29:26,520 --> 00:29:30,760 Speaker 1: I care deeply about the treatment of black folks, folks 495 00:29:30,800 --> 00:29:33,800 Speaker 1: of color, marginalized people, both here in the United States 496 00:29:33,840 --> 00:29:36,120 Speaker 1: and around the globe. That is something that I care 497 00:29:36,520 --> 00:29:39,320 Speaker 1: deep like my my entire life is about that. And 498 00:29:39,920 --> 00:29:42,800 Speaker 1: I am not able right now to have a conversation 499 00:29:42,960 --> 00:29:47,720 Speaker 1: on our largest social media platforms about the status of 500 00:29:47,880 --> 00:29:50,600 Speaker 1: the folks that I care about my own community around 501 00:29:50,600 --> 00:29:54,520 Speaker 1: the globe because of bad actors and disinformation. It's like, 502 00:29:55,080 --> 00:29:56,760 Speaker 1: and so I think that that's the thing I always 503 00:29:56,800 --> 00:29:59,920 Speaker 1: hit on, is that what we what what we all 504 00:30:00,160 --> 00:30:03,280 Speaker 1: was out on, is having a media ecosystem where the 505 00:30:03,320 --> 00:30:06,120 Speaker 1: conversations that we need to be having critically are are 506 00:30:06,200 --> 00:30:08,520 Speaker 1: able to be had. We don't have that right now. 507 00:30:08,720 --> 00:30:11,960 Speaker 1: You know if even you, like I see the pushback 508 00:30:12,040 --> 00:30:14,080 Speaker 1: that you get trying to make this point of like, 509 00:30:14,200 --> 00:30:17,320 Speaker 1: yes there is racism happening in Ukraine, of course, and 510 00:30:17,480 --> 00:30:20,720 Speaker 1: yes there are state actors trying to manipulate how we 511 00:30:20,800 --> 00:30:25,320 Speaker 1: respond to it. And people will respond to you saying like, oh, 512 00:30:25,400 --> 00:30:28,520 Speaker 1: you're negating racism or you're saying racism doesn't exist, and 513 00:30:28,800 --> 00:30:32,040 Speaker 1: it just goes to show that we are losing out 514 00:30:32,160 --> 00:30:37,320 Speaker 1: on having a media a digital media ecosystem where we 515 00:30:37,320 --> 00:30:40,000 Speaker 1: can have these conversations and where we can actually move 516 00:30:40,120 --> 00:30:43,600 Speaker 1: forward on these issues that are so critically important. Right, 517 00:30:44,200 --> 00:30:47,160 Speaker 1: I just want to get this in there. Mean, first thing, 518 00:30:47,200 --> 00:30:51,120 Speaker 1: we need legislation too. We we definitely and I hate 519 00:30:51,120 --> 00:30:54,200 Speaker 1: to say this, but we're going to need legislation to 520 00:30:54,760 --> 00:31:00,200 Speaker 1: help us. Um kind of you know, when this war, 521 00:31:00,240 --> 00:31:04,560 Speaker 1: because that's what we're in now. We're in a disinformation war. Um, 522 00:31:04,600 --> 00:31:07,400 Speaker 1: and the bad guys, I hate to say this, are winning. 523 00:31:07,960 --> 00:31:13,560 Speaker 1: They really are because it's really easy, really really easy 524 00:31:13,680 --> 00:31:17,720 Speaker 1: to you know, to have platform manipulation. It's really easy 525 00:31:17,760 --> 00:31:22,480 Speaker 1: to change opinions on social media. People do not understand 526 00:31:23,040 --> 00:31:27,200 Speaker 1: just how easy it is because something you said, Um, 527 00:31:27,360 --> 00:31:29,280 Speaker 1: you know, like I look at this tweet and it 528 00:31:29,320 --> 00:31:34,240 Speaker 1: almost seems like it's tailored for me. Man, it is, 529 00:31:34,960 --> 00:31:39,560 Speaker 1: it is. It is really easy. And I've done this experiment. 530 00:31:39,800 --> 00:31:43,440 Speaker 1: I've actually done this experiment. It's really easy to craft 531 00:31:43,480 --> 00:31:47,360 Speaker 1: a tweet to make it go viral. It's really easy 532 00:31:47,400 --> 00:31:52,760 Speaker 1: to craft a tweet to sparking emotion in a certain group. Um, 533 00:31:52,840 --> 00:31:56,160 Speaker 1: whether you are l g B t Q plus, whether 534 00:31:56,200 --> 00:31:58,440 Speaker 1: you are black, whether you're a woman, whether you're a male, 535 00:31:58,520 --> 00:32:02,080 Speaker 1: whether you're an insult I don't what you are. If 536 00:32:02,120 --> 00:32:05,560 Speaker 1: there are ways that you can craft tweets and if 537 00:32:05,600 --> 00:32:07,640 Speaker 1: you do it the right time, at the right time 538 00:32:08,160 --> 00:32:11,640 Speaker 1: of the day, and you use the certain keywords, it's 539 00:32:11,680 --> 00:32:15,480 Speaker 1: going to go viral. Okay, almost every single time, it's 540 00:32:15,520 --> 00:32:18,840 Speaker 1: going to go viral. Um. It's no different than marketing. 541 00:32:19,320 --> 00:32:21,760 Speaker 1: And there are there are people that are getting paid 542 00:32:21,800 --> 00:32:24,960 Speaker 1: a lot of money. Uh, you know, they're they're bad 543 00:32:25,000 --> 00:32:29,000 Speaker 1: actors to figure out ways of doing these things, and 544 00:32:29,040 --> 00:32:31,800 Speaker 1: you know, they have their systems on how to make 545 00:32:31,840 --> 00:32:34,800 Speaker 1: things go viral. How to you know, to manipulate this 546 00:32:34,920 --> 00:32:38,520 Speaker 1: group of people to do x y and z um. 547 00:32:38,560 --> 00:32:42,840 Speaker 1: So we need legislation number one UM to kind of 548 00:32:43,360 --> 00:32:45,600 Speaker 1: you know, I don't. I don't agree with this, this 549 00:32:45,640 --> 00:32:49,600 Speaker 1: whole thing that like everyone needs to be verified because 550 00:32:49,640 --> 00:32:53,560 Speaker 1: there are legitimate reasons why someone would not want to 551 00:32:53,600 --> 00:32:58,360 Speaker 1: be verified. So I'm actually not against anonymous accounts. However, 552 00:32:58,520 --> 00:33:03,680 Speaker 1: I am against accounts that are tending to be something else. So, 553 00:33:04,200 --> 00:33:09,760 Speaker 1: you know, legislation, for example, preventing people from creating accounts 554 00:33:09,800 --> 00:33:12,680 Speaker 1: for the sole purpose of platform manipulation could be one thing. 555 00:33:12,960 --> 00:33:16,400 Speaker 1: Because don't be mistaken, it's not just happening in Russia 556 00:33:16,640 --> 00:33:19,320 Speaker 1: or you know, some other far off place. You have 557 00:33:19,920 --> 00:33:23,600 Speaker 1: people here in the United States, groups of people that 558 00:33:23,680 --> 00:33:27,600 Speaker 1: are creating fake accounts to manipulate whether it's you know, 559 00:33:27,640 --> 00:33:30,840 Speaker 1: regarding elections, whether it's white supremacists that are trying to 560 00:33:31,000 --> 00:33:33,800 Speaker 1: so discord within the black community, whatever it may be. 561 00:33:34,120 --> 00:33:37,160 Speaker 1: So that should be illegal number one. Um. And then 562 00:33:37,200 --> 00:33:42,200 Speaker 1: the other thing is making platforms do more because they're 563 00:33:42,240 --> 00:33:45,240 Speaker 1: just doing the bear the bear minimum And we all 564 00:33:45,240 --> 00:33:47,960 Speaker 1: know this, anyone that's been on social media, you know, 565 00:33:48,440 --> 00:33:53,000 Speaker 1: for the past month, maybe um know that the platforms 566 00:33:53,000 --> 00:33:56,520 Speaker 1: are not doing enough. Um, So there needs to be 567 00:33:56,600 --> 00:34:00,160 Speaker 1: legislation to kind of force them to do more or 568 00:34:00,840 --> 00:34:03,920 Speaker 1: because why would they you know, why would Twitter, for example, 569 00:34:04,000 --> 00:34:08,080 Speaker 1: remove ten thousand accounts when they don't have to, because 570 00:34:08,120 --> 00:34:11,360 Speaker 1: that's money for them. When you think about the state 571 00:34:11,560 --> 00:34:16,160 Speaker 1: of our our media landscape, are you hopeful, like, like, 572 00:34:16,440 --> 00:34:18,560 Speaker 1: do you think it's a lost cause? Do you think 573 00:34:19,160 --> 00:34:20,920 Speaker 1: you know, it's just such a cess pool and these 574 00:34:20,920 --> 00:34:22,799 Speaker 1: platforms are going to do anything and we're never gonna 575 00:34:22,840 --> 00:34:27,160 Speaker 1: get useful legislation or are you hopeful that we'll get 576 00:34:27,160 --> 00:34:34,799 Speaker 1: somewhere to make it possible to have meaningful subset of change. Right. Um, 577 00:34:34,840 --> 00:34:37,000 Speaker 1: I think it's going to take a big event, a 578 00:34:37,000 --> 00:34:40,520 Speaker 1: big event, you know, maybe like a terrorist attack where 579 00:34:40,920 --> 00:34:46,120 Speaker 1: and I always give this this example. There's really nothing 580 00:34:46,280 --> 00:34:53,560 Speaker 1: stopping someone right now from using social media to to two. Say, 581 00:34:53,640 --> 00:34:58,480 Speaker 1: for example, I'm gonna give you an example here. Um, 582 00:34:58,680 --> 00:35:07,560 Speaker 1: let's say someone goes and they say, hey, yo, let's 583 00:35:07,560 --> 00:35:10,080 Speaker 1: get a group of people. We're gonna we're going to 584 00:35:11,120 --> 00:35:14,520 Speaker 1: make it look like that there are a bunch of 585 00:35:14,680 --> 00:35:18,439 Speaker 1: black folks that are going around New York City and 586 00:35:18,560 --> 00:35:23,200 Speaker 1: just stabbing people. And they go on social media and 587 00:35:23,239 --> 00:35:26,000 Speaker 1: they start posting this stuff, and you know, they even 588 00:35:26,040 --> 00:35:30,640 Speaker 1: have videos of black folks stabbing people. Now you got 589 00:35:31,440 --> 00:35:34,279 Speaker 1: but a bunch of Caucasian white folks. They're like, oh 590 00:35:34,280 --> 00:35:36,720 Speaker 1: my god, there are black folks that are going around 591 00:35:36,719 --> 00:35:40,000 Speaker 1: New York and they are stabbing people, you know, and 592 00:35:40,040 --> 00:35:42,239 Speaker 1: now they're walking down the street and they're nervous, and 593 00:35:42,360 --> 00:35:44,520 Speaker 1: all of this is a hoax. This whole entire thing 594 00:35:44,600 --> 00:35:48,160 Speaker 1: is a hoax. But it's going viral. It's going viral 595 00:35:48,160 --> 00:35:50,400 Speaker 1: on Twitter, it's going viral on Facebook, it's going viral, 596 00:35:50,440 --> 00:35:54,759 Speaker 1: and it's everywhere and it's all fake. I can tell 597 00:35:54,800 --> 00:35:58,760 Speaker 1: you right now. There's nothing stopping this from happening right now. Um, 598 00:35:58,800 --> 00:36:03,120 Speaker 1: because the platforms like Twitter and and and and they do, 599 00:36:03,719 --> 00:36:05,799 Speaker 1: you know, like when stuff starts to get out of hand, 600 00:36:05,840 --> 00:36:09,520 Speaker 1: they do take action, but they take action too late. Um, 601 00:36:09,640 --> 00:36:12,040 Speaker 1: so you may have an hour or two that goes 602 00:36:12,320 --> 00:36:15,239 Speaker 1: on before you know, goes by excuse me, before they 603 00:36:15,239 --> 00:36:18,640 Speaker 1: take action. Um, that's more than enough. And we've seen 604 00:36:18,680 --> 00:36:20,919 Speaker 1: this before in the past. It's you know, if there's 605 00:36:20,960 --> 00:36:23,120 Speaker 1: a mass shooting all of a sudden, you see like 606 00:36:23,160 --> 00:36:26,520 Speaker 1: the same picture from like the last five mass shootings 607 00:36:26,520 --> 00:36:28,600 Speaker 1: where they claim it's this guy or whatever, and then 608 00:36:28,600 --> 00:36:31,399 Speaker 1: that goes via, oh is this guy? Well, there's not 609 00:36:31,520 --> 00:36:35,720 Speaker 1: anything really right now stopping anyone from you know, creating 610 00:36:35,760 --> 00:36:38,040 Speaker 1: like a fake attack, which I will call it then 611 00:36:38,120 --> 00:36:40,439 Speaker 1: you know, in a sense of terrorist attack where you're 612 00:36:40,520 --> 00:36:43,960 Speaker 1: creating this this this this this fake you know the 613 00:36:44,040 --> 00:36:47,480 Speaker 1: thing that's happening, and people are getting terrified because they think, 614 00:36:47,480 --> 00:36:49,680 Speaker 1: oh my god, like they're black folks that are going around, 615 00:36:49,840 --> 00:36:52,080 Speaker 1: you know, they're they're fed up and they're stabbing or 616 00:36:52,160 --> 00:36:54,560 Speaker 1: killing white folks and what are we gonna do and 617 00:36:54,600 --> 00:36:56,920 Speaker 1: all this other stuff. Um, and that's just like a 618 00:36:56,920 --> 00:36:59,959 Speaker 1: weird example that I gave, but you can clearly see 619 00:37:00,080 --> 00:37:05,240 Speaker 1: how platform manipulation could go from something starting on Twitter 620 00:37:05,360 --> 00:37:08,560 Speaker 1: or Facebook or wherever and then spilling into the real world. 621 00:37:08,800 --> 00:37:12,360 Speaker 1: And we got in we actually have real real world 622 00:37:12,400 --> 00:37:17,480 Speaker 1: examples of that. Um you know, back in going into 623 00:37:17,760 --> 00:37:23,239 Speaker 1: seventeen with the whole um Pizza Gate thing, where you know, 624 00:37:23,280 --> 00:37:28,040 Speaker 1: you have that that individual who really thought Hillary Clinton 625 00:37:28,760 --> 00:37:34,320 Speaker 1: was sex trafficking kids. Then we have won six Um 626 00:37:34,360 --> 00:37:38,480 Speaker 1: a lot of that was organized online and it's spilled 627 00:37:38,480 --> 00:37:40,840 Speaker 1: into the real world and you got these crazy people 628 00:37:40,880 --> 00:37:45,400 Speaker 1: that were storming the capitol, you know. So there's nothing 629 00:37:45,719 --> 00:37:49,640 Speaker 1: stopping you know, someone else from doing this. An event 630 00:37:49,719 --> 00:37:53,000 Speaker 1: like that, well then prompt legislators here in the United 631 00:37:53,040 --> 00:37:57,480 Speaker 1: States to say enough is enough, we need to do something. Um. 632 00:37:57,719 --> 00:38:02,319 Speaker 1: So I gave a long answer to say that, Yes, 633 00:38:02,360 --> 00:38:07,479 Speaker 1: I do think legislation is coming. I do believe that 634 00:38:07,560 --> 00:38:10,959 Speaker 1: things are going to get better. I do I think eventually, 635 00:38:11,719 --> 00:38:14,040 Speaker 1: you know, people are gonna just say enough is enough 636 00:38:14,440 --> 00:38:17,120 Speaker 1: and things are going to move in the right direction. 637 00:38:17,960 --> 00:38:20,840 Speaker 1: And I do believe that platforms are going to be 638 00:38:21,040 --> 00:38:24,960 Speaker 1: forced to have to take action. UM So, you know, 639 00:38:25,080 --> 00:38:27,560 Speaker 1: the question, I think the real question is not if 640 00:38:27,640 --> 00:38:30,600 Speaker 1: what win? Are we talking another year? Are we talking 641 00:38:30,680 --> 00:38:35,480 Speaker 1: five years? I don't. I don't have hopefully sooner rather 642 00:38:35,560 --> 00:38:37,640 Speaker 1: than later, because I want to be out of business. 643 00:38:37,719 --> 00:38:40,279 Speaker 1: I want bots and to be out of business. I 644 00:38:40,320 --> 00:38:43,040 Speaker 1: want to be able to retire and not have to 645 00:38:43,080 --> 00:38:46,840 Speaker 1: deal with you know, inauthentic accounts and bots and stuff. 646 00:38:47,960 --> 00:38:50,239 Speaker 1: I mean, wouldn't it be great if we didn't have 647 00:38:50,360 --> 00:38:53,760 Speaker 1: to wait for some sort of you know, calamitous events, 648 00:38:53,920 --> 00:38:57,560 Speaker 1: and people with power to make this change would just 649 00:38:57,760 --> 00:39:00,480 Speaker 1: do it, Like, wouldn't that be great? Well, you know, 650 00:39:00,600 --> 00:39:03,399 Speaker 1: something really quickly and we didn't talk about this, but 651 00:39:03,560 --> 00:39:08,360 Speaker 1: really really quickly. So all right, So the platforms have 652 00:39:08,440 --> 00:39:12,000 Speaker 1: been blocking you know, Russia and you know, they've been 653 00:39:12,040 --> 00:39:14,960 Speaker 1: blocking certain areas and things of that of that nature, 654 00:39:16,320 --> 00:39:19,600 Speaker 1: and I've had people reach out to me. I've had 655 00:39:19,760 --> 00:39:23,960 Speaker 1: journalists reach out and say, hey, have you noticed a 656 00:39:24,080 --> 00:39:29,640 Speaker 1: decline and like trolling like this, things seem a bit quieter, 657 00:39:30,000 --> 00:39:33,000 Speaker 1: you know, all you guys noticing this. And I tweeted 658 00:39:33,000 --> 00:39:35,799 Speaker 1: about that earlier and I said the short answers, Yes, 659 00:39:36,920 --> 00:39:39,960 Speaker 1: there's definitely a decline over the last you know, like 660 00:39:40,080 --> 00:39:43,080 Speaker 1: let's say, to the last three or four days of 661 00:39:43,320 --> 00:39:46,399 Speaker 1: just like the vitriol and the trolling, I mean, because 662 00:39:46,440 --> 00:39:49,200 Speaker 1: we were just seeing like a lot of stuff regarding 663 00:39:49,320 --> 00:39:52,759 Speaker 1: Biden and Biden you know, he can't remember when he 664 00:39:52,800 --> 00:39:56,280 Speaker 1: did yesterday, you know, just nonsense like that, and we've 665 00:39:56,320 --> 00:40:00,880 Speaker 1: definitely seen a decrease. Now, we've also seen an increase 666 00:40:01,200 --> 00:40:07,560 Speaker 1: in accounts praising Vladimir Putin, and we've seen you know, 667 00:40:07,800 --> 00:40:12,120 Speaker 1: fake accounts once again saying that Ukrainians are racist and 668 00:40:12,160 --> 00:40:16,759 Speaker 1: it's a racist country. But overall, we've definitely seen a 669 00:40:16,840 --> 00:40:19,319 Speaker 1: decline in the trolling. You know, And I made a 670 00:40:19,400 --> 00:40:23,600 Speaker 1: joke not on Twitter, this is personally and I'm just like, God, 671 00:40:23,719 --> 00:40:25,960 Speaker 1: I wish it was like this every single day, Like 672 00:40:26,120 --> 00:40:29,200 Speaker 1: I wish that you can go onto social media and 673 00:40:29,200 --> 00:40:32,359 Speaker 1: actually interact with people and not have to deal with 674 00:40:32,400 --> 00:40:37,840 Speaker 1: the constant trolling. So you we we we were getting 675 00:40:37,920 --> 00:40:41,600 Speaker 1: a glimpse of what life could be like if the 676 00:40:41,640 --> 00:40:45,239 Speaker 1: platforms were actually to take this more seriously. And we 677 00:40:45,320 --> 00:40:47,960 Speaker 1: deserve that. We deserve to be able to go on 678 00:40:48,120 --> 00:40:52,960 Speaker 1: to our largest communications platforms and have a conversation without 679 00:40:53,000 --> 00:40:58,120 Speaker 1: being trolled, without being harassed, Like we deserve that everybody deserves, absolutely, 680 00:40:58,440 --> 00:41:03,319 Speaker 1: especially women and women of color, because at the end 681 00:41:03,360 --> 00:41:07,440 Speaker 1: of the day, and we've provided data on this. Women 682 00:41:08,040 --> 00:41:10,960 Speaker 1: are at the top of the list in terms of 683 00:41:10,960 --> 00:41:14,319 Speaker 1: people who are constantly targeted and attacked, and women of 684 00:41:14,360 --> 00:41:20,000 Speaker 1: color are the number one. UM and it's and platforms 685 00:41:20,040 --> 00:41:22,719 Speaker 1: do need to do better at at at you know, 686 00:41:23,719 --> 00:41:27,200 Speaker 1: curtailing a lot of this stuff that's happening. But you're 687 00:41:27,239 --> 00:41:31,120 Speaker 1: absolutely right. First thing, a platform like Twitter. Sometimes I 688 00:41:31,120 --> 00:41:35,600 Speaker 1: get really disappointed with Twitter because Twitter, for me, you know, 689 00:41:36,080 --> 00:41:39,239 Speaker 1: it's people will talking about like Facebook and you know, Instagram. 690 00:41:39,320 --> 00:41:42,880 Speaker 1: I think Twitter is the most powerful platform on the planet. 691 00:41:43,440 --> 00:41:46,560 Speaker 1: I believe that to my core. And the reason behind 692 00:41:46,640 --> 00:41:53,319 Speaker 1: that is because unlike other social networks, Um, Twitter can 693 00:41:53,440 --> 00:41:58,560 Speaker 1: drive news cycles. You know Twitter, you know, I can 694 00:41:58,600 --> 00:42:00,719 Speaker 1: put something out on Twitter into read something and it 695 00:42:00,760 --> 00:42:03,080 Speaker 1: could be picked up by a major prop uh you know, 696 00:42:03,120 --> 00:42:07,280 Speaker 1: outlet or publication or whatever. Um. You know, Joe Biden 697 00:42:07,560 --> 00:42:10,720 Speaker 1: can go right now, President Biden can go and tweet 698 00:42:10,800 --> 00:42:14,840 Speaker 1: something out about Ukraine and it will go viral. I 699 00:42:14,880 --> 00:42:18,040 Speaker 1: mean it could literally start a war depending on what 700 00:42:18,080 --> 00:42:21,120 Speaker 1: he you know, tweets out. So you know, people are 701 00:42:21,239 --> 00:42:25,680 Speaker 1: using Twitter and journalists and world leaders are using Twitter 702 00:42:26,200 --> 00:42:31,240 Speaker 1: to get news and information and everything out and unlike 703 00:42:31,239 --> 00:42:36,120 Speaker 1: Facebook and Instagram, it's a platform for in a hub 704 00:42:36,160 --> 00:42:42,239 Speaker 1: for information period. So you would think with you know, 705 00:42:42,560 --> 00:42:46,200 Speaker 1: with a platform like this, that the people on Twitter 706 00:42:46,440 --> 00:42:48,839 Speaker 1: would say, hey, you know something, we really need to 707 00:42:48,880 --> 00:42:52,120 Speaker 1: make this place a lot better because we're like where 708 00:42:52,160 --> 00:42:56,400 Speaker 1: people go for serious news. You know, a lot of 709 00:42:56,440 --> 00:42:58,960 Speaker 1: people don't even go to that. They don't even have 710 00:42:59,080 --> 00:43:01,680 Speaker 1: like cable anymore, or you know, they're not even like, 711 00:43:02,280 --> 00:43:05,640 Speaker 1: you know, going and buying newspapers. Unfortunately, they're going to 712 00:43:05,719 --> 00:43:08,560 Speaker 1: Twitter to get their news. So you would think the 713 00:43:08,600 --> 00:43:11,160 Speaker 1: folks that Twitter would say, hey, it's time for us 714 00:43:11,160 --> 00:43:14,439 Speaker 1: to really take our own platform seriously, Like they're they're 715 00:43:15,520 --> 00:43:18,120 Speaker 1: I hate saying this, and and and there's nothing wrong 716 00:43:18,120 --> 00:43:20,879 Speaker 1: with the n f T s, but I'm just like, 717 00:43:21,280 --> 00:43:24,880 Speaker 1: why are you focusing on n f T like profile 718 00:43:24,960 --> 00:43:30,640 Speaker 1: images where you should be focusing on the rampid disinformation 719 00:43:30,680 --> 00:43:33,480 Speaker 1: and harassment on your platform? Like who asks for n 720 00:43:33,520 --> 00:43:39,160 Speaker 1: f T profile pictures? Literally every time they released something, 721 00:43:39,200 --> 00:43:41,720 Speaker 1: I'm like, who asked for this? Why don't you focus 722 00:43:41,719 --> 00:43:43,759 Speaker 1: on You've got a lot on your plate in terms 723 00:43:43,800 --> 00:43:46,239 Speaker 1: of making a fun, safer and better, Like, why don't 724 00:43:46,239 --> 00:43:49,680 Speaker 1: you focus on that? I don't understand it. Like when 725 00:43:49,680 --> 00:43:53,319 Speaker 1: I saw that, I was just like, who asked for this? 726 00:43:54,080 --> 00:43:58,160 Speaker 1: You know? So I mean, look, I understand what my 727 00:43:58,320 --> 00:44:00,600 Speaker 1: needs may be and what your needs may be. Maybe 728 00:44:00,640 --> 00:44:04,520 Speaker 1: a little bit different from what the developer needs maybe, um, 729 00:44:04,560 --> 00:44:08,120 Speaker 1: but they need to really sit down with folks and 730 00:44:08,160 --> 00:44:11,080 Speaker 1: get an idea of what their platform really is about 731 00:44:11,120 --> 00:44:13,920 Speaker 1: to other people. And I know, look, not everyone uses 732 00:44:14,120 --> 00:44:16,759 Speaker 1: Twitter for news and things like that. There are people 733 00:44:16,800 --> 00:44:19,719 Speaker 1: on there who are just doing their thing. I get that. 734 00:44:20,600 --> 00:44:24,839 Speaker 1: But Twitter can definitely drive new cycles and because of that, 735 00:44:25,840 --> 00:44:28,520 Speaker 1: the folks that Twitter need to to to do more, 736 00:44:29,440 --> 00:44:33,319 Speaker 1: you know, they definitely need to do more. Well hopefully. 737 00:44:33,360 --> 00:44:36,480 Speaker 1: I think that your work is really creating the conditions 738 00:44:36,480 --> 00:44:38,879 Speaker 1: for them to really see that. I think that's very 739 00:44:38,880 --> 00:44:42,600 Speaker 1: clear to me. And it sounds like you don't agree 740 00:44:42,840 --> 00:44:46,640 Speaker 1: you know something. Um, I'm sorry and I completely apologized 741 00:44:46,640 --> 00:44:52,040 Speaker 1: to cut you off. Um. I think I think our 742 00:44:52,120 --> 00:44:55,960 Speaker 1: work for you know, the general republic and journalists and 743 00:44:55,960 --> 00:44:59,760 Speaker 1: stuff like researchers. I think they look at our work 744 00:45:00,040 --> 00:45:03,560 Speaker 1: and obviously want us to continue, and they, you know, 745 00:45:03,800 --> 00:45:08,200 Speaker 1: value what we're doing. Twitter on the other hand, UM, 746 00:45:08,239 --> 00:45:11,160 Speaker 1: I think we're kind of a thorn sometimes in their side, 747 00:45:12,160 --> 00:45:14,640 Speaker 1: because we expose a lot of things that they probably 748 00:45:14,680 --> 00:45:18,839 Speaker 1: don't want to be exposed. Um. So you know, I'm 749 00:45:18,880 --> 00:45:20,799 Speaker 1: not saying Twitter would love for us to disappear. I'm 750 00:45:20,800 --> 00:45:23,319 Speaker 1: not going to say that because I do believe they 751 00:45:23,880 --> 00:45:27,040 Speaker 1: also find value in what we're doing. Um, but I 752 00:45:27,080 --> 00:45:29,920 Speaker 1: think they probably would like it if we're like less 753 00:45:29,960 --> 00:45:34,239 Speaker 1: effective at what we're doing. Something tells me you don't 754 00:45:34,239 --> 00:45:38,200 Speaker 1: have any plans to become less effective? No, no, not 755 00:45:38,320 --> 00:45:42,239 Speaker 1: at all, not at all. Well, Christopher, this has been 756 00:45:42,440 --> 00:45:44,960 Speaker 1: such a good conversation. Where can people keep up with 757 00:45:45,000 --> 00:45:49,520 Speaker 1: all of your work? Oh? Um? Well, first thing, you know, 758 00:45:49,560 --> 00:45:54,239 Speaker 1: our website is bought Bot Sentinel s E N T 759 00:45:54,560 --> 00:45:58,759 Speaker 1: I in e L dot com. Um, they can follow me. 760 00:45:59,640 --> 00:46:06,760 Speaker 1: I'm at see bou z y. Um that's Twitter. And yeah, 761 00:46:06,800 --> 00:46:09,640 Speaker 1: I mean, look like I said, I use my account 762 00:46:09,960 --> 00:46:13,480 Speaker 1: to try to educate people, and you know, I'm I'm 763 00:46:13,600 --> 00:46:18,920 Speaker 1: very vocal about things. Um, I don't hold my tongue. Um. 764 00:46:18,960 --> 00:46:21,279 Speaker 1: So you know, if you want to follow me on 765 00:46:21,320 --> 00:46:23,680 Speaker 1: Twitter and learn more about this stuff and other issues 766 00:46:23,719 --> 00:46:25,640 Speaker 1: as well, you can do that. But if you're just 767 00:46:25,760 --> 00:46:28,760 Speaker 1: more focused on our technology, you can go to the website. 768 00:46:29,600 --> 00:46:32,720 Speaker 1: People of Color in Ukraine deserve to make their voices 769 00:46:32,800 --> 00:46:35,760 Speaker 1: heard without having to compete with disinformers and bad actors 770 00:46:35,760 --> 00:46:38,960 Speaker 1: on social media platforms to do so. And we all 771 00:46:39,040 --> 00:46:41,520 Speaker 1: deserve a digital media landscape that can be used to 772 00:46:41,520 --> 00:46:44,680 Speaker 1: get authentic, accurate information about what's happening in our world, 773 00:46:45,080 --> 00:46:49,400 Speaker 1: especially during a crisis. We all deserve better. You can 774 00:46:49,440 --> 00:46:52,440 Speaker 1: help support black students in Ukraine and find more resources 775 00:46:52,440 --> 00:46:55,120 Speaker 1: that Black Women for Black Lives. Go to Black Women 776 00:46:55,120 --> 00:46:57,080 Speaker 1: for Black Lives dot org or click the link in 777 00:46:57,080 --> 00:47:00,320 Speaker 1: the show description and we'll be continuing the conver station 778 00:47:00,360 --> 00:47:07,520 Speaker 1: around what's happening in Ukraine later this week. Got a 779 00:47:07,560 --> 00:47:09,600 Speaker 1: story about an interesting thing in tech, or just want 780 00:47:09,640 --> 00:47:11,600 Speaker 1: to say hi, You can be us at Hello at 781 00:47:11,640 --> 00:47:14,000 Speaker 1: tang godi dot com. You can also find transcripts for 782 00:47:14,000 --> 00:47:16,719 Speaker 1: today's episode at tangdi dot com. There Are No Girls 783 00:47:16,760 --> 00:47:19,120 Speaker 1: on the Internet was created by me Bridget Tod. It's 784 00:47:19,120 --> 00:47:21,960 Speaker 1: a production of I Heart Radio and Unboss creative Jonathan 785 00:47:22,000 --> 00:47:25,000 Speaker 1: Strickland as our executive producer, Terry Harrison as our producer, 786 00:47:25,040 --> 00:47:28,520 Speaker 1: and sound engineer. Michael Amato is our contributing producer. I'm 787 00:47:28,560 --> 00:47:31,399 Speaker 1: your host, Bridget Todd. If you want to help us grow, 788 00:47:31,600 --> 00:47:34,760 Speaker 1: rate and review us on Apple Podcasts. For more podcasts 789 00:47:34,760 --> 00:47:36,839 Speaker 1: from I heart Radio, check out the iHeart Radio app, 790 00:47:36,880 --> 00:47:55,640 Speaker 1: Apple podcast, or wherever you get your podcasts. If you 791 00:47:55,680 --> 00:47:58,719 Speaker 1: liked this episode, help us out by subscribing. You can 792 00:47:58,760 --> 00:48:01,080 Speaker 1: also support the show by by merch at tangodi dot 793 00:48:01,160 --> 00:48:03,560 Speaker 1: com slash store and sign up for my brand new 794 00:48:03,600 --> 00:48:07,560 Speaker 1: newsletter at tangodi dot com slash Newsletter That's t A 795 00:48:07,880 --> 00:48:11,360 Speaker 1: n G O t I dot com