1 00:00:04,200 --> 00:00:05,920 Speaker 1: There Are No Girls on the Internet. As a production 2 00:00:05,960 --> 00:00:13,640 Speaker 1: of iHeartRadio and Unbossed Creative, I'm brigitat and this is 3 00:00:13,640 --> 00:00:19,160 Speaker 1: There Are No Girls on the Internet. Graduation is supposed 4 00:00:19,200 --> 00:00:22,079 Speaker 1: to be a time for eager college grads making speeches 5 00:00:22,440 --> 00:00:25,920 Speaker 1: and walking across the stage to receive their hard earned diplomas, 6 00:00:26,720 --> 00:00:31,520 Speaker 1: but campuses around the country at places like usc Columbia, 7 00:00:31,560 --> 00:00:36,440 Speaker 1: and Emery have either shrunk or canceled graduation ceremonies in 8 00:00:36,479 --> 00:00:40,479 Speaker 1: the wake of protests demanding universities divest from Israel, in 9 00:00:40,520 --> 00:00:44,720 Speaker 1: other words, withdrawal any funds their university endowments have invested 10 00:00:44,760 --> 00:00:48,800 Speaker 1: in companies that are linked to Israel. The protests have 11 00:00:48,960 --> 00:00:52,840 Speaker 1: really escalated recently, and even before that, A digital billboard 12 00:00:52,840 --> 00:00:56,760 Speaker 1: truck funded by a well moneyed conservative group drove around 13 00:00:56,880 --> 00:01:01,160 Speaker 1: university campuses at Columbia, Harvard, and UPenn with pictures and 14 00:01:01,280 --> 00:01:05,280 Speaker 1: names of students, accusing them of being quote their campuses 15 00:01:05,560 --> 00:01:09,479 Speaker 1: leading anti semites. One student whose picture and name were 16 00:01:09,480 --> 00:01:13,080 Speaker 1: on a billboard truck at Columbia spoke to Verge, saying, 17 00:01:13,400 --> 00:01:16,240 Speaker 1: I literally did not leave my apartment the days my 18 00:01:16,319 --> 00:01:19,200 Speaker 1: friends told me about it. The student said that her 19 00:01:19,280 --> 00:01:21,920 Speaker 1: name was listed on the truck because a club that 20 00:01:21,959 --> 00:01:24,280 Speaker 1: she was no longer a part of had signed on 21 00:01:24,400 --> 00:01:27,440 Speaker 1: to an open letter urging Columbia to cut ties with Israel. 22 00:01:27,920 --> 00:01:30,319 Speaker 1: I completely wiped as much as I could of my 23 00:01:30,400 --> 00:01:33,760 Speaker 1: online presence and stated my apartment as much as I could, 24 00:01:33,800 --> 00:01:38,200 Speaker 1: the student said. Meanwhile, Canary Mission, a website that lists 25 00:01:38,240 --> 00:01:41,400 Speaker 1: people perceived as being supportive of Palestine in order to 26 00:01:41,480 --> 00:01:44,680 Speaker 1: keep them from getting future job prospects, has stocked students 27 00:01:44,720 --> 00:01:47,760 Speaker 1: across the country. It is your duty to ensure that 28 00:01:47,800 --> 00:01:51,840 Speaker 1: today's radicals are not tomorrow's employees. A video describing the 29 00:01:51,840 --> 00:01:56,160 Speaker 1: project explains Caroline Cinders and their colleague Sam are part 30 00:01:56,160 --> 00:02:00,400 Speaker 1: of Convocation Research and Design, or Chords for short people 31 00:02:00,440 --> 00:02:03,040 Speaker 1: who are being doxed or at risk for being doxed, 32 00:02:03,400 --> 00:02:05,720 Speaker 1: train people on how to stay safe both online and 33 00:02:05,760 --> 00:02:09,000 Speaker 1: off while engaging in protest, and advocate for technology to 34 00:02:09,040 --> 00:02:12,200 Speaker 1: be designed in more responsible ways. When I first caught 35 00:02:12,240 --> 00:02:14,960 Speaker 1: up with Caroline and Sam, I thought this whole conversation 36 00:02:15,000 --> 00:02:17,760 Speaker 1: would be pretty straightforward, you know, turn off your phone 37 00:02:17,760 --> 00:02:20,400 Speaker 1: out of protest, that kind of thing. But as we spoke, 38 00:02:20,919 --> 00:02:24,200 Speaker 1: Caroline and Sam described just how charged of a landscape 39 00:02:24,280 --> 00:02:27,760 Speaker 1: we're talking about. And I realized the conversation is so 40 00:02:27,960 --> 00:02:35,680 Speaker 1: much more complicated than that. So when I first reached 41 00:02:35,680 --> 00:02:37,520 Speaker 1: out to y'all to do this episode, I thought it 42 00:02:37,560 --> 00:02:40,320 Speaker 1: was going to be a pretty basic guide for how 43 00:02:40,400 --> 00:02:44,359 Speaker 1: folks protesting on campus and off campus can stay safe digitally. 44 00:02:44,840 --> 00:02:47,560 Speaker 1: I thought we'd be talking about pretty basic things like 45 00:02:48,200 --> 00:02:50,200 Speaker 1: use a pass code to unlock your phone so that 46 00:02:50,200 --> 00:02:52,160 Speaker 1: if you're detained by police they have a harder time 47 00:02:52,200 --> 00:02:55,400 Speaker 1: getting into it, or cover any distinctive tattoos, that kind 48 00:02:55,440 --> 00:02:58,440 Speaker 1: of thing. But then when you and I started talking, 49 00:02:58,880 --> 00:03:01,720 Speaker 1: I realized there was so much more going on here, 50 00:03:01,760 --> 00:03:03,600 Speaker 1: and then I needed to take a step back. You 51 00:03:03,720 --> 00:03:06,880 Speaker 1: all told me about things like provocateurs setting up fake 52 00:03:07,000 --> 00:03:10,680 Speaker 1: dating profiles and then going on fake dates with protesters 53 00:03:10,880 --> 00:03:13,600 Speaker 1: and trying to secretly record them saying things to make 54 00:03:13,639 --> 00:03:16,840 Speaker 1: them look bad James O'Keeffe style, or how right wing 55 00:03:16,919 --> 00:03:20,520 Speaker 1: influencers are kind of selling themselves as a citizen journalists 56 00:03:20,600 --> 00:03:23,760 Speaker 1: and trying to make names for themselves by engineering viral 57 00:03:23,840 --> 00:03:27,880 Speaker 1: content of protesters looking bad on top of threats to 58 00:03:27,960 --> 00:03:30,840 Speaker 1: protesters that you might traditionally think of, you know, threats 59 00:03:30,880 --> 00:03:34,399 Speaker 1: from campus administration or police. So can you just give 60 00:03:34,480 --> 00:03:36,760 Speaker 1: us kind of the lay of the land in terms 61 00:03:36,760 --> 00:03:39,560 Speaker 1: of the threats that these student protesters are facing right now. 62 00:03:40,280 --> 00:03:44,800 Speaker 2: These threats are wide and varied. I think student activists 63 00:03:44,880 --> 00:03:49,600 Speaker 2: are seeing threats not only from outside, but from inside 64 00:03:49,640 --> 00:03:54,200 Speaker 2: as well, So they're having to contend with school administration, 65 00:03:56,480 --> 00:04:03,840 Speaker 2: sometimes hostile students who are against what they're protesting for, 66 00:04:04,440 --> 00:04:10,800 Speaker 2: as well as outside forces like the police or outside 67 00:04:11,760 --> 00:04:18,440 Speaker 2: sometimes infiltrators like people like Project Bearitas style where they're 68 00:04:18,440 --> 00:04:23,240 Speaker 2: trying to get into protests in order to record people 69 00:04:24,320 --> 00:04:27,320 Speaker 2: who they perceive as their political opposition in order to 70 00:04:27,400 --> 00:04:29,800 Speaker 2: make them look bad and then posting that on the 71 00:04:29,800 --> 00:04:36,400 Speaker 2: internet for clout or subscriptions or money, as well as 72 00:04:36,640 --> 00:04:40,000 Speaker 2: a variety of other threats that I think a lot 73 00:04:40,000 --> 00:04:41,440 Speaker 2: of people don't really take into account. 74 00:04:42,040 --> 00:04:45,320 Speaker 1: So you talked about people doing this for clout or engagement. 75 00:04:45,560 --> 00:04:47,600 Speaker 1: Do you think that's a big undercurrent of what we're 76 00:04:47,600 --> 00:04:49,400 Speaker 1: seeing here, Like people who are like, oh, this is 77 00:04:49,440 --> 00:04:52,200 Speaker 1: a great opportunity to put out some viral video that 78 00:04:52,240 --> 00:04:55,480 Speaker 1: makes a protester look bad or look uninformed, or look 79 00:04:56,200 --> 00:04:59,039 Speaker 1: threatening or dangerous. I'll put that online and become a 80 00:04:59,080 --> 00:05:00,279 Speaker 1: superstar myself. 81 00:05:00,760 --> 00:05:03,919 Speaker 3: I mean, we are more in a time of the 82 00:05:04,000 --> 00:05:07,799 Speaker 3: kind of like citizen journalists some of them call themselves, 83 00:05:07,880 --> 00:05:10,440 Speaker 3: or like man on the street interviews where those are 84 00:05:10,520 --> 00:05:14,280 Speaker 3: very popular on like TikTok or Instagram or Twitter or 85 00:05:14,320 --> 00:05:17,480 Speaker 3: YouTube or rumble, like the list goes on and on 86 00:05:17,560 --> 00:05:20,360 Speaker 3: of all these different platforms that they're able to monetize 87 00:05:20,400 --> 00:05:24,800 Speaker 3: these videos for and it is very big in the 88 00:05:24,800 --> 00:05:29,919 Speaker 3: the cultural climate that that these protests are happening in. 89 00:05:32,320 --> 00:05:36,719 Speaker 2: So yes and no, like they are a small part 90 00:05:37,000 --> 00:05:38,359 Speaker 2: of these protests. 91 00:05:37,960 --> 00:05:42,800 Speaker 3: But any large event I feel like that's happening happening 92 00:05:42,800 --> 00:05:47,080 Speaker 3: collectively in the country is going to have probably a 93 00:05:47,080 --> 00:05:50,839 Speaker 3: similar amount of people that are chasing it for some 94 00:05:51,040 --> 00:05:52,880 Speaker 3: type of engagement and. 95 00:05:52,839 --> 00:05:54,360 Speaker 4: Just to build on that. You know, I really do 96 00:05:54,400 --> 00:05:57,320 Speaker 4: think we are in the age of the influencer. Like, 97 00:05:57,360 --> 00:05:59,160 Speaker 4: I think that is something a lot of folks to 98 00:05:59,200 --> 00:06:03,600 Speaker 4: feel comfortable saying. It is really hard to say, you know, 99 00:06:03,760 --> 00:06:06,320 Speaker 4: citation needed in terms of how many folks are attending 100 00:06:06,400 --> 00:06:13,360 Speaker 4: these protests in person or following them online right and 101 00:06:13,440 --> 00:06:17,600 Speaker 4: commenting in a way that is related to influencer or 102 00:06:17,640 --> 00:06:21,320 Speaker 4: citizen journalism. Like there are a variety of organizations that 103 00:06:21,400 --> 00:06:25,839 Speaker 4: are trying to identify student protesters and docs them and 104 00:06:25,839 --> 00:06:28,000 Speaker 4: put their information online. Like one that comes to mind 105 00:06:28,040 --> 00:06:31,719 Speaker 4: is Camary Mission for example. But yeah, there are a 106 00:06:31,760 --> 00:06:34,640 Speaker 4: lot of folks that are either or not a lot, 107 00:06:34,680 --> 00:06:36,680 Speaker 4: but there are there are definitely folks that are showing 108 00:06:36,720 --> 00:06:39,720 Speaker 4: up to the protests that are we could argue, have 109 00:06:40,000 --> 00:06:44,680 Speaker 4: you know, maybe some more malicious intentions that are in 110 00:06:44,720 --> 00:06:48,400 Speaker 4: this morsus in journalism or influencer space. But there's also 111 00:06:48,480 --> 00:06:54,720 Speaker 4: lots of folks watching online trying to identify different different 112 00:06:54,760 --> 00:06:58,560 Speaker 4: folks at these protests and sort of doing a kind 113 00:06:58,640 --> 00:07:00,800 Speaker 4: of let's say, like recap or an analysis. And this 114 00:07:00,880 --> 00:07:04,280 Speaker 4: is stuff you know, we've seen in many other different 115 00:07:04,360 --> 00:07:06,920 Speaker 4: kinds of spaces and ways. Like what comes to mind 116 00:07:06,960 --> 00:07:09,400 Speaker 4: for me is, you know the Johnny Depp amber Heard 117 00:07:09,440 --> 00:07:14,360 Speaker 4: trial where we saw so many sort of armchair investigators 118 00:07:14,400 --> 00:07:20,480 Speaker 4: and heavy heavy quotes, body language experts like this, this 119 00:07:20,560 --> 00:07:23,360 Speaker 4: is the lip readers and things like that, and and 120 00:07:24,280 --> 00:07:26,520 Speaker 4: but that had like a real impact on how people 121 00:07:26,600 --> 00:07:31,840 Speaker 4: really perceived that trial and how I would argue in 122 00:07:31,880 --> 00:07:35,160 Speaker 4: really discoloring amber Heard not as a victim but as 123 00:07:35,640 --> 00:07:38,040 Speaker 4: a perpetrator, when in fact she was a victim, right, 124 00:07:38,080 --> 00:07:40,280 Speaker 4: And so I think, you know, we're still seeing a 125 00:07:40,320 --> 00:07:44,000 Speaker 4: lot of that here and now with folks I think 126 00:07:44,040 --> 00:07:47,480 Speaker 4: also maybe not physically being at the protest, but commenting 127 00:07:47,560 --> 00:07:53,320 Speaker 4: on them, analyzing them, right, and providing different kinds of 128 00:07:54,080 --> 00:07:55,880 Speaker 4: like wrongful assessments. 129 00:07:56,040 --> 00:07:58,680 Speaker 1: And similar to what we saw with the Amber Heard 130 00:07:58,760 --> 00:08:02,640 Speaker 1: Johnny Depth trial. Do you have you seen that those 131 00:08:02,760 --> 00:08:06,960 Speaker 1: kind of armchair folks who aren't necessarily involved in the 132 00:08:07,000 --> 00:08:10,520 Speaker 1: protest but are like you know, commenting on the viral 133 00:08:10,600 --> 00:08:13,320 Speaker 1: video they saw from the protests or whatever, that that 134 00:08:13,480 --> 00:08:17,480 Speaker 1: is having an impact on how every day people are 135 00:08:17,520 --> 00:08:20,400 Speaker 1: perceiving what's going on on college campuses across the country. 136 00:08:21,280 --> 00:08:25,000 Speaker 4: I think it's leading to like stratification for sure, and 137 00:08:25,040 --> 00:08:27,360 Speaker 4: I think some of that is also you know, I 138 00:08:27,360 --> 00:08:30,760 Speaker 4: would argue actually also coming from a place even of 139 00:08:31,000 --> 00:08:33,640 Speaker 4: sadly like traditional media. One of the things I like 140 00:08:33,640 --> 00:08:37,360 Speaker 4: to highlight is we don't live in a harassment literate society, 141 00:08:37,400 --> 00:08:41,760 Speaker 4: and I think a lot of the analysis that is 142 00:08:41,800 --> 00:08:46,680 Speaker 4: sort of existing around this, this this particular conflict, right, 143 00:08:46,840 --> 00:08:50,960 Speaker 4: is sort of caught up in a really lack of nuance. Right, 144 00:08:51,040 --> 00:08:55,400 Speaker 4: So the inability to see let's say, the people of 145 00:08:55,440 --> 00:09:00,160 Speaker 4: Gaza as individuals that we are watching a genocide unfold, 146 00:09:00,600 --> 00:09:07,160 Speaker 4: that we are watching things where many respected, reputable international bodies, right, 147 00:09:07,200 --> 00:09:09,960 Speaker 4: are weighing in and saying like this is unprecedented in 148 00:09:10,080 --> 00:09:12,880 Speaker 4: terms of like a famine that's being caused, in terms 149 00:09:12,880 --> 00:09:15,160 Speaker 4: of the attack, in terms of the amount of journalists killed, 150 00:09:15,160 --> 00:09:17,160 Speaker 4: in terms of the amount of children that are killed 151 00:09:17,760 --> 00:09:22,920 Speaker 4: in this particular conflict, right, And a lot of what 152 00:09:23,000 --> 00:09:25,760 Speaker 4: I think a lot was happening is a version of 153 00:09:25,800 --> 00:09:30,679 Speaker 4: context collapse in which I think some folks are weaponizing, 154 00:09:33,080 --> 00:09:37,600 Speaker 4: are weaponizing anti Semitism to push for other agendas, and 155 00:09:37,640 --> 00:09:40,719 Speaker 4: that is also creating a space in which it's very 156 00:09:40,720 --> 00:09:44,200 Speaker 4: difficult to have one could argue a nuanced conversation, right, 157 00:09:44,880 --> 00:09:48,920 Speaker 4: And I think that is a large part of this. 158 00:09:49,200 --> 00:09:51,960 Speaker 4: And then from there that kind of gives bad actors 159 00:09:52,000 --> 00:09:56,959 Speaker 4: a space to push different kinds of agendas and different 160 00:09:57,040 --> 00:09:59,800 Speaker 4: kinds of information and also in a way, almost again 161 00:09:59,840 --> 00:10:05,960 Speaker 4: like justify the doxing of different activists, right. And so 162 00:10:06,160 --> 00:10:11,240 Speaker 4: I think it's sort of hard to like definitively say, 163 00:10:11,320 --> 00:10:17,200 Speaker 4: but I do see on on like the you know, 164 00:10:17,640 --> 00:10:21,200 Speaker 4: on the like writer or conservative end uh, this sort 165 00:10:21,200 --> 00:10:26,880 Speaker 4: of lack of nuance and inability to understand like a 166 00:10:26,960 --> 00:10:30,040 Speaker 4: human rights conflict really muddying the waters in terms of 167 00:10:30,080 --> 00:10:33,679 Speaker 4: also how do you contextualize or talk about let's say, 168 00:10:33,720 --> 00:10:34,920 Speaker 4: like student protesters. 169 00:10:35,600 --> 00:10:39,520 Speaker 1: So we talked a lot about like media entities. I 170 00:10:39,559 --> 00:10:42,800 Speaker 1: guess I'll say, who are known provocateurs that like nobody 171 00:10:42,840 --> 00:10:46,800 Speaker 1: should trust. But I do think that national reporting is 172 00:10:46,880 --> 00:10:48,760 Speaker 1: not all it's not I have not seen a lot 173 00:10:48,760 --> 00:10:51,600 Speaker 1: of national reporting that is super clear about what is 174 00:10:51,640 --> 00:10:54,760 Speaker 1: going on, like the fact that we're talking about nineteen 175 00:10:54,920 --> 00:10:58,320 Speaker 1: like a nineteen year old college freshman or something being 176 00:10:58,400 --> 00:11:03,720 Speaker 1: up against a coordinated, organized, well funded institution with a 177 00:11:03,880 --> 00:11:07,160 Speaker 1: mission to dox them and make them look bad, right, 178 00:11:07,200 --> 00:11:09,960 Speaker 1: and so like, I don't feel like we are really 179 00:11:10,640 --> 00:11:14,520 Speaker 1: getting a lot of opportunities to have that full story told. 180 00:11:15,240 --> 00:11:17,560 Speaker 1: I think that the way that you have described it, Caroline, 181 00:11:17,559 --> 00:11:20,120 Speaker 1: as like we just don't live in a harassment literate 182 00:11:20,200 --> 00:11:24,200 Speaker 1: society where you know the actual context of what that 183 00:11:24,240 --> 00:11:26,720 Speaker 1: would be like and what and like why that is 184 00:11:26,760 --> 00:11:30,200 Speaker 1: happening is not being reflected perhaps, And I guess I wonder, like, 185 00:11:30,600 --> 00:11:32,880 Speaker 1: how can we get to a place where that's that 186 00:11:33,040 --> 00:11:35,760 Speaker 1: story is being told more honestly, where people really understand 187 00:11:35,760 --> 00:11:39,840 Speaker 1: that like, yeah, you're talking about a college student for 188 00:11:39,920 --> 00:11:43,120 Speaker 1: who and then a billionaire funds a truck with their 189 00:11:43,160 --> 00:11:45,440 Speaker 1: picture and their name on it to drive around their campus, 190 00:11:45,520 --> 00:11:49,720 Speaker 1: right or like, like, how truly fucked up? That really is. 191 00:11:49,920 --> 00:11:53,160 Speaker 4: Totally and thank you so much for that. I I 192 00:11:54,559 --> 00:11:57,160 Speaker 4: don't know how we get towards a harassment literate society. 193 00:11:57,160 --> 00:11:59,720 Speaker 4: That's why I'm really grateful for podcasts like No Girls 194 00:11:59,720 --> 00:12:01,880 Speaker 4: on the So I've been really grateful for a lot 195 00:12:01,880 --> 00:12:05,040 Speaker 4: of the programming we've seen across different kinds of civil 196 00:12:05,040 --> 00:12:10,200 Speaker 4: society organizations. Been extremely grateful for teen Vogue and it's 197 00:12:10,280 --> 00:12:14,080 Speaker 4: like existence over the past few years. I think a 198 00:12:14,080 --> 00:12:18,600 Speaker 4: lot of this is really sort of insisting on having 199 00:12:19,520 --> 00:12:21,920 Speaker 4: nuanced conversations. But I think a lot of it also 200 00:12:21,960 --> 00:12:27,480 Speaker 4: actually does come down to different kinds of education, and 201 00:12:27,559 --> 00:12:30,280 Speaker 4: I don't know at what level that should should happen 202 00:12:30,559 --> 00:12:33,439 Speaker 4: or exist in Like, for example, with our organization, we 203 00:12:33,760 --> 00:12:35,760 Speaker 4: don't really work a lot with children for a variety 204 00:12:35,800 --> 00:12:40,440 Speaker 4: of reasons. Some of that is also just like regulatory reasons. 205 00:12:40,480 --> 00:12:43,840 Speaker 4: It's not one of our advocacy focuses because children are 206 00:12:43,960 --> 00:12:47,360 Speaker 4: like under eighteen, they're just a different legal group than adults. 207 00:12:48,800 --> 00:12:50,320 Speaker 4: But you know, I think there's something to be said 208 00:12:50,400 --> 00:12:55,280 Speaker 4: around how do we how do we sort of talk 209 00:12:55,320 --> 00:12:59,120 Speaker 4: about things like digital harm and also offline harm. But 210 00:12:59,160 --> 00:13:01,520 Speaker 4: I think that this is also an issue that adults 211 00:13:01,600 --> 00:13:06,520 Speaker 4: run into as well, Like you can't necessarily summarize, I 212 00:13:06,559 --> 00:13:10,400 Speaker 4: think often or I think it's difficult to summarize a 213 00:13:10,440 --> 00:13:13,240 Speaker 4: lot of harassment cases into a tweet, right, to summarize 214 00:13:13,280 --> 00:13:17,320 Speaker 4: it in a few characters. And I think in this 215 00:13:17,400 --> 00:13:22,560 Speaker 4: sort of space of us trying to maybe editorialize or 216 00:13:22,800 --> 00:13:26,760 Speaker 4: in you know, take a stance on something that often 217 00:13:26,800 --> 00:13:31,480 Speaker 4: really collapses the nuance of what we're talking about. I 218 00:13:31,520 --> 00:13:35,200 Speaker 4: also think that there's like a binary in which people 219 00:13:35,640 --> 00:13:39,640 Speaker 4: tend to approach good and bad, and then that sort 220 00:13:39,640 --> 00:13:43,240 Speaker 4: of weighs into harrassment. I think that there's also a 221 00:13:43,280 --> 00:13:45,480 Speaker 4: deeper context here. So this is one of the things 222 00:13:46,200 --> 00:13:48,000 Speaker 4: I've noticed in some of the trainings we do with 223 00:13:48,040 --> 00:13:51,720 Speaker 4: folks that are like victims that are facing harrassment or 224 00:13:51,760 --> 00:13:56,560 Speaker 4: have been harassed. And I've also noted this with folks 225 00:13:56,559 --> 00:13:58,960 Speaker 4: that are, let's say, into being friends of her assers. 226 00:13:59,000 --> 00:14:02,600 Speaker 4: It can be very stabilizing and difficult to sort of 227 00:14:02,600 --> 00:14:04,959 Speaker 4: come to terms with that someone you care about might 228 00:14:05,000 --> 00:14:09,640 Speaker 4: harm someone else. Folks often I've found in my experience, 229 00:14:09,800 --> 00:14:14,600 Speaker 4: So this is like in my observations, like they'll sort 230 00:14:14,640 --> 00:14:19,480 Speaker 4: of reflect on their own personal feelings about it, right, 231 00:14:19,520 --> 00:14:23,320 Speaker 4: and what that says about them. And it's one of 232 00:14:23,320 --> 00:14:26,200 Speaker 4: those things where I like to say, harassment isn't complicated, 233 00:14:26,440 --> 00:14:29,920 Speaker 4: it's your feelings about the harassmer that are complicated, right, Like, 234 00:14:29,960 --> 00:14:33,560 Speaker 4: those are the complexities. So if you're a fan of 235 00:14:33,680 --> 00:14:38,680 Speaker 4: Johnny Depp, it's probably very difficult to reconcile your fandom 236 00:14:39,280 --> 00:14:42,800 Speaker 4: and like this thing you've invested in, even with clear 237 00:14:42,880 --> 00:14:47,920 Speaker 4: evidence that he has harmed someone, right, or if someone 238 00:14:47,960 --> 00:14:50,480 Speaker 4: is your friend. So then what I've found is people 239 00:14:50,520 --> 00:14:53,280 Speaker 4: try to look for logical reasons, like, oh, what did 240 00:14:53,320 --> 00:14:57,480 Speaker 4: the victim do? There must be a reason that this 241 00:14:57,600 --> 00:15:01,520 Speaker 4: thing or person or institution or country I really like 242 00:15:02,240 --> 00:15:05,720 Speaker 4: is doing this. There has to be a logical reason. 243 00:15:06,520 --> 00:15:07,800 Speaker 4: And one of the things I like to point out 244 00:15:07,800 --> 00:15:10,240 Speaker 4: to is like sometimes there's not. It's like the bitch 245 00:15:10,280 --> 00:15:13,000 Speaker 4: eating crackers meme. Someone just might not like that other 246 00:15:13,120 --> 00:15:15,920 Speaker 4: person and that's all that it takes, and they happen 247 00:15:15,960 --> 00:15:19,800 Speaker 4: to like you. And that is sometimes just how harassment unfolds. 248 00:15:19,880 --> 00:15:20,080 Speaker 5: Right. 249 00:15:20,800 --> 00:15:24,440 Speaker 4: Other times people are seeking out a weaker opponent to 250 00:15:24,560 --> 00:15:29,240 Speaker 4: feel stronger. You know, there's all different reasons. My work 251 00:15:29,240 --> 00:15:32,920 Speaker 4: in particular doesn't really focus on the psychology of the 252 00:15:32,960 --> 00:15:35,560 Speaker 4: harasser or why they harass. That doesn't necessarily help me 253 00:15:35,720 --> 00:15:40,680 Speaker 4: help victims. What helps me help victims is often looking 254 00:15:40,680 --> 00:15:43,640 Speaker 4: at like how they're being targeted, how are systems being 255 00:15:43,640 --> 00:15:47,560 Speaker 4: subverted to harm them, how do we improve those systems, 256 00:15:47,560 --> 00:15:50,040 Speaker 4: and how do we also support victims in a trauma 257 00:15:50,080 --> 00:15:53,600 Speaker 4: informed way. So I think this is where we're sort 258 00:15:53,640 --> 00:15:57,240 Speaker 4: of seeing this almost at scale. I think the complexities 259 00:15:57,280 --> 00:16:02,720 Speaker 4: here are also in terms of policy, they get very complex. 260 00:16:03,080 --> 00:16:05,320 Speaker 4: I would say in terms of is it a genocide 261 00:16:05,360 --> 00:16:08,400 Speaker 4: or not complex it is a genocide. But I think 262 00:16:08,400 --> 00:16:12,680 Speaker 4: this is where people also don't understand international relations or 263 00:16:12,720 --> 00:16:16,560 Speaker 4: international politics, I e. That the people of Gaza are 264 00:16:16,600 --> 00:16:20,720 Speaker 4: not Hamas, that they don't understand how like aid work works, 265 00:16:20,760 --> 00:16:24,920 Speaker 4: that they don't understand different rules of law and rules 266 00:16:24,960 --> 00:16:28,480 Speaker 4: of war. In terms of also how or how journalists 267 00:16:28,520 --> 00:16:33,560 Speaker 4: and the media are allowed to engage in document how 268 00:16:33,600 --> 00:16:38,160 Speaker 4: different spaces or sites are targeted or not targeted, right, 269 00:16:38,480 --> 00:16:41,480 Speaker 4: how aid and food is allowed to flow in and out. 270 00:16:41,680 --> 00:16:44,120 Speaker 4: Like these are we work in human rights. These are 271 00:16:44,160 --> 00:16:46,920 Speaker 4: even areas that are complex to me because I don't 272 00:16:46,960 --> 00:16:50,600 Speaker 4: work in like war torn areas, right, So these are 273 00:16:50,640 --> 00:16:54,000 Speaker 4: also very complex systems to myself as someone who is 274 00:16:54,040 --> 00:16:56,680 Speaker 4: a human rights expert. And so I think there's no 275 00:16:57,000 --> 00:17:01,119 Speaker 4: space right now with how Internet conversation has been defined 276 00:17:01,240 --> 00:17:03,320 Speaker 4: or how we're engaging in it to be able to 277 00:17:03,360 --> 00:17:06,320 Speaker 4: have a conversation. I can't give you a one tweet 278 00:17:07,359 --> 00:17:10,040 Speaker 4: description or summary of this, like I have to give 279 00:17:10,080 --> 00:17:13,520 Speaker 4: you a long essay. And then this also butts up 280 00:17:13,560 --> 00:17:19,280 Speaker 4: against you, know, then different kinds of miss and disinformation 281 00:17:19,520 --> 00:17:23,040 Speaker 4: that I think build on what Whitney Phillips calls people's 282 00:17:23,080 --> 00:17:25,840 Speaker 4: deep memetic framework, so beliefs that you have and then 283 00:17:25,880 --> 00:17:29,720 Speaker 4: you see those reflected in other spaces. So if you've 284 00:17:29,720 --> 00:17:33,920 Speaker 4: ever like I'm from Louisiana, I very distinctly remember Hurricane Katrina. 285 00:17:34,600 --> 00:17:37,199 Speaker 4: You know, I can understand how certain folks in New 286 00:17:37,320 --> 00:17:41,200 Speaker 4: Orleans and Louisiana and Mississippi, where my mom's family is from, 287 00:17:41,960 --> 00:17:46,840 Speaker 4: like might have a slight distrust of disaster relief programs 288 00:17:47,000 --> 00:17:49,720 Speaker 4: or trusting the government to like handle disaster relief, right 289 00:17:49,760 --> 00:17:52,840 Speaker 4: because people have lived through many hurricanes and not seen 290 00:17:52,920 --> 00:17:55,800 Speaker 4: that go very well. So, like that's a deep memetic 291 00:17:55,880 --> 00:17:58,959 Speaker 4: frame of them saying like, oh, can I trust an 292 00:17:59,000 --> 00:17:59,960 Speaker 4: international body? 293 00:18:00,240 --> 00:18:00,400 Speaker 5: Right? 294 00:18:00,760 --> 00:18:03,240 Speaker 4: And while those are different things, you can see how 295 00:18:04,040 --> 00:18:06,880 Speaker 4: some of that mistrust gets sown and how like missin 296 00:18:06,920 --> 00:18:12,960 Speaker 4: disinformation can sort of exacerbate that at scale. So then 297 00:18:13,000 --> 00:18:15,800 Speaker 4: how do you have a conversation with someone who's had 298 00:18:15,880 --> 00:18:18,160 Speaker 4: lets of negative experiences with FEMA to then be like, well, 299 00:18:18,200 --> 00:18:20,440 Speaker 4: here's why actually you should trust like this you and 300 00:18:20,600 --> 00:18:24,359 Speaker 4: organization that you've never heard of that only operates in 301 00:18:24,400 --> 00:18:27,640 Speaker 4: this one region. It becomes actually very difficult to have 302 00:18:27,880 --> 00:18:31,280 Speaker 4: those conversations. And I think this is what I mean, 303 00:18:31,400 --> 00:18:33,560 Speaker 4: like these are the ripple effects of not living in 304 00:18:33,600 --> 00:18:37,080 Speaker 4: a harassment literate society, is that we can't look at 305 00:18:37,080 --> 00:18:40,040 Speaker 4: things just through a good and bad binary. You have 306 00:18:40,080 --> 00:18:42,640 Speaker 4: to look at the context. You have to look at 307 00:18:42,960 --> 00:18:45,879 Speaker 4: impact versus intent, So like what is the impact of 308 00:18:45,920 --> 00:18:49,959 Speaker 4: someone's actions versus like what they say their intent is. 309 00:18:50,600 --> 00:18:54,560 Speaker 4: You have to also look at I think, or I think, 310 00:18:54,640 --> 00:18:58,399 Speaker 4: really analyze and think very deeply about one's own ego 311 00:18:58,440 --> 00:19:02,080 Speaker 4: in these situations, and like the seeking of justice or 312 00:19:02,119 --> 00:19:05,640 Speaker 4: like retribution, that that sometimes results in more and more 313 00:19:05,640 --> 00:19:08,720 Speaker 4: and more harm. And this is also very complex in 314 00:19:08,760 --> 00:19:11,080 Speaker 4: which you want to allow a space for victims to 315 00:19:11,160 --> 00:19:15,879 Speaker 4: be able to vocalize anger and distrust and dissent, like 316 00:19:15,880 --> 00:19:18,600 Speaker 4: they're like, you're allowed to be angry. This also then 317 00:19:18,800 --> 00:19:24,160 Speaker 4: conflates or combats our idea very like I would say 318 00:19:24,160 --> 00:19:27,159 Speaker 4: global Northwestern American idea of like what a victim is. 319 00:19:27,240 --> 00:19:29,679 Speaker 4: There isn't one kind of victim. There's so many different 320 00:19:29,760 --> 00:19:33,480 Speaker 4: kinds of victims. There's no one way to embody victimhood. 321 00:19:34,200 --> 00:19:37,119 Speaker 4: And I think that's also a complexity people don't understand, 322 00:19:37,200 --> 00:19:39,800 Speaker 4: which is how we then get into I don't know 323 00:19:39,800 --> 00:19:41,520 Speaker 4: if I believe that person or I would have done 324 00:19:41,560 --> 00:19:44,600 Speaker 4: this in this situation, And the answer is like, you 325 00:19:44,640 --> 00:19:47,119 Speaker 4: don't know what you would do in that situation until 326 00:19:47,119 --> 00:19:51,120 Speaker 4: you're in that situation. And so that's also a very 327 00:19:51,520 --> 00:19:55,440 Speaker 4: strange and skewed way to view how an individual or 328 00:19:55,480 --> 00:20:02,480 Speaker 4: a group of people are responding to trauma. 329 00:20:03,000 --> 00:20:15,360 Speaker 5: Let's take quick break at our back. 330 00:20:16,960 --> 00:20:20,320 Speaker 1: It reminds me so much of what we saw around 331 00:20:20,400 --> 00:20:23,600 Speaker 1: gamer Gate in some ways, and just this idea that 332 00:20:23,960 --> 00:20:27,560 Speaker 1: it's so much about, like what's happening is maybe not 333 00:20:27,680 --> 00:20:31,280 Speaker 1: so complex. The feelings surrounding it might be the complex thing. 334 00:20:31,640 --> 00:20:36,000 Speaker 1: And then the bit where we then don't have a 335 00:20:36,240 --> 00:20:40,280 Speaker 1: media that is informed enough or harassment literate enough to 336 00:20:40,760 --> 00:20:44,360 Speaker 1: really lay out what's happening, right, And so they try 337 00:20:44,400 --> 00:20:47,680 Speaker 1: to find a way of like reporting along those binaries 338 00:20:47,720 --> 00:20:50,880 Speaker 1: of like well maybe they maybe they they really do 339 00:20:51,000 --> 00:20:54,440 Speaker 1: just care about ethics and game journalism, and like maybe 340 00:20:54,480 --> 00:20:56,680 Speaker 1: this woman really did deserve it and have it coming, 341 00:20:56,760 --> 00:20:59,800 Speaker 1: and maybe you know, maybe women have taken things too 342 00:21:00,080 --> 00:21:02,960 Speaker 1: are in their criticism of gaming or whatever. Rather than 343 00:21:03,400 --> 00:21:07,560 Speaker 1: actually laying out like the sort of complexities that you 344 00:21:07,640 --> 00:21:09,679 Speaker 1: did and the nuance that you just did, it's so 345 00:21:09,880 --> 00:21:13,040 Speaker 1: much easier to have it be this binary, simple thing. 346 00:21:13,320 --> 00:21:15,840 Speaker 1: And I almost wonder if they're if they're like giving 347 00:21:15,920 --> 00:21:17,640 Speaker 1: us what we want in a kind of way, because 348 00:21:17,800 --> 00:21:20,960 Speaker 1: we want simple answers. Sometimes we want like oh bad guy, 349 00:21:21,040 --> 00:21:23,280 Speaker 1: good guy, or here's the reason they did that, and 350 00:21:23,920 --> 00:21:26,000 Speaker 1: what they sometimes what we don't want is like, oh, 351 00:21:26,000 --> 00:21:29,600 Speaker 1: well it's actually a really complicated situation totally. 352 00:21:29,600 --> 00:21:32,920 Speaker 4: I mean, this is something I see where I talk 353 00:21:32,960 --> 00:21:36,960 Speaker 4: about a lot in my coaching with different victims of harassment, 354 00:21:37,119 --> 00:21:41,400 Speaker 4: is that one of the one of the very unsatisfying 355 00:21:41,480 --> 00:21:45,440 Speaker 4: things that comes out of of harassment. There's many unsatisfying things. 356 00:21:45,440 --> 00:21:48,560 Speaker 4: There's many awful things. There's many harmful things. Is that 357 00:21:48,880 --> 00:21:51,440 Speaker 4: you might never get a why, and the why might 358 00:21:51,480 --> 00:21:57,880 Speaker 4: be something that feels simplistic or minimal or naive, or 359 00:21:58,320 --> 00:22:01,960 Speaker 4: you know, not even very well thought out. And one 360 00:22:02,000 --> 00:22:06,720 Speaker 4: of the things I try to really coach people through 361 00:22:06,840 --> 00:22:10,159 Speaker 4: is it might also not be worth thinking about why, 362 00:22:11,080 --> 00:22:14,280 Speaker 4: Like it might actually, you know, it is your being targeted, 363 00:22:14,320 --> 00:22:16,680 Speaker 4: but it might not have anything to do with you. 364 00:22:16,960 --> 00:22:20,000 Speaker 4: And in terms of seeking the why, like why this 365 00:22:20,040 --> 00:22:24,160 Speaker 4: person is doing this, that that might not give you 366 00:22:24,240 --> 00:22:26,840 Speaker 4: the peace of mind or the closure that you're looking for. 367 00:22:27,440 --> 00:22:30,480 Speaker 4: And I think that's also I think that's really hard 368 00:22:30,520 --> 00:22:33,439 Speaker 4: for people. And I know that, like when I have 369 00:22:33,480 --> 00:22:36,960 Speaker 4: faced harassment, sometimes that's even hard for me, even though 370 00:22:36,960 --> 00:22:40,120 Speaker 4: I know that, like I know that if someone were 371 00:22:40,160 --> 00:22:43,320 Speaker 4: to tell me why, it wouldn't be it wouldn't be 372 00:22:43,320 --> 00:22:46,399 Speaker 4: the answer that I'm looking for. It maybe wouldn't solve 373 00:22:46,480 --> 00:22:51,440 Speaker 4: any of the conflicting feelings I'm feeling about that particular instance. 374 00:22:52,240 --> 00:22:54,040 Speaker 4: And I think, you know, this is where it is 375 00:22:54,080 --> 00:22:57,480 Speaker 4: sometimes important to separate harrassment research and harassment like literature 376 00:22:57,560 --> 00:23:02,480 Speaker 4: from let's say international politics and war and conflict. But 377 00:23:03,280 --> 00:23:06,639 Speaker 4: I do think it is at times and important to 378 00:23:06,640 --> 00:23:12,000 Speaker 4: sort of understand, Like the why can be incredibly simplistic 379 00:23:12,080 --> 00:23:15,800 Speaker 4: and heavy quotes, like I think a lot about my 380 00:23:15,880 --> 00:23:18,720 Speaker 4: partner's family. He was born in nineteen ninety one in 381 00:23:18,800 --> 00:23:22,359 Speaker 4: the Western Balkans, when Yugoslavia was breaking apart, and like, 382 00:23:22,400 --> 00:23:25,840 Speaker 4: what are the whys there? There's a lot of whys 383 00:23:25,920 --> 00:23:29,399 Speaker 4: that Yugoslavia was breaking apart. There's a lot of whys 384 00:23:29,560 --> 00:23:33,240 Speaker 4: in which a group different groups were targeted, and a 385 00:23:33,240 --> 00:23:35,640 Speaker 4: lot of those whys are not satisfying, you know, because 386 00:23:35,640 --> 00:23:41,560 Speaker 4: it comes down to hate and discrimination and Islamophobia and 387 00:23:41,680 --> 00:23:47,879 Speaker 4: like very entrenched like ethnic ties and views of a 388 00:23:47,880 --> 00:23:51,119 Speaker 4: particular region. And that's an overly simplistic way to even 389 00:23:51,200 --> 00:23:53,879 Speaker 4: look right at that region. But that's also a why, 390 00:23:54,040 --> 00:23:57,200 Speaker 4: and that doesn't explain or excuse anything. And I also 391 00:23:57,280 --> 00:24:01,879 Speaker 4: don't know if that improves what what it feels like 392 00:24:01,960 --> 00:24:04,720 Speaker 4: to have lived through that. That's just an observation, right, 393 00:24:05,280 --> 00:24:09,320 Speaker 4: And I think sometimes you know, some like sometimes the 394 00:24:09,359 --> 00:24:13,200 Speaker 4: most awful things that happen there is a simple answer again, 395 00:24:13,200 --> 00:24:15,359 Speaker 4: which is unsatisfying, which is just we live in a 396 00:24:15,400 --> 00:24:22,000 Speaker 4: society that is full of bias and hate and power differentials. 397 00:24:22,040 --> 00:24:25,520 Speaker 1: True, but I could see how that's not the most 398 00:24:25,800 --> 00:24:30,119 Speaker 1: satisfying answer, particularly if you've been in a situation that 399 00:24:30,160 --> 00:24:32,840 Speaker 1: has like upended your life, right Like if you're like, oh, 400 00:24:33,400 --> 00:24:35,280 Speaker 1: someone got a picture of me at a protest and 401 00:24:35,320 --> 00:24:37,879 Speaker 1: now I am unable to live a normal life. Having 402 00:24:37,880 --> 00:24:41,119 Speaker 1: the answer be like, oh, well, we live in a 403 00:24:41,200 --> 00:24:45,000 Speaker 1: society that's full of hate that people somebody identified you 404 00:24:45,040 --> 00:24:47,359 Speaker 1: as an easy target to pick on, and that's what 405 00:24:47,400 --> 00:24:50,080 Speaker 1: they did. I could see how that could be unsatisfying. 406 00:24:50,200 --> 00:24:52,640 Speaker 1: But it goes back to what you said about sometimes 407 00:24:52,640 --> 00:24:56,920 Speaker 1: the why is not necessarily worth dwelling on totally. 408 00:24:57,000 --> 00:24:58,520 Speaker 4: And this is something where I'd like to say, like 409 00:24:58,840 --> 00:25:01,399 Speaker 4: that also doesn't excuse the harm you're facing, Like like 410 00:25:01,440 --> 00:25:03,680 Speaker 4: you shouldn't be facing that, right, Like that's something that 411 00:25:03,760 --> 00:25:07,520 Speaker 4: no one should be exacting or putting on to you 412 00:25:07,680 --> 00:25:12,080 Speaker 4: for you to experience, which I think is why Sam 413 00:25:12,119 --> 00:25:16,520 Speaker 4: and I really do focus on victims their care. What 414 00:25:16,560 --> 00:25:21,159 Speaker 4: are the ways in which systems, inadvertently or you know, 415 00:25:21,240 --> 00:25:25,640 Speaker 4: via their own design, create space, create flaws and vulnerabilities 416 00:25:25,640 --> 00:25:29,080 Speaker 4: and spaces for harm because I don't need to know 417 00:25:29,119 --> 00:25:31,679 Speaker 4: the why to focus on the victim. We don't need 418 00:25:31,720 --> 00:25:35,720 Speaker 4: to know the why to support someone and even for us, 419 00:25:35,800 --> 00:25:37,320 Speaker 4: I think, even if I were to put on my 420 00:25:37,400 --> 00:25:42,440 Speaker 4: research hat, the why isn't also a satisfying thing for 421 00:25:42,640 --> 00:25:46,199 Speaker 4: me to seek personally, even in a research context. 422 00:25:47,520 --> 00:25:49,080 Speaker 1: So you might be listening to this and think that 423 00:25:49,119 --> 00:25:51,480 Speaker 1: it sounds like I'm trying to dissuade you from showing 424 00:25:51,560 --> 00:25:54,159 Speaker 1: up to a protest irl because you could find yourself 425 00:25:54,240 --> 00:25:57,560 Speaker 1: a target for this kind of harassment surveillance and criminalization. 426 00:25:58,200 --> 00:26:00,679 Speaker 1: But Caroline and Sam don't see it that way. In fact, 427 00:26:00,960 --> 00:26:03,200 Speaker 1: they say that you should still make your voice heard 428 00:26:03,359 --> 00:26:06,240 Speaker 1: while also having a good understanding of the realities of 429 00:26:06,240 --> 00:26:10,240 Speaker 1: our surveillance landscape and what's at stake. When I reached out, 430 00:26:10,560 --> 00:26:12,360 Speaker 1: I thought this conversation was going to be a lot 431 00:26:12,400 --> 00:26:15,280 Speaker 1: more simple that it ended up being. And I think 432 00:26:15,320 --> 00:26:18,639 Speaker 1: that is reflective of the need to talk about this 433 00:26:18,680 --> 00:26:21,360 Speaker 1: whole conversation in a way that is surveillance literate, right, 434 00:26:21,359 --> 00:26:24,840 Speaker 1: that like really takes into account the full sense of 435 00:26:24,920 --> 00:26:29,520 Speaker 1: like why experts like yourselves recommend make certain recommendations to people, 436 00:26:30,280 --> 00:26:35,480 Speaker 1: how it connects to a larger criminalization and surveillance landscape 437 00:26:35,480 --> 00:26:37,800 Speaker 1: when it comes to things like protest in descent, And 438 00:26:37,840 --> 00:26:40,680 Speaker 1: so I wonder, like do you think we live in 439 00:26:40,720 --> 00:26:44,439 Speaker 1: a surveillance literate society, and do you think people have 440 00:26:44,600 --> 00:26:46,920 Speaker 1: a good sense of like how these things are all connected. 441 00:26:48,840 --> 00:26:49,040 Speaker 5: Oh? 442 00:26:49,080 --> 00:26:52,520 Speaker 3: Absolutely, absolutely not. We do not live in a surveillance 443 00:26:53,880 --> 00:26:58,320 Speaker 3: literate society. I mean there's just the capabilities of statent 444 00:26:58,400 --> 00:27:02,919 Speaker 3: on state actors is is not really completely understood. I 445 00:27:02,920 --> 00:27:06,840 Speaker 3: feel like people are oftentimes protesters or activists, shall we say, 446 00:27:06,920 --> 00:27:11,240 Speaker 3: are oftentimes operating with a knowledge base that's maybe like five, ten, 447 00:27:11,760 --> 00:27:17,240 Speaker 3: fifteen years even sometimes backdated. So or sometimes people will 448 00:27:17,280 --> 00:27:20,800 Speaker 3: just be like, oh, well, the adversary maybe the state 449 00:27:21,480 --> 00:27:24,199 Speaker 3: we'll say that's the adversary in this example is so 450 00:27:24,280 --> 00:27:27,760 Speaker 3: advanced that why should I even bother? Like they can 451 00:27:27,920 --> 00:27:31,600 Speaker 3: read everything that I'm doing, they can read my mind. 452 00:27:32,160 --> 00:27:36,879 Speaker 2: Basically, They're just that capable. Not the case. 453 00:27:38,400 --> 00:27:45,119 Speaker 3: The opposition is oftentimes not as sophisticated as we think. 454 00:27:45,880 --> 00:27:49,320 Speaker 3: And there are things that we can implement best practices 455 00:27:49,760 --> 00:27:53,840 Speaker 3: in digital security and privacy that we can implement that 456 00:27:53,920 --> 00:27:59,480 Speaker 3: will keep us safe er. And it's like super simple 457 00:27:59,480 --> 00:28:03,760 Speaker 3: stuff you signal with disappearing messages for communications, like don't 458 00:28:03,800 --> 00:28:09,080 Speaker 3: just use text messages or phone calls, like super simple 459 00:28:09,119 --> 00:28:13,520 Speaker 3: stuff like that will keep people safer, like you said 460 00:28:13,560 --> 00:28:16,520 Speaker 3: in the beginning of this podcast, like don't have a 461 00:28:16,680 --> 00:28:20,040 Speaker 3: face unlock on your phone or fingerprint unlock on your phone, 462 00:28:20,920 --> 00:28:23,680 Speaker 3: because the cops, if you are arrested, can just take 463 00:28:23,720 --> 00:28:25,159 Speaker 3: the phone and hold it up to your face and 464 00:28:25,160 --> 00:28:27,359 Speaker 3: then unlock your phone. 465 00:28:27,600 --> 00:28:31,359 Speaker 2: Stuff like that. But backing up a little to surveillance. 466 00:28:32,680 --> 00:28:39,080 Speaker 3: You know, the capacity for surveillance is really increased with 467 00:28:39,240 --> 00:28:46,080 Speaker 3: the proliferation of AI assisted facial recognition or you know 468 00:28:46,400 --> 00:28:50,280 Speaker 3: HD cameras that can do like a thousand X zoom 469 00:28:51,000 --> 00:28:55,920 Speaker 3: and still have like four K quality, or even like 470 00:28:56,200 --> 00:28:58,680 Speaker 3: we could talk about all the different optics that are 471 00:28:58,680 --> 00:29:01,800 Speaker 3: on like helicopter cameras, police helicopter cameras that can like 472 00:29:01,840 --> 00:29:06,360 Speaker 3: see in thermal, in infrared, in different heat signature patterns 473 00:29:06,400 --> 00:29:12,560 Speaker 3: in you know, movement outlines and stuff like that, to 474 00:29:12,840 --> 00:29:16,320 Speaker 3: where they can also like zoom in to where they 475 00:29:16,320 --> 00:29:20,320 Speaker 3: can essentially see a protesters screen on their phone from 476 00:29:20,360 --> 00:29:20,960 Speaker 3: a helicopter. 477 00:29:21,320 --> 00:29:21,920 Speaker 2: That type of. 478 00:29:21,840 --> 00:29:26,280 Speaker 3: Stuff, or just like super stuff that's been around for 479 00:29:26,320 --> 00:29:28,880 Speaker 3: like decades, like police poll cams that they'll just like 480 00:29:29,240 --> 00:29:34,080 Speaker 3: stick somewhere and people just won't notice, or applars, automatic 481 00:29:34,160 --> 00:29:37,400 Speaker 3: license plate readers to kind of map, like where people 482 00:29:37,440 --> 00:29:41,160 Speaker 3: are driving around all of these things. They exist, they're 483 00:29:41,200 --> 00:29:45,080 Speaker 3: in the real world, and they're used by law enforcement 484 00:29:45,600 --> 00:29:47,920 Speaker 3: on a daily basis almost And this is just like 485 00:29:48,000 --> 00:29:49,680 Speaker 3: the physical world that we're talking about. 486 00:29:49,720 --> 00:29:52,200 Speaker 2: This isn't even the digital world where we're. 487 00:29:52,000 --> 00:29:57,680 Speaker 3: Talking about, like them having the capabilities of seeing all 488 00:29:57,720 --> 00:30:03,600 Speaker 3: of your social media accounts interlinked and essentially pulled together 489 00:30:03,640 --> 00:30:07,120 Speaker 3: in one little package deal that is maybe like this 490 00:30:07,280 --> 00:30:10,880 Speaker 3: is Sam, Like this is his Facebook, this is his Instagram, 491 00:30:10,920 --> 00:30:13,479 Speaker 3: this is his Tumblr, this is his MySpace from fifteen 492 00:30:13,560 --> 00:30:18,520 Speaker 3: years ago. They have these capabilities, but we can do 493 00:30:18,640 --> 00:30:25,360 Speaker 3: things to prevent them from having fuller access to them, 494 00:30:25,320 --> 00:30:29,000 Speaker 3: and we can make things private. We can have burner accounts, 495 00:30:29,000 --> 00:30:32,800 Speaker 3: burner emails, burner phone numbers, things that aren't maybe directly 496 00:30:32,840 --> 00:30:33,760 Speaker 3: associated with us. 497 00:30:33,800 --> 00:30:35,080 Speaker 2: And there again this. 498 00:30:35,080 --> 00:30:39,440 Speaker 3: Does boil back down to best practices in digital security 499 00:30:39,440 --> 00:30:40,080 Speaker 3: and privacy. 500 00:30:40,960 --> 00:30:44,280 Speaker 1: Yeah, I have heard the feeling like, oh, the state 501 00:30:44,400 --> 00:30:47,280 Speaker 1: they have everything about me? Why bother? I've heard that 502 00:30:47,360 --> 00:30:51,240 Speaker 1: described as like a kind of nihilism, like surveillance nihilism, 503 00:30:51,240 --> 00:30:55,440 Speaker 1: where you're like it doesn't even matter anymore. I like, 504 00:30:56,320 --> 00:30:59,120 Speaker 1: I get it, because the list of ways the state 505 00:30:59,480 --> 00:31:02,120 Speaker 1: surveils US is vast and I could see, I could 506 00:31:02,280 --> 00:31:07,240 Speaker 1: I totally understand that as a reaction, but Sam, you're 507 00:31:07,280 --> 00:31:10,160 Speaker 1: so right like it. There are still things we could do, 508 00:31:10,560 --> 00:31:14,800 Speaker 1: basic steps that we could take to maintain privacy, and 509 00:31:14,840 --> 00:31:17,600 Speaker 1: I think the state, it kind of like, is counting 510 00:31:17,640 --> 00:31:19,600 Speaker 1: on us being like, oh, well, there's no point of 511 00:31:19,640 --> 00:31:21,040 Speaker 1: doing any of this. I may as well just leave 512 00:31:21,040 --> 00:31:22,840 Speaker 1: my phone unlocked. I may as well just like not 513 00:31:22,920 --> 00:31:25,440 Speaker 1: wear a mask. I may as well just whatever, because 514 00:31:25,440 --> 00:31:27,240 Speaker 1: they already you know, they already have everything. 515 00:31:27,520 --> 00:31:27,800 Speaker 5: It is. 516 00:31:27,960 --> 00:31:29,800 Speaker 1: It is, there are things you can do, and the 517 00:31:29,840 --> 00:31:33,120 Speaker 1: state totally benefits from us thinking that that's not true, 518 00:31:33,120 --> 00:31:35,400 Speaker 1: that there's nothing we can do, despite the fact that 519 00:31:35,440 --> 00:31:38,600 Speaker 1: I do understand that as a reaction totally. 520 00:31:38,640 --> 00:31:41,720 Speaker 4: And I think there's something else also here too, where 521 00:31:42,960 --> 00:31:45,520 Speaker 4: I want to highlight where I'm about to say sounds contradictory, 522 00:31:45,520 --> 00:31:48,920 Speaker 4: and I'm going to try my best to say it 523 00:31:48,960 --> 00:31:53,480 Speaker 4: in a way with nuance lay it on us. The 524 00:31:53,520 --> 00:31:56,160 Speaker 4: state is very powerful, and I think also at times 525 00:31:56,240 --> 00:32:00,720 Speaker 4: people overestimate or don't totally understand how the tools of 526 00:32:00,760 --> 00:32:03,240 Speaker 4: the state work, so they have a lot of data 527 00:32:03,800 --> 00:32:07,080 Speaker 4: on us. But also like there's a lot of things 528 00:32:07,120 --> 00:32:10,760 Speaker 4: that surveillance technology can't do that. I think often people 529 00:32:10,800 --> 00:32:16,480 Speaker 4: misunderstand that it can do. And I think that isn't 530 00:32:16,640 --> 00:32:19,000 Speaker 4: That isn't to say we should all take a sigh 531 00:32:19,040 --> 00:32:21,680 Speaker 4: of relief, you know. I think we should all be 532 00:32:21,720 --> 00:32:25,560 Speaker 4: like breathing in and out constantly, you know, trying to 533 00:32:25,640 --> 00:32:28,320 Speaker 4: quell different levels of anxiety. And I say, this is 534 00:32:28,360 --> 00:32:29,600 Speaker 4: a highly anxious person. 535 00:32:29,920 --> 00:32:30,240 Speaker 5: Same. 536 00:32:31,040 --> 00:32:33,560 Speaker 4: But but one of the things I think it is important, 537 00:32:33,560 --> 00:32:35,840 Speaker 4: and I'm thinking about this in like a protest context, 538 00:32:36,040 --> 00:32:39,440 Speaker 4: is you know, like the state has a lot of 539 00:32:39,520 --> 00:32:43,440 Speaker 4: data on a lot of people, as we learned from 540 00:32:44,000 --> 00:32:48,160 Speaker 4: from like Edward Snowden and and like the prison program 541 00:32:48,200 --> 00:32:51,640 Speaker 4: for example. But also there's like so much data that 542 00:32:51,680 --> 00:32:54,000 Speaker 4: at times it can be hard to identify people. And 543 00:32:54,000 --> 00:32:56,320 Speaker 4: that's the other end of security nihilism that I see 544 00:32:56,520 --> 00:32:58,800 Speaker 4: is people being like, I'm just a drop of data 545 00:32:58,840 --> 00:33:02,280 Speaker 4: in a very large data bucket. And for me, it's like, well, 546 00:33:02,320 --> 00:33:04,920 Speaker 4: you never know when the state is going to decide 547 00:33:04,920 --> 00:33:09,040 Speaker 4: to look at you, And if you have any marginalized identity, 548 00:33:09,120 --> 00:33:13,600 Speaker 4: then you know already that bad actors of the state, 549 00:33:13,760 --> 00:33:15,960 Speaker 4: like a local police force, they don't need very much 550 00:33:16,360 --> 00:33:18,480 Speaker 4: to decide to look at you. In fact, they need 551 00:33:18,480 --> 00:33:22,880 Speaker 4: almost nothing to decide to arrest you to like, you know, 552 00:33:23,120 --> 00:33:26,280 Speaker 4: fuck up aspects of your life, et cetera. And that's 553 00:33:26,280 --> 00:33:29,600 Speaker 4: only getting more and more worse now, especially in the 554 00:33:29,720 --> 00:33:32,560 Speaker 4: United States. If we look at the overturning of Roe v. Wade, 555 00:33:32,640 --> 00:33:35,960 Speaker 4: of attacks on gender affirming care, like it's so difficult 556 00:33:36,000 --> 00:33:38,160 Speaker 4: to sort of just do things we should be able 557 00:33:38,240 --> 00:33:40,640 Speaker 4: to do. One of the things I want to highlight 558 00:33:40,640 --> 00:33:42,320 Speaker 4: this is something I think we've seen a little bit 559 00:33:42,320 --> 00:33:47,320 Speaker 4: in our training, is people sort of at times sort 560 00:33:47,360 --> 00:33:51,880 Speaker 4: of assuming that let's say, like police surveillance is magical, 561 00:33:52,440 --> 00:33:56,360 Speaker 4: or that like AI is magical. It's not. There are 562 00:33:56,440 --> 00:33:59,280 Speaker 4: things we actually can do to be safe. And I 563 00:33:59,320 --> 00:34:02,560 Speaker 4: think that's like what I want to sort of emphasize. 564 00:34:02,560 --> 00:34:04,680 Speaker 4: This is like the space of nuance, Like we should 565 00:34:04,720 --> 00:34:07,360 Speaker 4: be afraid, and also there are things we can do 566 00:34:08,160 --> 00:34:11,000 Speaker 4: to try to like mitigate and reduce these harms and 567 00:34:11,120 --> 00:34:15,440 Speaker 4: be safer, and we should do those things. We should 568 00:34:15,520 --> 00:34:17,480 Speaker 4: especially do those things, and we should do those things 569 00:34:17,480 --> 00:34:22,040 Speaker 4: if we're also in community with marginalized community members. So 570 00:34:22,239 --> 00:34:27,720 Speaker 4: like I'm a white, non binary person, you know, I 571 00:34:27,800 --> 00:34:30,600 Speaker 4: was born in the United States. For me, going to 572 00:34:30,719 --> 00:34:34,560 Speaker 4: a protest unmasked even though it's COVID, So actually you 573 00:34:34,560 --> 00:34:37,759 Speaker 4: should all be wearing masks out there anyway. But like 574 00:34:37,840 --> 00:34:40,880 Speaker 4: if I were to go hypothetically unmasked, which I wouldn't do, 575 00:34:42,760 --> 00:34:44,680 Speaker 4: Like me getting arrested is very different than someone else 576 00:34:44,760 --> 00:34:47,239 Speaker 4: getting arrested. But I shouldn't be worried just about me. 577 00:34:47,920 --> 00:34:50,399 Speaker 4: I should be worried about the people I'm standing with, right, 578 00:34:50,800 --> 00:34:53,319 Speaker 4: And I should be worried about how I've saved those 579 00:34:53,320 --> 00:34:56,160 Speaker 4: people in my phone, And I should be worried about 580 00:34:56,280 --> 00:34:58,920 Speaker 4: what kinds of things can be done with just a 581 00:34:58,960 --> 00:35:02,360 Speaker 4: little bit of like nudging from the police. 582 00:35:02,680 --> 00:35:02,879 Speaker 5: Right. 583 00:35:03,400 --> 00:35:08,120 Speaker 4: And this is where understanding security measures and privacy measures 584 00:35:08,480 --> 00:35:11,920 Speaker 4: and having good what Matt Mitchell calls like security hygiene 585 00:35:11,920 --> 00:35:16,440 Speaker 4: and digital hygiene is really important. Right, So like disappearing messages, 586 00:35:16,560 --> 00:35:20,520 Speaker 4: using signal, not bringing my phone at all to a protest, 587 00:35:21,080 --> 00:35:25,120 Speaker 4: these are really helpful things versus going to a protest 588 00:35:25,160 --> 00:35:28,880 Speaker 4: and thinking you need like a farity bag and a 589 00:35:28,960 --> 00:35:31,719 Speaker 4: mic jammer and all these things. But then let's say 590 00:35:31,760 --> 00:35:35,600 Speaker 4: you're connecting to public Wi Fi and you're messaging and 591 00:35:35,640 --> 00:35:39,759 Speaker 4: you're posting on Twitter, like that has almost negated the 592 00:35:39,840 --> 00:35:42,560 Speaker 4: other things you also don't necessarily need something like a 593 00:35:42,600 --> 00:35:46,520 Speaker 4: mic jammer if you like, you know, if you don't 594 00:35:46,520 --> 00:35:47,680 Speaker 4: have malware on your phone. 595 00:35:47,760 --> 00:35:47,920 Speaker 2: Right. 596 00:35:47,960 --> 00:35:50,200 Speaker 4: So I think that there's these things where people sometimes 597 00:35:50,640 --> 00:35:55,160 Speaker 4: sort of over estimate the capabilities of some of the 598 00:35:55,200 --> 00:35:59,880 Speaker 4: tools that the police have and then underestimate how little 599 00:36:00,160 --> 00:36:04,040 Speaker 4: evidence the state needs to seize your devices or be 600 00:36:04,120 --> 00:36:07,920 Speaker 4: able to engage with with your phone. And so I 601 00:36:07,920 --> 00:36:10,400 Speaker 4: think it's this balance of understanding where it does like 602 00:36:10,760 --> 00:36:17,720 Speaker 4: security on the device stop, and like good protest tactics start, 603 00:36:17,840 --> 00:36:21,359 Speaker 4: like my good physical security, right, And I think these 604 00:36:21,400 --> 00:36:25,240 Speaker 4: are very much intertwined. And I think that's also another 605 00:36:25,320 --> 00:36:29,439 Speaker 4: level of complexity we've been dealing with, Like we've also 606 00:36:29,480 --> 00:36:32,080 Speaker 4: worked with activists who are really nervous and like want 607 00:36:32,120 --> 00:36:34,680 Speaker 4: to put their phone in the freezer or the microwave. 608 00:36:34,800 --> 00:36:37,200 Speaker 4: And you know, that's something too where it's like I 609 00:36:37,239 --> 00:36:40,799 Speaker 4: totally hear that you're scared if you want to do that, 610 00:36:41,640 --> 00:36:44,840 Speaker 4: Like I can understand how that makes you feel safer, 611 00:36:45,120 --> 00:36:48,319 Speaker 4: But the issue more is like, let's talk about what 612 00:36:48,360 --> 00:36:51,759 Speaker 4: would be happening on your phone that would cause that 613 00:36:51,920 --> 00:36:57,080 Speaker 4: to happen, and also that there's an even more serious 614 00:36:57,160 --> 00:36:59,279 Speaker 4: question of that means there's something on your phone that 615 00:36:59,360 --> 00:37:02,719 Speaker 4: is the listening in all other different instances, and so 616 00:37:03,680 --> 00:37:06,200 Speaker 4: if you're really worried about that, then the problem is 617 00:37:06,200 --> 00:37:07,920 Speaker 4: something we need to look at on the phone. 618 00:37:08,400 --> 00:37:08,600 Speaker 2: Right. 619 00:37:08,640 --> 00:37:13,160 Speaker 4: The problem is spyware or malware on your phone, right, 620 00:37:14,040 --> 00:37:17,759 Speaker 4: And that's something we need to deal with immediately. And 621 00:37:17,840 --> 00:37:20,960 Speaker 4: I think that's also something that I think is very 622 00:37:21,000 --> 00:37:26,040 Speaker 4: difficult to understand or work through if if you aren't 623 00:37:26,040 --> 00:37:29,600 Speaker 4: a technology expert. And that sucks, because you know, we 624 00:37:29,640 --> 00:37:35,120 Speaker 4: want people to have the most accurate and like salient 625 00:37:35,160 --> 00:37:39,200 Speaker 4: information as possible, and it I think a lot of 626 00:37:39,200 --> 00:37:41,840 Speaker 4: barriers to this is having to be constantly updated with 627 00:37:42,200 --> 00:37:45,040 Speaker 4: how technology works, what are the different kinds of tools 628 00:37:45,040 --> 00:37:47,200 Speaker 4: and apparatuses of the state, and then how do you 629 00:37:47,239 --> 00:37:49,680 Speaker 4: get that information into people's hands. 630 00:37:54,800 --> 00:38:10,719 Speaker 1: More after a quick break, let's get right back into it. Yeah, 631 00:38:10,719 --> 00:38:13,080 Speaker 1: I'm almost cringing a little bit because I definitely went 632 00:38:13,120 --> 00:38:15,920 Speaker 1: to a meeting where we all put our phones in 633 00:38:15,920 --> 00:38:18,279 Speaker 1: the freezer because somebody saw it on the Snowden Doc. 634 00:38:18,400 --> 00:38:21,719 Speaker 1: And then I definitely like logged onto Starbucks WiFi. I 635 00:38:21,760 --> 00:38:24,120 Speaker 1: had a whole conversation about what we talked about via 636 00:38:25,000 --> 00:38:29,600 Speaker 1: Starbucks WiFi, via just SMS messengers like oh well, like 637 00:38:30,200 --> 00:38:33,640 Speaker 1: the more like it felt cool to put our phones 638 00:38:33,680 --> 00:38:36,680 Speaker 1: in the freezer, but I took no other security steps 639 00:38:36,680 --> 00:38:38,960 Speaker 1: that day, and in fact did things that were like 640 00:38:39,120 --> 00:38:43,840 Speaker 1: risky that you know, a little common sense, basic considerations 641 00:38:44,080 --> 00:38:48,000 Speaker 1: would have probably been more effective or made a bigger 642 00:38:48,000 --> 00:38:51,920 Speaker 1: impact on my security or my made a bigger impact 643 00:38:51,960 --> 00:38:54,000 Speaker 1: on my security than like, let's all put our phones 644 00:38:54,000 --> 00:38:56,800 Speaker 1: in the freezer. And I think, Caroline, you made a 645 00:38:56,840 --> 00:39:01,480 Speaker 1: point about people not being tech expert. I wonder, you know, 646 00:39:01,560 --> 00:39:04,480 Speaker 1: in twenty twenty four, with the ubiquity of smartphones and 647 00:39:04,520 --> 00:39:08,080 Speaker 1: facial recognition technology and doxing and like all of these 648 00:39:08,800 --> 00:39:13,840 Speaker 1: technological innovations and advancements, do you think that folks feel 649 00:39:14,080 --> 00:39:17,239 Speaker 1: a barrier to protest or to speak up and use 650 00:39:17,280 --> 00:39:20,279 Speaker 1: their voices because it seems like, well, this is so much, 651 00:39:20,360 --> 00:39:23,680 Speaker 1: this is so opaque. Some of the guides and way 652 00:39:23,680 --> 00:39:28,080 Speaker 1: that people talk about technology and security feels not accessible. 653 00:39:28,239 --> 00:39:30,279 Speaker 1: So I'm just gonna like not show up because who 654 00:39:30,320 --> 00:39:32,560 Speaker 1: has the time? Like I wonder, is that something that 655 00:39:32,560 --> 00:39:33,439 Speaker 1: you've seen in your work? 656 00:39:33,880 --> 00:39:36,880 Speaker 4: So I haven't personally seen that, And some of that 657 00:39:37,040 --> 00:39:39,719 Speaker 4: I will highlight might be from where we sit as 658 00:39:39,760 --> 00:39:44,880 Speaker 4: an organization because we tend to work with other community organizations. 659 00:39:45,480 --> 00:39:49,160 Speaker 4: We tend to work with human rights defenders, journalists, activists, 660 00:39:49,760 --> 00:39:53,120 Speaker 4: and then members of the general public who like want 661 00:39:53,200 --> 00:39:56,000 Speaker 4: to engage with this knowledge. So I would say that like, 662 00:39:56,120 --> 00:39:59,680 Speaker 4: I haven't seen necessarily a deterrence. What I have seen 663 00:39:59,760 --> 00:40:03,960 Speaker 4: is people showing up but still being scared and or 664 00:40:04,800 --> 00:40:10,000 Speaker 4: showing up and then something bad happens and they weren't prepared, 665 00:40:10,239 --> 00:40:13,480 Speaker 4: let's say, for for for what was happening, and that 666 00:40:13,560 --> 00:40:15,560 Speaker 4: I want to highlight that's not there. That's not their fault, 667 00:40:15,680 --> 00:40:20,160 Speaker 4: Like we live under surveillance capitalism, how software and hardware 668 00:40:20,200 --> 00:40:22,760 Speaker 4: has been designed is not the fault of the user 669 00:40:23,040 --> 00:40:27,200 Speaker 4: or the vulnerable individual. That's the fault of capitalism and 670 00:40:27,239 --> 00:40:30,960 Speaker 4: big tech. And like a lot of not regulation we 671 00:40:31,040 --> 00:40:33,960 Speaker 4: have in the United States, right, and so I think 672 00:40:34,120 --> 00:40:37,719 Speaker 4: luckily at least you know, Again, also we're speaking from 673 00:40:37,760 --> 00:40:42,520 Speaker 4: a very specific sort of space convocation, our lab, in 674 00:40:42,560 --> 00:40:45,799 Speaker 4: which we are often engaging with people that are you know, 675 00:40:45,880 --> 00:40:51,200 Speaker 4: human rights defenders, journalists, activists, community organizations. So we haven't 676 00:40:51,280 --> 00:40:54,640 Speaker 4: seen a hesitation. But what we have seen is people 677 00:40:54,680 --> 00:40:59,840 Speaker 4: recognizing that there are like skills and tools that they 678 00:41:00,200 --> 00:41:03,160 Speaker 4: that they don't have, and they're seeing that also in 679 00:41:03,200 --> 00:41:07,160 Speaker 4: real time. I think right now because of the amount 680 00:41:07,200 --> 00:41:11,799 Speaker 4: of doxing attempts that are happening on social media, and 681 00:41:11,880 --> 00:41:14,000 Speaker 4: so I think that's weighing into our people are now 682 00:41:14,719 --> 00:41:17,520 Speaker 4: a bit more aware. You know, there's been many stories, 683 00:41:17,560 --> 00:41:20,000 Speaker 4: as you know, Bridges, as you pointed out, with billion 684 00:41:20,000 --> 00:41:23,920 Speaker 4: paires renting buses and putting people's faces on them or 685 00:41:23,920 --> 00:41:27,080 Speaker 4: putting people's names on them. And I think that is, 686 00:41:27,520 --> 00:41:29,359 Speaker 4: you know, causing folks to reflect and be like, oh, 687 00:41:29,360 --> 00:41:31,400 Speaker 4: like that could be me, and I still need to 688 00:41:31,400 --> 00:41:34,160 Speaker 4: show up. I still want to show up, but how 689 00:41:34,200 --> 00:41:37,520 Speaker 4: do I how do I create or maintain some safety 690 00:41:37,560 --> 00:41:40,120 Speaker 4: knowing that that is a potential outcome. So that's a 691 00:41:40,120 --> 00:41:43,200 Speaker 4: little bit more of I think what we've been seeing. 692 00:41:43,520 --> 00:41:46,480 Speaker 1: I started this conversation wanting to use the focus or 693 00:41:46,520 --> 00:41:50,200 Speaker 1: framing of like campus protesters, campus activists, and what's happening 694 00:41:50,239 --> 00:41:52,719 Speaker 1: on campus is right now, But how have you seen 695 00:41:52,760 --> 00:41:55,960 Speaker 1: these same tactics being used to target anybody, like people 696 00:41:55,960 --> 00:41:59,760 Speaker 1: who are not necessarily protesters, who maybe work for companies 697 00:41:59,760 --> 00:42:03,400 Speaker 1: that are like deemed to woke or have in some 698 00:42:03,520 --> 00:42:07,960 Speaker 1: way have been like perceived as ideologically against the bad 699 00:42:08,000 --> 00:42:10,279 Speaker 1: actors who are doing the dosing, Like, is this the 700 00:42:10,360 --> 00:42:13,839 Speaker 1: kind of threat that really all of us might need 701 00:42:13,880 --> 00:42:15,640 Speaker 1: to be aware of, whether or not we've ever set 702 00:42:15,719 --> 00:42:17,800 Speaker 1: foot on an IRL protest on a campus. 703 00:42:18,840 --> 00:42:22,719 Speaker 4: I would say so. I would say, with how you know, 704 00:42:23,080 --> 00:42:27,400 Speaker 4: regardless of the country you live in, with how politics 705 00:42:27,400 --> 00:42:29,839 Speaker 4: have been going over the past few years, it is 706 00:42:30,239 --> 00:42:35,440 Speaker 4: always good. It's very important to be thinking about your 707 00:42:35,440 --> 00:42:39,040 Speaker 4: own digital footprint, data that's out there about you, and 708 00:42:39,160 --> 00:42:41,680 Speaker 4: how it can be used or misused to harm you. 709 00:42:42,520 --> 00:42:47,040 Speaker 4: I think that that's something we all now especially really 710 00:42:47,040 --> 00:42:48,240 Speaker 4: need to be thinking about. 711 00:42:49,120 --> 00:42:51,120 Speaker 1: I don't want people to listen to this episode and 712 00:42:51,320 --> 00:42:54,960 Speaker 1: think every threat that we have discussed is something that 713 00:42:55,000 --> 00:42:59,360 Speaker 1: they personally like, will be are likely to become a 714 00:42:59,360 --> 00:43:02,239 Speaker 1: target for. Like, I don't want people to be paranoid. 715 00:43:02,280 --> 00:43:04,800 Speaker 1: I want people to be informed and smart, right, And 716 00:43:04,840 --> 00:43:08,480 Speaker 1: I guess, like, in your work, how have you prepared 717 00:43:08,560 --> 00:43:12,600 Speaker 1: people to understand like they're specific their specific needs in 718 00:43:12,640 --> 00:43:13,480 Speaker 1: this whole conversation. 719 00:43:14,080 --> 00:43:15,960 Speaker 4: Oh gosh, I think this is one of the hardest things. 720 00:43:16,040 --> 00:43:18,520 Speaker 4: This is where this is why we do I think 721 00:43:18,560 --> 00:43:21,640 Speaker 4: really targeted workshops. But Samya, do you want to do 722 00:43:21,680 --> 00:43:22,000 Speaker 4: you want to. 723 00:43:21,960 --> 00:43:25,040 Speaker 2: Weigh in the answer is threat modeling. 724 00:43:25,600 --> 00:43:29,160 Speaker 4: Oh, you were going to say that, I was going 725 00:43:29,239 --> 00:43:31,480 Speaker 4: to say that, Sam is going to say it. 726 00:43:31,719 --> 00:43:35,719 Speaker 3: Well, we all have different threat models, right, and what 727 00:43:36,239 --> 00:43:38,439 Speaker 3: Carl's threat model is going to be way different than mine, 728 00:43:38,719 --> 00:43:41,280 Speaker 3: and what bridgets is is going to be way different 729 00:43:41,320 --> 00:43:45,120 Speaker 3: than Carlos. Threat modeling is the process of trying to 730 00:43:45,160 --> 00:43:51,200 Speaker 3: figure out the possibility or probability of a threat that 731 00:43:52,160 --> 00:43:59,640 Speaker 3: the person may encounter and weighing that weighing the consequences 732 00:43:59,680 --> 00:44:03,759 Speaker 3: of that threat on how realistic it is that it 733 00:44:03,800 --> 00:44:07,239 Speaker 3: will happen or will not happen. And I think that 734 00:44:07,960 --> 00:44:13,640 Speaker 3: people can try to figure out what their personal threat 735 00:44:13,640 --> 00:44:19,600 Speaker 3: model is by considering who the bad actors that they 736 00:44:19,600 --> 00:44:24,080 Speaker 3: may encounter are and what their capabilities are, and then 737 00:44:24,840 --> 00:44:27,800 Speaker 3: what they're trying to protect. So that might maybe student 738 00:44:28,120 --> 00:44:33,040 Speaker 3: protesters that want to keep their anonymity, and so maybe 739 00:44:33,080 --> 00:44:35,799 Speaker 3: they will not bring their phone to a protest, or 740 00:44:35,840 --> 00:44:38,920 Speaker 3: maybe they will wear a mask or cover their tattoos 741 00:44:38,960 --> 00:44:45,640 Speaker 3: in order to not be identified physically. So that's just 742 00:44:45,680 --> 00:44:49,520 Speaker 3: like one example of a of a threat posed to 743 00:44:52,920 --> 00:44:57,600 Speaker 3: campus activists. And this threat modeling process can really be 744 00:44:59,360 --> 00:45:03,080 Speaker 3: used for all aspects of life. You can threat model 745 00:45:03,360 --> 00:45:05,360 Speaker 3: everything in your daily life. 746 00:45:05,480 --> 00:45:07,279 Speaker 4: I mean, I just to build on that. Like one 747 00:45:07,320 --> 00:45:09,440 Speaker 4: thing I want to highlight is we all threat model 748 00:45:09,640 --> 00:45:12,759 Speaker 4: every day, as Sam is saying, like you can use 749 00:45:12,760 --> 00:45:14,680 Speaker 4: it in your everyday life, and you do, Like when 750 00:45:14,719 --> 00:45:17,359 Speaker 4: you decide to cross the street not at the light, 751 00:45:18,080 --> 00:45:20,719 Speaker 4: you are threat modeling right when you're sort of making 752 00:45:20,719 --> 00:45:26,560 Speaker 4: a decision around how you're going to get home or 753 00:45:26,600 --> 00:45:29,040 Speaker 4: go to go somewhere. That is like a form of 754 00:45:29,400 --> 00:45:33,960 Speaker 4: threat modeling. And I think I think that there, this 755 00:45:34,080 --> 00:45:36,440 Speaker 4: is I think this is what gets really tied into 756 00:45:36,480 --> 00:45:40,240 Speaker 4: then trying to understand a bit more about surveillance literacy 757 00:45:40,520 --> 00:45:43,600 Speaker 4: and like security literacy and privacy literacy is really important. 758 00:45:43,640 --> 00:45:48,440 Speaker 4: Threat modeling is incredibly important. It's how you can decide, 759 00:45:48,960 --> 00:45:52,319 Speaker 4: you know, it's how you can maintain some safety. What 760 00:45:52,440 --> 00:45:55,880 Speaker 4: I think is harder when the challenges is also helping 761 00:45:55,960 --> 00:46:01,120 Speaker 4: folks feel safe and secure around threat mode. And some 762 00:46:01,200 --> 00:46:03,879 Speaker 4: of that now comes down to how do we understand 763 00:46:03,960 --> 00:46:09,040 Speaker 4: like the tactics and tools of our adversaries. That's understanding 764 00:46:09,040 --> 00:46:11,719 Speaker 4: there why right so why it doesn't matter, but it's 765 00:46:11,800 --> 00:46:15,160 Speaker 4: understanding like what are they using? And so I think 766 00:46:15,960 --> 00:46:21,520 Speaker 4: for folks that are going to actions, please go. Please 767 00:46:22,200 --> 00:46:26,200 Speaker 4: try to wear something that sort of helps anonymize you. 768 00:46:26,719 --> 00:46:32,040 Speaker 4: So I would not recommend wearing your you know, cal 769 00:46:32,200 --> 00:46:39,080 Speaker 4: state the year you're graduating shirt, or like your really 770 00:46:39,120 --> 00:46:42,080 Speaker 4: awesome jacket that you made that's one of a kind. 771 00:46:43,080 --> 00:46:46,400 Speaker 4: I would recommend wearing something that's a little bit more plain. 772 00:46:47,320 --> 00:46:51,400 Speaker 4: I would really try to cover your face, cover your tattoos. 773 00:46:52,880 --> 00:46:55,400 Speaker 4: I would recommend leaving your phone at home if you 774 00:46:55,440 --> 00:47:00,000 Speaker 4: feel comfortable doing that, you know, I think this gets 775 00:47:00,080 --> 00:47:02,960 Speaker 4: into a different space if we're talking about folks that 776 00:47:03,040 --> 00:47:12,080 Speaker 4: are either there to observe or document. There's a lot 777 00:47:12,080 --> 00:47:16,000 Speaker 4: of great guides out there on how to document a 778 00:47:16,000 --> 00:47:20,920 Speaker 4: protest safely. Some of that, you know, we point to 779 00:47:20,960 --> 00:47:24,799 Speaker 4: our friends at open Archive and Witness who have really 780 00:47:24,800 --> 00:47:28,160 Speaker 4: great guides written for human rights defenders on how to 781 00:47:28,680 --> 00:47:31,759 Speaker 4: document actions and safely upload them. We recommend following that, 782 00:47:33,040 --> 00:47:36,040 Speaker 4: you know, please check out different safety guides that have 783 00:47:36,080 --> 00:47:38,800 Speaker 4: been put out, you know, pretty recently from the eff 784 00:47:38,880 --> 00:47:40,839 Speaker 4: or the Markup in terms of how to stay safe 785 00:47:40,880 --> 00:47:45,120 Speaker 4: at a protest. We're updating, we're updating and creating a 786 00:47:45,120 --> 00:47:47,920 Speaker 4: new anti doxing guide, and we're also putting out guides 787 00:47:47,960 --> 00:47:50,439 Speaker 4: hopefully soon. But a big thing is, you know, maybe 788 00:47:50,480 --> 00:47:52,360 Speaker 4: don't bring your phone with you, and if you have 789 00:47:52,400 --> 00:47:55,000 Speaker 4: an iPhone and you need to bring your phone, consider 790 00:47:55,080 --> 00:47:57,560 Speaker 4: turning it off, putting it lockdown, mown, and turning it off. 791 00:47:57,880 --> 00:47:58,120 Speaker 5: Yeah. 792 00:47:58,160 --> 00:48:01,560 Speaker 1: Well, actually hear from eff technologist who wrote that guide 793 00:48:01,680 --> 00:48:05,040 Speaker 1: next week about some concrete tips for digital security at protests. 794 00:48:05,080 --> 00:48:07,680 Speaker 1: So folks should definitely tune in, But are you all 795 00:48:07,760 --> 00:48:09,560 Speaker 1: working on any guides that folks should know about. 796 00:48:10,160 --> 00:48:13,080 Speaker 4: One thing is like, you know, if you turn your 797 00:48:13,120 --> 00:48:15,480 Speaker 4: phone on and you've brought with you at the protest 798 00:48:15,640 --> 00:48:18,880 Speaker 4: and you're like tweeting about where you are and you're 799 00:48:18,960 --> 00:48:22,640 Speaker 4: taking a photo of where you are, that might negate 800 00:48:22,920 --> 00:48:26,040 Speaker 4: a lot of the safety tips that you've already gone through, right, 801 00:48:26,160 --> 00:48:29,200 Speaker 4: And so one thing to consider is also like can 802 00:48:29,239 --> 00:48:31,600 Speaker 4: you put that out later? Can you scrub metadata from it? 803 00:48:33,320 --> 00:48:37,600 Speaker 4: Are you doxing accidentally your fellow protesters? Like are they 804 00:48:37,840 --> 00:48:41,120 Speaker 4: are their faces covered? You can use Signals face blurring 805 00:48:41,440 --> 00:48:44,680 Speaker 4: tool which they have you can blur out people's faces. 806 00:48:46,719 --> 00:48:49,520 Speaker 4: That also helps strip the image of metadata. So there's 807 00:48:49,600 --> 00:48:52,320 Speaker 4: like all these different things you can do, and I 808 00:48:52,400 --> 00:48:54,840 Speaker 4: think it's worth doing those and going to the protest. 809 00:48:54,920 --> 00:48:55,719 Speaker 2: I think some of this is. 810 00:48:55,719 --> 00:48:59,279 Speaker 4: Also shifting our own concepts of what it means to 811 00:48:59,360 --> 00:49:01,640 Speaker 4: sort of document and protest safely. 812 00:49:02,520 --> 00:49:03,680 Speaker 2: And I think some of that is. 813 00:49:05,160 --> 00:49:08,879 Speaker 4: Recognizing that, like going to the protest is almost more 814 00:49:08,920 --> 00:49:13,239 Speaker 4: important than publishing an image that you were there. I 815 00:49:13,280 --> 00:49:16,680 Speaker 4: think there's other ways to talk about being there, And 816 00:49:16,880 --> 00:49:19,640 Speaker 4: that's not to discourage people from posting, but rather it's 817 00:49:19,719 --> 00:49:23,080 Speaker 4: to say threat model and really think about what's in 818 00:49:23,160 --> 00:49:26,000 Speaker 4: this image? You know, what does this image reveal? 819 00:49:26,400 --> 00:49:26,520 Speaker 2: Right? 820 00:49:26,640 --> 00:49:29,400 Speaker 4: What does this image reveal about me? Does it reveal 821 00:49:29,440 --> 00:49:36,200 Speaker 4: about other people? Could someone be identified? Who is you know, 822 00:49:36,600 --> 00:49:40,440 Speaker 4: who I'm protesting with? How could this negatively impact them? 823 00:49:40,840 --> 00:49:41,000 Speaker 5: Right? 824 00:49:41,480 --> 00:49:43,480 Speaker 4: I think it is thinking about some of those some 825 00:49:43,640 --> 00:49:49,759 Speaker 4: of those things as we engage in collective action. And 826 00:49:49,920 --> 00:49:51,879 Speaker 4: so those are like some of the tips I want 827 00:49:51,920 --> 00:49:54,400 Speaker 4: people to like think about, which is, you know, make 828 00:49:54,440 --> 00:49:56,200 Speaker 4: a plan with your friends later of when you're going 829 00:49:56,280 --> 00:49:58,920 Speaker 4: to meet up and pick a time and make sure 830 00:49:58,960 --> 00:50:01,759 Speaker 4: you know how to get there, and and if you 831 00:50:01,800 --> 00:50:04,200 Speaker 4: don't show up in a certain amount of time, maybe 832 00:50:04,239 --> 00:50:06,800 Speaker 4: that's a signal to them that something has happened, and 833 00:50:06,920 --> 00:50:09,399 Speaker 4: like have that conversation. And these are like really safe 834 00:50:09,440 --> 00:50:14,960 Speaker 4: ways to still go about and engage in this really necessary. 835 00:50:15,239 --> 00:50:17,279 Speaker 4: I would argue, like civic action that we need to 836 00:50:17,360 --> 00:50:22,000 Speaker 4: be engaging in, and that's just a really great way 837 00:50:22,080 --> 00:50:26,320 Speaker 4: to cut down on ensuring your your phone isn't, you know, 838 00:50:26,840 --> 00:50:34,759 Speaker 4: contributing to this ongoing surveillance apparatus, or just turn your 839 00:50:34,800 --> 00:50:37,879 Speaker 4: phone off and don't turn it on until it's over. 840 00:50:38,680 --> 00:50:41,440 Speaker 1: Caroline Sam, thank you so much for being here, and 841 00:50:42,000 --> 00:50:45,000 Speaker 1: like truly thank you for your work. We need folks 842 00:50:45,120 --> 00:50:48,120 Speaker 1: like you who are making it easier and safer for 843 00:50:48,280 --> 00:50:51,000 Speaker 1: everybody to use their voices right now. So I hope 844 00:50:51,040 --> 00:50:52,759 Speaker 1: this gives people a sense of how they can do that. 845 00:50:53,400 --> 00:50:59,000 Speaker 1: Thanks for being here. If you're looking for ways to 846 00:50:59,040 --> 00:51:01,640 Speaker 1: support the show, check out our March store at tangody 847 00:51:01,680 --> 00:51:05,320 Speaker 1: dot com slash store. Got a story about an interesting 848 00:51:05,360 --> 00:51:07,320 Speaker 1: thing in tech, or just want to say hi, You 849 00:51:07,400 --> 00:51:09,640 Speaker 1: can reach us at Hello at teangody dot com. You 850 00:51:09,719 --> 00:51:12,359 Speaker 1: can also find transcripts for today's episode at tenggody dot com. 851 00:51:12,920 --> 00:51:14,560 Speaker 1: There Are No Girls on the Internet was created by 852 00:51:14,600 --> 00:51:17,960 Speaker 1: me Bridget tod It's a production of iHeartRadio and Unboss Creative, 853 00:51:18,480 --> 00:51:22,040 Speaker 1: edited by Joey pat. Jonathan Strickland is our executive producer. 854 00:51:22,400 --> 00:51:25,640 Speaker 1: Tari Harrison is our producer and sound engineer. Michael Almado 855 00:51:25,719 --> 00:51:28,680 Speaker 1: is our contributing producer. I'm your host, Bridget Todd. If 856 00:51:28,719 --> 00:51:30,440 Speaker 1: you want to help us grow, rate and review us 857 00:51:30,440 --> 00:51:34,080 Speaker 1: on Apple Podcasts. For more podcasts from iHeartRadio, check out 858 00:51:34,080 --> 00:51:37,040 Speaker 1: the iHeartRadio app, Apple Podcasts, or wherever you get your podcasts.