1 00:00:00,920 --> 00:00:03,960 Speaker 1: So yeah, I think that's part of it. Who who 2 00:00:04,000 --> 00:00:08,440 Speaker 1: should be involved in this conversation, Who should feel entitled 3 00:00:08,520 --> 00:00:10,520 Speaker 1: to be a part of this conversation, And I think 4 00:00:10,560 --> 00:00:13,399 Speaker 1: that's all of us, in particularly people who experience harm 5 00:00:13,480 --> 00:00:17,079 Speaker 1: from these systems, or harm from surveillance, or harm from 6 00:00:17,120 --> 00:00:26,040 Speaker 1: you know, all kinds of power imbalances in society. There 7 00:00:26,040 --> 00:00:27,760 Speaker 1: are no girls on the Internet. As a production of 8 00:00:27,760 --> 00:00:35,000 Speaker 1: I Heart Radio and Unbossed Creative, I'm Bridget Todd, and 9 00:00:35,080 --> 00:00:39,360 Speaker 1: this is there are no girls on the Internet. So 10 00:00:39,520 --> 00:00:41,760 Speaker 1: I talk a lot about the harm that technology has 11 00:00:41,760 --> 00:00:46,599 Speaker 1: been responsible for, particularly in marginalized communities, But ultimately I 12 00:00:46,680 --> 00:00:50,159 Speaker 1: am a tech optimist, and I see criticizing and fatiguing 13 00:00:50,200 --> 00:00:53,560 Speaker 1: technology and demanding it to be better as an expression 14 00:00:53,600 --> 00:00:56,560 Speaker 1: of my deep love of technology. You know, I love 15 00:00:56,560 --> 00:00:58,560 Speaker 1: it enough to want it to be better and to 16 00:00:58,680 --> 00:01:02,120 Speaker 1: really believe that it can be. And that same ethos 17 00:01:02,280 --> 00:01:06,720 Speaker 1: is what drives Mozilla's Solana Larson as well. Hi, Bridget, 18 00:01:06,760 --> 00:01:12,600 Speaker 1: I'm Solana, so Lana Larson, and my title is editor 19 00:01:13,080 --> 00:01:19,600 Speaker 1: of the Internet Health Report on Mozilla's Insights team. Salana 20 00:01:19,640 --> 00:01:21,800 Speaker 1: and I worked on a podcast for Mozilla called I 21 00:01:21,959 --> 00:01:25,679 Speaker 1: R L Work Together. We explored the peril and promise 22 00:01:25,760 --> 00:01:30,400 Speaker 1: of AI. For Solana, this work is grounded in optimism 23 00:01:30,440 --> 00:01:34,400 Speaker 1: around the possibilities of technology. She saw all the positive 24 00:01:34,440 --> 00:01:36,640 Speaker 1: ways it could be used to shape our world early on, 25 00:01:37,319 --> 00:01:40,120 Speaker 1: but after watching the ways technology has been used to 26 00:01:40,120 --> 00:01:44,200 Speaker 1: facilitate things like mass surveillance and criminalization, got hard to 27 00:01:44,200 --> 00:01:48,160 Speaker 1: be so optimistic. Originally, I had wanted to be a journalist, 28 00:01:48,400 --> 00:01:50,440 Speaker 1: so that's where it all started. But I was really 29 00:01:50,520 --> 00:01:53,680 Speaker 1: drawn to internet topics and writing for the Internet. And 30 00:01:53,720 --> 00:01:56,200 Speaker 1: around the time that I got started, the Internet was 31 00:01:56,240 --> 00:02:00,320 Speaker 1: still new, the newspapers were still coming online. There were 32 00:02:00,440 --> 00:02:04,240 Speaker 1: very few people who who were still taught, I mean, 33 00:02:04,280 --> 00:02:08,079 Speaker 1: who had started to talk about the possibilities and the opportunities. 34 00:02:08,120 --> 00:02:10,400 Speaker 1: I guess I was really excited about how the Internet 35 00:02:10,400 --> 00:02:14,240 Speaker 1: could bring us together, and for the first ten fifteen 36 00:02:14,320 --> 00:02:16,240 Speaker 1: years of my career it was all about how can 37 00:02:16,280 --> 00:02:19,120 Speaker 1: we use the Internet to create bonds between people in 38 00:02:19,120 --> 00:02:22,440 Speaker 1: different countries. I work for a website called Open Democracy, 39 00:02:22,520 --> 00:02:26,120 Speaker 1: which was all about global politics and exchanges of ideas 40 00:02:26,639 --> 00:02:29,800 Speaker 1: different perspectives from around the world. And then when blogs 41 00:02:29,840 --> 00:02:34,000 Speaker 1: started happening, I became the editor of a website called 42 00:02:34,000 --> 00:02:37,800 Speaker 1: Global Voices that was pitching itself as an alternative to 43 00:02:38,440 --> 00:02:42,639 Speaker 1: international news, or as an accompaniment to international news, I 44 00:02:42,680 --> 00:02:45,680 Speaker 1: should say, using the voices of bloggers from all over 45 00:02:45,680 --> 00:02:49,000 Speaker 1: the world. So I've been working in this realm of 46 00:02:49,080 --> 00:02:53,440 Speaker 1: digital activism, citizen journalism and really trying to use the 47 00:02:53,480 --> 00:02:58,840 Speaker 1: Internet to bridge people's understandings of one another. And I 48 00:02:58,880 --> 00:03:01,720 Speaker 1: think after some years of doing this, a lot of 49 00:03:01,800 --> 00:03:04,760 Speaker 1: us who were very optimistic about the Internet started to 50 00:03:04,880 --> 00:03:07,839 Speaker 1: sour um and just started to see a lot of 51 00:03:08,080 --> 00:03:12,880 Speaker 1: um surveillance, a lot of UM people ending up in 52 00:03:12,960 --> 00:03:14,880 Speaker 1: jail for you know, for for those of us who 53 00:03:14,880 --> 00:03:18,160 Speaker 1: are working in international communities, a lot of like the 54 00:03:18,200 --> 00:03:21,800 Speaker 1: Arab Spring uprisings, things that were happening around the world, 55 00:03:21,800 --> 00:03:26,240 Speaker 1: that we're all around Internet culture, we're backfiring in a sense. 56 00:03:26,440 --> 00:03:29,440 Speaker 1: And then you know, with the Snowden leagues and all 57 00:03:29,480 --> 00:03:32,120 Speaker 1: we learned about surveillance around the world, it was just 58 00:03:32,160 --> 00:03:35,640 Speaker 1: difficult to find a way to be optimistic about, you know, 59 00:03:35,800 --> 00:03:39,720 Speaker 1: the great promise of the Internet. And what I found 60 00:03:39,760 --> 00:03:43,320 Speaker 1: in Mozilla, which you know then became a job to 61 00:03:43,440 --> 00:03:48,400 Speaker 1: create this annual report about the health of the global Internet. Um, 62 00:03:48,520 --> 00:03:51,960 Speaker 1: what I found was a way to be optimistic because 63 00:03:53,200 --> 00:03:54,960 Speaker 1: I think we had been working a lot in these 64 00:03:55,000 --> 00:03:59,440 Speaker 1: communications or activism circles, and Mozilla had a very technical 65 00:03:59,440 --> 00:04:03,000 Speaker 1: approach to a lot of these problems, and the builder 66 00:04:03,040 --> 00:04:06,040 Speaker 1: approach or the technical approaches like let's fix it, let's 67 00:04:06,080 --> 00:04:11,160 Speaker 1: make something, let's build something. And it was contact with 68 00:04:11,200 --> 00:04:14,000 Speaker 1: the community who sort of remembered building the Internet in 69 00:04:14,000 --> 00:04:18,160 Speaker 1: the first place, for building browsers or you know. This 70 00:04:18,320 --> 00:04:22,000 Speaker 1: approach to the Internet was something we made, we can 71 00:04:22,080 --> 00:04:25,359 Speaker 1: change it, we can fix it. Was really refreshing, you know, 72 00:04:25,480 --> 00:04:28,320 Speaker 1: in a world with all of these political problems and 73 00:04:28,400 --> 00:04:31,599 Speaker 1: human rights problems that are difficult to to change, Suddenly 74 00:04:31,640 --> 00:04:34,600 Speaker 1: the Internet seemed a lot easier to tinker with than 75 00:04:35,240 --> 00:04:40,320 Speaker 1: you know, human rights or dictatorships or or women's rights. Um. 76 00:04:40,360 --> 00:04:42,240 Speaker 1: So that that was That's kind of how that was 77 00:04:42,240 --> 00:04:46,720 Speaker 1: a long story. But yeah, the Internet Health Report, how 78 00:04:46,720 --> 00:04:48,640 Speaker 1: do we measure the health of the Internet and how 79 00:04:48,640 --> 00:04:50,520 Speaker 1: do we do it from year to year? That's been 80 00:04:50,560 --> 00:04:53,760 Speaker 1: the project. So can you tell us more about what 81 00:04:53,880 --> 00:04:56,560 Speaker 1: the Internet Health Report is and how it's changed over 82 00:04:56,600 --> 00:05:01,159 Speaker 1: the years. Yeah, it's always been a very creative publication, 83 00:05:01,920 --> 00:05:05,560 Speaker 1: so I've tried to divide it into different topics. It's 84 00:05:05,600 --> 00:05:09,279 Speaker 1: always had a lot of visuals. It's always been about 85 00:05:09,440 --> 00:05:14,640 Speaker 1: collecting a lot of stories, perspectives, compilations of research, pulling 86 00:05:14,680 --> 00:05:19,120 Speaker 1: together a lot of information from different parts, different corners 87 00:05:19,200 --> 00:05:23,440 Speaker 1: of internet politics and internet you know, tech circles, and 88 00:05:23,440 --> 00:05:25,760 Speaker 1: then to try and tell a story of where are 89 00:05:25,800 --> 00:05:28,560 Speaker 1: we right now. Originally we had wanted to make some 90 00:05:28,640 --> 00:05:32,120 Speaker 1: kind of index or a number or a score. But 91 00:05:32,200 --> 00:05:34,600 Speaker 1: the more that we looked at others who have done 92 00:05:34,600 --> 00:05:37,960 Speaker 1: similar things or really got to the heart of what 93 00:05:38,000 --> 00:05:42,080 Speaker 1: we wanted to to explore with this publication, it didn't 94 00:05:42,120 --> 00:05:47,120 Speaker 1: seem fitting to narrow down such a huge, you know, 95 00:05:47,320 --> 00:05:50,919 Speaker 1: part of human experience into just like this quantifiable metric. 96 00:05:51,520 --> 00:05:53,880 Speaker 1: And I think particularly when you're looking at the entire 97 00:05:53,920 --> 00:05:56,080 Speaker 1: world at once and you want to make something that's 98 00:05:56,080 --> 00:06:00,760 Speaker 1: respectful of global experience, it's difficult to just say, oh, 99 00:06:00,800 --> 00:06:03,600 Speaker 1: something's going well or something's going bad. Like in every 100 00:06:03,800 --> 00:06:05,800 Speaker 1: country of the world, you have things that are going 101 00:06:05,839 --> 00:06:09,120 Speaker 1: better and things that are going worse. Um, depending on 102 00:06:09,279 --> 00:06:11,599 Speaker 1: where your focus is, like let's say we're in North 103 00:06:11,640 --> 00:06:14,159 Speaker 1: America or Europe, then you might completely leave out the 104 00:06:14,200 --> 00:06:19,760 Speaker 1: experience of entire continents languages. So more and more it's 105 00:06:19,800 --> 00:06:24,960 Speaker 1: been diving into different topics momentarily and and doing like 106 00:06:25,000 --> 00:06:28,719 Speaker 1: a snapshot in time of well, how does it how 107 00:06:28,720 --> 00:06:33,240 Speaker 1: do submarine internet cables look right now? Or um, how 108 00:06:33,279 --> 00:06:37,200 Speaker 1: does harassment on the web look like right now? Or um, 109 00:06:37,200 --> 00:06:41,440 Speaker 1: what's this thing about social media taxes in African countries? Um? 110 00:06:41,640 --> 00:06:44,200 Speaker 1: And so forth, So trying to to give a really 111 00:06:44,240 --> 00:06:48,400 Speaker 1: broad overview, and then over time, I think Mozilla has 112 00:06:48,440 --> 00:06:51,880 Speaker 1: really focused on this topic of AI, you know, not 113 00:06:51,960 --> 00:06:54,160 Speaker 1: just for the Internet Health Report, but in all our 114 00:06:54,600 --> 00:06:58,400 Speaker 1: programmatic work and the fellowships that we're doing, really identified 115 00:06:58,440 --> 00:07:01,680 Speaker 1: AI as this is the next challenge of the Internet. 116 00:07:01,760 --> 00:07:04,039 Speaker 1: Like if we're trying to be forward looking and thinking 117 00:07:04,080 --> 00:07:06,680 Speaker 1: about where do we have an opportunity to make a 118 00:07:06,680 --> 00:07:10,360 Speaker 1: difference now for the Internet of the future, AI is 119 00:07:10,400 --> 00:07:13,080 Speaker 1: an area where we can really focus. So this year 120 00:07:13,160 --> 00:07:17,240 Speaker 1: we decided to focus on AI. And you know, I 121 00:07:17,240 --> 00:07:20,520 Speaker 1: think we've all been through a pandemic. People don't really 122 00:07:20,600 --> 00:07:23,760 Speaker 1: have capacity to read long things at the moment um. 123 00:07:23,920 --> 00:07:27,880 Speaker 1: Podcasts are what people enjoy and listen to. And I 124 00:07:27,920 --> 00:07:30,000 Speaker 1: think what we always wanted to do with this publication 125 00:07:30,080 --> 00:07:33,720 Speaker 1: was really too inspire, you know, not just say what's 126 00:07:33,760 --> 00:07:38,200 Speaker 1: going wrong or like give some cold metric of what's happening, 127 00:07:38,240 --> 00:07:40,360 Speaker 1: but to give people a sense of what can be 128 00:07:40,400 --> 00:07:43,800 Speaker 1: done to make things better. And I think with people's 129 00:07:43,880 --> 00:07:48,440 Speaker 1: voices and people's experiences, you can you can convey a 130 00:07:48,520 --> 00:07:53,680 Speaker 1: lot more emotion I think in a way that's easier consumed. 131 00:07:54,200 --> 00:07:56,880 Speaker 1: So yeah, this year we made the Internet Health Report 132 00:07:57,320 --> 00:08:02,720 Speaker 1: a podcast, and we're able to m you know, create 133 00:08:02,920 --> 00:08:06,960 Speaker 1: create new new connections, new links, for instance, with you, 134 00:08:07,600 --> 00:08:11,040 Speaker 1: um so, being able to create this kind of project 135 00:08:11,080 --> 00:08:16,480 Speaker 1: together and and you know, explore this topic in a 136 00:08:16,520 --> 00:08:24,520 Speaker 1: different way has been really fantastic. Let's take a quick 137 00:08:24,560 --> 00:08:42,640 Speaker 1: break out her back. So lots of organizations do an 138 00:08:42,640 --> 00:08:45,880 Speaker 1: annual report every year, and if we're being honest, maybe 139 00:08:46,040 --> 00:08:49,360 Speaker 1: no one really reads them. But Salana and the team 140 00:08:49,360 --> 00:08:52,040 Speaker 1: at the Internet Health Report at Mozilla wanted to do 141 00:08:52,080 --> 00:08:55,600 Speaker 1: something different. They decided to release their report as a podcast, 142 00:08:55,880 --> 00:08:59,360 Speaker 1: anchored in the real life stories of the researchers, activists, 143 00:08:59,400 --> 00:09:02,600 Speaker 1: and technolog just who lived them. Oh, I mean, working 144 00:09:02,640 --> 00:09:05,080 Speaker 1: on this project with you has been I mean I 145 00:09:05,080 --> 00:09:06,959 Speaker 1: could talk all day. It's been a dream for me. 146 00:09:07,040 --> 00:09:10,160 Speaker 1: But I think you're so right. There's something about it 147 00:09:10,280 --> 00:09:14,440 Speaker 1: being a podcast where you get to hear in your 148 00:09:14,480 --> 00:09:17,880 Speaker 1: earbuds the stories and the voices of these people, and 149 00:09:17,920 --> 00:09:20,400 Speaker 1: so like, the stories are really the thing that that 150 00:09:20,720 --> 00:09:23,400 Speaker 1: centers the work. And so I just think there's something 151 00:09:23,440 --> 00:09:26,160 Speaker 1: about hearing people explain themselves and explain what it was 152 00:09:26,280 --> 00:09:29,040 Speaker 1: like to you know, realize that you were working on 153 00:09:29,080 --> 00:09:32,640 Speaker 1: a project involving killer machines at Google, or you know, 154 00:09:33,400 --> 00:09:36,720 Speaker 1: lose your wife from cancer and want to make sure 155 00:09:36,760 --> 00:09:38,599 Speaker 1: that other people didn't have to suffer the way that 156 00:09:38,640 --> 00:09:40,760 Speaker 1: you did, and so building something to prevent it. Like, 157 00:09:41,040 --> 00:09:44,640 Speaker 1: there's something about hearing the voices of the people at 158 00:09:44,679 --> 00:09:46,760 Speaker 1: the center of these stories that really makes them come 159 00:09:46,800 --> 00:09:49,040 Speaker 1: to life in a way that you know, I don't 160 00:09:49,080 --> 00:09:51,800 Speaker 1: know that that reading a report ever could, but it's 161 00:09:51,840 --> 00:09:54,880 Speaker 1: what I really enjoy about your podcast as well, is 162 00:09:55,120 --> 00:09:57,280 Speaker 1: the way you you get close to people. But then 163 00:09:57,320 --> 00:09:59,720 Speaker 1: you also use that as an entry point to discuss 164 00:09:59,760 --> 00:10:04,120 Speaker 1: the politics or to discuss the technology um and I 165 00:10:04,200 --> 00:10:07,920 Speaker 1: think people need that entry point to topics like this 166 00:10:08,040 --> 00:10:10,400 Speaker 1: because a lot of the time when we do hear 167 00:10:10,440 --> 00:10:14,000 Speaker 1: about them, it is just like cold. I mean, who 168 00:10:14,040 --> 00:10:17,040 Speaker 1: cares about a computer? Right? You care about the people 169 00:10:17,280 --> 00:10:20,440 Speaker 1: and how they're affected by that computer. So I think 170 00:10:20,480 --> 00:10:23,840 Speaker 1: that that's That's why it's been great to work with 171 00:10:23,880 --> 00:10:26,760 Speaker 1: you on this and what you know. I'm also curious 172 00:10:26,760 --> 00:10:30,800 Speaker 1: to see what you'll carry into the work going forward, 173 00:10:30,880 --> 00:10:33,640 Speaker 1: you know, and and being able to explore all these 174 00:10:33,679 --> 00:10:37,000 Speaker 1: stories together of these people around the world, it's been great. 175 00:10:37,679 --> 00:10:40,320 Speaker 1: I do feel like when you come when it comes 176 00:10:40,320 --> 00:10:45,079 Speaker 1: to topics like technology or especially AI, I think someone 177 00:10:45,120 --> 00:10:47,560 Speaker 1: who doesn't think of themselves as like a hard tech 178 00:10:47,640 --> 00:10:50,160 Speaker 1: person might think that that's nothing to do with me. 179 00:10:50,520 --> 00:10:53,800 Speaker 1: And I like the way that the Internet Health Report 180 00:10:53,880 --> 00:10:56,920 Speaker 1: really frames those stories in a way that's so accessible 181 00:10:56,920 --> 00:10:59,880 Speaker 1: that's like, actually, there is a lot of impact on 182 00:11:00,080 --> 00:11:02,080 Speaker 1: your life if this is the way that AI is 183 00:11:02,120 --> 00:11:06,360 Speaker 1: being used by governments, by law enforcement officials, by you know, 184 00:11:07,000 --> 00:11:10,480 Speaker 1: other agencies. So I guess I wonder, you know, how 185 00:11:10,520 --> 00:11:14,120 Speaker 1: do we make people understand what's at stake and and 186 00:11:14,559 --> 00:11:16,760 Speaker 1: how how have you worked to make people really be 187 00:11:16,800 --> 00:11:19,320 Speaker 1: able to see themselves reflected in these issues that you 188 00:11:19,400 --> 00:11:24,720 Speaker 1: that you care so deeply about. Yeah, it's it's tough 189 00:11:24,800 --> 00:11:28,600 Speaker 1: because you can also get sometimes you can get too 190 00:11:28,600 --> 00:11:33,440 Speaker 1: superficial on some of these topics. Like I think people understand, Okay, 191 00:11:33,480 --> 00:11:37,440 Speaker 1: here's social media, you know, like that there's there's disinformation 192 00:11:37,640 --> 00:11:40,040 Speaker 1: or this is how I'm affected by social media or 193 00:11:40,240 --> 00:11:42,200 Speaker 1: like you can you can find some of those entry 194 00:11:42,200 --> 00:11:45,559 Speaker 1: points easier, and I think we've gotten a little bit deeper. 195 00:11:46,000 --> 00:11:48,640 Speaker 1: You know, we're also looking at okay, but how does 196 00:11:48,640 --> 00:11:51,600 Speaker 1: this work in healthcare? How does this work in governance? 197 00:11:51,720 --> 00:11:54,280 Speaker 1: Or what is it that's really happening with surveillance? So 198 00:11:54,840 --> 00:11:59,360 Speaker 1: I guess one step removed from the users cell phone, 199 00:12:00,400 --> 00:12:03,920 Speaker 1: So it does require some imagination from people. But I think, 200 00:12:04,440 --> 00:12:06,600 Speaker 1: you know, that's where the stakes really get a lot 201 00:12:06,720 --> 00:12:10,360 Speaker 1: higher and where you're talking about life and actual death. 202 00:12:10,679 --> 00:12:15,280 Speaker 1: And the really confusing thing about this topic is that 203 00:12:15,360 --> 00:12:20,360 Speaker 1: you're the entities that you have to be concerned about 204 00:12:20,480 --> 00:12:23,240 Speaker 1: are also the ones that you're friends with and you 205 00:12:23,360 --> 00:12:26,560 Speaker 1: use every day. So I'm thinking specifically about Big tet 206 00:12:26,720 --> 00:12:29,960 Speaker 1: you know, Google, We probably all use it every day 207 00:12:30,000 --> 00:12:32,600 Speaker 1: for our email or Internet searches and stuff. And then 208 00:12:32,640 --> 00:12:35,959 Speaker 1: to be confronted with this fact that they also are 209 00:12:36,040 --> 00:12:40,120 Speaker 1: involved in, you know, mass surveillance in different ways through 210 00:12:40,120 --> 00:12:43,520 Speaker 1: their cloud computing contracts or contracts with the with the 211 00:12:43,520 --> 00:12:49,840 Speaker 1: Pentagon or other um agencies. These are difficult things to 212 00:12:50,200 --> 00:12:53,600 Speaker 1: uh to grasp. Or Amazon, you know, we shop on 213 00:12:53,720 --> 00:12:58,080 Speaker 1: Amazon or but you know, Amazon also has relationships with 214 00:12:58,120 --> 00:13:01,720 Speaker 1: the police or also as a stake in surveillance tech 215 00:13:01,960 --> 00:13:06,719 Speaker 1: and so and and with governments. Governments survey and they 216 00:13:06,760 --> 00:13:08,439 Speaker 1: do a lot of things, but we also need them 217 00:13:08,440 --> 00:13:11,000 Speaker 1: to make policies and to be our friends and to 218 00:13:11,440 --> 00:13:16,440 Speaker 1: protect our privacy. And so it's it's a difficult topic 219 00:13:16,559 --> 00:13:21,480 Speaker 1: to navigate because you know, everybody's wearing so many different 220 00:13:21,520 --> 00:13:25,120 Speaker 1: hats and the things that need to happen, like so 221 00:13:25,160 --> 00:13:28,240 Speaker 1: many different things need to happen at once for like 222 00:13:28,640 --> 00:13:32,200 Speaker 1: massive change to happen. How do we make it interesting? 223 00:13:32,960 --> 00:13:36,199 Speaker 1: You know, I think it's it's partly these these people's 224 00:13:36,240 --> 00:13:40,840 Speaker 1: stories and then just highlighting the mere facts. Even though 225 00:13:40,840 --> 00:13:43,400 Speaker 1: we use these technologies every day, we're just not aware 226 00:13:43,400 --> 00:13:46,560 Speaker 1: of all these things. So the experience that people have 227 00:13:46,640 --> 00:13:49,439 Speaker 1: when they hear this, oh my goodness, I didn't know. 228 00:13:50,040 --> 00:13:52,280 Speaker 1: Or even when you explain how uber works or what 229 00:13:52,360 --> 00:13:54,120 Speaker 1: it's like to be a driver, if you haven't had 230 00:13:54,120 --> 00:13:57,720 Speaker 1: that experience yourself, people are really surprised and taken it back. 231 00:13:58,360 --> 00:14:00,839 Speaker 1: So yeah, we just have to get better at talking 232 00:14:00,880 --> 00:14:05,760 Speaker 1: about it, demystifying it, um, you know, allowing people to 233 00:14:05,800 --> 00:14:10,600 Speaker 1: ask their questions. Um, presenting it in a way that 234 00:14:10,760 --> 00:14:14,760 Speaker 1: isn't intimidating, because this is an area where experts like 235 00:14:14,920 --> 00:14:18,800 Speaker 1: to pontificate and they like to be important, I think, 236 00:14:19,040 --> 00:14:23,440 Speaker 1: and that makes it difficult for for newcomers to come 237 00:14:23,480 --> 00:14:26,600 Speaker 1: to come to the conversation. So yeah, I think that's 238 00:14:26,640 --> 00:14:30,520 Speaker 1: part of it. Who who should be involved in this conversation? 239 00:14:30,880 --> 00:14:34,080 Speaker 1: Who should feel entitled to be a part of this conversation, 240 00:14:34,120 --> 00:14:36,360 Speaker 1: And I think that's all of us, and particularly people 241 00:14:36,360 --> 00:14:39,960 Speaker 1: who experience harm from these systems, or harm from surveillance, 242 00:14:40,360 --> 00:14:43,360 Speaker 1: or harm from you know, all kinds of power and 243 00:14:43,400 --> 00:14:48,800 Speaker 1: balances in society. Yeah, that's I think that's key. That's 244 00:14:48,800 --> 00:14:50,760 Speaker 1: something that we that we talked about a lot on 245 00:14:50,800 --> 00:14:54,280 Speaker 1: this podcast, where you know, I think that we really 246 00:14:54,280 --> 00:14:58,360 Speaker 1: need a big culture shift around who feels like they're 247 00:14:58,400 --> 00:15:01,360 Speaker 1: allowed to have a speak on these issues, to see 248 00:15:01,400 --> 00:15:03,880 Speaker 1: themselves in these issues, to center themselves in these issues. 249 00:15:04,240 --> 00:15:07,000 Speaker 1: You know, it's not it should not just be you know, 250 00:15:07,080 --> 00:15:09,800 Speaker 1: the people with power who are making the decisions, who 251 00:15:09,840 --> 00:15:13,120 Speaker 1: also mostly happened to be a lot of white you 252 00:15:13,160 --> 00:15:17,520 Speaker 1: know men, a lot of white stratesis gender men, uh, 253 00:15:17,720 --> 00:15:20,440 Speaker 1: who are of a certain economic class like those like we, 254 00:15:20,600 --> 00:15:23,800 Speaker 1: I feel like we've gotten a situation where, for whatever reason, 255 00:15:24,440 --> 00:15:27,200 Speaker 1: we feel like those are the only people whose voices matter. 256 00:15:27,640 --> 00:15:30,880 Speaker 1: And in fact, when you think about who is impacted 257 00:15:30,880 --> 00:15:33,520 Speaker 1: by this technology was harmed by it, we need to 258 00:15:33,600 --> 00:15:35,800 Speaker 1: be able to take up a much bigger space in 259 00:15:35,800 --> 00:15:39,360 Speaker 1: the conversation to reflect the role that we actually have 260 00:15:39,560 --> 00:15:42,520 Speaker 1: and what's actually at stake for the rest of us. Absolutely, 261 00:15:42,720 --> 00:15:46,000 Speaker 1: and that's that's true worldwide. One of one of the 262 00:15:46,400 --> 00:15:49,960 Speaker 1: researchers that we interviewed in the final episode of the 263 00:15:50,000 --> 00:15:53,320 Speaker 1: podcast one about health care, she has this quote that 264 00:15:53,480 --> 00:15:57,560 Speaker 1: really it really struck a nerve with me, where she 265 00:15:57,720 --> 00:16:01,320 Speaker 1: talks about she was researching how a I diagnostic systems 266 00:16:01,360 --> 00:16:04,040 Speaker 1: are being rolled out in rural India where there aren't 267 00:16:04,040 --> 00:16:05,880 Speaker 1: a lot of doctors, and so they roll out these 268 00:16:05,880 --> 00:16:09,800 Speaker 1: systems and they're they're able to screen people, scan them, 269 00:16:09,880 --> 00:16:14,760 Speaker 1: and send some tests to a major hospital somewhere far away. 270 00:16:14,800 --> 00:16:18,680 Speaker 1: And she says, some of these systems have not been tested. 271 00:16:18,840 --> 00:16:23,480 Speaker 1: They're being tested actively in a patient scenario, in a 272 00:16:23,560 --> 00:16:28,520 Speaker 1: situation where people have no other option for healthcare. Big 273 00:16:28,560 --> 00:16:32,800 Speaker 1: companies you know, whose names we know and are familiar with, 274 00:16:33,080 --> 00:16:35,720 Speaker 1: are involved in this kind of testing. And then they say, well, 275 00:16:35,880 --> 00:16:40,360 Speaker 1: we got these people's consent, and but they present consent 276 00:16:40,480 --> 00:16:44,080 Speaker 1: form in the language that the person doesn't know, and 277 00:16:44,440 --> 00:16:47,920 Speaker 1: it's terminology that they're not familiar with. And how she 278 00:16:48,040 --> 00:16:52,560 Speaker 1: described it was, it's the mass and fantilization of entire population, 279 00:16:53,040 --> 00:16:57,520 Speaker 1: of an entire population. And when you treat people as 280 00:16:57,960 --> 00:17:01,720 Speaker 1: you know, in this way, there's just so much not 281 00:17:01,840 --> 00:17:04,600 Speaker 1: even just in how the system is designed, but how 282 00:17:04,640 --> 00:17:08,520 Speaker 1: it's rolled out, how you expect people, you know, to 283 00:17:08,680 --> 00:17:12,960 Speaker 1: coexist with them. If there's so much offensive behavior at 284 00:17:13,000 --> 00:17:16,679 Speaker 1: every level of the chain. And so these aren't just 285 00:17:16,760 --> 00:17:21,120 Speaker 1: tech questions. These are human questions and rights questions, and 286 00:17:21,320 --> 00:17:25,920 Speaker 1: there's varieties of that all in any kind of field 287 00:17:25,920 --> 00:17:29,360 Speaker 1: where these technologies exist. We need people to be speaking 288 00:17:29,400 --> 00:17:31,960 Speaker 1: of and we need to be defending people's rights to 289 00:17:32,680 --> 00:17:37,600 Speaker 1: you know, their own autonomy physical and digital, because it 290 00:17:37,640 --> 00:17:47,960 Speaker 1: makes things better, you know. Yeah, more after a quick break, 291 00:17:58,119 --> 00:18:02,920 Speaker 1: let's get right back into it. AI will do this. 292 00:18:03,280 --> 00:18:06,600 Speaker 1: AI does that. It is really easy to think of 293 00:18:06,640 --> 00:18:11,040 Speaker 1: AI and other technologies as doing things, but really it's 294 00:18:11,040 --> 00:18:14,880 Speaker 1: the people and companies behind that technology that are doing 295 00:18:14,920 --> 00:18:18,439 Speaker 1: the things. You know, AI doesn't discriminate against people of 296 00:18:18,480 --> 00:18:22,040 Speaker 1: color or strengthen the surveillance state. It's the people who 297 00:18:22,119 --> 00:18:25,280 Speaker 1: make AI that are doing that. Computers and the Internet 298 00:18:25,280 --> 00:18:28,159 Speaker 1: are powerful tools, and the people who shape those tools 299 00:18:28,160 --> 00:18:31,680 Speaker 1: at scale have a responsibility to make them safe. I'm 300 00:18:31,720 --> 00:18:34,200 Speaker 1: reminded of something that you said to me early on 301 00:18:34,320 --> 00:18:37,439 Speaker 1: working on this project together. You said that you, in 302 00:18:37,560 --> 00:18:40,720 Speaker 1: writing the Internet Health Report, try to stay away from 303 00:18:40,760 --> 00:18:46,560 Speaker 1: assigning motivations or intentions to technology. So instead of being like, oh, 304 00:18:46,680 --> 00:18:49,880 Speaker 1: AI does this, it's like all the people who make 305 00:18:49,960 --> 00:18:53,520 Speaker 1: AI does this. You know, what, how is that thinking 306 00:18:53,720 --> 00:18:56,440 Speaker 1: shaped your work? Because I do think that it's really 307 00:18:56,440 --> 00:18:59,200 Speaker 1: easy to think, oh, technology, it's just gonna do what 308 00:18:59,320 --> 00:19:02,720 Speaker 1: the technology does. It is neutral, But that obscure is 309 00:19:02,760 --> 00:19:06,360 Speaker 1: the fact that there are people behind it that make decisions, 310 00:19:06,359 --> 00:19:08,560 Speaker 1: and that that can be so difficult to keep at 311 00:19:08,600 --> 00:19:13,200 Speaker 1: the forefront. That's right, people and companies. Yeah, and especially 312 00:19:13,200 --> 00:19:16,160 Speaker 1: with AI. You know, there's this fantasy of an autonomous 313 00:19:16,680 --> 00:19:19,919 Speaker 1: robot or some kind of computer brain that does stuff 314 00:19:20,000 --> 00:19:22,919 Speaker 1: on it on its own, and it doesn't It doesn't 315 00:19:22,920 --> 00:19:25,400 Speaker 1: help us get anywhere. You know, that's just not how 316 00:19:25,480 --> 00:19:28,960 Speaker 1: it works. It's these are systems created by people that 317 00:19:29,000 --> 00:19:32,200 Speaker 1: are actually kind of stupid in the way that they work. 318 00:19:32,440 --> 00:19:36,000 Speaker 1: You know, you give them data they learned. I mean, 319 00:19:36,040 --> 00:19:38,520 Speaker 1: we shouldn't even be using the word learning, right, but 320 00:19:38,600 --> 00:19:42,199 Speaker 1: they replicate or they're able to spot patterns. And so 321 00:19:42,280 --> 00:19:45,600 Speaker 1: when you highlight some of some of the errors or 322 00:19:45,640 --> 00:19:49,760 Speaker 1: the or the false you know, findings of systems like this, 323 00:19:50,280 --> 00:19:53,560 Speaker 1: you just you start to realize that it's not always 324 00:19:53,600 --> 00:19:55,960 Speaker 1: all that it's made out to be. You know, there's 325 00:19:56,000 --> 00:19:59,120 Speaker 1: a lot of marketing lingo that that these systems get 326 00:19:59,200 --> 00:20:04,360 Speaker 1: wrapped up in. And so when yeah, I'm completely allergic 327 00:20:04,400 --> 00:20:06,720 Speaker 1: to when people say AI does this, or a I 328 00:20:06,800 --> 00:20:09,919 Speaker 1: will do this, or AI will make this. Like the 329 00:20:10,000 --> 00:20:12,520 Speaker 1: only way that AI is going to do anything is 330 00:20:12,560 --> 00:20:18,159 Speaker 1: if we people, you know, ask it to do something exactly. 331 00:20:18,520 --> 00:20:20,840 Speaker 1: You know. Also, we've talked a bit about some of 332 00:20:20,880 --> 00:20:25,000 Speaker 1: the harms and sort of the difficult things to accept 333 00:20:25,040 --> 00:20:28,399 Speaker 1: about the way that technology and AI has functioned for 334 00:20:28,440 --> 00:20:31,080 Speaker 1: so many folks. But like you also strike me as 335 00:20:31,119 --> 00:20:33,959 Speaker 1: someone who is quite optimistic. You know, your work at 336 00:20:34,000 --> 00:20:38,400 Speaker 1: Mozilla is really about getting to a web and an 337 00:20:38,440 --> 00:20:41,880 Speaker 1: internet that we want. Um, what kind of web do 338 00:20:41,880 --> 00:20:45,720 Speaker 1: do you want? Well? I want one where more people 339 00:20:45,760 --> 00:20:49,800 Speaker 1: are involved. Like that's I don't I don't imagine that 340 00:20:49,880 --> 00:20:56,840 Speaker 1: we can completely change how big tech works overnight. These 341 00:20:56,840 --> 00:20:59,960 Speaker 1: are these are extremely powerful systems. I think right now, 342 00:21:00,920 --> 00:21:05,879 Speaker 1: it's about ensuring that alternatives can also coexist, and that 343 00:21:05,960 --> 00:21:09,199 Speaker 1: the web can be a place where people can create 344 00:21:09,320 --> 00:21:13,200 Speaker 1: things for their own communities and you know where where 345 00:21:13,200 --> 00:21:18,679 Speaker 1: there is that openness and opportunity for creativity. Yeah, to 346 00:21:18,800 --> 00:21:21,440 Speaker 1: enable those kinds of collaborations, because that's where I still 347 00:21:21,480 --> 00:21:23,960 Speaker 1: see that there is a lot of positive and important 348 00:21:23,960 --> 00:21:28,400 Speaker 1: work to be done. And oftentimes it's these smaller projects 349 00:21:28,440 --> 00:21:31,359 Speaker 1: or grassroots project or the project of an individual, or 350 00:21:31,400 --> 00:21:35,000 Speaker 1: even artistic projects that can kind of set an example 351 00:21:35,160 --> 00:21:37,040 Speaker 1: for what we would like to see happen on a 352 00:21:37,040 --> 00:21:41,040 Speaker 1: bigger scale. So it's hugely important that we all be 353 00:21:41,840 --> 00:21:44,919 Speaker 1: creating or co creating or thinking about how we can 354 00:21:44,960 --> 00:21:48,560 Speaker 1: build things together. And this isn't just something for technical 355 00:21:48,600 --> 00:21:51,480 Speaker 1: people to think about. This is something for I think 356 00:21:51,680 --> 00:21:55,720 Speaker 1: all different sectors to be thinking about together, because I 357 00:21:55,760 --> 00:21:59,639 Speaker 1: think the really interesting thing or challenging thing about AI 358 00:21:59,800 --> 00:22:03,720 Speaker 1: is the way that it is becoming a part of 359 00:22:04,280 --> 00:22:08,400 Speaker 1: all kinds of different businesses, all kinds of areas where 360 00:22:08,440 --> 00:22:12,960 Speaker 1: there's data, all kinds of governance, or even the nonprofit world. 361 00:22:13,359 --> 00:22:16,480 Speaker 1: Anywhere where there's data, there's an opportunity to use AI 362 00:22:16,560 --> 00:22:19,480 Speaker 1: in some way, and sometimes it can be in ways 363 00:22:19,480 --> 00:22:23,720 Speaker 1: that are genuinely helpful too. I think, you know, rights causes, 364 00:22:23,760 --> 00:22:26,879 Speaker 1: and that's that's what we've been trying to highlight in 365 00:22:26,920 --> 00:22:30,800 Speaker 1: the podcast too, looking for people who are doing something 366 00:22:30,920 --> 00:22:34,520 Speaker 1: in a different way, and that you know, when you 367 00:22:34,680 --> 00:22:37,479 Speaker 1: see people who are building their own data sets or 368 00:22:37,480 --> 00:22:41,879 Speaker 1: creating their own voice recognition systems for their languages, you 369 00:22:42,040 --> 00:22:46,080 Speaker 1: realize the imbalance that there is that you know, it 370 00:22:46,200 --> 00:22:48,520 Speaker 1: wasn't created in the first place, that these things don't 371 00:22:48,560 --> 00:22:52,360 Speaker 1: exist already. A lot of ways that technology and systems 372 00:22:52,400 --> 00:22:54,159 Speaker 1: are designed to work. We just sort of take it 373 00:22:54,200 --> 00:22:56,919 Speaker 1: for granted, right We just think, oh, that's just the 374 00:22:56,960 --> 00:23:00,080 Speaker 1: way it is. But it doesn't have to be. And 375 00:23:00,119 --> 00:23:02,119 Speaker 1: so we need these people to shine a light on 376 00:23:02,600 --> 00:23:05,719 Speaker 1: how could it be different or where is that injustice? 377 00:23:05,720 --> 00:23:08,000 Speaker 1: So what is the data that's missing? How could we 378 00:23:08,080 --> 00:23:11,800 Speaker 1: be approaching this problem differently? And that does not mean that, 379 00:23:12,040 --> 00:23:15,679 Speaker 1: you know, we need to teach big tech, big companies 380 00:23:15,720 --> 00:23:17,800 Speaker 1: how to do it. It might just mean that we 381 00:23:17,840 --> 00:23:20,520 Speaker 1: need to find ways and find resources to do these 382 00:23:20,600 --> 00:23:24,560 Speaker 1: things ourselves. Our show is all about identity and the 383 00:23:24,600 --> 00:23:28,359 Speaker 1: Internet and how it can really impact how people who 384 00:23:28,400 --> 00:23:32,400 Speaker 1: are traditionally marginalized like what they bring to these conversations. 385 00:23:32,720 --> 00:23:34,919 Speaker 1: Do you feel like your identity as like a Danish 386 00:23:34,960 --> 00:23:38,359 Speaker 1: Puerto Rican woman, like, like, does that impact this this 387 00:23:38,560 --> 00:23:42,040 Speaker 1: kind of optimism that you have about an Internet that 388 00:23:42,119 --> 00:23:45,639 Speaker 1: is more inclusive, includes more people, more collaborative. Um. Do 389 00:23:45,640 --> 00:23:48,000 Speaker 1: you think that your identity has shaped what you bring 390 00:23:48,080 --> 00:23:52,480 Speaker 1: to the work? Um? Yeah, I think it does it definitely. 391 00:23:52,680 --> 00:23:55,560 Speaker 1: I mean I think it impacts my approach to everything 392 00:23:55,600 --> 00:23:57,840 Speaker 1: really because I've got some North in me, I've got 393 00:23:57,880 --> 00:24:02,600 Speaker 1: some South in me of at some different languages, um, 394 00:24:02,720 --> 00:24:05,760 Speaker 1: and different experiences, And so when you're able to kind 395 00:24:05,760 --> 00:24:08,600 Speaker 1: of step out of yourself and see something from a 396 00:24:08,640 --> 00:24:12,760 Speaker 1: different perspective, I think when you're willing to do that 397 00:24:13,040 --> 00:24:15,560 Speaker 1: at every level, you know, I can give you a 398 00:24:15,560 --> 00:24:18,880 Speaker 1: lot of empathy but also some imagination for how how 399 00:24:18,960 --> 00:24:22,160 Speaker 1: things could be or or how they might be. So yeah, 400 00:24:22,200 --> 00:24:24,800 Speaker 1: it is a big part of it. Even even more though, 401 00:24:24,840 --> 00:24:28,440 Speaker 1: I think it's just working with communities for so many 402 00:24:28,440 --> 00:24:31,520 Speaker 1: different years who have been using the Internet to to 403 00:24:31,680 --> 00:24:36,320 Speaker 1: do good in different way, particularly with the Global Voices community, 404 00:24:36,320 --> 00:24:42,119 Speaker 1: where we also had so many translation projects with you know, 405 00:24:42,400 --> 00:24:46,600 Speaker 1: citizen journalism that was translated in different directions, and just 406 00:24:46,760 --> 00:24:50,600 Speaker 1: reading news stories from around the world firsthand perspective news 407 00:24:50,640 --> 00:24:53,439 Speaker 1: stories from around the world. Yeah, I just know a 408 00:24:53,480 --> 00:24:58,800 Speaker 1: lot of strange things about different parts of the world. UM. 409 00:24:58,880 --> 00:25:02,040 Speaker 1: So that yeah, that's that's definitely part of it. But 410 00:25:02,200 --> 00:25:04,640 Speaker 1: I think when you're when you're working with an organization 411 00:25:04,720 --> 00:25:08,720 Speaker 1: like Mozilla, you do come into contact with a lot 412 00:25:08,760 --> 00:25:13,040 Speaker 1: of people in communities who have that sense of optimism 413 00:25:13,160 --> 00:25:15,959 Speaker 1: or have that drive to try and build something and 414 00:25:16,000 --> 00:25:19,040 Speaker 1: do something, and that that is very nice. When it 415 00:25:19,080 --> 00:25:25,119 Speaker 1: comes to the state of the Internet. Are you hopeful, Um, 416 00:25:25,240 --> 00:25:29,800 Speaker 1: I'm hopeful about some things. UM, And those are the 417 00:25:29,800 --> 00:25:33,199 Speaker 1: ones that I try to focus on. I spend a 418 00:25:33,240 --> 00:25:36,800 Speaker 1: lot of time convincing myself not to get too mad 419 00:25:36,840 --> 00:25:41,520 Speaker 1: about or to to jaded or too upset about, you know, 420 00:25:42,080 --> 00:25:46,840 Speaker 1: the global surveillance society. UM. I do feel like a 421 00:25:46,840 --> 00:25:50,080 Speaker 1: lot of things are getting worse, particularly when it comes 422 00:25:50,119 --> 00:25:53,840 Speaker 1: to surveillance and lack of privacy and the way these 423 00:25:53,840 --> 00:25:59,000 Speaker 1: systems are just kind of taking over really important things 424 00:25:59,200 --> 00:26:05,480 Speaker 1: in dangerous way. So I'm concerned, But I also see 425 00:26:05,480 --> 00:26:08,720 Speaker 1: a lot of good things happening. And having worked just 426 00:26:08,840 --> 00:26:12,080 Speaker 1: on this project for the last five six years, the 427 00:26:12,160 --> 00:26:16,840 Speaker 1: conversation has evolved. We we are, and I mean we 428 00:26:17,080 --> 00:26:22,400 Speaker 1: as humans all around the world and in the media 429 00:26:22,720 --> 00:26:26,119 Speaker 1: and even on social media. There's a lot more understanding 430 00:26:26,160 --> 00:26:29,480 Speaker 1: for how these systems work, what the harms are, what 431 00:26:29,600 --> 00:26:33,680 Speaker 1: the potential is. Um. You know, five six years ago 432 00:26:34,600 --> 00:26:36,600 Speaker 1: there there there hadn't been. That was just like the 433 00:26:36,640 --> 00:26:40,880 Speaker 1: beginning of Cambridge and Analytica. There's been so many UM 434 00:26:41,040 --> 00:26:45,320 Speaker 1: data privacy policies, a lot of things happening in a 435 00:26:45,320 --> 00:26:49,399 Speaker 1: good direction as well, So it's always about, yeah, trying 436 00:26:49,400 --> 00:26:51,960 Speaker 1: to see both the good and the bad at once 437 00:26:52,400 --> 00:26:55,199 Speaker 1: UM and keeping both those things in focus so that 438 00:26:55,240 --> 00:26:59,119 Speaker 1: you can keep moving forward. That's I mean, that's it 439 00:26:59,160 --> 00:27:02,720 Speaker 1: in a nutshell rite the Internet technology, it's really about 440 00:27:04,000 --> 00:27:07,160 Speaker 1: being able to hold two spaces at once, like, oh, 441 00:27:07,200 --> 00:27:11,200 Speaker 1: this is such a powerful gift and this technology provides 442 00:27:11,200 --> 00:27:13,919 Speaker 1: such a good opportunity for connection, but it can also 443 00:27:14,320 --> 00:27:17,600 Speaker 1: be used to do some really scary, horrible stuff. I 444 00:27:17,640 --> 00:27:20,400 Speaker 1: feel like you've just really summed it up nicely. Yeah, yeah, 445 00:27:20,480 --> 00:27:24,040 Speaker 1: I mean, that's that's everybody's daily experience, right, Like you 446 00:27:24,119 --> 00:27:28,239 Speaker 1: probably love Twitter and you probably hate Twitter or you know. 447 00:27:28,720 --> 00:27:32,560 Speaker 1: I love that I can do things easily online or 448 00:27:32,680 --> 00:27:35,600 Speaker 1: order food or delivery or whatever, but I also hate 449 00:27:35,600 --> 00:27:39,000 Speaker 1: that these systems are exploiting people in the worst possible way. 450 00:27:39,400 --> 00:27:43,760 Speaker 1: So yeah, we need to work together and we need 451 00:27:43,800 --> 00:27:47,879 Speaker 1: to fight back because these systems didn't exist just a 452 00:27:47,920 --> 00:27:52,240 Speaker 1: few years ago, and we can change them. Someone of 453 00:27:52,320 --> 00:27:55,360 Speaker 1: where can folks listen to the podcast and just generally 454 00:27:55,400 --> 00:27:56,919 Speaker 1: keep up with the work that you're doing with the 455 00:27:56,920 --> 00:28:01,120 Speaker 1: Internet Health Report and beyond, Well, they should listen to 456 00:28:01,440 --> 00:28:05,399 Speaker 1: our podcast because it's yours as well. Um, they should 457 00:28:05,400 --> 00:28:12,040 Speaker 1: go to dot Internet Health Report dot org. Um it's 458 00:28:12,080 --> 00:28:15,720 Speaker 1: called I r L podcast. You can find it everywhere 459 00:28:16,480 --> 00:28:19,840 Speaker 1: where there's podcasts. Is there anything that I did not 460 00:28:20,040 --> 00:28:21,840 Speaker 1: ask that you want to make sure it gets included? 461 00:28:23,440 --> 00:28:26,119 Speaker 1: I think the only thing I'm curious to ask you, 462 00:28:26,760 --> 00:28:30,199 Speaker 1: I'm curious to ask you what you What do you 463 00:28:30,280 --> 00:28:34,119 Speaker 1: think you'll bring with you from the podcast? Like, have 464 00:28:34,200 --> 00:28:39,840 Speaker 1: you noticed has it changed your mind about anything? Oh? 465 00:28:39,880 --> 00:28:42,280 Speaker 1: What a good question. I was actually just thinking about this. 466 00:28:43,000 --> 00:28:46,880 Speaker 1: I think it's changed my mind. I think before this 467 00:28:46,960 --> 00:28:50,880 Speaker 1: podcast I was a little I mean, this doesn't make 468 00:28:50,920 --> 00:28:53,920 Speaker 1: me sound great, but it's the truth. I think I 469 00:28:53,960 --> 00:28:59,400 Speaker 1: had a much more United States domestic focus on these issues, 470 00:28:59,720 --> 00:29:02,720 Speaker 1: and I kind of told myself, you don't really know 471 00:29:02,800 --> 00:29:06,520 Speaker 1: a lot about like geoglobal politics or you know what's 472 00:29:06,560 --> 00:29:08,800 Speaker 1: going on globally, so you got to focus on the 473 00:29:08,840 --> 00:29:11,800 Speaker 1: United States. From listening to I R. L and helping 474 00:29:11,800 --> 00:29:14,120 Speaker 1: to make it, I definitely have a better sense of 475 00:29:14,160 --> 00:29:17,800 Speaker 1: the way that these issues are global and so we're 476 00:29:17,800 --> 00:29:20,760 Speaker 1: experiencing something like a harm in the United States, that 477 00:29:20,840 --> 00:29:24,440 Speaker 1: harm is is deeper felt abroad, and that those harms 478 00:29:24,480 --> 00:29:27,440 Speaker 1: are connected and lengked, and so I think it's definitely 479 00:29:27,600 --> 00:29:31,000 Speaker 1: made me think a little further out than just my 480 00:29:31,040 --> 00:29:34,000 Speaker 1: own bubble in the United States, because yeah, these issues 481 00:29:34,040 --> 00:29:36,600 Speaker 1: are global, and I think that you do a beautiful 482 00:29:36,680 --> 00:29:38,680 Speaker 1: job of really demonstrating that. I think it will be 483 00:29:39,160 --> 00:29:42,520 Speaker 1: so easy to just have this be a conversation that 484 00:29:42,640 --> 00:29:45,520 Speaker 1: begins and ends in the West, but that wouldn't be 485 00:29:45,560 --> 00:29:48,200 Speaker 1: a full conversation, that wouldn't be the honest truth about 486 00:29:48,320 --> 00:29:52,800 Speaker 1: what the situation is. Yeah. Yeah, I've found that part 487 00:29:53,040 --> 00:29:55,479 Speaker 1: interesting as well. I mean, because I've learned just as 488 00:29:55,560 --> 00:29:58,120 Speaker 1: much listening to the people who are talking and sharing 489 00:29:58,160 --> 00:30:01,880 Speaker 1: their stories on the podcast and anyone, but this way 490 00:30:01,920 --> 00:30:04,600 Speaker 1: that you know, when we talk about the experience of 491 00:30:04,640 --> 00:30:09,400 Speaker 1: people in rural India, where we talk about um spatial 492 00:30:09,520 --> 00:30:13,240 Speaker 1: injustice in South Africa and you know data sets to 493 00:30:13,320 --> 00:30:17,400 Speaker 1: help combat that injustice. Just how much we share in 494 00:30:17,520 --> 00:30:21,160 Speaker 1: common on these topics, you know that that there's something 495 00:30:21,240 --> 00:30:27,240 Speaker 1: recognizable in that experience everywhere, and that even in the 496 00:30:27,280 --> 00:30:30,880 Speaker 1: most low tech parts of the world, there is this 497 00:30:31,240 --> 00:30:36,080 Speaker 1: highly advanced technology. Is something that I think will surprise people. 498 00:30:36,400 --> 00:30:40,320 Speaker 1: It still surprises me sometimes that really it doesn't matter 499 00:30:40,360 --> 00:30:44,920 Speaker 1: if you're online or offline. AI is everywhere now and 500 00:30:45,000 --> 00:30:48,480 Speaker 1: the Internet is everywhere now, and and that it can 501 00:30:48,520 --> 00:30:52,640 Speaker 1: make a difference to your life good or bad. Um 502 00:30:52,680 --> 00:30:57,280 Speaker 1: you know, like like the the the guests who describe 503 00:30:57,400 --> 00:31:01,520 Speaker 1: the voice chat bot that he made. He's been working 504 00:31:01,560 --> 00:31:06,400 Speaker 1: on voice recognition systems for UM major language in Wanda, 505 00:31:06,600 --> 00:31:11,640 Speaker 1: ken Your Wanda, and they created this this COVID chatbot 506 00:31:11,720 --> 00:31:15,040 Speaker 1: where you can call it up on the phone and 507 00:31:15,240 --> 00:31:18,360 Speaker 1: ask it questions about where to get vaccines and different 508 00:31:18,400 --> 00:31:22,160 Speaker 1: things related to public health. And when we were thinking 509 00:31:22,200 --> 00:31:24,800 Speaker 1: about whether to include that story in the podcast, I 510 00:31:25,720 --> 00:31:27,800 Speaker 1: sent him an email and I said, remy, how many 511 00:31:27,880 --> 00:31:31,840 Speaker 1: people are using this does it still exist? You know, 512 00:31:31,880 --> 00:31:34,760 Speaker 1: because they had won some award and there was a hackathon, 513 00:31:34,960 --> 00:31:37,200 Speaker 1: and you know, it was like a neat idea. But 514 00:31:37,440 --> 00:31:39,880 Speaker 1: you never know if these things take off. And he said, oh, yeah, 515 00:31:40,120 --> 00:31:45,760 Speaker 1: we just hit two million users the other day, so 516 00:31:45,880 --> 00:31:49,440 Speaker 1: I'll say people still use it. Yeah, yeah, and so 517 00:31:49,880 --> 00:31:52,680 Speaker 1: and this is a system that's designed for for people 518 00:31:52,960 --> 00:31:55,959 Speaker 1: who maybe just have feature phones um or who aren't 519 00:31:56,360 --> 00:31:58,360 Speaker 1: you know, you don't even have to be able to 520 00:31:58,400 --> 00:32:02,760 Speaker 1: read or write, but still AI and it's still Internet 521 00:32:03,160 --> 00:32:08,560 Speaker 1: and yeah. So so I feel like sometimes those low, 522 00:32:10,160 --> 00:32:15,080 Speaker 1: low connectivity contexts help us realize a lot of things 523 00:32:15,160 --> 00:32:18,680 Speaker 1: about life in you know, let's say, in the US 524 00:32:18,840 --> 00:32:22,120 Speaker 1: or places where there's high connectivity. It makes you think 525 00:32:22,160 --> 00:32:24,680 Speaker 1: about what you have and what you're able to do, 526 00:32:24,840 --> 00:32:28,200 Speaker 1: and what's good and maybe taken for granted about the Internet. 527 00:32:28,640 --> 00:32:31,240 Speaker 1: But it also makes you think about, oh, hey, there 528 00:32:31,240 --> 00:32:33,120 Speaker 1: are actually also a lot of people in the US 529 00:32:33,200 --> 00:32:36,120 Speaker 1: who can't read or write English, or who don't have 530 00:32:36,200 --> 00:32:39,080 Speaker 1: internet connections, or who only have slow internet connections and 531 00:32:39,080 --> 00:32:42,000 Speaker 1: so forth. So I think we share a lot more 532 00:32:42,040 --> 00:32:45,400 Speaker 1: in common on these these topics in particular than then 533 00:32:45,440 --> 00:32:48,880 Speaker 1: I think most people are aware of I find it fascinating. 534 00:32:49,320 --> 00:32:53,400 Speaker 1: You know that that approach to thinking about the Internet 535 00:32:53,520 --> 00:32:57,080 Speaker 1: as this global connector, but you know it also means 536 00:32:57,120 --> 00:32:59,880 Speaker 1: that we all need to be, you know, fighting fighting 537 00:33:00,040 --> 00:33:04,080 Speaker 1: for for it to be better. The Internet is at 538 00:33:04,080 --> 00:33:07,720 Speaker 1: once frightening and full of hope, and telling the stories 539 00:33:07,760 --> 00:33:09,960 Speaker 1: of the people like Solana who are fighting to make 540 00:33:09,960 --> 00:33:13,520 Speaker 1: the Internet better makes me hopeful, too hopeful that the 541 00:33:13,560 --> 00:33:16,160 Speaker 1: people who want to use the Internet to spread harm 542 00:33:16,280 --> 00:33:19,080 Speaker 1: will never be more powerful than the voices of all 543 00:33:19,120 --> 00:33:22,600 Speaker 1: the different people saying no, I don't think so, and 544 00:33:22,720 --> 00:33:26,880 Speaker 1: I believe that all of us can actually make a difference. Y'all. 545 00:33:26,920 --> 00:33:29,200 Speaker 1: Fighting for a better Internet means a lot to me, 546 00:33:29,360 --> 00:33:32,320 Speaker 1: So please, please please check out the I r L podcast. 547 00:33:39,000 --> 00:33:41,080 Speaker 1: If you're looking for ways to support the show, check 548 00:33:41,120 --> 00:33:43,720 Speaker 1: out our mark store at tangodi dot com slash store. 549 00:33:44,960 --> 00:33:47,000 Speaker 1: Got a story about an interesting thing in tech, or 550 00:33:47,040 --> 00:33:48,880 Speaker 1: just want to say hi, You can reach us at 551 00:33:48,920 --> 00:33:51,680 Speaker 1: Hello at tangodi dot com. You can also find transcripts 552 00:33:51,680 --> 00:33:54,120 Speaker 1: for today's episode at tangdi dot com. There Are No 553 00:33:54,200 --> 00:33:56,800 Speaker 1: Girls on the Internet was created by me Brigita. It's 554 00:33:56,800 --> 00:33:59,760 Speaker 1: a production of iHeart Radio and Unboss Creative, edited by 555 00:33:59,800 --> 00:34:03,520 Speaker 1: Joe we Pad Jonathan Strickland as our executive producer. Terry 556 00:34:03,560 --> 00:34:06,640 Speaker 1: Harrison is our producer and sound engineer. Michael Amata was 557 00:34:06,640 --> 00:34:09,680 Speaker 1: our contributing producer. I'm your host, Bridget Todd. If you 558 00:34:09,680 --> 00:34:11,360 Speaker 1: want to help us grow, rate and review us on 559 00:34:11,400 --> 00:34:14,839 Speaker 1: Apple Podcasts. For more podcasts from I heart Radio, check 560 00:34:14,840 --> 00:34:17,000 Speaker 1: out the iHeart Radio app, Apple podcast, or wherever you 561 00:34:17,040 --> 00:34:17,960 Speaker 1: get your podcasts.