1 00:00:00,080 --> 00:00:04,520 Speaker 1: Yeah. Welcome to How to Citizen with Baritune Day, a 2 00:00:04,600 --> 00:00:08,400 Speaker 1: podcast that reimagine citizen as a verb, not a legal status. 3 00:00:09,240 --> 00:00:11,639 Speaker 1: This season is all about tech and how it can 4 00:00:11,680 --> 00:00:15,960 Speaker 1: bring us together instead of tearing us apart. We're bringing 5 00:00:16,000 --> 00:00:18,720 Speaker 1: you the people using technology for so much more than 6 00:00:18,800 --> 00:00:23,000 Speaker 1: revenue and user growth. They're using it to help us citizen. 7 00:00:29,400 --> 00:00:35,239 Speaker 1: So first, I'm going to open the circle. Sky above me, 8 00:00:35,880 --> 00:00:44,520 Speaker 1: earth below me, love around me, divine within me, Mother, father, kind, ancestors. 9 00:00:44,600 --> 00:00:48,519 Speaker 1: Thank you for your wisdom which flows into us through us. 10 00:00:49,880 --> 00:00:53,600 Speaker 1: The reading that we undertake today is for the joy 11 00:00:53,640 --> 00:00:56,200 Speaker 1: and liberation of the sitter and the greater joy and 12 00:00:56,240 --> 00:01:00,440 Speaker 1: liberation of all. Thank you you had me at open 13 00:01:00,480 --> 00:01:07,040 Speaker 1: in the circle. That other voice you're hearing is Shaowei Wang. 14 00:01:07,760 --> 00:01:10,920 Speaker 1: Right now, they're reading my tarot cards, an old tech 15 00:01:11,000 --> 00:01:15,240 Speaker 1: of sorts. The cards can provide insights into our past, present, 16 00:01:15,400 --> 00:01:18,640 Speaker 1: and future. And this reading hits pretty close to home. 17 00:01:19,840 --> 00:01:24,120 Speaker 1: My mother was a very spiritually curious person. I was 18 00:01:24,200 --> 00:01:27,360 Speaker 1: baptized Catholic, but attended an Episcopal church from most of 19 00:01:27,360 --> 00:01:31,440 Speaker 1: my childhood. As my mom explored her own spirituality, she 20 00:01:31,640 --> 00:01:35,120 Speaker 1: just dragged me along with her to Buddhist temples to chant, 21 00:01:35,600 --> 00:01:38,720 Speaker 1: to our living room where she consulted the Taoist teaching 22 00:01:38,800 --> 00:01:42,960 Speaker 1: Book of Changes, to arenas for Native American pow wows, 23 00:01:42,959 --> 00:01:45,800 Speaker 1: and to her computer where she would generate and read 24 00:01:45,880 --> 00:01:49,600 Speaker 1: my astrological chart with her own software. Because of all 25 00:01:49,600 --> 00:01:53,040 Speaker 1: this history, I've always been open minded about the different 26 00:01:53,040 --> 00:01:56,600 Speaker 1: paths we can take to find meaning and insights. So Tarot, 27 00:01:56,720 --> 00:02:01,120 Speaker 1: that was an easy yes. Now shall weighs pulling three 28 00:02:01,160 --> 00:02:03,680 Speaker 1: cards to help frame my current state of mind. So 29 00:02:03,760 --> 00:02:07,320 Speaker 1: the middle card is the two of Pentacles, and so 30 00:02:07,440 --> 00:02:10,920 Speaker 1: as you see it, it's this iconography of someone who 31 00:02:11,440 --> 00:02:15,079 Speaker 1: is juggling, and in the back there's actually a lot 32 00:02:15,120 --> 00:02:23,240 Speaker 1: of water, so water meaning emotions. It's someone who you know, 33 00:02:23,400 --> 00:02:27,040 Speaker 1: you kind of see them, and they're like a court 34 00:02:27,240 --> 00:02:32,760 Speaker 1: jester almost. Um. So it's a sense of I'm juggling 35 00:02:32,919 --> 00:02:38,680 Speaker 1: a lot, particularly in the material round, so just like money, job, 36 00:02:38,840 --> 00:02:41,840 Speaker 1: things like that. And in the background is also this 37 00:02:41,960 --> 00:02:46,520 Speaker 1: tidal wave of emotion, like things look fun and playful 38 00:02:46,600 --> 00:02:49,600 Speaker 1: on the outside because I'm juggling for an audience, but 39 00:02:49,720 --> 00:02:52,560 Speaker 1: in the back there's a lot of emotion that's being 40 00:02:52,680 --> 00:02:56,800 Speaker 1: kind of damned up. I take that court jester or 41 00:02:56,800 --> 00:03:00,840 Speaker 1: comment as a compliment. Now, if you saw my Google calendar, 42 00:03:01,280 --> 00:03:04,200 Speaker 1: you know how real the juggler image is to my life. 43 00:03:04,240 --> 00:03:09,200 Speaker 1: Right now, I'm managing many commitments, including this podcast. I 44 00:03:09,320 --> 00:03:12,280 Speaker 1: often consider the fact that I deal with difficult topics 45 00:03:12,320 --> 00:03:16,000 Speaker 1: like race and democracy. I refer to what as handling 46 00:03:16,080 --> 00:03:23,040 Speaker 1: hazardous material. It takes an emotional toll, and as practiced 47 00:03:23,080 --> 00:03:27,000 Speaker 1: as I am at performing have it all togetherness, I'm 48 00:03:27,040 --> 00:03:30,600 Speaker 1: often holding back a lot of emotions associated with my 49 00:03:30,720 --> 00:03:34,560 Speaker 1: chosen work. That emotional water in the background of the card. 50 00:03:35,200 --> 00:03:39,160 Speaker 1: And on the other side, we have the Night of Swords, 51 00:03:40,080 --> 00:03:42,800 Speaker 1: and we have the Three of Cups, But the Night 52 00:03:42,840 --> 00:03:47,440 Speaker 1: of Sorts is someone who is just like has this 53 00:03:47,720 --> 00:03:50,880 Speaker 1: energy that's just like, Oh, there's a problem, let's do 54 00:03:50,960 --> 00:03:56,400 Speaker 1: something about it. How can we fix this immediately? There's 55 00:03:56,440 --> 00:03:59,520 Speaker 1: this one side of me that's just in the material realm. 56 00:03:59,560 --> 00:04:02,160 Speaker 1: As we're going through things, we have to fix it. 57 00:04:02,200 --> 00:04:03,880 Speaker 1: We have to get things done, we have to move 58 00:04:03,880 --> 00:04:06,800 Speaker 1: on to the next thing, moving at like a million 59 00:04:06,920 --> 00:04:14,120 Speaker 1: miles an hour. This is so me. I love to 60 00:04:14,160 --> 00:04:18,200 Speaker 1: fix things. I literally fixed computers to help pay for college, 61 00:04:18,920 --> 00:04:21,800 Speaker 1: and I'm always jumping to solutions in the face of 62 00:04:22,279 --> 00:04:25,800 Speaker 1: almost any problem, even when the people around me don't 63 00:04:25,839 --> 00:04:29,240 Speaker 1: want me to come up with a solution. And then 64 00:04:29,240 --> 00:04:31,600 Speaker 1: on the other side is the very real side of 65 00:04:31,680 --> 00:04:35,520 Speaker 1: when we're doing community work, when we're dealing with the 66 00:04:35,560 --> 00:04:41,359 Speaker 1: emotions of other people. That's a kind of slowness that 67 00:04:41,560 --> 00:04:44,720 Speaker 1: is very much, you know, counter to the Night of Swords. 68 00:04:44,760 --> 00:04:48,120 Speaker 1: Who's like about to Russian So at least from this 69 00:04:48,240 --> 00:04:51,960 Speaker 1: terror reading. And I'm curious if any of this resonates 70 00:04:52,040 --> 00:04:54,960 Speaker 1: with you, this notion of juggling between the two and 71 00:04:55,000 --> 00:04:57,440 Speaker 1: the sense of like I just want to like fix 72 00:04:57,480 --> 00:04:59,440 Speaker 1: it and do something about it. And then the other 73 00:04:59,480 --> 00:05:02,920 Speaker 1: part that's, you know, slow down, you know, talk it through, 74 00:05:03,000 --> 00:05:11,400 Speaker 1: talk about feelings. This is dead on, this is you, you 75 00:05:10,839 --> 00:05:16,200 Speaker 1: you got me. It's exactly where I am really and 76 00:05:16,240 --> 00:05:18,400 Speaker 1: then a lot of who I am and how I 77 00:05:18,480 --> 00:05:20,480 Speaker 1: present and what's going on to the surface. But the 78 00:05:20,520 --> 00:05:24,520 Speaker 1: support I'm finding shall wait, that's this podcast, you know, 79 00:05:24,760 --> 00:05:28,120 Speaker 1: like you also just read for how to Citizen, So 80 00:05:28,200 --> 00:05:31,520 Speaker 1: thank you. That is one of the most potent ways 81 00:05:31,560 --> 00:05:35,240 Speaker 1: of meeting a person that I've ever experienced. You have 82 00:05:35,279 --> 00:05:37,120 Speaker 1: a bit of a gift, so thanks for sharing it. 83 00:05:38,480 --> 00:05:43,960 Speaker 1: I know, I know, a tarot reading seems random but 84 00:05:44,040 --> 00:05:48,040 Speaker 1: tarot isn't just woo woo fortune telling. I love reading 85 00:05:48,120 --> 00:05:52,159 Speaker 1: Tarot for others and I always view it as helping 86 00:05:52,160 --> 00:05:55,640 Speaker 1: others hold space, or like holding up a mirror, if 87 00:05:55,680 --> 00:06:01,200 Speaker 1: you will, And that's exactly what we're doing today, my guests. 88 00:06:01,200 --> 00:06:04,520 Speaker 1: Shall Wei Wang is going to help us hold a mirror, 89 00:06:04,839 --> 00:06:08,599 Speaker 1: not just to me, but to the entire tech industry. 90 00:06:09,400 --> 00:06:12,600 Speaker 1: Shawi is not only a tower reader, but the lead 91 00:06:12,680 --> 00:06:16,360 Speaker 1: steward of Logic School, an online school that empowers tech 92 00:06:16,400 --> 00:06:20,559 Speaker 1: workers to transform the industry from within. They also wrote 93 00:06:20,560 --> 00:06:25,320 Speaker 1: the book called Blockchain Chicken Farm about tech in rural China. Cha. 94 00:06:25,440 --> 00:06:28,600 Speaker 1: We spent a lot of time traveling in China and 95 00:06:28,680 --> 00:06:32,560 Speaker 1: working in the tech industry themselves. Through these experiences, they 96 00:06:32,640 --> 00:06:35,640 Speaker 1: learned a lot about how to transform the tech industry. 97 00:06:35,760 --> 00:06:39,000 Speaker 1: And it may surprise you, but the solution is actually 98 00:06:39,200 --> 00:06:44,440 Speaker 1: pretty low tech. Take time, take patients, move at the 99 00:06:44,640 --> 00:06:48,680 Speaker 1: speed of trust and care. The act of talking to 100 00:06:48,800 --> 00:06:52,560 Speaker 1: people and just being with them. That's the work, right, 101 00:06:52,680 --> 00:06:56,159 Speaker 1: that's the transformation. When we come back from the break, 102 00:06:56,640 --> 00:06:59,520 Speaker 1: how a rural chicken farmer in China became a real 103 00:06:59,600 --> 00:07:08,840 Speaker 1: life landing a sketch, Hello, challweg, How are you good. 104 00:07:09,080 --> 00:07:11,800 Speaker 1: It's nice to meet you. By twin Day. Lovely to 105 00:07:11,840 --> 00:07:14,320 Speaker 1: meet you. First off, I want to talk to you 106 00:07:14,360 --> 00:07:18,800 Speaker 1: about your current work Logic School. Logic School is an 107 00:07:18,880 --> 00:07:22,720 Speaker 1: organizing school for tech workers. Above all, it's really a 108 00:07:22,720 --> 00:07:28,320 Speaker 1: community of twenty folks who get together every week and 109 00:07:28,720 --> 00:07:34,120 Speaker 1: laugh and cry and learn from activists, artists, people who 110 00:07:34,200 --> 00:07:39,160 Speaker 1: are trying to think about changing tech and the tech industry. UM. 111 00:07:39,200 --> 00:07:41,400 Speaker 1: As part of it, there were a series of final 112 00:07:41,440 --> 00:07:45,240 Speaker 1: projects that came out from the cohort and it's been 113 00:07:46,160 --> 00:07:49,280 Speaker 1: just such a joy and honor to serve as the 114 00:07:49,400 --> 00:07:53,600 Speaker 1: lead steward of that school and see the work that 115 00:07:53,640 --> 00:07:56,520 Speaker 1: people are doing. You say the Logic School is for 116 00:07:56,720 --> 00:08:01,240 Speaker 1: tech workers, will qualify someone as a tech worker? We 117 00:08:01,400 --> 00:08:05,200 Speaker 1: made the definition really broad on purpose, just to you know, 118 00:08:05,360 --> 00:08:09,520 Speaker 1: foster these incredible new connections. We had the gig worker 119 00:08:09,840 --> 00:08:13,880 Speaker 1: to someone who used to work actually in government policy 120 00:08:14,040 --> 00:08:16,920 Speaker 1: on tech um. It was a bit disillusioned, I don't 121 00:08:16,920 --> 00:08:21,080 Speaker 1: know what that says about regulation UM. And that we 122 00:08:21,200 --> 00:08:24,440 Speaker 1: also had you know, engineers, designers from some of the 123 00:08:24,480 --> 00:08:27,440 Speaker 1: big companies. So it was really cool to see that 124 00:08:27,880 --> 00:08:31,920 Speaker 1: conversation unfold. When when I think of a school for 125 00:08:32,000 --> 00:08:34,640 Speaker 1: tech workers The first thing that pops to mind is 126 00:08:34,679 --> 00:08:36,840 Speaker 1: a place like General Assembly or at a place that 127 00:08:36,920 --> 00:08:40,000 Speaker 1: kind of creates the classic image of a tech worker, 128 00:08:40,080 --> 00:08:43,199 Speaker 1: like they pump out coders and engineers and developers and 129 00:08:43,360 --> 00:08:47,000 Speaker 1: some version of those words, and the images typing long 130 00:08:47,040 --> 00:08:49,560 Speaker 1: into the night. Maybe that scene from the Social network 131 00:08:49,760 --> 00:08:54,000 Speaker 1: where everybody's like pounding beers and slamming keys. What is 132 00:08:54,040 --> 00:08:57,600 Speaker 1: your definition of tech worker and of tech work? I 133 00:08:57,640 --> 00:09:00,760 Speaker 1: love that that is like a very good and marketing 134 00:09:02,200 --> 00:09:05,640 Speaker 1: scheme on behalf of the tech industry where they're like, yeah, 135 00:09:05,679 --> 00:09:08,679 Speaker 1: there's you know, fridge full of kombucha and you're just 136 00:09:08,840 --> 00:09:13,840 Speaker 1: like hacking, like it's mostly snacks, right exactly. I think 137 00:09:13,960 --> 00:09:18,080 Speaker 1: for us at Logic School, you know, a tech worker 138 00:09:18,240 --> 00:09:22,480 Speaker 1: can be someone who's doing community technology, so instead of 139 00:09:22,520 --> 00:09:25,640 Speaker 1: working for a big company, they're thinking about like what's 140 00:09:25,679 --> 00:09:30,360 Speaker 1: the infrastructure, what's the projects that respond to the needs 141 00:09:30,400 --> 00:09:34,120 Speaker 1: of their local neighborhood. It can be someone who's beyond 142 00:09:34,480 --> 00:09:39,199 Speaker 1: the like I'm so rational, I'm so logical image that 143 00:09:39,240 --> 00:09:42,199 Speaker 1: we have um and really someone who has a lot 144 00:09:42,240 --> 00:09:45,520 Speaker 1: of care and thoughtfulness. You know, I think all of 145 00:09:45,559 --> 00:09:48,880 Speaker 1: these ideas of what a tech worker looks like that's 146 00:09:49,440 --> 00:09:54,200 Speaker 1: highly gendered, highly racialized, and you know has has a 147 00:09:54,240 --> 00:09:59,800 Speaker 1: lot to do with capitalism. How does the school itself work? 148 00:10:00,600 --> 00:10:05,120 Speaker 1: We met every week over zoom, had folks from Pittsburgh 149 00:10:05,160 --> 00:10:08,319 Speaker 1: all the way to Texas in the Bay Area, and 150 00:10:08,760 --> 00:10:13,360 Speaker 1: amazing guest lecturers come in like the Free Radicals, stop 151 00:10:13,520 --> 00:10:18,880 Speaker 1: lap d spying coalition to Kadija abdu Rakhman, who's working 152 00:10:18,960 --> 00:10:22,800 Speaker 1: on child welfare in the New York City area. And yeah, 153 00:10:22,880 --> 00:10:25,839 Speaker 1: just lots of dialogue and activities and feedback on each 154 00:10:25,880 --> 00:10:30,319 Speaker 1: other's projects. I think one of the most important questions 155 00:10:30,320 --> 00:10:33,559 Speaker 1: for us was, you know, who are your people, who's 156 00:10:33,600 --> 00:10:37,240 Speaker 1: your community? Who do you see yourself building tech for? 157 00:10:37,760 --> 00:10:43,800 Speaker 1: Right this sounds like the opposite of everything we've been 158 00:10:43,840 --> 00:10:47,760 Speaker 1: taught about the tech sector as a workplace. I think 159 00:10:47,800 --> 00:10:50,959 Speaker 1: a lot of us are like, it's very logical, it's inhumane, 160 00:10:51,040 --> 00:10:56,319 Speaker 1: it's non empathetic, it's profit seeking, it's overworked, and questions 161 00:10:56,400 --> 00:11:02,079 Speaker 1: about empathy and community and power they're just not associated 162 00:11:02,280 --> 00:11:06,160 Speaker 1: with tech generally. What was the impetus to create the 163 00:11:06,240 --> 00:11:09,440 Speaker 1: Logic School in this way? It was exactly what you 164 00:11:09,520 --> 00:11:13,880 Speaker 1: just said. I mean, there's very few spaces to talk 165 00:11:13,960 --> 00:11:18,000 Speaker 1: about power, to talk about you know, how do we 166 00:11:19,000 --> 00:11:25,240 Speaker 1: be empathetic? I mean there's places like after work extracurriculars 167 00:11:25,280 --> 00:11:28,240 Speaker 1: where you can learn how to be a better engineer, right, like, 168 00:11:28,640 --> 00:11:31,640 Speaker 1: how do I do better JavaScript on the job? Like 169 00:11:31,720 --> 00:11:35,319 Speaker 1: all these things, um, but logic school really response to that. 170 00:11:35,360 --> 00:11:38,480 Speaker 1: There's no space where it's like, I'm a tech worker 171 00:11:38,559 --> 00:11:41,760 Speaker 1: and I'm having kind of a crisis about what my 172 00:11:41,800 --> 00:11:45,360 Speaker 1: company is doing. How do I bring in empathy into 173 00:11:45,400 --> 00:11:49,280 Speaker 1: the workplace. It was actually interesting because some people definitely 174 00:11:49,320 --> 00:11:52,480 Speaker 1: try to bring in empathy from what they learned at 175 00:11:52,480 --> 00:11:55,840 Speaker 1: logic School into the workplace and it got shut down. 176 00:11:56,640 --> 00:11:59,120 Speaker 1: So I think it also says a lot about just 177 00:11:59,280 --> 00:12:02,360 Speaker 1: the way the tech industry is structured and what they 178 00:12:02,440 --> 00:12:07,480 Speaker 1: want to maintain. When you create this program, you invite 179 00:12:07,480 --> 00:12:10,560 Speaker 1: these people in meeting every week, what do you want 180 00:12:10,600 --> 00:12:14,760 Speaker 1: them to leave with? Honestly, I think that as part 181 00:12:14,800 --> 00:12:18,280 Speaker 1: of rethinking what school is, I think everyone came in 182 00:12:18,320 --> 00:12:21,760 Speaker 1: with a different goal because that's also like very different 183 00:12:21,760 --> 00:12:24,319 Speaker 1: than a job, right. A job is like we create 184 00:12:24,400 --> 00:12:26,440 Speaker 1: this space for you to do one thing. We have 185 00:12:26,559 --> 00:12:29,120 Speaker 1: these expectations of how you do on your job, and 186 00:12:29,160 --> 00:12:33,560 Speaker 1: you will be evaluated by every quarter. We had one 187 00:12:33,640 --> 00:12:39,400 Speaker 1: person who worked at Twitter during the length of the 188 00:12:39,440 --> 00:12:43,800 Speaker 1: President who I will not say his name, and you know, 189 00:12:43,920 --> 00:12:48,840 Speaker 1: had a lot of just personal all these like traumas, right, 190 00:12:49,080 --> 00:12:53,160 Speaker 1: and spent logic school processing through that and actually, you know, 191 00:12:53,320 --> 00:12:58,120 Speaker 1: talking about trust and safety more broadly, we had another 192 00:12:58,400 --> 00:13:04,079 Speaker 1: person who is actually building this incredible augmented reality app 193 00:13:04,200 --> 00:13:09,720 Speaker 1: now in Pittsburgh and his whole app for his community 194 00:13:09,840 --> 00:13:13,559 Speaker 1: to like celebrate black life in Pittsburgh and to really 195 00:13:13,600 --> 00:13:19,599 Speaker 1: counter these narratives of disappearance and gentrification. So it's a 196 00:13:19,760 --> 00:13:22,560 Speaker 1: whole range of what people wanted out of it, but 197 00:13:22,720 --> 00:13:25,600 Speaker 1: just trying to be like, hey, this this could be 198 00:13:25,640 --> 00:13:29,040 Speaker 1: a different tech That's why we're here. You know, I've 199 00:13:29,080 --> 00:13:33,200 Speaker 1: been frustrated myself at the lack of imagination and in 200 00:13:33,520 --> 00:13:35,160 Speaker 1: some ways I've said, we've taken some of the most 201 00:13:35,200 --> 00:13:38,480 Speaker 1: powerful machines that we've ever built and some of the 202 00:13:38,520 --> 00:13:41,640 Speaker 1: smartest people that we've ever had, and applied it to 203 00:13:41,760 --> 00:13:46,160 Speaker 1: like shipping ads. It's a very underwhelming use of a superpower. 204 00:13:46,760 --> 00:13:49,000 Speaker 1: I want to know more about you. You've been a 205 00:13:49,040 --> 00:13:53,800 Speaker 1: tech worker. Yeah, so there was this moment where I 206 00:13:53,840 --> 00:13:58,240 Speaker 1: was working in tech and it was and Trump got 207 00:13:58,280 --> 00:14:03,679 Speaker 1: elected and like all tech companies in the Bay Area. 208 00:14:03,720 --> 00:14:06,280 Speaker 1: At the time, you know, the CEO gives kind of 209 00:14:06,320 --> 00:14:10,480 Speaker 1: a little speech about like, this terrible thing has happened, 210 00:14:10,800 --> 00:14:14,320 Speaker 1: and now we have to realize that what we do 211 00:14:14,440 --> 00:14:17,600 Speaker 1: every day at our company is changing the world and 212 00:14:17,640 --> 00:14:19,800 Speaker 1: improving the world, and we still have to do it. 213 00:14:19,840 --> 00:14:22,640 Speaker 1: And it's actually fighting against like Trump and all of 214 00:14:22,680 --> 00:14:28,960 Speaker 1: what this like right wing is um is doing. I'm 215 00:14:29,120 --> 00:14:34,200 Speaker 1: all fired up in tingling and stuff. Okay, braveheart speech, right. Yeah. 216 00:14:34,840 --> 00:14:38,280 Speaker 1: At the same time, I was sitting there and I 217 00:14:38,360 --> 00:14:41,600 Speaker 1: was like, but our company is funded by like Dared 218 00:14:41,720 --> 00:14:49,200 Speaker 1: Kushner's brother, all these threads of funding. You know, it's 219 00:14:49,240 --> 00:14:53,240 Speaker 1: every quarter the venture capitalists who fund the company, they 220 00:14:53,280 --> 00:14:56,800 Speaker 1: come in and there's always this kind of standoff, right 221 00:14:56,960 --> 00:15:00,480 Speaker 1: like they're like, we need to see returns. This is 222 00:15:00,520 --> 00:15:02,760 Speaker 1: how you should change your business plan, this is how 223 00:15:02,800 --> 00:15:05,080 Speaker 1: you should run your company. And then it trickles down 224 00:15:05,120 --> 00:15:08,600 Speaker 1: to us, like the engineers working day to day, it's like, oh, 225 00:15:08,720 --> 00:15:11,360 Speaker 1: that thing you were working on, actually it doesn't matter anymore. 226 00:15:11,400 --> 00:15:14,800 Speaker 1: We're like pivoting to this new thing. And so just 227 00:15:14,920 --> 00:15:19,960 Speaker 1: realizing one this kind of culture of not care but 228 00:15:20,080 --> 00:15:25,160 Speaker 1: really bottom line returns, and then too the idea that 229 00:15:25,200 --> 00:15:29,280 Speaker 1: we're doing something to better the world, to change the world, 230 00:15:29,440 --> 00:15:33,360 Speaker 1: and yet you know, our work was really making making 231 00:15:33,360 --> 00:15:37,880 Speaker 1: other people rich essentially UM and not helping communities directly. 232 00:15:38,440 --> 00:15:43,840 Speaker 1: That I think gave me a sense of disillusionment. I'd 233 00:15:43,920 --> 00:15:46,880 Speaker 1: love to UM know a bit more about your path. 234 00:15:47,200 --> 00:15:50,720 Speaker 1: And I know you've written a book whose title just 235 00:15:50,840 --> 00:15:54,200 Speaker 1: makes me crack up every time I hear it, Blockchain 236 00:15:54,360 --> 00:15:58,000 Speaker 1: Chicken Farm. What experiences did you have in tech that 237 00:15:58,080 --> 00:16:00,920 Speaker 1: led you to rural China to write a book called 238 00:16:00,920 --> 00:16:04,720 Speaker 1: block Change Chicken for? My friend Jason came up with 239 00:16:04,760 --> 00:16:08,280 Speaker 1: that title, and I was just like so snappy. You know. 240 00:16:08,320 --> 00:16:11,360 Speaker 1: There was also a lot of anti China of rhetoric 241 00:16:11,720 --> 00:16:14,920 Speaker 1: at the time. They're still continues to be, but just 242 00:16:15,000 --> 00:16:19,800 Speaker 1: this idea that there's this foreign power battle of the 243 00:16:19,840 --> 00:16:24,920 Speaker 1: civilization stuff going on UM, and I really wanted to, 244 00:16:25,400 --> 00:16:28,760 Speaker 1: you know, question that idea that it's like, you know, 245 00:16:29,040 --> 00:16:33,320 Speaker 1: US versus China, and China is this foreign place that's 246 00:16:33,320 --> 00:16:36,480 Speaker 1: so different and scary. And I think the approach I 247 00:16:36,560 --> 00:16:40,160 Speaker 1: really wanted to take was to humanize UM and to 248 00:16:40,280 --> 00:16:43,760 Speaker 1: tell these stories on the ground of folks in rural China. 249 00:16:44,440 --> 00:16:47,800 Speaker 1: It made sense to me also because we really ignore 250 00:16:47,920 --> 00:16:51,440 Speaker 1: the rural um. I mean not just in the US, 251 00:16:51,560 --> 00:16:54,720 Speaker 1: but also in China, where it's just like we paint 252 00:16:54,760 --> 00:16:58,560 Speaker 1: these pictures in broad strokes of like what country side 253 00:16:58,840 --> 00:17:02,720 Speaker 1: people are like, and then it's actually way more complicated 254 00:17:02,800 --> 00:17:06,800 Speaker 1: and it connects to like a global story too, about 255 00:17:07,119 --> 00:17:12,640 Speaker 1: you know, agriculture, economics, all these like big picture systems 256 00:17:13,040 --> 00:17:18,040 Speaker 1: complicate China for me with the sites, the smells, the sounds, 257 00:17:18,560 --> 00:17:21,320 Speaker 1: the tastes that you experience that we miss out on 258 00:17:21,480 --> 00:17:24,960 Speaker 1: when we over generalize. I mean, I miss it so 259 00:17:25,119 --> 00:17:28,040 Speaker 1: much because I haven't been able to travel. So I'm 260 00:17:28,119 --> 00:17:33,360 Speaker 1: sorry if I get like nostalgic or emotional, I will 261 00:17:33,400 --> 00:17:40,440 Speaker 1: open a circle for you to have these feelings. Oh, 262 00:17:40,800 --> 00:17:43,600 Speaker 1: you know, my time in real China, there were villages 263 00:17:43,680 --> 00:17:46,960 Speaker 1: that I would go to um several times, like twice 264 00:17:46,960 --> 00:17:50,520 Speaker 1: a year, and it felt like a sense of returning home. 265 00:17:53,200 --> 00:17:56,600 Speaker 1: Whenever you get to a village, it's this really beautiful 266 00:17:56,640 --> 00:17:58,639 Speaker 1: thing where the first thing they ask is have you 267 00:17:58,680 --> 00:18:03,439 Speaker 1: eaten yet? And there's just such a priority and value 268 00:18:03,520 --> 00:18:07,080 Speaker 1: placed on food, especially you know for rural places where 269 00:18:07,440 --> 00:18:09,960 Speaker 1: a lot of the times, you know there might be famine, 270 00:18:10,480 --> 00:18:13,320 Speaker 1: there might not be enough to eat, and so people 271 00:18:13,400 --> 00:18:16,840 Speaker 1: present you with this like bowl of rice and sometimes 272 00:18:16,840 --> 00:18:19,840 Speaker 1: there's little dots on it in the rice because of 273 00:18:19,920 --> 00:18:25,439 Speaker 1: insects that have eaten the rice. And it just is 274 00:18:25,480 --> 00:18:28,800 Speaker 1: this feeling of like, oh, like you're literally giving me 275 00:18:28,960 --> 00:18:33,240 Speaker 1: food from your own grain store and feeling really touched 276 00:18:33,280 --> 00:18:47,840 Speaker 1: by that. What misunderstandings do you think people like us 277 00:18:47,880 --> 00:18:50,199 Speaker 1: have us in the US and the West in general. 278 00:18:50,880 --> 00:18:54,560 Speaker 1: What misunderstandings do we have about tech in China? I 279 00:18:54,560 --> 00:18:58,320 Speaker 1: would say the biggest misunderstanding that I've seen, I mean, 280 00:18:58,480 --> 00:19:01,640 Speaker 1: especially in relation to this anti China stuff, is that 281 00:19:01,680 --> 00:19:09,800 Speaker 1: like China is they're stealing everything right um, and that 282 00:19:09,840 --> 00:19:15,280 Speaker 1: there is absolutely zero freedom that you know, somehow the 283 00:19:15,359 --> 00:19:19,600 Speaker 1: people of China are complicit in what its government does, 284 00:19:20,400 --> 00:19:22,520 Speaker 1: you know? And when you're in rural China, which is 285 00:19:22,560 --> 00:19:27,480 Speaker 1: still like the population, folks are just living day to day, 286 00:19:27,520 --> 00:19:31,840 Speaker 1: trying to get by, making money, harvesting their crops, thinking 287 00:19:31,880 --> 00:19:35,040 Speaker 1: about their kids in their next generation and how they're 288 00:19:35,040 --> 00:19:39,960 Speaker 1: going to pay the school bills. Sounds very relatable. You 289 00:19:40,000 --> 00:19:42,159 Speaker 1: know what they sound like? Shall we? They sound like 290 00:19:42,320 --> 00:19:48,920 Speaker 1: people exactly. We've gotten to a point where it's hard 291 00:19:48,960 --> 00:19:53,840 Speaker 1: to see beyond certain narratives. We we got to get 292 00:19:53,880 --> 00:19:57,080 Speaker 1: to the title and and how your book landed on 293 00:19:57,240 --> 00:20:00,240 Speaker 1: blockchain Chicken farm. The book is full of store words 294 00:20:00,280 --> 00:20:03,439 Speaker 1: of people from the rural parts of China. What's the 295 00:20:03,480 --> 00:20:08,520 Speaker 1: story that led to this title Chinese economic development? It 296 00:20:08,640 --> 00:20:13,000 Speaker 1: happened really fast, in the span of like twenty thirty years. 297 00:20:13,040 --> 00:20:16,520 Speaker 1: So when you have gross that fast, things are going 298 00:20:16,560 --> 00:20:20,159 Speaker 1: to happen. The block chain chickens really came out of 299 00:20:20,200 --> 00:20:23,800 Speaker 1: this one small farmer in Guido Province where he was 300 00:20:23,880 --> 00:20:27,760 Speaker 1: raising free range chickens, and no one believed him that 301 00:20:27,840 --> 00:20:31,359 Speaker 1: they were free range. There's such distrust. So he said, 302 00:20:31,440 --> 00:20:34,040 Speaker 1: I've got these free range chickens. They're like, you're lying, 303 00:20:34,359 --> 00:20:37,520 Speaker 1: prove it. So he was like some county official came 304 00:20:37,520 --> 00:20:39,439 Speaker 1: in was like, well, you should put these chickens on 305 00:20:39,480 --> 00:20:43,199 Speaker 1: the block chain. Paul is right there. That's just not 306 00:20:43,359 --> 00:20:47,240 Speaker 1: a normal government response, you know, Like I just I 307 00:20:47,280 --> 00:20:51,280 Speaker 1: can't imagine like my DMV manager or some FDA official 308 00:20:51,359 --> 00:20:54,000 Speaker 1: here in the US like you should put this livestock 309 00:20:54,160 --> 00:20:59,720 Speaker 1: on the blockchain. What does that even mean. So there's 310 00:20:59,800 --> 00:21:02,960 Speaker 1: all these small tech companies in China who I think 311 00:21:03,040 --> 00:21:06,960 Speaker 1: just wat government contracts, and the one company offered this 312 00:21:07,040 --> 00:21:10,840 Speaker 1: product that was like, you know, the blockchain is this 313 00:21:11,000 --> 00:21:16,120 Speaker 1: ledger um so record keeping system that can't change or falsify, right, 314 00:21:16,280 --> 00:21:19,760 Speaker 1: so you could say, like the chicken is a pent 315 00:21:19,840 --> 00:21:22,800 Speaker 1: free range, and then it got sent to this slaughterhouse 316 00:21:23,440 --> 00:21:28,080 Speaker 1: and it was slaughtered on X y Z date and 317 00:21:28,119 --> 00:21:32,439 Speaker 1: now it's at your doorstep um. And these chickens were 318 00:21:32,480 --> 00:21:36,600 Speaker 1: heavily tracked. It was really wild, like it's like a 319 00:21:36,640 --> 00:21:41,919 Speaker 1: giant chicken surveillance network. Yes, there was actually a dashboard 320 00:21:42,080 --> 00:21:47,520 Speaker 1: where you could watch the chickens through cameras. This is 321 00:21:47,640 --> 00:21:53,159 Speaker 1: weirdly dystopic and hilarious and progressive all at the same time. 322 00:21:54,240 --> 00:21:57,000 Speaker 1: I know, right, it's like, oh, you could definitely see 323 00:21:57,160 --> 00:22:00,320 Speaker 1: that Portlandia sketch where they're like this chicken has been 324 00:22:00,359 --> 00:22:03,280 Speaker 1: massage and here's a picture of it. Here is the 325 00:22:03,440 --> 00:22:07,960 Speaker 1: chicken you'll get joined tonight. This is fantastic. Absolutely. His 326 00:22:08,040 --> 00:22:13,239 Speaker 1: name was Colin. So farmer needs people to believe that 327 00:22:13,320 --> 00:22:16,919 Speaker 1: his chickens are free range. County officials like, I know, 328 00:22:17,560 --> 00:22:19,760 Speaker 1: we prove it with the blockchain. Put these chickens on 329 00:22:19,800 --> 00:22:22,560 Speaker 1: the block chain. Did it work? Did it help the 330 00:22:22,600 --> 00:22:26,879 Speaker 1: farmer when he had this distributed certification through the blockchain ledger. 331 00:22:27,480 --> 00:22:32,879 Speaker 1: So I will say that it really did work. He 332 00:22:33,200 --> 00:22:36,640 Speaker 1: sold all of his chickens. Um the chickens each had 333 00:22:36,720 --> 00:22:41,840 Speaker 1: this gnarly chicken fitbit is like this bracelet. Stop you're 334 00:22:41,920 --> 00:22:47,000 Speaker 1: killing me. So they had a chicken okay, yeah, and 335 00:22:47,040 --> 00:22:50,040 Speaker 1: the tracker had a QR code. But when they slaughtered 336 00:22:50,040 --> 00:22:54,000 Speaker 1: the chicken, they actually keep the tracker on. So you 337 00:22:54,160 --> 00:22:57,720 Speaker 1: can buy the chicken online. And so when you get 338 00:22:57,800 --> 00:23:01,840 Speaker 1: the chicken, it's like this dead chicken, but it still 339 00:23:01,920 --> 00:23:07,360 Speaker 1: has this wrist thing attached to it. It's really a site. 340 00:23:07,680 --> 00:23:10,600 Speaker 1: So the chickens got a little chicken apple watch, you know, 341 00:23:10,760 --> 00:23:13,399 Speaker 1: which is like tracking its health. Does the person who 342 00:23:13,440 --> 00:23:16,480 Speaker 1: buys the chicken do they read that little tracker themselves 343 00:23:16,520 --> 00:23:19,240 Speaker 1: to kind of inspect it. Yeah, they can scan the 344 00:23:19,320 --> 00:23:21,600 Speaker 1: QR code and then read about it. So there's like 345 00:23:21,640 --> 00:23:24,160 Speaker 1: a picture of the chicken, how much the chicken waight 346 00:23:24,440 --> 00:23:28,879 Speaker 1: at birth, how many steps it took, because there's like 347 00:23:28,920 --> 00:23:33,560 Speaker 1: a phenomena like all the chicken got it sent thousand 348 00:23:33,560 --> 00:23:39,040 Speaker 1: steps in let's eat. So this is what you've just done, 349 00:23:39,680 --> 00:23:43,480 Speaker 1: as you've brought a Portlandia sketch to life. The truth 350 00:23:43,560 --> 00:23:51,119 Speaker 1: is stranger than fiction. Oh so this sounds like a 351 00:23:51,240 --> 00:23:55,000 Speaker 1: victory farmer gets people to believe his chickens are free 352 00:23:55,080 --> 00:23:57,879 Speaker 1: range because he's got the blockchain proof, sells out of 353 00:23:57,880 --> 00:24:01,679 Speaker 1: his chickens and now is like the biggest farmer in 354 00:24:01,760 --> 00:24:06,280 Speaker 1: rural China. What's how does this story proceed? Um? Sadly, 355 00:24:06,680 --> 00:24:10,640 Speaker 1: I think that this is another one of those situations 356 00:24:10,720 --> 00:24:14,320 Speaker 1: when we say, like we're building tech to quote unquote 357 00:24:14,359 --> 00:24:18,520 Speaker 1: improve people's lives. It's like, well, who for who you know? 358 00:24:18,680 --> 00:24:21,639 Speaker 1: Who do you count as your people and your community? 359 00:24:22,080 --> 00:24:25,680 Speaker 1: And this farmer was kind of abandoned by that tech 360 00:24:25,720 --> 00:24:29,399 Speaker 1: company and for the next season he's he's good at 361 00:24:29,480 --> 00:24:32,879 Speaker 1: raising chickens and thinking about chicken life. Um, he's not 362 00:24:33,080 --> 00:24:36,560 Speaker 1: a programmer. And when I asked him, you know, how 363 00:24:36,560 --> 00:24:41,520 Speaker 1: do you feel about blockchain? He was like, what's blockchain? Um, which, 364 00:24:41,720 --> 00:24:45,040 Speaker 1: to be honest, is a question that I think most 365 00:24:45,080 --> 00:24:47,760 Speaker 1: of us would ask, right, like what's black chain? But 366 00:24:48,440 --> 00:24:51,399 Speaker 1: there was really a sense that he became like dependent 367 00:24:51,560 --> 00:24:56,000 Speaker 1: on this very opaque product that he had no control over, 368 00:24:56,400 --> 00:24:59,840 Speaker 1: and when they pivot and when it becomes about profit 369 00:25:00,040 --> 00:25:03,159 Speaker 1: the bottom line, they had to move on to other projects. 370 00:25:05,280 --> 00:25:07,840 Speaker 1: How else have you seen tech companies exploiting folks in 371 00:25:07,880 --> 00:25:13,120 Speaker 1: world China, I would say with the e commerce villages, Um, 372 00:25:13,240 --> 00:25:18,880 Speaker 1: that was really fascinating because you know, the tech companies 373 00:25:18,960 --> 00:25:24,959 Speaker 1: they say, hey, we're providing livelihoods to the countryside. You know, 374 00:25:25,080 --> 00:25:30,040 Speaker 1: now you can work from anywhere and manufacture Halloween costumes 375 00:25:30,160 --> 00:25:33,800 Speaker 1: or you know, wooden block toys for taboo. And it 376 00:25:33,840 --> 00:25:36,920 Speaker 1: sounds great. I mean it really does. You can stay, 377 00:25:36,960 --> 00:25:39,119 Speaker 1: you can work from home. Where have I heard this before? 378 00:25:39,560 --> 00:25:43,320 Speaker 1: Continue and work from home is going to be like 379 00:25:43,400 --> 00:25:50,160 Speaker 1: the mantra of our century. And yeah, so these folks 380 00:25:50,200 --> 00:25:54,920 Speaker 1: they would be, you know, basically making Halloween costumes out 381 00:25:54,960 --> 00:25:58,880 Speaker 1: of their home workshops. Um. I saw old people like 382 00:25:59,000 --> 00:26:03,040 Speaker 1: their grandparents and uh, you know great aunts like helping 383 00:26:03,240 --> 00:26:06,399 Speaker 1: with the manufacturing and the packaging and the shipping. So 384 00:26:06,400 --> 00:26:09,359 Speaker 1: it was really a family business or you know, some 385 00:26:09,440 --> 00:26:14,600 Speaker 1: people might call it like family self exploitation. Um. There 386 00:26:14,680 --> 00:26:20,120 Speaker 1: was definitely this like rosy scene that the official government 387 00:26:20,240 --> 00:26:23,520 Speaker 1: line was trying to paint like this is poverty alleviation, 388 00:26:23,760 --> 00:26:28,760 Speaker 1: it's giving people like digital literacy skills. But then when 389 00:26:28,760 --> 00:26:31,240 Speaker 1: I actually started talking to some folks that are like, 390 00:26:31,400 --> 00:26:33,600 Speaker 1: this is like a scam, and we know it and 391 00:26:33,640 --> 00:26:36,240 Speaker 1: we're just trying to like get it while it's good 392 00:26:36,359 --> 00:26:41,080 Speaker 1: and make money while we can. So they were saying 393 00:26:41,240 --> 00:26:44,080 Speaker 1: that the sellers, if you're selling on the platform, you 394 00:26:44,080 --> 00:26:46,920 Speaker 1: have to pay fees, you have to buy ads. It's 395 00:26:46,960 --> 00:26:49,760 Speaker 1: like a race to the bottom to try and cut costs, 396 00:26:50,000 --> 00:26:54,320 Speaker 1: and you're just making cheaper and cheaper items, um that 397 00:26:54,359 --> 00:26:56,840 Speaker 1: are really flimsy, that are like you use it once 398 00:26:56,880 --> 00:26:59,800 Speaker 1: and it falls apart. But they're like, this is just 399 00:27:00,000 --> 00:27:02,560 Speaker 1: all part of the game and in a few years 400 00:27:02,600 --> 00:27:04,600 Speaker 1: this might not work, but we're going to get rich 401 00:27:04,680 --> 00:27:07,399 Speaker 1: while we can. And so it was interesting, you know, 402 00:27:07,560 --> 00:27:11,639 Speaker 1: to to see just like again this reliance on a 403 00:27:11,720 --> 00:27:16,159 Speaker 1: platform and how much control that e commerce platforms had 404 00:27:16,280 --> 00:27:20,720 Speaker 1: over sellers. We have the same story in the United 405 00:27:20,760 --> 00:27:23,640 Speaker 1: States and in other Western countries. Um. We've been talked 406 00:27:23,640 --> 00:27:27,359 Speaker 1: about it on this podcast about Amazon, uh, mostly in 407 00:27:27,400 --> 00:27:30,280 Speaker 1: the US and how this race to the bottom. So 408 00:27:30,359 --> 00:27:34,240 Speaker 1: the idea that the same stories playing out on the 409 00:27:34,280 --> 00:27:36,880 Speaker 1: literal other side of the world in communities we don't 410 00:27:36,880 --> 00:27:40,880 Speaker 1: identify with because we don't take time to know about them. 411 00:27:41,040 --> 00:27:45,879 Speaker 1: It's really upsetting, um and not that surprising. When I 412 00:27:45,920 --> 00:27:49,359 Speaker 1: pause to think about it, I will say. I also 413 00:27:49,520 --> 00:27:57,240 Speaker 1: saw other small villages that were enacting totally ambitious projects. 414 00:27:58,320 --> 00:28:04,960 Speaker 1: For example, I visited this um rice farming village, Rice Harmony. 415 00:28:05,119 --> 00:28:09,520 Speaker 1: That's that sounds great, Rice Harmony, I like that. Yeah, yeah, 416 00:28:09,560 --> 00:28:14,000 Speaker 1: that's definitely. Their vibe is like, you know, very community oriented, 417 00:28:14,119 --> 00:28:18,160 Speaker 1: and they were really trying to push against top down 418 00:28:18,560 --> 00:28:24,680 Speaker 1: initiatives um and reliance on like whether it's one technology 419 00:28:24,840 --> 00:28:28,520 Speaker 1: or like one government policy. Yeah, so this other way 420 00:28:28,880 --> 00:28:33,359 Speaker 1: is um definitely a little bit more difficult. After the break, 421 00:28:34,000 --> 00:28:42,440 Speaker 1: we go to Rice Harmony Village. So shall we tell 422 00:28:42,480 --> 00:28:45,760 Speaker 1: me about the Rice Harmony Village project? And what about 423 00:28:45,800 --> 00:28:49,760 Speaker 1: it is so different. So rice farming is in this region, 424 00:28:49,840 --> 00:28:53,040 Speaker 1: it's terraced and so each farmer has their own little 425 00:28:53,080 --> 00:28:56,440 Speaker 1: patty and the water flows from the top to the bottom, 426 00:28:56,480 --> 00:29:00,080 Speaker 1: and it's this kind of natural irrigation. And so for 427 00:29:00,080 --> 00:29:04,360 Speaker 1: a long time they were using high scale, up, high 428 00:29:04,480 --> 00:29:09,160 Speaker 1: yield tactics like pesticides and fertilizers and really quote unquote 429 00:29:09,200 --> 00:29:14,200 Speaker 1: modern agriculture, and they were noticing that, you know, there 430 00:29:14,240 --> 00:29:16,920 Speaker 1: was a decline in their soil, decline in just like 431 00:29:17,280 --> 00:29:21,280 Speaker 1: their crops and like the nutrition content of the rice. 432 00:29:21,960 --> 00:29:27,320 Speaker 1: And so they started to do this lottery system where 433 00:29:27,760 --> 00:29:31,040 Speaker 1: you wouldn't have contiguous patty, so you might have one 434 00:29:31,040 --> 00:29:33,239 Speaker 1: patty at the top, you might have one patty at 435 00:29:33,240 --> 00:29:37,320 Speaker 1: the bottom, have a different neighbor every five years, and 436 00:29:37,440 --> 00:29:41,560 Speaker 1: so as a result of this, you are really materially 437 00:29:41,960 --> 00:29:46,520 Speaker 1: interconnected to others. Like you know, if you spray pesticides 438 00:29:46,680 --> 00:29:49,200 Speaker 1: or dam off water, you're going to affect your neighbors, 439 00:29:49,240 --> 00:29:52,080 Speaker 1: but you also might be affecting like yourself. And it's 440 00:29:52,160 --> 00:29:56,680 Speaker 1: through this system that they decided to do organic regenerative farming, 441 00:29:57,280 --> 00:30:01,120 Speaker 1: which does not really quote unquotes gale up right. It's 442 00:30:01,160 --> 00:30:06,000 Speaker 1: all about like thinking about scale across time and different 443 00:30:06,000 --> 00:30:10,360 Speaker 1: generations and like the soil, you know, twenty years from now, 444 00:30:10,720 --> 00:30:12,360 Speaker 1: rather than like how are we going to make as 445 00:30:12,440 --> 00:30:16,080 Speaker 1: much rice as possible this next year? Yeah, why were 446 00:30:16,120 --> 00:30:19,480 Speaker 1: they using the pesticides in the first place? It was 447 00:30:19,520 --> 00:30:23,880 Speaker 1: really about yield, right, Like it's just this form of 448 00:30:24,240 --> 00:30:28,520 Speaker 1: UM having granular control over your yield. If you're like, 449 00:30:28,760 --> 00:30:32,600 Speaker 1: I see what you did there, granular control. Glad you 450 00:30:32,640 --> 00:30:39,120 Speaker 1: appreciated that the lottery system sounds like a super creative 451 00:30:39,200 --> 00:30:46,280 Speaker 1: way to engineer UM community and interconnectedness, Because if I'm 452 00:30:46,320 --> 00:30:48,360 Speaker 1: just looking out for myself. I don't only care about 453 00:30:48,360 --> 00:30:51,880 Speaker 1: the runoff, but if my lots are no longer contiguous, 454 00:30:52,600 --> 00:30:55,680 Speaker 1: then my interest is in the runoff two. And so 455 00:30:55,720 --> 00:30:58,760 Speaker 1: I'm forced to care about my neighbor. I'm basically I 456 00:30:58,800 --> 00:31:03,000 Speaker 1: am my name her. That's kind of mind blowing. How 457 00:31:03,040 --> 00:31:05,640 Speaker 1: did they come up with that system? It was a 458 00:31:05,760 --> 00:31:09,000 Speaker 1: really beautiful system. And when they were telling me about it, 459 00:31:09,160 --> 00:31:11,320 Speaker 1: I didn't expect it to go there, but they were 460 00:31:11,360 --> 00:31:14,680 Speaker 1: saying that for a long time. It really came out 461 00:31:14,720 --> 00:31:19,080 Speaker 1: of their practices of helping each other harvest every year. 462 00:31:19,480 --> 00:31:22,680 Speaker 1: It was always like, oh, my family is harvesting the 463 00:31:22,760 --> 00:31:25,520 Speaker 1: rice in my patty, but also like the neighbors are 464 00:31:25,560 --> 00:31:29,040 Speaker 1: helping to and we're just all sharing everything. We're sharing 465 00:31:29,200 --> 00:31:33,560 Speaker 1: you know, equipment, we're sharing labor. We're like helping each 466 00:31:33,560 --> 00:31:37,440 Speaker 1: other out. And so the patty lottery system really stemmed 467 00:31:37,440 --> 00:31:41,680 Speaker 1: out of that um this kind of longer, longer community practice. 468 00:31:42,240 --> 00:31:44,080 Speaker 1: And you know, they made it very clear to me 469 00:31:44,160 --> 00:31:46,640 Speaker 1: that it was not easy. They'd like showed me photos 470 00:31:46,640 --> 00:31:49,000 Speaker 1: and they'd be like, yeah, that guy he always like, 471 00:31:49,320 --> 00:31:52,400 Speaker 1: you know, we have meetings to talk about this system 472 00:31:52,440 --> 00:31:55,360 Speaker 1: and the lottery and who's doing what and that guy's 473 00:31:55,440 --> 00:32:00,640 Speaker 1: always like stirring up trouble, and that lady she's never satisfide. 474 00:32:00,840 --> 00:32:04,360 Speaker 1: And our community meetings they take like hours and no 475 00:32:04,360 --> 00:32:06,320 Speaker 1: one likes going to them, but we all show up. 476 00:32:06,920 --> 00:32:11,080 Speaker 1: You know, it's scale interpreted differently, small scale on purpose. 477 00:32:11,600 --> 00:32:13,920 Speaker 1: A lot of us are just accepted what's delivered to 478 00:32:14,000 --> 00:32:17,960 Speaker 1: us by the massive commercial interests. But in your Rice 479 00:32:18,360 --> 00:32:22,160 Speaker 1: Harmony village example, they developed their own tools at their 480 00:32:22,200 --> 00:32:27,640 Speaker 1: own lower tech which suited their needs. Honestly, we need 481 00:32:27,680 --> 00:32:31,640 Speaker 1: to question the tools that we are given and really 482 00:32:31,760 --> 00:32:37,280 Speaker 1: push our imaginations. We've used like the most incredible tech 483 00:32:37,520 --> 00:32:41,040 Speaker 1: to now sell ads, and I think just like thinking 484 00:32:41,080 --> 00:32:44,000 Speaker 1: about what we're doing with these tools, like through the 485 00:32:44,040 --> 00:32:47,000 Speaker 1: span of time and not just the immediate one year 486 00:32:47,160 --> 00:32:51,240 Speaker 1: five year return. That's that's really key. How did your 487 00:32:51,280 --> 00:32:55,400 Speaker 1: experiences in rural China shape your views of tech and 488 00:32:55,440 --> 00:32:59,440 Speaker 1: of tech work and tech organizing. You seem to believe 489 00:32:59,520 --> 00:33:01,320 Speaker 1: something a little differently on the other side of that 490 00:33:01,400 --> 00:33:07,800 Speaker 1: experience than you did before. In seeing places like Rice Harmony, 491 00:33:07,960 --> 00:33:12,520 Speaker 1: where the conversations are difficult, they take hours, there's a 492 00:33:12,640 --> 00:33:16,600 Speaker 1: kind of patience the villagers would be telling me like, 493 00:33:16,640 --> 00:33:19,440 Speaker 1: oh yeah, sometimes we get into fights and like, you know, 494 00:33:19,480 --> 00:33:21,280 Speaker 1: we let it simmer and we pick it up the 495 00:33:21,360 --> 00:33:24,520 Speaker 1: next day. I think it really countered my you know 496 00:33:24,800 --> 00:33:28,360 Speaker 1: approach to organizing as well, where it's like, you know, 497 00:33:28,480 --> 00:33:31,960 Speaker 1: let things be unresolved, you know, don't push the conversation, 498 00:33:32,440 --> 00:33:36,240 Speaker 1: take time, take patience, move at the speed of trust 499 00:33:36,400 --> 00:33:40,640 Speaker 1: and care rather than I need to like get these 500 00:33:40,680 --> 00:33:45,120 Speaker 1: ten sign ups for the union, right, and that also 501 00:33:46,240 --> 00:33:48,920 Speaker 1: you know, seeing right places like rice harmony. It's like 502 00:33:49,080 --> 00:33:52,920 Speaker 1: the act of talking to people and just being with them. 503 00:33:53,000 --> 00:33:57,240 Speaker 1: That's the work, right, that's the transformation. Like whatever happens, 504 00:33:57,320 --> 00:34:00,880 Speaker 1: whether you win or lose the campaign, it's really about 505 00:34:01,000 --> 00:34:04,720 Speaker 1: just creating that kind of relation that is that is powerful. 506 00:34:05,840 --> 00:34:09,040 Speaker 1: Mm hmm yeah, instead of move fast and break things, 507 00:34:09,239 --> 00:34:14,160 Speaker 1: you know, move slower and build things. It's like trust 508 00:34:14,160 --> 00:34:22,239 Speaker 1: like relationships the stem brain of science, tech, engineering math. 509 00:34:23,040 --> 00:34:25,440 Speaker 1: I think there's a little bit of a stereotype to it, 510 00:34:25,480 --> 00:34:27,319 Speaker 1: in the same way that we have some stereotypes about 511 00:34:27,360 --> 00:34:30,680 Speaker 1: rural China. But there is a pressure out of so 512 00:34:30,719 --> 00:34:34,160 Speaker 1: many of these products that most of us use for efficiency. 513 00:34:34,840 --> 00:34:38,840 Speaker 1: It's like how do I avoid discomfort? We pay for 514 00:34:38,920 --> 00:34:40,680 Speaker 1: it in some way or the other. It may feel 515 00:34:40,719 --> 00:34:43,160 Speaker 1: faster and more efficient, but there's a cost on the 516 00:34:43,200 --> 00:34:47,319 Speaker 1: back end. Like you said, move at the speed of trust. Uh, 517 00:34:47,320 --> 00:34:50,360 Speaker 1: there's something else to be gained by that. That's so powerful. 518 00:34:50,520 --> 00:34:53,960 Speaker 1: Thank you. I love your framing of it as this 519 00:34:54,120 --> 00:34:58,760 Speaker 1: avoidance of discomfort. It speaks to really power to write 520 00:34:58,800 --> 00:35:02,080 Speaker 1: like who gets to decide? Well, this is the new 521 00:35:02,120 --> 00:35:07,440 Speaker 1: experience that everyone in the world should have. So how 522 00:35:07,560 --> 00:35:10,000 Speaker 1: does your work at the largest school address some of 523 00:35:10,000 --> 00:35:14,680 Speaker 1: the types of exploitation you were seeing firsthand in rural China. Yeah, 524 00:35:14,920 --> 00:35:19,280 Speaker 1: so in in a few ways. I feel like there's 525 00:35:19,360 --> 00:35:21,879 Speaker 1: one threat of Logic School, which is about what are 526 00:35:21,880 --> 00:35:25,760 Speaker 1: the ways that we can change industry from the inside. So, 527 00:35:25,960 --> 00:35:29,680 Speaker 1: you know, there are folks um at Amazon, like Amazonians 528 00:35:29,760 --> 00:35:33,520 Speaker 1: for Climate Justice, UM, people who are organizing and trying 529 00:35:33,560 --> 00:35:37,160 Speaker 1: to really think about these things, right, and it's like, no, 530 00:35:37,280 --> 00:35:42,439 Speaker 1: we're gonna build tech that is different. UM. So it's 531 00:35:42,440 --> 00:35:45,160 Speaker 1: more of the like you know, Rice Harmony stance where 532 00:35:45,160 --> 00:35:48,000 Speaker 1: it's like, well, you know, forget about everything else, We're 533 00:35:48,000 --> 00:35:50,959 Speaker 1: just going to go our own way. And I think 534 00:35:51,000 --> 00:35:56,319 Speaker 1: both approaches are urgent and much needed right now. Right 535 00:35:56,880 --> 00:36:01,000 Speaker 1: UM and Logic School it's really about like cultivate dating, nurturing, 536 00:36:01,560 --> 00:36:05,440 Speaker 1: and like thinking through these different threads and also supporting 537 00:36:05,480 --> 00:36:07,959 Speaker 1: folks who are doing this on the ground right now. 538 00:36:08,760 --> 00:36:13,120 Speaker 1: I'm really glad that your answer to like should we 539 00:36:13,160 --> 00:36:18,160 Speaker 1: reform from within or build something new out is both? 540 00:36:19,120 --> 00:36:23,240 Speaker 1: So so let's push your imagination. You've done your first 541 00:36:23,280 --> 00:36:27,160 Speaker 1: cohort with Logic School, when you've had your inaugural class, 542 00:36:27,640 --> 00:36:30,680 Speaker 1: what comes next? What's your vision for where this this 543 00:36:30,800 --> 00:36:34,080 Speaker 1: school goes, and this experience goes. And I feel like 544 00:36:34,239 --> 00:36:38,240 Speaker 1: out of the first cohort of Logic School, seeing people 545 00:36:38,480 --> 00:36:42,480 Speaker 1: organize do these incredible projects, It's like, how can we 546 00:36:43,560 --> 00:36:47,640 Speaker 1: continue to support the first cohort but also future cohorts 547 00:36:47,680 --> 00:36:50,920 Speaker 1: on like doing these projects that they do want to 548 00:36:50,960 --> 00:36:53,160 Speaker 1: carry out in the world right so that they're not 549 00:36:53,280 --> 00:36:56,040 Speaker 1: like can I quit my tech job and pursue what 550 00:36:56,120 --> 00:37:00,040 Speaker 1: I'm actually passionate about and is meaningful and impactful. I 551 00:37:00,040 --> 00:37:03,280 Speaker 1: think there needs to be a huge amount of culture shift, 552 00:37:03,360 --> 00:37:06,080 Speaker 1: and I think that is happening. Whenever I talked to 553 00:37:06,680 --> 00:37:11,320 Speaker 1: new grads from you know, computer science programs, I'm like, wow, 554 00:37:11,920 --> 00:37:15,920 Speaker 1: you are like so aware, you are so thoughtful, You 555 00:37:16,080 --> 00:37:20,040 Speaker 1: like know more about radical history than like some professors 556 00:37:20,080 --> 00:37:24,400 Speaker 1: I've spoken to like, yes, I love that. UM. So 557 00:37:24,480 --> 00:37:27,680 Speaker 1: I guess in that sense, I feel optimistic about the 558 00:37:27,719 --> 00:37:31,640 Speaker 1: culture shifts that are coming and then regulation of what 559 00:37:31,640 --> 00:37:34,240 Speaker 1: what we currently are facing in the US at least 560 00:37:35,640 --> 00:37:38,600 Speaker 1: is there a place in those two or maybe something 561 00:37:38,640 --> 00:37:42,719 Speaker 1: you haven't identified the regulation the culture shift? What is 562 00:37:42,800 --> 00:37:48,680 Speaker 1: Logic schools role in getting us there? I feel like 563 00:37:48,800 --> 00:37:53,840 Speaker 1: it's definitely in the culture shift area. But I also 564 00:37:53,960 --> 00:38:00,320 Speaker 1: think creating these open, expansive spaces for folks to dream about, 565 00:38:00,600 --> 00:38:05,400 Speaker 1: you know, a better tech industry or better tech UM 566 00:38:05,440 --> 00:38:08,600 Speaker 1: that is to me really urgent because we don't have 567 00:38:08,640 --> 00:38:12,680 Speaker 1: a lot of spaces to do that. Right. Even if 568 00:38:12,719 --> 00:38:16,480 Speaker 1: you do, like a startup incubator, we're like, we're gonna 569 00:38:16,480 --> 00:38:19,319 Speaker 1: build better tech. It's like, what's the bottom line? What's 570 00:38:19,360 --> 00:38:23,960 Speaker 1: your pitch deck? UM? And Logic School is really about 571 00:38:24,040 --> 00:38:28,279 Speaker 1: creating that expansive space and to dream to rest. We 572 00:38:28,360 --> 00:38:32,000 Speaker 1: really care about rest at Logic School. UM to have 573 00:38:32,239 --> 00:38:40,319 Speaker 1: that fire going for reflection, fire for reflection. It's the 574 00:38:40,560 --> 00:38:45,200 Speaker 1: anti hustle propaganda and in a great spirit of a 575 00:38:45,200 --> 00:38:47,959 Speaker 1: new type of energy that I would also love to see. 576 00:38:49,640 --> 00:38:52,440 Speaker 1: We call the show how to citizen. Citizen is a 577 00:38:52,520 --> 00:38:55,480 Speaker 1: verb to us not a legal status to be weaponized 578 00:38:55,480 --> 00:39:00,440 Speaker 1: against certain communities. And when you interpret this word as 579 00:39:00,440 --> 00:39:04,640 Speaker 1: a verb, what does it mean to you, two citizen? 580 00:39:06,880 --> 00:39:10,160 Speaker 1: It's about showing up. It's about really showing up. I 581 00:39:10,160 --> 00:39:14,880 Speaker 1: think it also requires a degree of listening, um, you know, 582 00:39:15,000 --> 00:39:18,359 Speaker 1: and compassion, right, And so I think of this like 583 00:39:18,840 --> 00:39:22,080 Speaker 1: listen to understand the ways that you're sharing space, the 584 00:39:22,120 --> 00:39:26,360 Speaker 1: ways that your decisions affect and inform and change conditions 585 00:39:26,400 --> 00:39:30,040 Speaker 1: for others. So I think we use the word show 586 00:39:30,160 --> 00:39:34,480 Speaker 1: up like really casually, but to do it and to really, like, 587 00:39:34,880 --> 00:39:39,319 Speaker 1: you know, citizens, that's difficult, right. I want you to 588 00:39:39,400 --> 00:39:42,880 Speaker 1: picture a motivated, fired up person ready to show up, 589 00:39:43,160 --> 00:39:47,000 Speaker 1: and they're like, oh, blockchain, chickens, rice, living in harmony, 590 00:39:47,200 --> 00:39:51,040 Speaker 1: tech workers with empathy, put me in coach, What can 591 00:39:51,080 --> 00:39:56,000 Speaker 1: I do? You know? There's this great phrase from Buddhism, 592 00:39:56,200 --> 00:39:59,560 Speaker 1: clean the temple, so that you can actually sit get 593 00:39:59,560 --> 00:40:03,040 Speaker 1: yourself health and your home and your family and where 594 00:40:03,040 --> 00:40:06,200 Speaker 1: you're coming from right before you're like, I'm going to 595 00:40:06,280 --> 00:40:08,879 Speaker 1: go to the temple and like talk to other people now. 596 00:40:09,320 --> 00:40:12,160 Speaker 1: So I feel like that's been my work for a 597 00:40:12,200 --> 00:40:14,879 Speaker 1: few years. It's just like cleaning the temple and then 598 00:40:15,000 --> 00:40:18,319 Speaker 1: from there. You know, if there's an organization that you 599 00:40:18,360 --> 00:40:21,520 Speaker 1: want to be organizing with, email them, show up and 600 00:40:21,600 --> 00:40:25,200 Speaker 1: listen and be patient and be willing to have the 601 00:40:25,520 --> 00:40:32,960 Speaker 1: you know, difficult conversations. Very lastly, like have empathy. I've 602 00:40:33,000 --> 00:40:37,040 Speaker 1: noticed that sometimes even in communities where we're like trying 603 00:40:37,040 --> 00:40:39,799 Speaker 1: to organize or do different initiatives and we feel like 604 00:40:39,840 --> 00:40:42,719 Speaker 1: we're bettering the world in some way, it can be 605 00:40:42,800 --> 00:40:44,799 Speaker 1: really easy to be like we just want to win, 606 00:40:46,520 --> 00:40:51,200 Speaker 1: Like we can't trample over people's feelings, having a live joy, 607 00:40:51,880 --> 00:40:55,399 Speaker 1: you know, take care of each other movement, like I think, 608 00:40:55,440 --> 00:40:59,239 Speaker 1: at the heart of it, that's the work. I'm so 609 00:40:59,360 --> 00:41:02,320 Speaker 1: happy to hear that the industry and a capital T 610 00:41:02,640 --> 00:41:05,640 Speaker 1: capital I the tech industry has done a really good 611 00:41:05,719 --> 00:41:08,759 Speaker 1: job of selling a narrative of what tech is and 612 00:41:08,800 --> 00:41:12,320 Speaker 1: who a tech worker is and what he most likely 613 00:41:12,360 --> 00:41:16,680 Speaker 1: looks like, and then the media amplifies that. So the 614 00:41:16,760 --> 00:41:21,279 Speaker 1: public mind around what tech even is, it's very narrowly oriented. 615 00:41:21,760 --> 00:41:25,080 Speaker 1: And so if we can contribute to shifting that mindset, 616 00:41:25,560 --> 00:41:29,280 Speaker 1: expanding that imagination, will be better off. And we're certainly 617 00:41:29,320 --> 00:41:32,120 Speaker 1: better off for having spoken with you. So thank you 618 00:41:32,719 --> 00:41:39,600 Speaker 1: so much, Shaowei Wang tarot reader, philosopher, professor, activist, organizer, 619 00:41:40,239 --> 00:41:45,280 Speaker 1: blockchain chicken farmer, advocate keeping it real. Appreciate you, Thank 620 00:41:45,320 --> 00:41:47,799 Speaker 1: you very tin day. I appreciate you. Thank you for 621 00:41:47,840 --> 00:42:00,000 Speaker 1: having me by. Now we're all well aware that technolog 622 00:42:00,040 --> 00:42:03,960 Speaker 1: lergy can and often is used to take advantage of people, 623 00:42:04,680 --> 00:42:10,520 Speaker 1: but it can also help us to connect, to empathize 624 00:42:10,560 --> 00:42:13,840 Speaker 1: with one another, to strengthen the bonds of trust and 625 00:42:13,880 --> 00:42:18,279 Speaker 1: transparency that we so deeply crave in our communities, and 626 00:42:18,320 --> 00:42:24,280 Speaker 1: to accomplish that bigger ain't always better. I would argue, 627 00:42:24,440 --> 00:42:28,919 Speaker 1: in fact, that it's it's rarely better. Shawegh is redefining 628 00:42:28,960 --> 00:42:31,880 Speaker 1: what it means to be a tech worker, that the 629 00:42:31,920 --> 00:42:34,960 Speaker 1: world at tech doesn't have to be all hoodies and 630 00:42:35,120 --> 00:42:39,280 Speaker 1: energy drinks, that it can be, like a tarot reading, 631 00:42:40,320 --> 00:42:43,360 Speaker 1: a place that opens up a space to listen to 632 00:42:43,520 --> 00:42:48,440 Speaker 1: others and to hold up a mirror to ourselves, because 633 00:42:48,520 --> 00:42:52,080 Speaker 1: the truth is, the world is just one big rice 634 00:42:52,120 --> 00:42:56,200 Speaker 1: harmony village, and what we do in our communities trickles 635 00:42:56,239 --> 00:42:59,759 Speaker 1: down to impact others. Whether those impacts are good or bad, 636 00:43:00,560 --> 00:43:03,279 Speaker 1: that's up to us and the way we choose to 637 00:43:03,400 --> 00:43:11,600 Speaker 1: use tech. It can isolate or it can unite. When 638 00:43:11,640 --> 00:43:15,120 Speaker 1: the ever evolving world of technology tells us to move 639 00:43:15,239 --> 00:43:18,080 Speaker 1: fast and break things, we've got to be the ones 640 00:43:18,200 --> 00:43:22,440 Speaker 1: to slow down and listen, to show up, to step 641 00:43:22,480 --> 00:43:40,200 Speaker 1: back and open the circle. Next time, for our final episode, 642 00:43:40,600 --> 00:43:43,759 Speaker 1: we're asking an important question, how do we bridge the 643 00:43:43,800 --> 00:43:47,760 Speaker 1: digital divide so that everyone can citizen. I'll be honest 644 00:43:47,800 --> 00:43:51,040 Speaker 1: with you, I was so overwhelmed because I did not 645 00:43:51,280 --> 00:43:55,319 Speaker 1: have that level of connection to technology, and just the 646 00:43:55,400 --> 00:43:58,560 Speaker 1: phone ringing and trying to text and people calling and 647 00:43:58,600 --> 00:44:02,839 Speaker 1: pictures popping up, and I felt some anxiety and I 648 00:44:02,880 --> 00:44:08,160 Speaker 1: didn't expect that. And now it is time for some actions. 649 00:44:08,560 --> 00:44:12,560 Speaker 1: No tarot reading required. A lot of which you're about 650 00:44:12,600 --> 00:44:16,520 Speaker 1: to hear comes directly from shall weigh so extra appreciation 651 00:44:16,560 --> 00:44:20,080 Speaker 1: to them for giving me things to give you to do. 652 00:44:21,280 --> 00:44:25,720 Speaker 1: The first is an internal reflection. Think of what consent 653 00:44:25,920 --> 00:44:30,160 Speaker 1: and care means to you, and think of what consent 654 00:44:30,280 --> 00:44:34,000 Speaker 1: ful and careful tech would look like, would function like, 655 00:44:34,080 --> 00:44:38,520 Speaker 1: would feel like, What relationships would be strengthened by that 656 00:44:38,600 --> 00:44:43,080 Speaker 1: kind of tech? What might be shadowed? Next, let's get 657 00:44:43,120 --> 00:44:46,840 Speaker 1: informed about tech critiques and some better ways of doing 658 00:44:46,880 --> 00:44:51,520 Speaker 1: things with tech. Read about platform co ops. We have 659 00:44:51,920 --> 00:44:54,520 Speaker 1: a link to a great explainer in the show notes. 660 00:44:55,160 --> 00:44:59,760 Speaker 1: These are digital platforms think of like a ride share 661 00:45:00,280 --> 00:45:04,200 Speaker 1: or delivery service, but they're collectively owned and governed by 662 00:45:04,239 --> 00:45:07,239 Speaker 1: the people who depend on and participate in them, not 663 00:45:07,440 --> 00:45:10,640 Speaker 1: just a handful of investors looking to turn their one 664 00:45:10,680 --> 00:45:14,560 Speaker 1: million into ten million. Also follow the work of the 665 00:45:14,640 --> 00:45:17,759 Speaker 1: Gig Workers Collective. This is a group that shines a 666 00:45:17,880 --> 00:45:20,520 Speaker 1: light on and advocates for people who work at the 667 00:45:20,560 --> 00:45:24,160 Speaker 1: other end of our smartphone taps and swipes. It really 668 00:45:24,239 --> 00:45:28,759 Speaker 1: humanizes their experience. And most of us don't work in 669 00:45:29,040 --> 00:45:31,399 Speaker 1: that part of the economy, but we all engage with it. 670 00:45:31,680 --> 00:45:35,160 Speaker 1: So let's have more information about the impact of that engagement. 671 00:45:36,440 --> 00:45:38,880 Speaker 1: Speaking of engagement, here's some ways to step it up 672 00:45:38,920 --> 00:45:45,239 Speaker 1: a notch and publicly participate. Support community Internet and technology groups. 673 00:45:45,280 --> 00:45:50,640 Speaker 1: These are organizations like the Detroit Community Technology Project, NYC 674 00:45:50,920 --> 00:45:56,680 Speaker 1: MESH Oakland MESH. They provide local internet access, tech training 675 00:45:56,760 --> 00:46:01,319 Speaker 1: and tools by of and for the people. It's democratic 676 00:46:01,400 --> 00:46:05,080 Speaker 1: technology and check out this one uh The Tech Worker 677 00:46:05,200 --> 00:46:09,520 Speaker 1: Handbook by Ifoma a Zoma. This is a collection of 678 00:46:09,600 --> 00:46:13,279 Speaker 1: resources to better prepare and support tech workers who are 679 00:46:13,280 --> 00:46:16,920 Speaker 1: considering whether they should speak out on issues that are 680 00:46:16,920 --> 00:46:19,480 Speaker 1: in the public interest, like should they whistle blow? You 681 00:46:19,480 --> 00:46:22,680 Speaker 1: know what I'm saying, So recommend this to a tech 682 00:46:22,719 --> 00:46:26,720 Speaker 1: worker near you, but please do them and our general 683 00:46:26,760 --> 00:46:30,040 Speaker 1: freedom of favor, don't send it to their work email. Right, 684 00:46:30,120 --> 00:46:32,359 Speaker 1: Let's be smart about that now. Look, We've got links 685 00:46:32,360 --> 00:46:34,280 Speaker 1: to all of this and more at how do Citizen 686 00:46:34,320 --> 00:46:37,640 Speaker 1: dot com and in the episode show notes as usual. 687 00:46:38,120 --> 00:46:41,720 Speaker 1: Check us out on Instagram at how the Citizen tag 688 00:46:41,800 --> 00:46:45,600 Speaker 1: us in your posts about this episode? How did Shaowei 689 00:46:45,760 --> 00:46:49,160 Speaker 1: make you feel? Do you want them to do your tarot? 690 00:46:49,920 --> 00:46:52,520 Speaker 1: Hashtag how the Citizen? And let us know how this 691 00:46:52,560 --> 00:46:58,120 Speaker 1: one hates you? Stay tuned and keep citizen. How Do Citizen? 692 00:46:58,160 --> 00:47:00,560 Speaker 1: With barituone Day is a production of I Heart Radio 693 00:47:00,640 --> 00:47:04,440 Speaker 1: Podcasts and dust Light Productions. Our executive producers are Me 694 00:47:04,800 --> 00:47:08,920 Speaker 1: Barrett tune Day, Thurston, Elizabeth Stewart, and Misha Yusa. Our 695 00:47:08,960 --> 00:47:12,920 Speaker 1: senior producer is Tamika Adams, our producer is Ali Kilts, 696 00:47:13,320 --> 00:47:17,000 Speaker 1: and our assistant producer is Sam Paulson. Stephanie Cohen is 697 00:47:17,000 --> 00:47:20,920 Speaker 1: our editor, Valentino Rivera is our senior engineer, and Matthew 698 00:47:20,960 --> 00:47:25,000 Speaker 1: Laie is our apprentice. Original music by Andrew Eapen, with 699 00:47:25,040 --> 00:47:29,120 Speaker 1: additional original music for season two from Andrew Clausen, additional 700 00:47:29,160 --> 00:47:32,600 Speaker 1: production help from Arwin Nicks. This episode was produced and 701 00:47:32,640 --> 00:47:36,360 Speaker 1: sound designed by Matthew Laie. Special thanks to Joel Smith 702 00:47:36,400 --> 00:47:39,759 Speaker 1: from I Heart Radio and Rachel Garcia at dust Light Productions.