1 00:00:14,560 --> 00:00:15,600 Speaker 1: Welcome to tech stuff. 2 00:00:15,800 --> 00:00:19,080 Speaker 2: I'm Cara Price, and today I have two very special 3 00:00:19,079 --> 00:00:23,439 Speaker 2: interviews from an unexpected place, the theater world, for those 4 00:00:23,440 --> 00:00:25,160 Speaker 2: of you who don't know. In addition to being a 5 00:00:25,200 --> 00:00:28,760 Speaker 2: tech enthusiast, I'm also a very passionate theater goer. And 6 00:00:28,800 --> 00:00:31,280 Speaker 2: this season I noticed quite a few shows opening on 7 00:00:31,360 --> 00:00:34,280 Speaker 2: and off Broadway that grapple with the moral quandaries of 8 00:00:34,320 --> 00:00:35,760 Speaker 2: our tech fueled world. 9 00:00:35,880 --> 00:00:38,559 Speaker 1: So I went and saw two of them, Data and 10 00:00:38,640 --> 00:00:39,400 Speaker 1: Marjorie Prime. 11 00:00:40,000 --> 00:00:42,680 Speaker 2: Data focuses on some of the darker sides of Silicon 12 00:00:42,800 --> 00:00:46,159 Speaker 2: Valley behemoths, while Marjorie Prime considers what it would be 13 00:00:46,320 --> 00:00:49,280 Speaker 2: like to use grief tech to preserve a loved one's memory. 14 00:00:49,760 --> 00:00:51,920 Speaker 2: I sat down with both playwrights and I wanted to 15 00:00:51,920 --> 00:00:55,360 Speaker 2: share those conversations with you today. Just a warning, both 16 00:00:55,400 --> 00:00:58,560 Speaker 2: conversations have some spoilers, but don't worry, we'll tell you 17 00:00:58,600 --> 00:01:02,360 Speaker 2: when that happens. Let's start with Matthew Libby. He wrote Data, 18 00:01:02,680 --> 00:01:05,399 Speaker 2: which is currently running off Broadway through March twenty ninth. 19 00:01:05,880 --> 00:01:08,039 Speaker 2: Matthew wrote the play eight years ago, but it is 20 00:01:08,160 --> 00:01:10,560 Speaker 2: all too relevant today. You'll see what I mean. 21 00:01:11,040 --> 00:01:15,880 Speaker 1: Take a listen. Welcome Matthew Hi. 22 00:01:16,200 --> 00:01:18,920 Speaker 2: So, without giving away any spoilers, can you just give 23 00:01:19,000 --> 00:01:21,120 Speaker 2: us an overview of the play for those who haven't 24 00:01:21,120 --> 00:01:21,520 Speaker 2: seen it. 25 00:01:22,080 --> 00:01:22,440 Speaker 3: Yeah. 26 00:01:22,480 --> 00:01:26,000 Speaker 4: So Data is set in a Silicon Valley tech company, 27 00:01:26,080 --> 00:01:29,399 Speaker 4: a data mining company called Athena Technologies. 28 00:01:29,240 --> 00:01:32,200 Speaker 3: And it follows a young entry level. 29 00:01:32,000 --> 00:01:35,760 Speaker 4: Employee named Maniche who works on the user experience team 30 00:01:35,800 --> 00:01:38,000 Speaker 4: at this company. He's an entry level employee just out 31 00:01:38,040 --> 00:01:40,240 Speaker 4: of college, and at the beginning of the play, he 32 00:01:40,280 --> 00:01:44,160 Speaker 4: gets an offer to transfer to the more central, more 33 00:01:44,200 --> 00:01:48,160 Speaker 4: shadowy data analytics team and learns the true nature of 34 00:01:48,200 --> 00:01:51,480 Speaker 4: the company's work. And the rest of the play is 35 00:01:52,720 --> 00:01:55,840 Speaker 4: a moral thriller about what Maniche does with this information, 36 00:01:55,880 --> 00:01:58,360 Speaker 4: about what the super secret project at the core of 37 00:01:58,400 --> 00:01:59,040 Speaker 4: the company is. 38 00:01:59,280 --> 00:01:59,880 Speaker 1: So why was this? 39 00:02:00,000 --> 00:02:02,160 Speaker 2: It's an interesting story for you to tell as someone 40 00:02:02,200 --> 00:02:03,400 Speaker 2: who who's. 41 00:02:03,200 --> 00:02:05,920 Speaker 1: A writer and not in technology. 42 00:02:07,040 --> 00:02:07,440 Speaker 3: Yeah. 43 00:02:07,560 --> 00:02:10,359 Speaker 4: I write a lot about about tech, you know. I 44 00:02:10,680 --> 00:02:13,040 Speaker 4: did my undergrad at Stanford, so I came of age 45 00:02:13,040 --> 00:02:14,960 Speaker 4: in Silicon Valley, and I think a lot of what 46 00:02:15,000 --> 00:02:16,760 Speaker 4: the play is about is about the experience of coming 47 00:02:16,760 --> 00:02:19,600 Speaker 4: of age in Silicon Valley. And I think to young people, 48 00:02:20,520 --> 00:02:25,359 Speaker 4: especially people young people in the Bay Area, the tech 49 00:02:25,360 --> 00:02:27,680 Speaker 4: industry does a really good job of not just presenting 50 00:02:27,720 --> 00:02:31,440 Speaker 4: itself like the best option for your future, but kind 51 00:02:31,440 --> 00:02:33,480 Speaker 4: of the only option. There's a way of thinking about 52 00:02:33,520 --> 00:02:35,120 Speaker 4: it that's like peer pressure, but I think it's more 53 00:02:35,120 --> 00:02:37,320 Speaker 4: complicated than that, you know, It's it's one of these 54 00:02:37,320 --> 00:02:40,040 Speaker 4: things where it's like when you're a freshman, there's a 55 00:02:40,120 --> 00:02:41,880 Speaker 4: there's a class at Stanford called CS one or six A, 56 00:02:42,000 --> 00:02:43,519 Speaker 4: which is introductory Computer Science. 57 00:02:43,760 --> 00:02:46,960 Speaker 3: You code Java, you like code Brickbreaker and other. 58 00:02:46,919 --> 00:02:49,080 Speaker 4: Games, and it's just one of these things that like 59 00:02:49,160 --> 00:02:52,680 Speaker 4: everyone does. Computer science is just part of the kind 60 00:02:52,680 --> 00:02:55,600 Speaker 4: of like social fabric of life as a student there. 61 00:02:55,880 --> 00:02:58,680 Speaker 4: And so anyway, that's all to say that I always 62 00:02:58,760 --> 00:03:00,760 Speaker 4: knew I wanted to do this be an artist right 63 00:03:00,800 --> 00:03:04,680 Speaker 4: for film and TV and theater and create art, but 64 00:03:04,919 --> 00:03:06,920 Speaker 4: I kind of ended up on this detour while I 65 00:03:06,960 --> 00:03:09,560 Speaker 4: was at Stanford, and I ended up in this cognitive 66 00:03:09,600 --> 00:03:12,160 Speaker 4: science major, and that was not It also meant that 67 00:03:12,200 --> 00:03:14,040 Speaker 4: at a certain point towards the end of my time 68 00:03:14,080 --> 00:03:17,120 Speaker 4: in college, all of my friends were starting to like 69 00:03:18,120 --> 00:03:21,280 Speaker 4: get these internships, which we're going to segue into another internship, 70 00:03:21,280 --> 00:03:23,760 Speaker 4: which we're going to segue into a job. And by 71 00:03:23,800 --> 00:03:26,360 Speaker 4: the time I got to my late junior year, early 72 00:03:26,440 --> 00:03:30,800 Speaker 4: senior year, I started to feel very directionless because I, 73 00:03:30,840 --> 00:03:33,440 Speaker 4: you know, wanted to go to Hollywood and moved to 74 00:03:33,480 --> 00:03:36,480 Speaker 4: New York and like be a writer, and that didn't 75 00:03:36,520 --> 00:03:38,520 Speaker 4: have the same sort of like X to Y to 76 00:03:38,680 --> 00:03:42,360 Speaker 4: Z path. And so I had a bit of a crisis, 77 00:03:42,440 --> 00:03:46,400 Speaker 4: and I started asking friends to get me interviews places. 78 00:03:46,760 --> 00:03:49,120 Speaker 4: And one of the places I ended up applying to 79 00:03:49,160 --> 00:03:52,040 Speaker 4: and ended up getting a final round interview was Palenteer 80 00:03:52,360 --> 00:03:55,000 Speaker 4: And this would have been the fall I think it 81 00:03:55,040 --> 00:03:58,520 Speaker 4: would have been late twenty fifteen for an internship. In 82 00:03:58,600 --> 00:04:01,480 Speaker 4: the summer of twenty sixteen, I was in for a 83 00:04:01,520 --> 00:04:05,240 Speaker 4: technical writer internship, which felt me to be perfect right. 84 00:04:05,280 --> 00:04:08,120 Speaker 4: It's like it's writing, but it's about tech, and a 85 00:04:08,120 --> 00:04:09,760 Speaker 4: lot of what I'm interested in is like how to 86 00:04:09,760 --> 00:04:13,640 Speaker 4: distill complex ideas about tech into you know, very human, 87 00:04:13,680 --> 00:04:17,000 Speaker 4: present tense language. So I went to Pollenteer and I 88 00:04:17,000 --> 00:04:19,560 Speaker 4: did an on site interview and then I left, and 89 00:04:19,640 --> 00:04:21,680 Speaker 4: I found out a couple weeks later I didn't get 90 00:04:21,680 --> 00:04:22,360 Speaker 4: the internship. 91 00:04:23,279 --> 00:04:24,960 Speaker 1: But were you happy that you didn't get it at 92 00:04:24,960 --> 00:04:25,240 Speaker 1: the end of. 93 00:04:25,240 --> 00:04:27,919 Speaker 4: The day, Well, you know, I had had this was 94 00:04:27,960 --> 00:04:30,920 Speaker 4: it was an interesting time. And again this is part 95 00:04:30,920 --> 00:04:32,599 Speaker 4: of what's in the play too. But like I kind 96 00:04:32,680 --> 00:04:36,440 Speaker 4: of knew what Palateer did. This was before the first 97 00:04:36,480 --> 00:04:39,560 Speaker 4: Trump administration, and so I knew that they had government contracts. 98 00:04:39,600 --> 00:04:42,839 Speaker 4: I knew that, but they didn't quite have the reputation 99 00:04:42,920 --> 00:04:45,560 Speaker 4: that they do now. And so I was already starting 100 00:04:45,600 --> 00:04:47,080 Speaker 4: to feel myself have to do a little bit of 101 00:04:47,120 --> 00:04:49,360 Speaker 4: cognitive dissonance of like, what would it have meant for 102 00:04:49,480 --> 00:04:51,800 Speaker 4: my value system to work at a company that that 103 00:04:51,800 --> 00:04:54,479 Speaker 4: would have challenged that value system in some ways? And 104 00:04:54,520 --> 00:04:56,560 Speaker 4: that a couple of years later, you know, after I 105 00:04:56,640 --> 00:05:00,760 Speaker 4: graduated from school and I was re the news and 106 00:05:00,839 --> 00:05:04,680 Speaker 4: reading how a Nesh Palenteer was with the first Trump administration. 107 00:05:05,360 --> 00:05:07,920 Speaker 4: A lot of what I was feeling at that time 108 00:05:08,040 --> 00:05:10,840 Speaker 4: was just this sort of like hypothetical of how would 109 00:05:10,839 --> 00:05:12,880 Speaker 4: I be different if I had gotten that internship? 110 00:05:13,000 --> 00:05:13,200 Speaker 2: Right? What? 111 00:05:13,360 --> 00:05:15,080 Speaker 3: I still would I still be the same? 112 00:05:15,160 --> 00:05:15,200 Speaker 1: What? 113 00:05:15,320 --> 00:05:17,080 Speaker 3: I still think the same things I'm thinking now? What 114 00:05:17,240 --> 00:05:19,839 Speaker 3: I what? I would I be the same person even? 115 00:05:20,200 --> 00:05:20,400 Speaker 1: Right? 116 00:05:20,680 --> 00:05:22,520 Speaker 2: So one of the things I really like to ask 117 00:05:22,560 --> 00:05:24,680 Speaker 2: playwrights is like, where did you start? 118 00:05:24,880 --> 00:05:27,920 Speaker 1: Where did this begin? Was it the characters? Was it 119 00:05:28,000 --> 00:05:28,600 Speaker 1: the plot? 120 00:05:28,800 --> 00:05:29,040 Speaker 3: Yeah? 121 00:05:29,080 --> 00:05:31,560 Speaker 4: A lot of times when I write plays, I begin 122 00:05:31,600 --> 00:05:34,680 Speaker 4: with an image or a kind of specific theatrical conceit, 123 00:05:35,200 --> 00:05:37,320 Speaker 4: and I so I knew I wanted to write something 124 00:05:37,360 --> 00:05:41,839 Speaker 4: about Pallenteer or about about a Palneer like company. And 125 00:05:41,920 --> 00:05:44,080 Speaker 4: I was sitting I was living back home in LA 126 00:05:44,640 --> 00:05:48,160 Speaker 4: and I was sitting in my dad's you know, office study, 127 00:05:48,520 --> 00:05:52,279 Speaker 4: watching the TV. And I was watching the Camerage Analytica hearings. Yeah, 128 00:05:52,320 --> 00:05:57,400 Speaker 4: you know, Cambridgealytica being a data mining firm that improperly 129 00:05:57,480 --> 00:06:01,320 Speaker 4: or illegally used Facebook data for targeted advertising. And it 130 00:06:01,360 --> 00:06:03,480 Speaker 4: was this It felt like the sort of watershed moment, 131 00:06:03,520 --> 00:06:05,760 Speaker 4: at least to me, looking at the scope of Silicon 132 00:06:05,839 --> 00:06:07,880 Speaker 4: Valley and in the scope of Facebook as a company, 133 00:06:08,320 --> 00:06:11,679 Speaker 4: where people were kind of aware for the first time 134 00:06:12,000 --> 00:06:15,960 Speaker 4: that these companies had more power. I think it wasn't 135 00:06:15,960 --> 00:06:17,960 Speaker 4: all fun in games anymore. And I think I think 136 00:06:17,680 --> 00:06:20,240 Speaker 4: you can kind of trace back the sort of end 137 00:06:20,279 --> 00:06:24,000 Speaker 4: of the wild West in Silicon Valley to that. In 138 00:06:24,040 --> 00:06:26,479 Speaker 4: some ways, I feel like that, plus the pandemic and 139 00:06:26,520 --> 00:06:28,919 Speaker 4: a bunch of other economic factors obviously have driven the 140 00:06:28,920 --> 00:06:31,440 Speaker 4: companies into a little bit more of a like we 141 00:06:31,520 --> 00:06:34,160 Speaker 4: are actually the corporate bureaucracies that we swore we would 142 00:06:34,160 --> 00:06:35,120 Speaker 4: never be sort. 143 00:06:34,960 --> 00:06:36,440 Speaker 3: Of sort of vibe. 144 00:06:36,560 --> 00:06:39,039 Speaker 4: And I remember sitting there watching these hearings at the 145 00:06:39,040 --> 00:06:42,440 Speaker 4: time and recognizing them as this sort of big turning point, 146 00:06:42,720 --> 00:06:46,119 Speaker 4: and especially recognizing that, like I knew people who worked 147 00:06:46,120 --> 00:06:50,000 Speaker 4: at Facebook, and I was wondering if they were having 148 00:06:50,080 --> 00:06:53,120 Speaker 4: the same sort of quarter life crisis that I was having. 149 00:06:53,400 --> 00:06:55,480 Speaker 4: And I wondered if the fact that they were working 150 00:06:55,560 --> 00:06:58,160 Speaker 4: at these companies that were so powerful and demanded so 151 00:06:58,240 --> 00:07:02,400 Speaker 4: much of their time and energy kind of identity was 152 00:07:02,600 --> 00:07:06,040 Speaker 4: changing or complicating that quarter life crisis in any way. 153 00:07:06,360 --> 00:07:10,000 Speaker 4: And I had this image of two people at a 154 00:07:10,040 --> 00:07:12,680 Speaker 4: ping pong table playing ping pong. 155 00:07:12,800 --> 00:07:14,560 Speaker 1: Which is not a spoiler alert, which is how we 156 00:07:14,680 --> 00:07:15,840 Speaker 1: start them. 157 00:07:15,560 --> 00:07:19,040 Speaker 4: Yeah, exactly is there's a bunch of live ping pong 158 00:07:19,080 --> 00:07:21,560 Speaker 4: throughout the play, and that was that was the first 159 00:07:21,560 --> 00:07:23,800 Speaker 4: image I had. And it's also not as spoiled to 160 00:07:23,800 --> 00:07:26,040 Speaker 4: say there are scenes in the play where they're having 161 00:07:26,160 --> 00:07:30,320 Speaker 4: conversations of moral philosophy while playing ping pong. And that 162 00:07:30,480 --> 00:07:32,080 Speaker 4: was the first image I had for the play, was 163 00:07:32,120 --> 00:07:35,640 Speaker 4: this idea of a world in which the fun in 164 00:07:35,720 --> 00:07:38,080 Speaker 4: games of it, like the ping pong of it, was 165 00:07:38,160 --> 00:07:41,880 Speaker 4: butting up against the weight and the power in the 166 00:07:42,040 --> 00:07:44,840 Speaker 4: and the potential darkness of it, you know, And so 167 00:07:45,080 --> 00:07:46,360 Speaker 4: a lot of the play was about how do you 168 00:07:46,480 --> 00:07:51,680 Speaker 4: create a story where the sort of yeah, the bright 169 00:07:51,800 --> 00:07:55,280 Speaker 4: sunny sheen of Silicon Valley can be at odds with 170 00:07:55,400 --> 00:07:59,240 Speaker 4: the sort of nature of the work, or you know, 171 00:07:59,520 --> 00:08:01,720 Speaker 4: them of the play can be in conflict with the 172 00:08:01,760 --> 00:08:03,320 Speaker 4: content of the play in some ways. 173 00:08:03,720 --> 00:08:07,360 Speaker 2: So you started writing this play in twenty eighteen, it's 174 00:08:07,400 --> 00:08:09,920 Speaker 2: taken eight years to get off Broadway. 175 00:08:10,160 --> 00:08:12,760 Speaker 1: But can you tell us what the big super secret 176 00:08:12,760 --> 00:08:14,880 Speaker 1: project is that sits at the center of this play? 177 00:08:16,920 --> 00:08:21,920 Speaker 4: Yeah, I mean I I wasn't necessary like it's it's 178 00:08:21,960 --> 00:08:24,560 Speaker 4: in the structure of the play. That thing is there 179 00:08:24,600 --> 00:08:27,000 Speaker 4: is a reveal in that like it a lot of 180 00:08:27,000 --> 00:08:30,160 Speaker 4: the time elicits a reaction from the audience, but it 181 00:08:30,240 --> 00:08:33,560 Speaker 4: is not. It was not necessarily written to shock the 182 00:08:33,600 --> 00:08:38,080 Speaker 4: audience because I think it is. It is something that 183 00:08:38,880 --> 00:08:43,280 Speaker 4: has happened before and will is happening now and likely 184 00:08:43,320 --> 00:08:44,160 Speaker 4: will happen again. 185 00:08:44,720 --> 00:08:47,480 Speaker 1: And you can also spoil it if you want to 186 00:08:47,480 --> 00:08:48,200 Speaker 1: tell us, you can. 187 00:08:48,120 --> 00:08:48,960 Speaker 2: Spoil it a little bit. 188 00:08:49,000 --> 00:08:51,439 Speaker 4: Maybe we shouldn't get spoil it, yeah, yeah, yeah, spoil 189 00:08:51,480 --> 00:08:53,760 Speaker 4: it skip Hey, Yeah, we're going to put a spoiler 190 00:08:53,800 --> 00:08:56,600 Speaker 4: section here, No, I mean, so, yeah, when I you know, 191 00:08:56,600 --> 00:08:58,320 Speaker 4: when I first started writing the play, I started I 192 00:08:58,360 --> 00:09:02,319 Speaker 4: started working on it kind of right out after Kids 193 00:09:02,320 --> 00:09:05,640 Speaker 4: in Cages, that sort of immigration policy in the first 194 00:09:05,720 --> 00:09:08,880 Speaker 4: rom of administration, and very specifically, I'd read this article 195 00:09:08,920 --> 00:09:12,360 Speaker 4: where the headline was, you know, meet the company building 196 00:09:12,440 --> 00:09:17,360 Speaker 4: Trump's deportation machine, and it was about Palenteer. And again 197 00:09:17,400 --> 00:09:18,920 Speaker 4: this goes back to what I was saying before, of 198 00:09:18,960 --> 00:09:22,560 Speaker 4: like there was a real world in which I would 199 00:09:22,600 --> 00:09:25,520 Speaker 4: have been an employee of Palateer while all that was happening, 200 00:09:25,720 --> 00:09:29,040 Speaker 4: and it was just this thing of like what would 201 00:09:29,040 --> 00:09:30,160 Speaker 4: I have done if I was there? 202 00:09:30,400 --> 00:09:30,600 Speaker 3: Right? 203 00:09:31,000 --> 00:09:33,240 Speaker 4: And so the play obviously then takes that to an 204 00:09:33,280 --> 00:09:37,040 Speaker 4: extreme of again in spoiler territory, sort of whistleblowing plot. 205 00:09:37,480 --> 00:09:42,520 Speaker 4: But the idea of like of immigration being the sort 206 00:09:42,559 --> 00:09:45,960 Speaker 4: of hot button issue is like, you know, if I 207 00:09:46,000 --> 00:09:48,720 Speaker 4: had known at the time that when the play finally 208 00:09:48,760 --> 00:09:52,480 Speaker 4: got put up that that would elicit gasps of recognition, 209 00:09:53,480 --> 00:09:56,000 Speaker 4: you know, it would have been It's upsetting, right, It's 210 00:09:56,040 --> 00:09:57,640 Speaker 4: not right, Yeah, I mean, it's just all I can 211 00:09:57,679 --> 00:10:01,480 Speaker 4: say is that I find it upsetting that the play 212 00:10:01,520 --> 00:10:03,679 Speaker 4: is still relevant, you know, like it's one of those 213 00:10:03,679 --> 00:10:05,079 Speaker 4: things where it's like I long for it not. 214 00:10:05,120 --> 00:10:08,080 Speaker 1: To be you long for the play not to be relevant. 215 00:10:08,480 --> 00:10:08,840 Speaker 3: Yeah. 216 00:10:09,400 --> 00:10:11,840 Speaker 1: Can you talk a little bit about ma Nation, talk 217 00:10:11,880 --> 00:10:15,600 Speaker 1: about how he is the sort of moral center of 218 00:10:15,640 --> 00:10:16,200 Speaker 1: the play. 219 00:10:16,559 --> 00:10:16,839 Speaker 3: Yeah. 220 00:10:16,960 --> 00:10:20,040 Speaker 4: The whole kind of design of the character is that 221 00:10:20,360 --> 00:10:23,160 Speaker 4: he's at this place that a lot of people I 222 00:10:23,160 --> 00:10:25,040 Speaker 4: think are at right out of school, and that I 223 00:10:25,080 --> 00:10:27,880 Speaker 4: was definitely at right out of school, which is I 224 00:10:27,880 --> 00:10:30,520 Speaker 4: don't really know who I'm going to be as an 225 00:10:30,559 --> 00:10:32,840 Speaker 4: adult in the world, right, I don't really know. 226 00:10:33,160 --> 00:10:33,920 Speaker 3: I don't really know. 227 00:10:34,160 --> 00:10:35,960 Speaker 4: I think I know what I believe in, but I 228 00:10:35,960 --> 00:10:37,760 Speaker 4: don't really know how to implement that in the world. 229 00:10:37,960 --> 00:10:39,760 Speaker 4: I don't really know how to implement that in my work. 230 00:10:40,400 --> 00:10:42,600 Speaker 4: And I'm and I'm like, I'm now I'm out of 231 00:10:42,640 --> 00:10:45,240 Speaker 4: the structure of school, and I'm staring down the barrel 232 00:10:45,400 --> 00:10:48,760 Speaker 4: of the next fifty years of my life and just 233 00:10:48,760 --> 00:10:50,480 Speaker 4: trying to figure out who I want to be, right, 234 00:10:50,520 --> 00:10:53,160 Speaker 4: And so that was the that was the kind of 235 00:10:53,280 --> 00:10:56,400 Speaker 4: initial design of the character. Part of the goal then 236 00:10:56,520 --> 00:10:59,160 Speaker 4: was how do I surround that character with a bunch 237 00:10:59,200 --> 00:11:03,760 Speaker 4: of people who have very different viewpoints to answer those 238 00:11:03,840 --> 00:11:07,000 Speaker 4: questions of what it means to be a good person, 239 00:11:07,080 --> 00:11:08,640 Speaker 4: you know, what it means to do the right thing. 240 00:11:09,559 --> 00:11:13,280 Speaker 4: All of the other characters in the play, Riley, Jonah, 241 00:11:13,320 --> 00:11:16,360 Speaker 4: and Alex, they all at some point in the play 242 00:11:16,520 --> 00:11:18,520 Speaker 4: invoke this vision of what it means to do the 243 00:11:18,600 --> 00:11:22,080 Speaker 4: right thing. And the goal there is that Miniches is 244 00:11:22,120 --> 00:11:26,160 Speaker 4: sort of ping pong throughout the story, is being constantly 245 00:11:26,200 --> 00:11:30,160 Speaker 4: sort of convinced by different people in the company about 246 00:11:30,160 --> 00:11:32,520 Speaker 4: what the right thing to do is. And one of 247 00:11:32,559 --> 00:11:35,480 Speaker 4: my initial intentions with this play was, how do you 248 00:11:35,480 --> 00:11:38,000 Speaker 4: tell a story about Silicon Valley that's not about the 249 00:11:38,080 --> 00:11:42,360 Speaker 4: founder and that's actually about the entry level employees. What 250 00:11:42,520 --> 00:11:44,520 Speaker 4: is their relationship to the people at the top of 251 00:11:44,559 --> 00:11:47,120 Speaker 4: the company, right? And I'm very interested in that of 252 00:11:47,240 --> 00:11:49,120 Speaker 4: just like the way that the kind of values of 253 00:11:49,120 --> 00:11:51,880 Speaker 4: the company trickle down to the employees, even if the 254 00:11:51,920 --> 00:11:54,800 Speaker 4: company claims to have, you know, to foster open dialogue 255 00:11:54,840 --> 00:11:57,840 Speaker 4: and to welcome all viewpoints of opinion and stuff like that. 256 00:11:58,280 --> 00:12:00,720 Speaker 1: Do you think people are more or less willing to 257 00:12:00,800 --> 00:12:03,720 Speaker 1: accept that tech companies can be bad actors as opposed 258 00:12:03,760 --> 00:12:05,360 Speaker 1: to maybe how they felt eight years ago. 259 00:12:06,000 --> 00:12:08,120 Speaker 4: If Silicon Valley used to be this sort of again 260 00:12:08,240 --> 00:12:12,840 Speaker 4: like libertarian utopian bubble off in the Bay Area. The 261 00:12:12,920 --> 00:12:15,160 Speaker 4: sort of ethos of Silicon Valley is kind of broken 262 00:12:15,240 --> 00:12:17,679 Speaker 4: containment in some ways, Like there's just been a lot 263 00:12:17,720 --> 00:12:20,840 Speaker 4: of very public battles that have involved tech companies over 264 00:12:20,880 --> 00:12:23,000 Speaker 4: the last eight years, and maybe a way that in 265 00:12:23,040 --> 00:12:25,960 Speaker 4: a way that there wasn't before, you know, Facebook's relationship 266 00:12:25,960 --> 00:12:30,840 Speaker 4: with elections, TikTok, you know, open Ai, like in the 267 00:12:30,880 --> 00:12:35,880 Speaker 4: Sam Altman drama. You know, the Silicon Valley's problems have 268 00:12:36,000 --> 00:12:38,400 Speaker 4: become the world's problems in some ways. 269 00:12:38,720 --> 00:12:40,679 Speaker 2: Right, it can't be you can't live in the world 270 00:12:40,720 --> 00:12:42,880 Speaker 2: without caring about this stuff exactly. 271 00:12:42,920 --> 00:12:46,040 Speaker 4: Maybe in maybe a way that in twenty fourteen you 272 00:12:46,120 --> 00:12:49,240 Speaker 4: could just use Facebook and not really think about its impact. 273 00:12:49,360 --> 00:12:51,680 Speaker 4: It feels like the impact is I'm possible to avoid now. 274 00:12:52,000 --> 00:12:53,640 Speaker 4: And I think and I think, you know, I think 275 00:12:53,679 --> 00:12:56,080 Speaker 4: people do have will come into the play with a 276 00:12:56,120 --> 00:12:59,640 Speaker 4: certain amount of like judgment or you know, I think 277 00:12:59,679 --> 00:13:01,640 Speaker 4: that they'll come into it. They might come into the 278 00:13:01,640 --> 00:13:05,200 Speaker 4: play with a certain belief system. I think the play 279 00:13:05,679 --> 00:13:10,439 Speaker 4: does hopefully push people into a slightly more complicated, nuanced 280 00:13:10,480 --> 00:13:15,120 Speaker 4: position on these tech companies and specifically on like you know, 281 00:13:15,880 --> 00:13:19,079 Speaker 4: we have a character explain why it's a good thing 282 00:13:19,160 --> 00:13:22,200 Speaker 4: to be working with Ice, right, And again, the goal 283 00:13:22,280 --> 00:13:25,520 Speaker 4: is not to like make people sympathetic to palent Heer. 284 00:13:25,559 --> 00:13:32,480 Speaker 4: It's more just to identify that, especially as these conversations 285 00:13:32,600 --> 00:13:36,080 Speaker 4: enter the public sphere, that we have to remember that 286 00:13:36,480 --> 00:13:39,000 Speaker 4: what we're talking about are not black boxes. We're talking 287 00:13:39,040 --> 00:13:44,360 Speaker 4: about tools that are the response to human decisions and 288 00:13:44,440 --> 00:13:48,520 Speaker 4: human values and human biases, and that the system, and 289 00:13:48,559 --> 00:13:51,560 Speaker 4: that the system is ultimately more complicated than any one 290 00:13:51,640 --> 00:13:55,840 Speaker 4: individual story or narrative. And so yeah, I mean I've 291 00:13:55,880 --> 00:13:58,480 Speaker 4: seen people's response to a change, just as people have 292 00:13:58,559 --> 00:14:03,160 Speaker 4: started to gain a i think a consciousness of if 293 00:14:03,160 --> 00:14:06,400 Speaker 4: it's not even a moral valance, it's just the power 294 00:14:06,920 --> 00:14:09,320 Speaker 4: of these companies and these technologies in our world. 295 00:14:10,240 --> 00:14:12,520 Speaker 1: Well, this has been a wonderful interview. It's so great 296 00:14:12,559 --> 00:14:14,720 Speaker 1: to talk to you and to get a better sense 297 00:14:14,760 --> 00:14:17,080 Speaker 1: of just where your mind was at when you were 298 00:14:17,080 --> 00:14:19,680 Speaker 1: writing this show. So I really appreciate it, Matthew. 299 00:14:19,680 --> 00:14:21,280 Speaker 3: Thank you so much for having me. This is great. 300 00:14:22,160 --> 00:14:24,960 Speaker 2: After the break, we hear about Marjorie Prime, which was 301 00:14:24,960 --> 00:14:27,280 Speaker 2: a finalist for the Pulitzer Prize in Drama back in 302 00:14:27,320 --> 00:14:30,920 Speaker 2: twenty fifteen, the playwright Jordan Harrison and I discuss why 303 00:14:30,960 --> 00:14:40,960 Speaker 2: it's even more relevant today. Stay with us, Welcome back. 304 00:14:41,280 --> 00:14:44,960 Speaker 2: My next guest is Jordan Harrison. His play Marjorie Prime, 305 00:14:45,000 --> 00:14:47,440 Speaker 2: which premiered in New York ten years ago, was made 306 00:14:47,520 --> 00:14:50,160 Speaker 2: into a movie starring John Hamm and Gina Davis, and 307 00:14:50,280 --> 00:14:54,120 Speaker 2: is now back on Broadway until Sunday, February fifteenth. What's 308 00:14:54,160 --> 00:14:57,400 Speaker 2: incredible is that Jordan kind of predicted the growing grief 309 00:14:57,440 --> 00:15:00,640 Speaker 2: tech industry that now exists thanks to Jeneral AI and 310 00:15:00,720 --> 00:15:04,280 Speaker 2: companies like Here After AI and story File. I'll let 311 00:15:04,400 --> 00:15:06,480 Speaker 2: Jordan explain the plot in his own words. 312 00:15:06,840 --> 00:15:09,280 Speaker 5: It's about an eighty five year old woman who has 313 00:15:09,320 --> 00:15:12,720 Speaker 5: an AI version of her dead husband from when he's 314 00:15:12,760 --> 00:15:16,200 Speaker 5: a handsome thirty something, and kind of the flight of 315 00:15:16,280 --> 00:15:21,720 Speaker 5: fancy was making AI almost a member of the family, 316 00:15:21,920 --> 00:15:23,720 Speaker 5: like a person in the living room. 317 00:15:23,640 --> 00:15:24,960 Speaker 6: With the rest of the characters. 318 00:15:25,560 --> 00:15:29,560 Speaker 5: And ten years ago when it premiered had its New 319 00:15:29,640 --> 00:15:34,080 Speaker 5: York premiere off Broadway, that was exactly as I described it, 320 00:15:34,120 --> 00:15:35,000 Speaker 5: a flight of fancy. 321 00:15:35,040 --> 00:15:36,720 Speaker 6: It was kind of a fantastical thing. 322 00:15:36,800 --> 00:15:40,560 Speaker 5: And now people, I don't think audiences have any trouble 323 00:15:40,640 --> 00:15:44,320 Speaker 5: imagining that AI is playing a personal role in their lives. 324 00:15:44,720 --> 00:15:49,000 Speaker 2: Prior to writing this play, what has your relationship with 325 00:15:49,080 --> 00:15:53,120 Speaker 2: technology been, and like specifically your relationship with AI. Because 326 00:15:53,160 --> 00:15:55,600 Speaker 2: you're a writer, you know, you're not a technologist, so 327 00:15:56,440 --> 00:15:57,720 Speaker 2: I'm curious. 328 00:15:58,040 --> 00:16:02,200 Speaker 5: Yeah, I guess it's been an anxious and wary relationship 329 00:16:02,200 --> 00:16:05,640 Speaker 5: with technology. Like I'm starting from that place. But the 330 00:16:05,680 --> 00:16:07,560 Speaker 5: first thing that I knew when I, you know, I 331 00:16:07,600 --> 00:16:11,160 Speaker 5: opened the blank document and started Marjorie Brime, was that 332 00:16:11,240 --> 00:16:14,280 Speaker 5: I was interested in writing the play with the chatbot. 333 00:16:14,600 --> 00:16:17,880 Speaker 5: And in twenty twelve, that was a relatively exotic thing 334 00:16:17,920 --> 00:16:20,320 Speaker 5: to want to do. And I think maybe I thought, yeah, 335 00:16:20,400 --> 00:16:22,720 Speaker 5: I think I thought, oh, I'll only have to write 336 00:16:22,800 --> 00:16:23,480 Speaker 5: half the play. 337 00:16:24,200 --> 00:16:26,080 Speaker 6: So I thought that What I. 338 00:16:26,040 --> 00:16:29,440 Speaker 5: Tried to do is I downloaded whatever free chatbot program 339 00:16:29,480 --> 00:16:33,520 Speaker 5: I found and just had a conversation with it. And 340 00:16:33,600 --> 00:16:38,040 Speaker 5: I imagined that then there would be two human actors 341 00:16:38,040 --> 00:16:41,360 Speaker 5: on stage performing that conversation, and the audience would have 342 00:16:41,400 --> 00:16:44,160 Speaker 5: to figure out which was written by the computer. The 343 00:16:44,240 --> 00:16:47,480 Speaker 5: play itself would be a kind of touring test. And 344 00:16:48,040 --> 00:16:50,840 Speaker 5: in twenty twelve, I don't think I lasted two hours 345 00:16:50,920 --> 00:16:54,840 Speaker 5: writing with this chat pot. Everything was tell me more 346 00:16:54,840 --> 00:16:58,200 Speaker 5: about your mother. That sounds difficult, you know, it truly 347 00:16:58,320 --> 00:17:02,160 Speaker 5: was almost never not a back board, and so I 348 00:17:02,600 --> 00:17:06,359 Speaker 5: had to go about actually doing my job and creating 349 00:17:06,640 --> 00:17:09,560 Speaker 5: a play on my own. But the sort of chilly 350 00:17:09,760 --> 00:17:14,080 Speaker 5: experience of talking with a twenty twelve era chatbot and 351 00:17:14,119 --> 00:17:18,480 Speaker 5: it's misunderstandings or something that I kind of wove into. 352 00:17:18,280 --> 00:17:19,119 Speaker 6: The finished play. 353 00:17:19,280 --> 00:17:21,640 Speaker 5: Every now and then, you know, you think you're having 354 00:17:22,200 --> 00:17:25,200 Speaker 5: an intimate conversation with the Primes, which is what the 355 00:17:25,320 --> 00:17:28,359 Speaker 5: chatbots are called in the play, and then suddenly it'll say, 356 00:17:28,600 --> 00:17:30,600 Speaker 5: you know, I'm afraid I don't have that information, and 357 00:17:30,640 --> 00:17:33,560 Speaker 5: the rug gets ripped out from under you. 358 00:17:33,480 --> 00:17:36,639 Speaker 1: Because you're told, you're reminded that you're not actually talking 359 00:17:36,680 --> 00:17:40,480 Speaker 1: to someone. You started this as a project to kind 360 00:17:40,520 --> 00:17:43,600 Speaker 1: of test audiences to see if people could tell what 361 00:17:43,640 --> 00:17:48,160 Speaker 1: the difference, which is so unbelievably at the time prescient, 362 00:17:48,160 --> 00:17:51,520 Speaker 1: because like I would say, like one of the main 363 00:17:51,840 --> 00:17:54,320 Speaker 1: folk guy of our time is like being able to 364 00:17:54,320 --> 00:17:56,200 Speaker 1: tell the difference between human and machine. 365 00:17:56,400 --> 00:17:59,360 Speaker 5: Well, I mean, it's incredible how much it's a part 366 00:17:59,400 --> 00:18:00,520 Speaker 5: of our daily life lives now. 367 00:18:00,560 --> 00:18:02,080 Speaker 6: Like I guess on the topic of. 368 00:18:02,000 --> 00:18:05,359 Speaker 5: Marjorie Prime, as I wonder whether eventually we will get 369 00:18:05,520 --> 00:18:10,760 Speaker 5: comfortable with dead people still being in our lives, you know, 370 00:18:11,040 --> 00:18:12,920 Speaker 5: in the form of avatars. 371 00:18:12,480 --> 00:18:14,640 Speaker 6: That's a spooky thought because. 372 00:18:14,359 --> 00:18:17,560 Speaker 5: In my experience, we don't have much of a choice, 373 00:18:17,680 --> 00:18:19,879 Speaker 5: you know. The new gadgets come around the bend and 374 00:18:19,960 --> 00:18:23,639 Speaker 5: suddenly that's just part of the texture of life, you know. 375 00:18:24,200 --> 00:18:27,520 Speaker 5: And I should check this first, but before making this 376 00:18:27,640 --> 00:18:30,800 Speaker 5: brazen declaration. But I don't think that the term AI 377 00:18:31,080 --> 00:18:32,320 Speaker 5: ever appears in it. 378 00:18:32,440 --> 00:18:33,200 Speaker 1: I don't think it does. 379 00:18:33,359 --> 00:18:38,520 Speaker 5: Like, Yeah, and without being too spoilery, there are there 380 00:18:38,560 --> 00:18:42,080 Speaker 5: isn't just one AI character. People die in the play 381 00:18:42,119 --> 00:18:45,640 Speaker 5: as people do, and are replaced with AI versions of themselves, 382 00:18:45,960 --> 00:18:49,440 Speaker 5: and then the audience in our own lived experience for 383 00:18:49,760 --> 00:18:52,080 Speaker 5: an hour and twenty two minutes and sitting in our 384 00:18:52,119 --> 00:18:55,800 Speaker 5: theater seats like feels the difference between the real person 385 00:18:55,840 --> 00:18:58,360 Speaker 5: they knew and the AI in front of them. 386 00:18:58,640 --> 00:19:03,280 Speaker 2: Yeah, I think we're still like watching Marjorie Prime, because 387 00:19:03,400 --> 00:19:07,080 Speaker 2: I mean I think about this constantly. I had a 388 00:19:07,119 --> 00:19:10,639 Speaker 2: parent that passed away when I was very young, and 389 00:19:10,680 --> 00:19:13,560 Speaker 2: also I saw Marjorie Prime, and I think he would 390 00:19:13,560 --> 00:19:15,639 Speaker 2: be okay with me saying this. I saw Marjorie Prime 391 00:19:15,720 --> 00:19:21,040 Speaker 2: with someone who has Alzheimer's and I think we were 392 00:19:21,119 --> 00:19:25,280 Speaker 2: both on different ends of the spectrum thinking about what 393 00:19:25,440 --> 00:19:30,399 Speaker 2: it's like to have a living memory in your life 394 00:19:30,640 --> 00:19:35,919 Speaker 2: past the point of that memory's like corporeal existence, you know, 395 00:19:36,520 --> 00:19:40,320 Speaker 2: and like what that means and is that I think 396 00:19:40,359 --> 00:19:43,679 Speaker 2: the question that comes up in the play is like, 397 00:19:46,240 --> 00:19:48,919 Speaker 2: I guess there's the morality question, but there's also like 398 00:19:48,960 --> 00:19:53,560 Speaker 2: the humanity question, like is that human? And I and 399 00:19:53,640 --> 00:19:55,920 Speaker 2: I guess my question for you is like. 400 00:19:57,440 --> 00:20:01,280 Speaker 1: Would you have a prime yeah or not? Yeah? 401 00:20:01,320 --> 00:20:03,600 Speaker 5: I would, but yeah, that's something I get asked and 402 00:20:03,640 --> 00:20:05,879 Speaker 5: something I have to think about now. The test I 403 00:20:06,840 --> 00:20:09,800 Speaker 5: put myself to is like I lost a dear friend 404 00:20:09,960 --> 00:20:12,720 Speaker 5: in nineteen ninety eight we were in college, and like, it. 405 00:20:12,680 --> 00:20:15,080 Speaker 6: Would be so delicious to talk to her again. 406 00:20:15,560 --> 00:20:19,960 Speaker 5: But when I think of whatever app could assemble out 407 00:20:19,960 --> 00:20:23,720 Speaker 5: of like old video and photographs, it could only be 408 00:20:23,840 --> 00:20:27,720 Speaker 5: grotesque the distance between her, the real friend, and the 409 00:20:27,760 --> 00:20:30,800 Speaker 5: avatar friend. I think I would end up feeling farther 410 00:20:30,920 --> 00:20:33,800 Speaker 5: from her than when I started. 411 00:20:33,440 --> 00:20:33,600 Speaker 2: You know. 412 00:20:34,119 --> 00:20:37,159 Speaker 5: I think the question, certainly a big part of the 413 00:20:37,240 --> 00:20:40,200 Speaker 5: play is what does grief do to a family? 414 00:20:40,440 --> 00:20:41,560 Speaker 6: Unprocessed grief? 415 00:20:41,800 --> 00:20:45,800 Speaker 5: The generation before the play takes place, there's this terrible 416 00:20:45,880 --> 00:20:49,280 Speaker 5: tragedy and no one talks about it, and it continues 417 00:20:49,320 --> 00:20:51,280 Speaker 5: to be a big part of who they are and 418 00:20:51,320 --> 00:20:54,600 Speaker 5: who they are with each other. So I think the 419 00:20:54,640 --> 00:20:57,320 Speaker 5: way I think of it as if we had the 420 00:20:57,359 --> 00:21:01,760 Speaker 5: option of this really realistic version of our dead mom 421 00:21:01,800 --> 00:21:05,200 Speaker 5: and dad, our dead spouse, like, and we could talk 422 00:21:05,280 --> 00:21:10,600 Speaker 5: to it. Then is that confronting the grief or is 423 00:21:10,680 --> 00:21:13,480 Speaker 5: that being in denial of the grief? You know, and 424 00:21:14,040 --> 00:21:16,159 Speaker 5: I don't even mean denial, Like you would talk to 425 00:21:16,200 --> 00:21:18,399 Speaker 5: it and think that your spouse is still alive, but 426 00:21:18,600 --> 00:21:22,600 Speaker 5: you wouldn't feel the absence of them, And maybe that's 427 00:21:22,640 --> 00:21:24,320 Speaker 5: an important part of being a human. 428 00:21:25,640 --> 00:21:28,680 Speaker 2: So Jordan, obviously a lot has changed in the world 429 00:21:28,680 --> 00:21:31,639 Speaker 2: of AI since your play premiered ten years ago, But 430 00:21:31,720 --> 00:21:34,720 Speaker 2: has that changed the play at all for you? 431 00:21:34,720 --> 00:21:37,000 Speaker 5: You know, it's just tough, Like I guess, I don't. 432 00:21:37,240 --> 00:21:39,920 Speaker 5: Maybe this is a boring answer. I don't feel different, 433 00:21:40,880 --> 00:21:44,879 Speaker 5: I feel if anything. Like I used to say that 434 00:21:45,480 --> 00:21:47,840 Speaker 5: part of my project as a playwright is to track 435 00:21:47,920 --> 00:21:51,000 Speaker 5: the transition from the analog world to the digital world, 436 00:21:51,400 --> 00:21:54,639 Speaker 5: those growing pains, And now I'm a little closer to 437 00:21:54,720 --> 00:21:57,960 Speaker 5: saying that I'm tracking the transition from the. 438 00:21:58,000 --> 00:22:00,080 Speaker 6: Human age to the post human age. 439 00:22:00,200 --> 00:22:02,760 Speaker 5: And I guess I bring that up to say I'm 440 00:22:02,800 --> 00:22:06,200 Speaker 5: getting close to acclimated to the idea that we won't 441 00:22:06,200 --> 00:22:09,399 Speaker 5: be around forever, and that it seems to me it 442 00:22:09,440 --> 00:22:13,040 Speaker 5: seems likely that our inventions will remember us, and so 443 00:22:13,200 --> 00:22:19,280 Speaker 5: I'm interested in how they'll remember us, accurately, flatteringly, unflatteringly, 444 00:22:20,200 --> 00:22:20,800 Speaker 5: all the above. 445 00:22:21,119 --> 00:22:23,879 Speaker 1: What is the role of the playwright? Then, as we 446 00:22:23,920 --> 00:22:25,960 Speaker 1: move into mes human age. 447 00:22:27,600 --> 00:22:31,520 Speaker 5: I'm more confident in the role of the playwright than 448 00:22:31,560 --> 00:22:34,000 Speaker 5: I am in the role of the screenwriter or even 449 00:22:34,080 --> 00:22:34,720 Speaker 5: the novelist. 450 00:22:34,960 --> 00:22:38,440 Speaker 6: You know, I have a little more confidence in my jobs. 451 00:22:38,600 --> 00:22:41,840 Speaker 5: I mean, I do all those things, and I feel 452 00:22:41,920 --> 00:22:44,800 Speaker 5: like more confident in my job security as a playwright 453 00:22:44,840 --> 00:22:47,679 Speaker 5: because I see five year olds put on a play 454 00:22:47,800 --> 00:22:49,920 Speaker 5: without knowing that that's what they're doing every day. 455 00:22:50,000 --> 00:22:51,679 Speaker 6: So I do think as long as. 456 00:22:51,520 --> 00:22:55,920 Speaker 5: We have limbs and beating hearts and so forth, we're 457 00:22:56,040 --> 00:22:59,480 Speaker 5: capable of doing that in a way that our technology 458 00:22:59,560 --> 00:22:59,760 Speaker 5: is not. 459 00:23:01,800 --> 00:23:04,679 Speaker 1: Thank you, Jordan, Thank you so much for speaking to 460 00:23:04,720 --> 00:23:05,760 Speaker 1: me about your play today. 461 00:23:06,160 --> 00:23:07,000 Speaker 6: Thanks for having me. 462 00:23:22,920 --> 00:23:25,280 Speaker 2: That's it for text Uff this week. I'm Kara Price. 463 00:23:25,840 --> 00:23:28,840 Speaker 2: This episode was produced by Eliza Dennis, and Melissa Slaughter. 464 00:23:29,320 --> 00:23:33,080 Speaker 2: It was executive produced by me oz Va Lashan, Julia Nutter, 465 00:23:33,160 --> 00:23:37,320 Speaker 2: and Kate Osborne for Kaleidoscope and Katrina Norvell for iHeart Podcasts. 466 00:23:37,760 --> 00:23:40,560 Speaker 2: Jack Insley mixed this episode and Kyle Murdoch wrote our 467 00:23:40,600 --> 00:23:41,080 Speaker 2: theme song. 468 00:23:41,640 --> 00:23:43,040 Speaker 1: Please rate, review, and. 469 00:23:43,000 --> 00:23:45,920 Speaker 2: Reach out to us at tech Stuff podcast at gmail 470 00:23:45,960 --> 00:23:46,920 Speaker 2: dot com. 471 00:23:46,960 --> 00:23:47,880 Speaker 1: We want to hear from you.