1 00:00:05,840 --> 00:00:08,680 Speaker 1: Welcome back to Meeting of Mine's podcast. I'm Isaac Willauer. 2 00:00:08,720 --> 00:00:12,320 Speaker 1: I'm Boyer Research as director of Corporate Engagement. Today we 3 00:00:12,480 --> 00:00:15,640 Speaker 1: have Thomas Dias on the podcast. Thomas is the Foundation's 4 00:00:15,680 --> 00:00:19,439 Speaker 1: relations specialist at the Acton Institute in Grand Rapids, Michigan, 5 00:00:19,840 --> 00:00:23,720 Speaker 1: and a contributor to Actin's Religion and Liberty Online. Thomas 6 00:00:23,760 --> 00:00:26,520 Speaker 1: co runs Cairos, which is a sub stack magazine at 7 00:00:26,520 --> 00:00:30,560 Speaker 1: the intersection of philosophy, theology, and classical liberalism. His writing 8 00:00:30,600 --> 00:00:34,960 Speaker 1: explorers political economy, moral culture in the agentic future. Thomas, 9 00:00:34,960 --> 00:00:35,680 Speaker 1: welcome to the show. 10 00:00:36,320 --> 00:00:38,319 Speaker 2: Thank you for having me on, Isaac appreciate it. 11 00:00:38,800 --> 00:00:40,560 Speaker 1: So I want to talk about I guess that we're 12 00:00:40,560 --> 00:00:43,280 Speaker 1: really going to be talking about the agentic future part 13 00:00:43,280 --> 00:00:47,239 Speaker 1: of that mostly so you're part of this coalition on 14 00:00:47,280 --> 00:00:51,199 Speaker 1: the broadly kind of classical liberal political right. That is 15 00:00:51,360 --> 00:00:53,760 Speaker 1: coalition I'm also part of. Folks like Kevin Valier are 16 00:00:53,800 --> 00:00:56,760 Speaker 1: part of that. That's pretty pro ai right, and that 17 00:00:57,160 --> 00:00:59,480 Speaker 1: is we can talk about why that's kind of a 18 00:00:59,480 --> 00:01:01,639 Speaker 1: coalition and not the default setting on the right if 19 00:01:01,640 --> 00:01:06,800 Speaker 1: you like. But when it comes to talking about artificial 20 00:01:06,800 --> 00:01:11,560 Speaker 1: intelligence and especially integrating into your personal professional practice, do 21 00:01:11,600 --> 00:01:14,040 Speaker 1: you think some of that is for you. Where did 22 00:01:14,080 --> 00:01:16,280 Speaker 1: that come from? Do you think that that's just a 23 00:01:16,360 --> 00:01:19,160 Speaker 1: vocational necessity or in a field that uses AIS, you 24 00:01:19,280 --> 00:01:21,280 Speaker 1: use AI, or do you think that your embrace of 25 00:01:21,319 --> 00:01:25,039 Speaker 1: AI has also kind of been temperamental. Do you think 26 00:01:25,120 --> 00:01:27,480 Speaker 1: is there something about your personality that inclines you towards 27 00:01:27,480 --> 00:01:29,160 Speaker 1: that sort of thing, or is it just the necessity 28 00:01:29,200 --> 00:01:29,679 Speaker 1: of the practice. 29 00:01:29,720 --> 00:01:30,400 Speaker 3: What do you make of that? 30 00:01:31,080 --> 00:01:34,959 Speaker 4: Yeah, I think it's a combination of both. When I 31 00:01:35,000 --> 00:01:38,679 Speaker 4: was in high school, I was really really into entrepreneurship, 32 00:01:38,720 --> 00:01:40,280 Speaker 4: you know. I was one of those guys that started 33 00:01:40,319 --> 00:01:44,000 Speaker 4: a Shopify store. I worked very hard on it, you know, 34 00:01:44,080 --> 00:01:46,319 Speaker 4: and I saw myself like my vocation was to be 35 00:01:46,319 --> 00:01:49,400 Speaker 4: an entrepreneur, was to go and build something. And in 36 00:01:49,440 --> 00:01:52,400 Speaker 4: college I pursued that, especially my freshman and sophomore year, 37 00:01:52,960 --> 00:01:56,600 Speaker 4: and in my sophomore year, I really regained my Christian 38 00:01:56,640 --> 00:02:00,760 Speaker 4: faith very strongly. I had a pretty strong reversion to 39 00:02:00,840 --> 00:02:06,960 Speaker 4: Catholicism and that kind of that kind of shifted my 40 00:02:07,000 --> 00:02:10,960 Speaker 4: focus from trying to be a businessman to you know, 41 00:02:11,160 --> 00:02:16,400 Speaker 4: spiritual and philosophical things. And when I was getting more 42 00:02:16,440 --> 00:02:19,440 Speaker 4: into that and especially the political philosophical side of things 43 00:02:19,440 --> 00:02:23,559 Speaker 4: and trying to have my Christian faith inform my politics. 44 00:02:24,160 --> 00:02:27,080 Speaker 4: I came across the work of Kevin Valier, who you 45 00:02:27,160 --> 00:02:30,120 Speaker 4: just mentioned, who's a professor at the University of Toledo, 46 00:02:30,639 --> 00:02:33,639 Speaker 4: and saw how deeply he engaged with both religious and 47 00:02:33,680 --> 00:02:38,359 Speaker 4: philosophical sources, but also modern social science. And I really 48 00:02:38,400 --> 00:02:43,720 Speaker 4: appreciated how he combined those two things, especially to address 49 00:02:43,840 --> 00:02:49,720 Speaker 4: these modern integralist arguments, post liberal arguments that talk about 50 00:02:49,760 --> 00:02:53,600 Speaker 4: trying to have the state establish religion and these kinds 51 00:02:53,600 --> 00:02:55,920 Speaker 4: of things. And I found that really really interesting, and 52 00:02:55,960 --> 00:03:00,240 Speaker 4: so I applied to the Acting Institute's Emerging Leaders prom 53 00:03:00,400 --> 00:03:04,240 Speaker 4: where Kevin Valier is an affiliate scholar, and I met 54 00:03:04,280 --> 00:03:07,920 Speaker 4: him at acting's big conference and became his research assistant. 55 00:03:07,960 --> 00:03:12,000 Speaker 4: And basically, when he took the plunge into AI and 56 00:03:12,120 --> 00:03:16,160 Speaker 4: started thinking about it really deeply, I followed along and 57 00:03:16,760 --> 00:03:19,480 Speaker 4: dove into it myself, and it kind of reignited my 58 00:03:19,639 --> 00:03:23,800 Speaker 4: interest in entrepreneurship and technology and startups along with my 59 00:03:23,880 --> 00:03:25,840 Speaker 4: philosophical and religious interests. 60 00:03:26,360 --> 00:03:29,080 Speaker 1: It's interesting that it came along with the faith part, right, 61 00:03:29,120 --> 00:03:30,760 Speaker 1: because when I talk to a lot of like gen 62 00:03:30,880 --> 00:03:32,880 Speaker 1: Z people who are kind of on the right broadly 63 00:03:33,400 --> 00:03:36,000 Speaker 1: about getting back to like the like there's kind of 64 00:03:36,000 --> 00:03:38,360 Speaker 1: this trad stereotype that happens of, oh, we're just getting 65 00:03:38,400 --> 00:03:41,320 Speaker 1: back to religion for guys, especially like there's this whole 66 00:03:41,360 --> 00:03:44,360 Speaker 1: internet subculture of like you just eat steak and you 67 00:03:44,400 --> 00:03:47,160 Speaker 1: lift weights and you go to church. Like it feels 68 00:03:47,200 --> 00:03:50,200 Speaker 1: a little simplistic, especially because like it denotes a certain 69 00:03:50,240 --> 00:03:53,640 Speaker 1: political worldview, which is which is valid, but is also 70 00:03:53,760 --> 00:03:55,920 Speaker 1: it's a little simplistic when I hear people talk about 71 00:03:55,920 --> 00:04:00,640 Speaker 1: their like managing faith and kind of this technological age 72 00:04:01,000 --> 00:04:03,600 Speaker 1: that we live in, the default tendency seems to be 73 00:04:03,680 --> 00:04:05,960 Speaker 1: running away from technology. It's like, well, I learned that 74 00:04:06,000 --> 00:04:08,280 Speaker 1: it's all being run by demons, and now I just 75 00:04:08,320 --> 00:04:11,440 Speaker 1: read the Bible, and I'm like, I don't think. I 76 00:04:11,480 --> 00:04:13,680 Speaker 1: don't think those two. I don't think one of those 77 00:04:13,720 --> 00:04:14,480 Speaker 1: implies the other. 78 00:04:14,840 --> 00:04:15,160 Speaker 3: I don't know. 79 00:04:15,320 --> 00:04:17,520 Speaker 1: So you got back into faith and then you also 80 00:04:17,560 --> 00:04:19,840 Speaker 1: started leaning into AI. Do you do you find that 81 00:04:19,880 --> 00:04:22,640 Speaker 1: there's do you find that's kind of a logical progression 82 00:04:22,680 --> 00:04:23,960 Speaker 1: or do you find there's tension there? 83 00:04:24,839 --> 00:04:26,640 Speaker 4: No, I think there is tension, And I think you're right, 84 00:04:26,720 --> 00:04:30,360 Speaker 4: because you know when people do that and they totally 85 00:04:30,400 --> 00:04:35,760 Speaker 4: like reject technology. You know, that's the phrase the reject modernity, 86 00:04:35,839 --> 00:04:38,679 Speaker 4: return to tradition, right when people do that kind of thing. 87 00:04:39,560 --> 00:04:41,680 Speaker 4: I think there's a kind of truth there in the 88 00:04:41,720 --> 00:04:44,200 Speaker 4: sense that, you know, when I was thinking about it, 89 00:04:44,240 --> 00:04:46,760 Speaker 4: I kind of realized, Man, all I wanted to do 90 00:04:46,880 --> 00:04:50,080 Speaker 4: was make money and start a business and achieve things 91 00:04:50,279 --> 00:04:55,880 Speaker 4: or whatever, And here Jesus is telling me that that's 92 00:04:55,880 --> 00:04:58,360 Speaker 4: not what happiness is. And the happiness is much deeper 93 00:04:58,400 --> 00:05:01,440 Speaker 4: than that, and it's spiritual, not material, And so it 94 00:05:01,520 --> 00:05:06,000 Speaker 4: kind of makes sense why people think about that that way. 95 00:05:06,600 --> 00:05:08,839 Speaker 4: And so I think there is kind of a tension. 96 00:05:09,320 --> 00:05:11,600 Speaker 4: But at the same time, you know, especially when you're 97 00:05:11,600 --> 00:05:14,320 Speaker 4: thinking about politics and you're interested in politics like I am, 98 00:05:15,240 --> 00:05:19,560 Speaker 4: the material matters, you know, the political order matters. How 99 00:05:20,120 --> 00:05:25,279 Speaker 4: it's how it's organized, and what technologies are prevalent in 100 00:05:25,360 --> 00:05:27,720 Speaker 4: society really matter. And so if you're going to think 101 00:05:27,760 --> 00:05:32,200 Speaker 4: about society and making for a more just, you know, loving, peaceful, 102 00:05:32,480 --> 00:05:36,400 Speaker 4: Christian inspired society, you have to think about technology, and 103 00:05:36,720 --> 00:05:38,880 Speaker 4: you have to think about how to use that technology 104 00:05:39,120 --> 00:05:40,800 Speaker 4: for the common good. 105 00:05:41,160 --> 00:05:45,479 Speaker 1: Yeah, it's interesting you say that bit about the way 106 00:05:45,600 --> 00:05:48,599 Speaker 1: that making money and being kind of entrepreneurial often gets 107 00:05:48,640 --> 00:05:53,400 Speaker 1: pitted against faith, right. I saw this is It's weird 108 00:05:53,440 --> 00:05:56,080 Speaker 1: how the most obscure things you see online will spark 109 00:05:56,120 --> 00:05:58,279 Speaker 1: the most insight. I'm ninety nine percent sure of what 110 00:05:58,279 --> 00:06:00,680 Speaker 1: I'm about to read off as a YouTube comment, but 111 00:06:01,040 --> 00:06:04,920 Speaker 1: someone was put out this, this kind of maximum of 112 00:06:05,720 --> 00:06:08,400 Speaker 1: God doesn't want your skills, He just wants your obedience. 113 00:06:08,520 --> 00:06:11,560 Speaker 1: And that set me off in a way that there's 114 00:06:11,600 --> 00:06:13,560 Speaker 1: going to be a whole those of you subscribe to 115 00:06:13,560 --> 00:06:15,440 Speaker 1: my subs act, there's a whole You're probably going to 116 00:06:15,480 --> 00:06:17,839 Speaker 1: be cursed with a whole post of me complaining about that, 117 00:06:18,080 --> 00:06:21,240 Speaker 1: because to me, that's that's indicative of something that's very 118 00:06:21,279 --> 00:06:23,760 Speaker 1: deep in kind of our gen Z cultural mindset of 119 00:06:24,279 --> 00:06:28,560 Speaker 1: if we're trying to be truly spiritual, then the desire 120 00:06:28,600 --> 00:06:31,400 Speaker 1: to make money, the desire to be successful, the desire 121 00:06:31,400 --> 00:06:34,680 Speaker 1: to be ambitious, is somehow at odds with that. I 122 00:06:34,760 --> 00:06:36,200 Speaker 1: think it takes you. You have to kind of be 123 00:06:36,279 --> 00:06:39,480 Speaker 1: outside of consensus to say, well, now I'm a successful person, 124 00:06:39,520 --> 00:06:40,880 Speaker 1: I want to be good at my job. I think 125 00:06:40,920 --> 00:06:42,960 Speaker 1: I have a I think there I have an obligation 126 00:06:43,120 --> 00:06:45,400 Speaker 1: as a person of faith, especially as a Christian, to 127 00:06:45,480 --> 00:06:48,560 Speaker 1: be good at my job and for people who are 128 00:06:48,560 --> 00:06:52,839 Speaker 1: trying to do research, especially in fields like social science. 129 00:06:53,200 --> 00:06:56,760 Speaker 1: There's it's not as simple as you become a Christian, 130 00:06:56,760 --> 00:06:59,120 Speaker 1: you take faith seriously, and then you throw out all 131 00:06:59,160 --> 00:07:01,120 Speaker 1: this AI business, right, It's like no, no, no, no, no, 132 00:07:01,279 --> 00:07:04,479 Speaker 1: there's a pathway here to actually be really, really good 133 00:07:04,480 --> 00:07:09,039 Speaker 1: at your job that involves the use of these technologies 134 00:07:09,279 --> 00:07:12,520 Speaker 1: and reflexively having an engagement mindset, which is something that 135 00:07:12,600 --> 00:07:15,680 Speaker 1: Kevin and I have talked about before. Reflexively engaging as 136 00:07:15,720 --> 00:07:18,480 Speaker 1: opposed to reflexively kind of retreating. So talk to me 137 00:07:18,520 --> 00:07:21,000 Speaker 1: about that. I mean, you've worked with Kevin, obviously, you 138 00:07:21,520 --> 00:07:24,320 Speaker 1: have your own research interests. How do you use AI 139 00:07:24,480 --> 00:07:27,200 Speaker 1: in research kind of at a thirty thousand foot level, 140 00:07:27,480 --> 00:07:28,880 Speaker 1: What are some of the benefits? What are some of 141 00:07:28,880 --> 00:07:30,920 Speaker 1: the downsides to what you're seeing in terms of using 142 00:07:31,040 --> 00:07:32,560 Speaker 1: artificial intelligence in that way? 143 00:07:33,040 --> 00:07:36,880 Speaker 4: Yeah, no, I totally agree, And I think it's a 144 00:07:36,880 --> 00:07:40,800 Speaker 4: temptation yet to retreat from the world, especially a fallen 145 00:07:40,880 --> 00:07:46,240 Speaker 4: world one just like returning to your comments and to 146 00:07:46,320 --> 00:07:48,720 Speaker 4: not engage with it. But we can't afford to do that, 147 00:07:48,760 --> 00:07:50,520 Speaker 4: like you were saying, we have to engage with it. 148 00:07:50,560 --> 00:07:56,480 Speaker 4: We can't seed the entire world to people who may 149 00:07:56,520 --> 00:07:59,320 Speaker 4: not have the same understanding of human dignity that we do. 150 00:08:00,080 --> 00:08:02,080 Speaker 4: Our voice should be in that conversation. 151 00:08:02,280 --> 00:08:03,840 Speaker 1: They don't get to shape one hundred percent of the 152 00:08:03,840 --> 00:08:05,840 Speaker 1: future for one hundred percent of us. 153 00:08:06,360 --> 00:08:10,920 Speaker 4: Yes, exactly. And you know we're the salt, right, We're 154 00:08:10,960 --> 00:08:15,360 Speaker 4: the salt. So salt makes things better. We as Christians 155 00:08:15,400 --> 00:08:18,040 Speaker 4: can move around and engage with the world and make 156 00:08:18,120 --> 00:08:20,640 Speaker 4: what's in the world better and point out the good 157 00:08:20,640 --> 00:08:22,480 Speaker 4: things in the world and improve it and make it 158 00:08:22,520 --> 00:08:25,640 Speaker 4: better in light of the Gospel. So I think that's 159 00:08:26,080 --> 00:08:28,320 Speaker 4: an important vocation for us to remember. And I think 160 00:08:28,360 --> 00:08:33,440 Speaker 4: that includes research and thinking and writing, and what these 161 00:08:33,480 --> 00:08:36,680 Speaker 4: tools can do is really incredible. I don't think people 162 00:08:36,760 --> 00:08:42,079 Speaker 4: have realized the breadth of their capabilities in all types 163 00:08:42,120 --> 00:08:45,200 Speaker 4: of things. I think there's kind of a spectrum of 164 00:08:45,280 --> 00:08:48,880 Speaker 4: views on using AI for research and for intellectual tasks. 165 00:08:49,160 --> 00:08:51,760 Speaker 4: There's kind of like the minimalist view, which is like 166 00:08:51,800 --> 00:08:53,360 Speaker 4: you shouldn't use it, or if you do, you can 167 00:08:53,400 --> 00:08:57,160 Speaker 4: just kind of use it as Google, or you know, 168 00:08:57,200 --> 00:09:00,800 Speaker 4: there's a temptation that a lot of people in schools 169 00:09:00,800 --> 00:09:03,400 Speaker 4: all over the world and universities are falling into. And 170 00:09:03,480 --> 00:09:05,400 Speaker 4: you you mentioned this in one of your articles, that 171 00:09:05,679 --> 00:09:08,600 Speaker 4: you can just punt an assignment to AI and let 172 00:09:08,600 --> 00:09:11,000 Speaker 4: it do it for you. I mean, the funny extreme 173 00:09:11,120 --> 00:09:13,000 Speaker 4: version of this is the Claude Boys. Have you ever 174 00:09:13,040 --> 00:09:14,640 Speaker 4: heard of the claud Boys? 175 00:09:14,920 --> 00:09:16,600 Speaker 3: Oh, talk to me about the claud Boys. 176 00:09:17,040 --> 00:09:18,880 Speaker 4: I think it's so like this group of teenagers that 177 00:09:19,679 --> 00:09:22,800 Speaker 4: decided to let Claude the AI model like make every 178 00:09:22,800 --> 00:09:27,080 Speaker 4: single decision in their life and every single you know, 179 00:09:27,280 --> 00:09:29,320 Speaker 4: ask it what to say and what to do, and 180 00:09:29,640 --> 00:09:34,240 Speaker 4: they so like that's an extreme version of like a 181 00:09:34,320 --> 00:09:36,439 Speaker 4: maximal usage of AI. 182 00:09:36,520 --> 00:09:39,040 Speaker 1: But there's something going for them out of curiosity, I 183 00:09:39,040 --> 00:09:42,240 Speaker 1: can only wonder what happens when you when you punt everything. 184 00:09:42,280 --> 00:09:43,720 Speaker 1: So Claude for those of you who don't know, Claude 185 00:09:43,720 --> 00:09:45,559 Speaker 1: is one of the major AI models. What happened to 186 00:09:45,600 --> 00:09:47,480 Speaker 1: the Claud boys? What do they spend their time doing now? 187 00:09:47,880 --> 00:09:50,600 Speaker 1: Because they're outsourced. 188 00:09:50,360 --> 00:09:50,760 Speaker 3: You know what. 189 00:09:50,840 --> 00:09:52,959 Speaker 2: I have not checked in on them recently, but. 190 00:09:53,360 --> 00:09:55,400 Speaker 3: I'm gonna check in on that keep going. 191 00:09:55,559 --> 00:09:57,520 Speaker 4: I would like to see a brain scan. I would 192 00:09:57,559 --> 00:09:59,240 Speaker 4: try to like to see a brain scan of how 193 00:09:59,280 --> 00:09:59,760 Speaker 4: that's going. 194 00:09:59,760 --> 00:10:01,240 Speaker 3: But that's fascinating. 195 00:10:01,640 --> 00:10:06,040 Speaker 4: I think that basically the most important distinction when using. 196 00:10:05,840 --> 00:10:08,480 Speaker 2: AI is activity versus passivity. 197 00:10:08,920 --> 00:10:13,760 Speaker 4: If you're being passive and you're just accepting uncritically, it's 198 00:10:14,160 --> 00:10:18,319 Speaker 4: outputs without thinking, reflecting, judging, and even pushing back on 199 00:10:18,360 --> 00:10:20,320 Speaker 4: what the model gives you, which you should do, and 200 00:10:20,360 --> 00:10:22,920 Speaker 4: it actually helps with the task at hand, is to 201 00:10:23,000 --> 00:10:23,679 Speaker 4: push back. 202 00:10:23,480 --> 00:10:25,880 Speaker 2: On the model when you see something you don't really like. 203 00:10:26,559 --> 00:10:29,640 Speaker 4: If you're not doing that, then it's a problem and 204 00:10:29,679 --> 00:10:32,760 Speaker 4: actually your output's probably gonna be bad because AI cannot 205 00:10:32,800 --> 00:10:35,000 Speaker 4: judge things. It does not have taste, it does not 206 00:10:35,080 --> 00:10:38,960 Speaker 4: have feelings by which to judge its own outputs. You 207 00:10:39,000 --> 00:10:42,560 Speaker 4: as the human has to do that. And so I 208 00:10:42,559 --> 00:10:45,240 Speaker 4: think what's important when using AI is to always think 209 00:10:45,240 --> 00:10:49,000 Speaker 4: about it first, read about it first, and think through 210 00:10:49,040 --> 00:10:52,120 Speaker 4: your vision before you put it into the AI, and 211 00:10:52,200 --> 00:10:53,880 Speaker 4: then you can have AI help you develop that. 212 00:10:54,559 --> 00:10:55,600 Speaker 3: I think that's so crucial. 213 00:10:55,679 --> 00:10:57,640 Speaker 1: I mean, I've said it before, I mean I'll say 214 00:10:57,679 --> 00:10:59,280 Speaker 1: it again. I think it seems to me that the 215 00:10:59,320 --> 00:11:03,840 Speaker 1: people who are using AI the most judiciously understand very 216 00:11:03,920 --> 00:11:07,760 Speaker 1: clearly what whether it's an LM, whether it's kind of 217 00:11:07,760 --> 00:11:11,480 Speaker 1: a generative thing, what is it specifically the AI is 218 00:11:11,559 --> 00:11:12,760 Speaker 1: that I'm asking AI to do. 219 00:11:12,840 --> 00:11:13,120 Speaker 3: Right now? 220 00:11:13,160 --> 00:11:15,000 Speaker 1: Am I asking it to be a fact finder? Am 221 00:11:15,000 --> 00:11:17,199 Speaker 1: I asking it to fact check something? Am I asking 222 00:11:17,240 --> 00:11:19,480 Speaker 1: it to gather information? Or am I asking it to 223 00:11:19,520 --> 00:11:21,959 Speaker 1: make a call that requires discernment that it doesn't have, 224 00:11:22,720 --> 00:11:24,960 Speaker 1: which to your point about the cloud boys, which genuinely, 225 00:11:24,960 --> 00:11:26,880 Speaker 1: I didn't know about this, and I've I looked it 226 00:11:26,920 --> 00:11:30,800 Speaker 1: up while you were talking, and I'm now horrified and 227 00:11:30,880 --> 00:11:31,640 Speaker 1: also amused. 228 00:11:31,679 --> 00:11:32,080 Speaker 3: I don't know. 229 00:11:32,200 --> 00:11:37,520 Speaker 1: Strangely, I'm disappointed, but also it's whatever. There's a comparison 230 00:11:37,600 --> 00:11:40,320 Speaker 1: we can make there that I won't, but that I 231 00:11:40,320 --> 00:11:42,400 Speaker 1: think you do have to know that because the people, 232 00:11:42,480 --> 00:11:44,760 Speaker 1: it seems who are making the most games with AI 233 00:11:44,880 --> 00:11:49,040 Speaker 1: are using it for peak information generating, peak fact finding. 234 00:11:49,080 --> 00:11:51,600 Speaker 1: This sort of stuff that takes you hours and hours 235 00:11:51,600 --> 00:11:53,880 Speaker 1: to go through can now be done very quickly. I mean, 236 00:11:53,880 --> 00:11:56,280 Speaker 1: this happens. We have boy of research use it all 237 00:11:56,320 --> 00:11:59,240 Speaker 1: the time. The Copilot is fantastic for these sorts of things. 238 00:11:59,520 --> 00:12:01,559 Speaker 1: If you need an estimate on a model, if you 239 00:12:01,600 --> 00:12:04,960 Speaker 1: need an estimate on things that involve numbers, if you 240 00:12:05,040 --> 00:12:07,200 Speaker 1: need estimates on where to go to look for things, 241 00:12:07,240 --> 00:12:08,960 Speaker 1: it's great. If you need it to make a call 242 00:12:09,160 --> 00:12:11,520 Speaker 1: on how to talk to someone, how to talk to 243 00:12:11,559 --> 00:12:13,080 Speaker 1: a company how to make a call in kind of 244 00:12:13,080 --> 00:12:14,160 Speaker 1: corporate engagement world. 245 00:12:14,240 --> 00:12:14,840 Speaker 3: It can't do that. 246 00:12:14,920 --> 00:12:17,160 Speaker 1: It can't do that at all, Right, And it seems 247 00:12:17,160 --> 00:12:19,200 Speaker 1: to me that is because you're right that there is 248 00:12:19,200 --> 00:12:22,720 Speaker 1: a spectrum, Right, there's all the way from everything. AI 249 00:12:22,840 --> 00:12:24,920 Speaker 1: is demonic and we're not going to touch it at all, 250 00:12:25,240 --> 00:12:27,240 Speaker 1: and you should just kind of like put holy water 251 00:12:27,280 --> 00:12:29,120 Speaker 1: on your computer. Which I'm like that that will in 252 00:12:29,200 --> 00:12:31,360 Speaker 1: fact do something, but maybe just not what you want. 253 00:12:31,760 --> 00:12:35,839 Speaker 1: All the way to AGI artificial general intelligence is two 254 00:12:35,960 --> 00:12:38,679 Speaker 1: years away, and we need to all act as if 255 00:12:38,679 --> 00:12:41,080 Speaker 1: that is just inevitable, when in fact all the AGI 256 00:12:41,120 --> 00:12:43,600 Speaker 1: predictions have been kind of a lot of them are 257 00:12:43,679 --> 00:12:47,440 Speaker 1: way too optimistic. So there's some of the benefits. What 258 00:12:47,520 --> 00:12:51,079 Speaker 1: are some of the downsides that you've seen in how 259 00:12:51,120 --> 00:12:51,720 Speaker 1: you use AI? 260 00:12:53,679 --> 00:12:56,840 Speaker 4: Yeah, I just want to recommend real quick on what 261 00:12:56,880 --> 00:13:00,840 Speaker 4: you're saying. There's an article by Luke Burgess. He's the 262 00:13:00,840 --> 00:13:05,120 Speaker 4: founder of the Clooney Institute. He writes some very interesting things, 263 00:13:06,360 --> 00:13:09,600 Speaker 4: and he wrote an article called the Bowl Market in 264 00:13:09,640 --> 00:13:13,200 Speaker 4: the Humanities, which basically says what you're saying, Like, when 265 00:13:13,200 --> 00:13:18,400 Speaker 4: things involve numbers, when things involve technical skill, AI is 266 00:13:18,440 --> 00:13:21,760 Speaker 4: becoming very, very very good at that. But like we 267 00:13:21,800 --> 00:13:24,880 Speaker 4: were talking about things that have to do with judgment, 268 00:13:25,000 --> 00:13:28,280 Speaker 4: things that have to do with evaluating ends, evaluating goals, 269 00:13:28,360 --> 00:13:33,120 Speaker 4: which goals to pursue taste. That is still very much 270 00:13:33,160 --> 00:13:35,680 Speaker 4: in the human domain, and it's important to develop those 271 00:13:35,679 --> 00:13:38,320 Speaker 4: skills as AI is able to take care of the 272 00:13:38,400 --> 00:13:41,520 Speaker 4: things that, like you said, take last and lots of time. 273 00:13:42,120 --> 00:13:44,640 Speaker 1: Yeah, I feel like that's an easy argument to make 274 00:13:44,679 --> 00:13:46,599 Speaker 1: the gen Z people at some level, because I was 275 00:13:46,679 --> 00:13:48,200 Speaker 1: just kind of a window into and you can tell 276 00:13:48,240 --> 00:13:50,120 Speaker 1: me if this is relevant to your emotional experience. This 277 00:13:50,160 --> 00:13:52,440 Speaker 1: could just be me. I don't know, but to me, 278 00:13:52,600 --> 00:13:56,200 Speaker 1: especially when we went through COVID, right there was this 279 00:13:56,240 --> 00:13:58,520 Speaker 1: whole sense of there are a lot of experts who 280 00:13:58,559 --> 00:14:00,959 Speaker 1: are making a lot of recommendation is based on data, 281 00:14:01,559 --> 00:14:07,120 Speaker 1: but the actual moral arguments underneath are remarkably absent. And 282 00:14:07,160 --> 00:14:09,080 Speaker 1: I mean even outside of COVID, I mean, right now 283 00:14:09,120 --> 00:14:11,640 Speaker 1: we have there's all these announcements coming out from SpaceX 284 00:14:11,640 --> 00:14:15,880 Speaker 1: talking about building a lunar self sustaining city. Building the 285 00:14:15,880 --> 00:14:18,480 Speaker 1: math to get to a lunar self sustained sustaining city 286 00:14:19,120 --> 00:14:21,440 Speaker 1: is one thing, and it's an area which presumably AI 287 00:14:21,560 --> 00:14:24,920 Speaker 1: is very useful. The question of why it matters that 288 00:14:24,960 --> 00:14:28,040 Speaker 1: we are expanding and taking dominion on the cosmos is 289 00:14:28,120 --> 00:14:32,480 Speaker 1: not something that the chat, GPT or a copilot can 290 00:14:32,520 --> 00:14:33,160 Speaker 1: feed you in the. 291 00:14:33,160 --> 00:14:36,080 Speaker 2: Same way, right right exactly. 292 00:14:36,400 --> 00:14:40,480 Speaker 4: And I think gen Z uh to your point, I 293 00:14:40,520 --> 00:14:44,960 Speaker 4: think gen Z has experienced technology enough. We're familiar with it. 294 00:14:45,040 --> 00:14:49,440 Speaker 4: We're digitally native, as you've put it, and we've seen 295 00:14:49,920 --> 00:14:54,440 Speaker 4: kind of its negative downsides. It's it's it's problems. And 296 00:14:54,520 --> 00:14:57,560 Speaker 4: we as gen Z people, we have a pension for 297 00:14:57,720 --> 00:15:00,120 Speaker 4: being ironic, you know, for being pessimistic for me and 298 00:15:00,240 --> 00:15:04,520 Speaker 4: a joke out of any out of everything, which is hilarious. 299 00:15:05,120 --> 00:15:09,880 Speaker 4: But what we lack is, like you said, like is 300 00:15:09,920 --> 00:15:12,160 Speaker 4: it worth it to do this thing? Or what should 301 00:15:12,240 --> 00:15:14,400 Speaker 4: what should we be doing? You know, what is the 302 00:15:14,440 --> 00:15:17,760 Speaker 4: positive vision for how we should use AI? And I 303 00:15:17,800 --> 00:15:20,400 Speaker 4: think that's something we could really use. I mean, like 304 00:15:20,680 --> 00:15:23,880 Speaker 4: you know, on the downsides of you know, AI and research, 305 00:15:23,920 --> 00:15:25,720 Speaker 4: I think a lot of gen Z people see it. 306 00:15:27,000 --> 00:15:30,160 Speaker 4: You know, it's gonna make a stupid uh, which might 307 00:15:30,200 --> 00:15:36,400 Speaker 4: be true to some extent, but you know for some yeah, uh, 308 00:15:36,560 --> 00:15:40,960 Speaker 4: But there is opportunity here, there's opportunity, and we should 309 00:15:40,960 --> 00:15:45,120 Speaker 4: start developing positive visions of what a flourishing society with 310 00:15:45,240 --> 00:15:48,880 Speaker 4: AI looks like, rather than just kind of what's the 311 00:15:49,280 --> 00:15:50,720 Speaker 4: what's the what's the phrase being a. 312 00:15:51,160 --> 00:15:56,120 Speaker 1: Doom doom, don't don't don't succumb to dumerism. 313 00:15:55,880 --> 00:15:57,000 Speaker 2: Don't don't don't be a duomer. 314 00:15:57,120 --> 00:15:59,680 Speaker 1: Yeah, yeah, one hundred per I think that point about 315 00:15:59,680 --> 00:16:03,480 Speaker 1: passing is right on Thomas, because there's this because gen 316 00:16:03,560 --> 00:16:06,800 Speaker 1: Z is a very pessimistic generation. And I used to 317 00:16:06,800 --> 00:16:08,520 Speaker 1: think it was just kind of a temperamental thing that 318 00:16:08,560 --> 00:16:15,040 Speaker 1: was harmless. Now I'm realizing pessimism is the opposite of ambition, right. 319 00:16:15,080 --> 00:16:19,280 Speaker 1: Pessimism is the opposite of having a really creational mindset, right, 320 00:16:19,280 --> 00:16:23,160 Speaker 1: because when you have a creational mindset, you can basically say, Okay, 321 00:16:23,320 --> 00:16:25,320 Speaker 1: I have a mandate from God to create things and 322 00:16:25,960 --> 00:16:30,600 Speaker 1: exert dominion whatever sphere I exist in, and so the 323 00:16:30,680 --> 00:16:33,000 Speaker 1: endeavors I take to get there are what I should 324 00:16:33,040 --> 00:16:36,400 Speaker 1: be doing. And pessimism is I mean, it's that Totien quote, right, 325 00:16:36,440 --> 00:16:38,840 Speaker 1: Despair is for those who see the end beyond all 326 00:16:39,000 --> 00:16:41,920 Speaker 1: doubt or whatever. I'm definitely butchering the phrasing, or maybe 327 00:16:41,920 --> 00:16:44,280 Speaker 1: I'm not, who knows, but I don't know if you're 328 00:16:44,280 --> 00:16:46,440 Speaker 1: a pessimist. You're like, well, none of it's gonna work. 329 00:16:46,560 --> 00:16:49,920 Speaker 1: It's all terrible. This isn't even worth our time. And 330 00:16:50,440 --> 00:16:54,000 Speaker 1: the builder right that, the constructive person, the wise person, 331 00:16:54,040 --> 00:16:56,040 Speaker 1: is able to look at that and say no, no, 332 00:16:56,080 --> 00:16:59,280 Speaker 1: there's a gradation of the sum of human effort between 333 00:16:59,280 --> 00:17:01,840 Speaker 1: worthwhile effort. It's a non worthwhile efforts. And I refuse 334 00:17:01,880 --> 00:17:04,119 Speaker 1: to say that all of them are the same. And 335 00:17:04,160 --> 00:17:05,760 Speaker 1: so the building mindset. I want to go to this 336 00:17:05,800 --> 00:17:09,400 Speaker 1: piece that you've written at Religion and Liberty Online entitled 337 00:17:09,440 --> 00:17:15,040 Speaker 1: AI and the Return of Architectonic Labor, seems to offer 338 00:17:15,560 --> 00:17:17,879 Speaker 1: part of that vision. I want to read a little 339 00:17:17,880 --> 00:17:19,600 Speaker 1: bit from it right now, and then I'm going to 340 00:17:19,640 --> 00:17:21,159 Speaker 1: ask you what in the world you mean by all 341 00:17:21,200 --> 00:17:24,439 Speaker 1: of this, starting with what is architectonic? But this is 342 00:17:24,440 --> 00:17:27,720 Speaker 1: what you've written, This opportunity is genuine, referring to AI, 343 00:17:28,200 --> 00:17:31,320 Speaker 1: what once required years of specialized training now lies within 344 00:17:31,400 --> 00:17:34,080 Speaker 1: reach of anyone willing to learn how to direct these 345 00:17:34,080 --> 00:17:37,160 Speaker 1: new instruments. The deeper question is whether we will build 346 00:17:37,200 --> 00:17:40,879 Speaker 1: economic institutions that encourage people to use these tools for 347 00:17:41,000 --> 00:17:47,119 Speaker 1: genuine creation rather than passive consumption. So, first of all, 348 00:17:47,320 --> 00:17:48,639 Speaker 1: what's architectonic labor. 349 00:17:49,960 --> 00:17:53,399 Speaker 4: Yeah, so I came across that word while reading the 350 00:17:53,480 --> 00:17:57,920 Speaker 4: last chapter of a book by a French political philosopher 351 00:17:58,000 --> 00:18:00,920 Speaker 4: named Eve Simone called Philosophy of Demic Credit Government, where 352 00:18:00,920 --> 00:18:05,920 Speaker 4: he's basically evaluating the effect of industrialization on labor. And 353 00:18:06,240 --> 00:18:09,080 Speaker 4: he says that the hyper specialization, and this is an 354 00:18:09,160 --> 00:18:11,919 Speaker 4: argument that's been talked about before, like Adam Smith, who 355 00:18:11,960 --> 00:18:15,399 Speaker 4: I mentioned in the beginning of the article, where while 356 00:18:16,160 --> 00:18:20,600 Speaker 4: the industrial age has led to incredible material wealth, it 357 00:18:20,640 --> 00:18:23,439 Speaker 4: put a lot of people in these hyper specialized jobs 358 00:18:24,359 --> 00:18:29,480 Speaker 4: where they're doing very very menial, very specific, small repetitive tasks, 359 00:18:30,720 --> 00:18:35,680 Speaker 4: and they're not participating in governing or planning a whole. 360 00:18:36,200 --> 00:18:39,480 Speaker 4: And so the positive example of that that Simone uses 361 00:18:39,520 --> 00:18:43,520 Speaker 4: is like the family farm, where the farmer plans out 362 00:18:43,600 --> 00:18:46,840 Speaker 4: the crops, what's planted when where in the plot of 363 00:18:46,920 --> 00:18:50,959 Speaker 4: land he reads the seasons and he tracks the growth 364 00:18:51,080 --> 00:18:53,520 Speaker 4: and harvest of the crops from beginning to end throughout 365 00:18:53,560 --> 00:18:57,040 Speaker 4: all of its phases. And that's kind of lost in industrialization. 366 00:18:57,440 --> 00:19:01,000 Speaker 4: And he uses the word architectom like function, the phrase 367 00:19:01,080 --> 00:19:05,800 Speaker 4: architectonic function from Aristotle to describe that. And I thought, 368 00:19:05,840 --> 00:19:07,440 Speaker 4: first of all, that was just a really cool word. 369 00:19:08,560 --> 00:19:11,720 Speaker 1: Oh yeah, it rolls real nice off the tongue, architectonic. 370 00:19:11,760 --> 00:19:14,320 Speaker 4: It's great, Yeah, and I thought, you know, and it's 371 00:19:14,400 --> 00:19:16,600 Speaker 4: it's also kind of intuitive, you know, because you can imagine, 372 00:19:16,600 --> 00:19:20,680 Speaker 4: like an architect right, designs plans, provides a vision. 373 00:19:22,800 --> 00:19:24,840 Speaker 2: And so I think again, that's kind of. 374 00:19:24,800 --> 00:19:29,480 Speaker 4: The difference maker between whether people will flourish or flounder 375 00:19:29,520 --> 00:19:33,320 Speaker 4: with AI is are they being active, are they planning, 376 00:19:33,440 --> 00:19:34,080 Speaker 4: are they thinking? 377 00:19:34,119 --> 00:19:36,560 Speaker 2: Are they providing vision? Are they reflecting? 378 00:19:36,960 --> 00:19:40,440 Speaker 4: Or are they just passively consuming whatever it is that 379 00:19:40,480 --> 00:19:44,520 Speaker 4: AI produces, which unfortunately is a trap we've fallen into 380 00:19:44,600 --> 00:19:49,040 Speaker 4: with the past technologies that we've come up with. You know, 381 00:19:49,080 --> 00:19:52,280 Speaker 4: the TV is a very passive technology. We just kind 382 00:19:52,280 --> 00:19:55,640 Speaker 4: of sit there and watch it. Radio was too, and 383 00:19:56,440 --> 00:19:59,639 Speaker 4: same thing with social media TikTok and Facebook and everything. 384 00:20:00,200 --> 00:20:02,440 Speaker 1: Yeah, what's interesting you mentioned first of all, I guess, 385 00:20:02,480 --> 00:20:04,720 Speaker 1: just a thought on the word architectonic. I mean, presumably 386 00:20:04,760 --> 00:20:07,120 Speaker 1: that's a Greek word, and part of that word is tecton, 387 00:20:07,119 --> 00:20:10,600 Speaker 1: which is a term for like a skilled artisan. And ironically, 388 00:20:10,760 --> 00:20:13,119 Speaker 1: and for those of you who are listening who know 389 00:20:13,160 --> 00:20:15,679 Speaker 1: about Jerry Boyer's book The Maker Versus the Takers, You've 390 00:20:15,680 --> 00:20:18,119 Speaker 1: probably heard that term because Jesus was a tecton, right, 391 00:20:18,200 --> 00:20:20,520 Speaker 1: Jesus and his father Joseph were tectons. There are skilled 392 00:20:20,600 --> 00:20:23,480 Speaker 1: artisans in that way, because what you're describing is this 393 00:20:23,520 --> 00:20:26,320 Speaker 1: world in which you're not just putting a box in 394 00:20:26,359 --> 00:20:29,960 Speaker 1: a widget at point x right. You're actually overseeing the 395 00:20:29,960 --> 00:20:32,199 Speaker 1: creation of something that's more holistic, and you see it 396 00:20:32,240 --> 00:20:35,000 Speaker 1: through more, you see it through more iterations of what 397 00:20:35,080 --> 00:20:39,200 Speaker 1: it eventually becomes. And there's an element to which obviously 398 00:20:39,240 --> 00:20:42,199 Speaker 1: that occurs at scale in a kind of in a 399 00:20:42,320 --> 00:20:45,119 Speaker 1: really broad free enterprise system. You obviously don't see all 400 00:20:45,160 --> 00:20:47,440 Speaker 1: parts of that happening in your own backyard or even 401 00:20:47,480 --> 00:20:48,840 Speaker 1: in your own house in the way it kind of 402 00:20:49,160 --> 00:20:52,359 Speaker 1: would have worked pre Industrial Revolution. But with AI and 403 00:20:52,720 --> 00:20:54,440 Speaker 1: the example you mentioned I think is really good, which 404 00:20:54,480 --> 00:20:56,320 Speaker 1: is vibe coding, and vibe coding for those of you 405 00:20:56,320 --> 00:20:57,919 Speaker 1: who don't know, for those of you who do know, 406 00:20:57,960 --> 00:20:59,639 Speaker 1: this is going to be a really annoying explanation, But 407 00:21:00,160 --> 00:21:02,760 Speaker 1: with me, vibe coding is basically this thing where you 408 00:21:02,800 --> 00:21:05,359 Speaker 1: tell Claude code this thing, and then it built, and 409 00:21:05,400 --> 00:21:10,160 Speaker 1: then Claude codes that thing which has been has had 410 00:21:10,160 --> 00:21:13,119 Speaker 1: some disastrous moments like with the t app that crashed 411 00:21:13,160 --> 00:21:16,719 Speaker 1: because people Vibe coded it with no security functions. But 412 00:21:16,760 --> 00:21:19,040 Speaker 1: the thing that AI does, you're arguing, and seems to 413 00:21:19,040 --> 00:21:23,120 Speaker 1: me correct, is AI allows you to actually control much 414 00:21:23,160 --> 00:21:25,639 Speaker 1: more of the actual creative process. You don't have to 415 00:21:25,680 --> 00:21:28,880 Speaker 1: outsource things to people who may or may not share 416 00:21:28,880 --> 00:21:30,880 Speaker 1: your values nearly as much because you have the ability 417 00:21:30,960 --> 00:21:34,280 Speaker 1: to do it in house, which is interesting to me. 418 00:21:35,280 --> 00:21:41,280 Speaker 4: Right. Kevin Value uses this kind of metaphor or phrase 419 00:21:42,040 --> 00:21:47,280 Speaker 4: that AI it democratizes intelligence, it lets people. You know, 420 00:21:47,320 --> 00:21:51,240 Speaker 4: for example, and I wanted to be an entrepreneur, I 421 00:21:51,680 --> 00:21:54,240 Speaker 4: kept thinking, oh, I need to find a technical co founder, 422 00:21:54,720 --> 00:21:57,600 Speaker 4: you know, somebody who knows how to code, because I 423 00:21:57,600 --> 00:21:59,440 Speaker 4: don't know how to code, but I have these ideas 424 00:21:59,440 --> 00:22:01,520 Speaker 4: and I want to make them happen, you know. 425 00:22:01,480 --> 00:22:05,920 Speaker 3: And you can build a technical co founder right right. 426 00:22:06,359 --> 00:22:08,760 Speaker 4: And you know that's also one of the risks, is 427 00:22:08,800 --> 00:22:13,040 Speaker 4: that you can stay in your room by yourself Vibe 428 00:22:13,080 --> 00:22:16,240 Speaker 4: coding all day, building apps and not speaking to other people, 429 00:22:16,240 --> 00:22:19,280 Speaker 4: and it can be this very individualistic endeavor. And you 430 00:22:19,359 --> 00:22:21,000 Speaker 4: know that's one of the risks of AI too, is 431 00:22:21,000 --> 00:22:25,320 Speaker 4: this kind of individualism, which is why I bring up 432 00:22:25,320 --> 00:22:30,879 Speaker 4: the idea of economic institutions and designing them for creative 433 00:22:31,080 --> 00:22:34,800 Speaker 4: but also cooperative labor. I think in a world in 434 00:22:34,840 --> 00:22:38,800 Speaker 4: the future where AI is just you know, the world 435 00:22:38,840 --> 00:22:41,560 Speaker 4: is saturated with AI and AI agents doing all different 436 00:22:41,560 --> 00:22:44,720 Speaker 4: types of things, and the productive benefits have gotten to 437 00:22:44,760 --> 00:22:47,600 Speaker 4: the point where perhaps we live in a world where 438 00:22:48,440 --> 00:22:50,639 Speaker 4: people don't have to work nearly as much as they 439 00:22:50,720 --> 00:22:56,040 Speaker 4: used to in order to survive and thrive materially. You know, 440 00:22:56,080 --> 00:22:59,359 Speaker 4: at that point, why would you go to work, especially 441 00:22:59,600 --> 00:23:01,760 Speaker 4: if you're If you would go to a job where 442 00:23:01,800 --> 00:23:04,160 Speaker 4: you're just doing some repetitive thing over and over again, 443 00:23:04,600 --> 00:23:09,040 Speaker 4: it would seem that the corporation or the economic institution 444 00:23:09,119 --> 00:23:11,200 Speaker 4: you're working at would need to give you some share 445 00:23:11,240 --> 00:23:14,359 Speaker 4: in the decision making or in some share in the 446 00:23:15,320 --> 00:23:18,040 Speaker 4: governance of the institution to get you out of bed 447 00:23:18,080 --> 00:23:21,800 Speaker 4: in the day, you know, to go to work. And 448 00:23:21,840 --> 00:23:25,560 Speaker 4: so I think all these factors kind of go into 449 00:23:25,600 --> 00:23:28,680 Speaker 4: it of how we design our society with AI. 450 00:23:29,240 --> 00:23:31,879 Speaker 1: Yeah, I think that's very profound. I mean, you mentioned 451 00:23:31,880 --> 00:23:35,760 Speaker 1: this bit here about we mentioned the thing about genuine 452 00:23:35,760 --> 00:23:39,160 Speaker 1: creation versus past consumption before right, you ask these two questions, 453 00:23:39,160 --> 00:23:42,800 Speaker 1: will enterprises be structured to give workers real agency, and 454 00:23:42,920 --> 00:23:46,600 Speaker 1: will people be encouraged to govern something meaningful in their lives, 455 00:23:47,240 --> 00:23:50,280 Speaker 1: not merely to consume and obey. If we actively pursue 456 00:23:50,280 --> 00:23:51,840 Speaker 1: these goals, we can live in a world of both 457 00:23:51,880 --> 00:23:55,720 Speaker 1: meaningful work and material prosperity. I think that's I think 458 00:23:55,760 --> 00:24:00,199 Speaker 1: that's really really quite profound. It's the worry of that 459 00:24:00,240 --> 00:24:01,840 Speaker 1: a lot of people who are kind of anti AI 460 00:24:02,000 --> 00:24:06,200 Speaker 1: have is. Although I will say I haven't heard that 461 00:24:06,280 --> 00:24:09,520 Speaker 1: the critique you just made of if you train, if 462 00:24:09,520 --> 00:24:11,600 Speaker 1: people learn to build the things that they want to 463 00:24:11,600 --> 00:24:14,240 Speaker 1: build with AI, without any help, they're going to be 464 00:24:15,520 --> 00:24:17,640 Speaker 1: you can just sit in your bedroom and just recreate 465 00:24:17,680 --> 00:24:20,000 Speaker 1: the world that way. I haven't heard that critique nearly 466 00:24:20,040 --> 00:24:23,280 Speaker 1: as much as I've heard the kind of more base 467 00:24:23,320 --> 00:24:24,879 Speaker 1: case of it, which is, well, if you spend all 468 00:24:24,960 --> 00:24:28,480 Speaker 1: your time talking to some AI girlfriend. I think those 469 00:24:28,480 --> 00:24:32,080 Speaker 1: are two different versions of the same critique. I don't know, 470 00:24:32,200 --> 00:24:37,560 Speaker 1: but that is fundamentally the dilemma of every creator, though, 471 00:24:37,600 --> 00:24:39,400 Speaker 1: isn't It is? Do you want to spend all your 472 00:24:39,440 --> 00:24:42,640 Speaker 1: time creating and building things that are meaningful, and how 473 00:24:42,640 --> 00:24:45,600 Speaker 1: do you balance that with the necessity to, like, you know, 474 00:24:45,880 --> 00:24:50,000 Speaker 1: go outside and be in community with other people. And 475 00:24:51,440 --> 00:24:55,159 Speaker 1: the other point of that is, if you're genuinely taking 476 00:24:55,160 --> 00:24:58,159 Speaker 1: a greater creative role in the things that you're building, 477 00:24:59,480 --> 00:25:03,520 Speaker 1: one that has profound benefits for you mentally and should 478 00:25:03,560 --> 00:25:05,520 Speaker 1: be in some way helps alleviate some of those mental 479 00:25:05,520 --> 00:25:09,280 Speaker 1: health issues in its own way. But also it's a 480 00:25:09,320 --> 00:25:12,080 Speaker 1: good thing for people to be taking a greater creational 481 00:25:12,160 --> 00:25:14,960 Speaker 1: role in the world, right, because that's what we're called 482 00:25:15,000 --> 00:25:17,280 Speaker 1: to do, right. I mean, you're an actor right now. 483 00:25:17,320 --> 00:25:20,720 Speaker 1: I interned at acting in twenty three. We both have 484 00:25:21,080 --> 00:25:23,280 Speaker 1: interfaced with folks like David Bonson, who you're talking about 485 00:25:23,280 --> 00:25:26,199 Speaker 1: the necessity of meaningful work, especially for the worker, right 486 00:25:26,200 --> 00:25:29,760 Speaker 1: because God made work for the worker. I think this 487 00:25:29,840 --> 00:25:33,760 Speaker 1: is a brilliant new opportunity that AI offers. 488 00:25:34,040 --> 00:25:34,200 Speaker 3: Two. 489 00:25:34,840 --> 00:25:37,800 Speaker 1: Yes, it creates a world where there is the possibility 490 00:25:37,800 --> 00:25:41,600 Speaker 1: for greater destruction because every kind of great I don't 491 00:25:41,640 --> 00:25:43,640 Speaker 1: want to say greatly before it because that's a horrible term. 492 00:25:43,640 --> 00:25:45,760 Speaker 3: It's been ruined by history for obvious reasons. 493 00:25:46,040 --> 00:25:50,199 Speaker 1: But this is a great new opportunity for Yes, you 494 00:25:50,200 --> 00:25:52,760 Speaker 1: can do bad things with AI, but also your creative power, 495 00:25:52,760 --> 00:25:55,240 Speaker 1: your ability to co create with God as it were 496 00:25:56,280 --> 00:25:59,000 Speaker 1: and not as it were, just as it is is 497 00:25:59,160 --> 00:26:04,240 Speaker 1: meaningfully built, is meaningfully greater, it's meaningfully much much larger. 498 00:26:04,880 --> 00:26:09,200 Speaker 1: And I don't know. I'm reminded of that Wendell Berry essay, 499 00:26:09,359 --> 00:26:11,840 Speaker 1: and everyone who's heard the last podcast episode we did 500 00:26:11,880 --> 00:26:13,520 Speaker 1: where I talked about Wendell Barry knows that this is 501 00:26:13,560 --> 00:26:16,280 Speaker 1: not a compliment. But he has this essay on the computer, 502 00:26:16,840 --> 00:26:18,920 Speaker 1: which is, in my mind, just one of the foolish, 503 00:26:18,960 --> 00:26:21,560 Speaker 1: most foolish things ever written, where he basically says, I 504 00:26:21,560 --> 00:26:24,040 Speaker 1: don't want to use a computer because my view of 505 00:26:24,040 --> 00:26:28,479 Speaker 1: whether technology is good is it uses less energy than 506 00:26:28,520 --> 00:26:31,719 Speaker 1: the thing it replaces. And I'm like, well, that's kind 507 00:26:31,760 --> 00:26:34,679 Speaker 1: of dumb, because what if what if it produces more 508 00:26:34,720 --> 00:26:37,560 Speaker 1: than the thing he replaced than it replaces, then obviously 509 00:26:37,600 --> 00:26:39,720 Speaker 1: it's going to take up more energy. And Wendell Berry 510 00:26:40,160 --> 00:26:42,560 Speaker 1: famously didn't really get that, but that's its own issue. 511 00:26:43,560 --> 00:26:46,119 Speaker 1: We're kind of getting into We had a couple of 512 00:26:46,160 --> 00:26:49,160 Speaker 1: years in the twenty twenties where it was very where 513 00:26:49,720 --> 00:26:52,000 Speaker 1: early adopters jumped in on AI. Now we're kind of 514 00:26:52,040 --> 00:26:53,920 Speaker 1: it feels like we're getting into a place where consumer 515 00:26:53,960 --> 00:26:55,919 Speaker 1: sentiments are kind of shifting. There's a lot of public 516 00:26:55,960 --> 00:26:59,719 Speaker 1: concern about what AI can or can't do without asking 517 00:26:59,800 --> 00:27:02,719 Speaker 1: you for clairvoyance. I guess where do you think we're going, 518 00:27:03,400 --> 00:27:05,560 Speaker 1: especially our generation, right, you and I who are who 519 00:27:05,560 --> 00:27:07,320 Speaker 1: are like kind of gen Z people. Where do you 520 00:27:07,359 --> 00:27:08,840 Speaker 1: think gen Z is going to go with AI in 521 00:27:08,880 --> 00:27:10,199 Speaker 1: the next couple of years. Do you think we're going 522 00:27:10,240 --> 00:27:14,320 Speaker 1: to regress back to actually I don't want Jack GPT 523 00:27:14,440 --> 00:27:16,399 Speaker 1: in my life at all, or do you think we're 524 00:27:16,440 --> 00:27:18,720 Speaker 1: going to go into Actually there is a meaningful balance 525 00:27:18,720 --> 00:27:21,600 Speaker 1: to be struck here between being totally tech free and 526 00:27:21,760 --> 00:27:24,040 Speaker 1: spending all your time with AI agents you spent you 527 00:27:24,160 --> 00:27:24,959 Speaker 1: created to keep you. 528 00:27:26,200 --> 00:27:28,159 Speaker 4: I know we've been talking about, you know, gen Z 529 00:27:28,280 --> 00:27:30,320 Speaker 4: needs to be more optimistic. 530 00:27:30,920 --> 00:27:34,399 Speaker 1: And now we're about to all of that. Yeah, but 531 00:27:34,520 --> 00:27:35,960 Speaker 1: no talk to me about that. We can talk about 532 00:27:35,960 --> 00:27:37,199 Speaker 1: maybe how to stave off some of that. 533 00:27:37,880 --> 00:27:39,200 Speaker 2: Yes, yeah, I think. 534 00:27:40,880 --> 00:27:45,920 Speaker 4: You know, we we have seen brain rot enter every 535 00:27:46,000 --> 00:27:48,760 Speaker 4: single look and cranny of our lives. I mean you 536 00:27:48,840 --> 00:27:50,719 Speaker 4: just go, like on the New York City subway and 537 00:27:50,720 --> 00:27:52,680 Speaker 4: see how many people are looking at their phones, are 538 00:27:52,720 --> 00:27:55,480 Speaker 4: scrolling through whatever you're like. 539 00:27:55,560 --> 00:27:58,880 Speaker 1: I think everybody's not building apps with Claude on the subway. Yeah, 540 00:27:58,880 --> 00:28:00,879 Speaker 1: I don't think puppy videos. 541 00:28:00,760 --> 00:28:02,679 Speaker 2: But more and more people might start doing that. 542 00:28:02,800 --> 00:28:04,919 Speaker 4: But anyway, but you know, I think we've all had 543 00:28:04,920 --> 00:28:07,280 Speaker 4: those dystopian moments where like we're on our phone and 544 00:28:07,280 --> 00:28:09,480 Speaker 4: we look up and we see that everybody else is 545 00:28:09,520 --> 00:28:12,080 Speaker 4: on their phone and it's like, WHOA, how do we 546 00:28:12,119 --> 00:28:15,400 Speaker 4: get here? That is weird? And it seems like AI 547 00:28:15,520 --> 00:28:20,080 Speaker 4: is just going to it's going to inflate the capacity 548 00:28:20,160 --> 00:28:23,119 Speaker 4: for that to happen. I think there's going to be 549 00:28:23,200 --> 00:28:25,280 Speaker 4: like hyper brain rot available to us. 550 00:28:25,640 --> 00:28:26,560 Speaker 2: And you can. 551 00:28:26,440 --> 00:28:29,560 Speaker 4: See that in the in what the models and what 552 00:28:29,600 --> 00:28:32,560 Speaker 4: the AI companies are building now and the differences between them, 553 00:28:33,040 --> 00:28:37,080 Speaker 4: and you can see open AI and grock seem to 554 00:28:37,160 --> 00:28:41,200 Speaker 4: not have a problem with producing hyper brain rot and 555 00:28:41,280 --> 00:28:43,600 Speaker 4: letting people use AI for hyper brain rot as long 556 00:28:43,800 --> 00:28:47,320 Speaker 4: as long as it gets them to use their product. Right, 557 00:28:47,360 --> 00:28:50,880 Speaker 4: You've seen both companies express openness. I think, you know, 558 00:28:50,960 --> 00:28:54,480 Speaker 4: grockets you can it is already happening to allow for 559 00:28:54,520 --> 00:28:58,400 Speaker 4: people to make pornography, uh using their AI like that 560 00:28:58,480 --> 00:29:03,520 Speaker 4: is that is happening. Groc has like these anime egirl 561 00:29:03,840 --> 00:29:06,840 Speaker 4: you know, girlfriends that you could talk to on there, 562 00:29:06,880 --> 00:29:11,600 Speaker 4: and so it's already happening. And I think we can 563 00:29:11,640 --> 00:29:14,520 Speaker 4: avoid that. And I think a counter example, like a 564 00:29:14,520 --> 00:29:17,920 Speaker 4: good example of a way that an AI company is 565 00:29:17,960 --> 00:29:21,320 Speaker 4: actually trying to be moral about this, trying to put 566 00:29:21,400 --> 00:29:24,520 Speaker 4: human flourishing at the center, and that gives us hope 567 00:29:24,560 --> 00:29:27,000 Speaker 4: and that, you know, it makes me grateful to live 568 00:29:27,000 --> 00:29:29,280 Speaker 4: in a kind of free enterprise system where there are 569 00:29:29,320 --> 00:29:33,240 Speaker 4: options here, where there's competition. Anthropic is doing a much 570 00:29:33,240 --> 00:29:38,960 Speaker 4: better job at reflecting morally on how they want their 571 00:29:40,200 --> 00:29:42,600 Speaker 4: product to be used. Like it's not perfect obviously from 572 00:29:42,640 --> 00:29:44,920 Speaker 4: a Christian worldview, for example, you know, for example, but 573 00:29:45,240 --> 00:29:50,520 Speaker 4: they're thinking about how can we make AI put human 574 00:29:50,600 --> 00:29:54,880 Speaker 4: autonomy in freedom at the center. How can we try 575 00:29:55,040 --> 00:29:57,720 Speaker 4: and make the way that AI behaves in the outputs 576 00:29:57,760 --> 00:30:01,080 Speaker 4: it has, you know, reflect certain version choose or values 577 00:30:01,240 --> 00:30:04,720 Speaker 4: that we have. If you look at the front page 578 00:30:04,720 --> 00:30:06,880 Speaker 4: of the claud Constitution, which is kind of like they're 579 00:30:06,920 --> 00:30:11,600 Speaker 4: guiding moral document. I encourage people to check it out 580 00:30:11,600 --> 00:30:14,520 Speaker 4: and read it. They hired a full time philosopher to 581 00:30:14,640 --> 00:30:16,600 Speaker 4: think through this whole thing, which is an insane amount 582 00:30:16,640 --> 00:30:18,280 Speaker 4: of power if you think about it. But if you 583 00:30:18,280 --> 00:30:23,440 Speaker 4: look at the acknowledgments, there's all different types of philosophers 584 00:30:23,440 --> 00:30:26,640 Speaker 4: and engineers and people on there. But and this is 585 00:30:27,360 --> 00:30:30,480 Speaker 4: consistent with something somebody told me a spiritual director in 586 00:30:30,560 --> 00:30:34,400 Speaker 4: Silicon Valley. You have two members of the Catholic clergy 587 00:30:35,560 --> 00:30:39,960 Speaker 4: who contributed to thinking through this document, you know, showing 588 00:30:40,000 --> 00:30:45,160 Speaker 4: like they're open to ethical perspectives, moral perspectives, metaphysical perspectives, 589 00:30:46,240 --> 00:30:47,720 Speaker 4: and how to think through how to use AI. So 590 00:30:47,760 --> 00:30:50,920 Speaker 4: I think there's hope here and what Christians need to 591 00:30:50,960 --> 00:30:55,880 Speaker 4: do is engage with it. Christians need to learn these tools, 592 00:30:56,000 --> 00:30:59,960 Speaker 4: use these tools right rooted in the spirit and prayer 593 00:31:00,400 --> 00:31:04,240 Speaker 4: so that we don't get caught up in bad stuff 594 00:31:04,760 --> 00:31:07,760 Speaker 4: or in AI psychosis or anything, but engage with them 595 00:31:07,760 --> 00:31:10,040 Speaker 4: and seek how can we contribute to the conversation. 596 00:31:10,160 --> 00:31:11,840 Speaker 2: And I think there's a lot of opportunity there. 597 00:31:12,320 --> 00:31:14,640 Speaker 1: I think that's great. I love that you that you 598 00:31:14,720 --> 00:31:17,120 Speaker 1: touched on being in the spirit and prayer. I mean, 599 00:31:17,160 --> 00:31:21,040 Speaker 1: the reality is with every technological advance, there's always the 600 00:31:21,040 --> 00:31:24,280 Speaker 1: possibility for abuse, and the possibility for self inflicted abuse. 601 00:31:24,320 --> 00:31:27,440 Speaker 1: Right that happens to our minds and our souls. But 602 00:31:28,200 --> 00:31:30,840 Speaker 1: the spiritual disciplines exist for a reason. The spiritual disciplines 603 00:31:30,880 --> 00:31:35,240 Speaker 1: didn't don't stop being meaningful. Now that we're in a 604 00:31:35,280 --> 00:31:38,400 Speaker 1: technological aid group where you can have a machine that 605 00:31:38,440 --> 00:31:41,760 Speaker 1: creates an image of anything. In fact, it becomes more 606 00:31:41,800 --> 00:31:44,520 Speaker 1: so if anything right, great, anything. You want to leave 607 00:31:44,560 --> 00:31:46,160 Speaker 1: us with this on this topic. 608 00:31:47,360 --> 00:31:51,560 Speaker 4: Uh no, But I guess I could say anybody listening 609 00:31:51,560 --> 00:31:55,480 Speaker 4: out there who's morally inclined, who's scared about AI, I 610 00:31:55,480 --> 00:31:59,719 Speaker 4: would say, yeah, don't run away from it, Engage with it, 611 00:31:59,760 --> 00:32:02,120 Speaker 4: think about it, get familiar with it, dive into it, 612 00:32:02,200 --> 00:32:05,000 Speaker 4: and contribute to the conversation because we need you. 613 00:32:05,640 --> 00:32:06,480 Speaker 3: I mean, that's brilliant. 614 00:32:06,480 --> 00:32:10,360 Speaker 1: And the obviously the the augment to that is God 615 00:32:10,400 --> 00:32:11,960 Speaker 1: will be with you if you pray for it, as 616 00:32:12,000 --> 00:32:14,160 Speaker 1: he is in all things and has been ever since 617 00:32:14,720 --> 00:32:17,880 Speaker 1: technology began, which is to say creation. Thomas, thank you 618 00:32:17,880 --> 00:32:19,520 Speaker 1: so much for being on the show. I appreciate your 619 00:32:19,520 --> 00:32:21,840 Speaker 1: insights so much. We're gonna have to have you back sometime. 620 00:32:22,320 --> 00:32:23,800 Speaker 2: Thank you so much, EAIC appreciate it. 621 00:32:23,920 --> 00:32:24,600 Speaker 3: And thank you to. 622 00:32:24,840 --> 00:32:27,040 Speaker 1: All of you for joining us for another episode of 623 00:32:27,280 --> 00:32:29,000 Speaker 1: Meeting of Minds. Talk to you next time.