Ellen Twomey: Welcome to the podcast. Today we're talking about the future is formation, not training. Let's start off with a prayer, and because it's the feast of the presentation of our Lord, we'll say one in honor of the presentation. In the name of the Father and of the Son and of the Holy Spirit. Amen. On this holy feast of the presentation of the Lord, we commemorate Mary and Joseph Joseph's offering of Jesus in the temple, fulfilling the law and revealing him as the light to the nations. Here's the prayer. Almighty and ever living God who consecrated our only begotten Son in the temple as the light of the Gentiles and the glory of your people Israel, grant that we may offer ourselves wholly to you as a living sacrifice holy and pleasing in your sight. Through the intercession of the Blessed Virgin Mary, the humble handmaid who presented her son, and Saint Simeon and Anna who recognize the Messiah and the infant Savior, dispel the shadows of sin from our hearts, and Fill us with the light of Christ that we may walk as children of the light and bear a faithful witness to your salvation to all the nations who live and reign with the Father and the Holy Spirit God forever and ever. Amen. Amen. All right. Welcome. I'm excited to talk about the future's formation. Let's dive in. Are you excited to talk about this? I am. I am. Particularly on this feast day, which in the East we call the feast of the encounter. Mmm. I think that touches a lot on what we're going to be talking about with regard to formation and how it it differs from training. Hmm, I agree. Mm the homily this morning was on the magnanimity of the presentation and and the beauty that can be found, and there certainly is that underlying that underlying theme here. So Let's get started by diving into you know what do we mean by the future is formation not training? And and and why do you think that? And I happen to agree, so I'll I'll calm that when you're done, but wh why why do you think that? Yeah, you know, I I think that formation ends up approaching the human being a little bit more holistically. there's this concept in in Lonergan's thought called authenticity. Which is kind of the result of a moral, a spiritual, an intellectual sort of conversion where you realize that You are a certain kind of thing and you understand yourself and the way in which you operate, both as a human and as an individual, a little bit more richly. and so in pursuit of that as we talked about epis last episode, the unrestricted desire to know, you're becoming more authentically you as a result of a that s kind of self-appropriation of the thing that you are through this kind of thoughtful process. and some of that i is like requires some some deep narrow intellectualness around a certain discipline because that teach it kind of leads over and under other disciplines as you understand how you understand in that vein. But it's also a whole lot broader too where that formational aspect ends up incorporating all pieces of you as a human you know in that in that less narrow sense in that really broadly Le Velaris broadly universal sort of sense that the university and all its disciples disciplines are so important for. And so this this narrow technical training, while it's great, and and and important, I mean the science and all of our disciplines require some of that some of that specific work, the formational aspect it remains kind of a broader endeavor, involves the whole person and is less discreetly intellectual, if that makes sense. Mm-hmm. Mm-hmm. So do we still need training in your opinion? definitely. But I think it's less of a job of the university. It It may have been at one point in time in the university's existence, right, where that that sort of training aspect is is the only place where those books were kept. Or it was the only place where that kind of expertise that the professor had could be accessed. but you know, s starting with the starting with books really, then starting with the internet and then kind of moving into the way in which we're able to access a lot of information and now of course with the evidence. of AI, access information in a very personally curated sort of way, where we're able to pattern our experience with the engagement with these AI people so that we're able to come to understanding and insight better. that that that narrow aspect is is something that has been democratized in in a in a in a large way. This isn't to say that you still don't need that apprenticeship model for getting really good at a particular particular subject area, in in encountering the other in that fashion where where that kind of learning really happens. but it it's at it's at a more It's f further down the tip of the spear because more of the blade of the spear can be grasped with with some of these tools, especially when used in in a way that respects your own human flourish. Mm-hmm. I th that that's a great point. And the w we'll probably we'll we'll touch on it later. You talked about the authenticity, but the but the ambiguity that it that the tool presents. So I'm I'm I I open apologies that I'm so into Chat GPT, but I I have these developed GPTs, so I use it all the time. So so so I I go to my prompt and I can type anything. It's much like the internet as you say, I can type anything. What do I want? That there's an inherent ambiguity in that tool, in that in in what we're using and and what we're and so now this n this will be I'll be the philosopher for a minute, Taylor, but the you know who am I In using this tool. turns out that matters a whole lot because I might prompt moral things, I might prompt amoral things, I may get lazy and and prompt things so that I don't have to do work. And then you say, well, well, that's what you're that's what I'm supposed to do. Well, at what level am I supposed to do that? And we we've touched on that before that you know, if we're if you're not really growing. in in becoming better. If you outsource, for example, all of your writing to Chat GPT, you'll be in trouble. I've been using it for for mathematical modeling. Turns out if you outsource all your mathematical models it it will fail you. That's not it's not perfect. It's it's a good start, but you got you better check the numbers. So I think that the the nar when you talk about the narrow scope, you went right to apprentice model Which was interesting to me. But with training, I mean, is that the only way to do training, the apprentice model? Seems like the logical one to do, but No, I think training has inherent to like a an understanding of a use of a tool. Tool really broadly, right? Whereas like, you know, I need to be trained on how to use Excel or I need to be trained on you know, frame a house. I there's something about you using a tool, that happens as a part of that. Now I think where the master apprentice model really finds its strength is when the formation and the tool use end up being so interwoven that it's really hard to separate them out. y you know, I I I think of y you know, law, for example, used to be a very much more apprentice, master sort of model. And actually still is in some states. You don't you don't necessarily have to go to law school in some states you can do it in an apprenticeship sort of model. but w it's like the work itself and like the writing of it and and the application to particular cases ends up being the theory that's being presented in some ways. per perhaps a more d like a cut and dry one is like a plumbing a plumbing or electrical work, right, where the the it's hard to explain in theory how to go about doing that. And you just have to watch again and again and again and have your further pertinent questions refined by a master who's already seen those sets of scenarios, you know, ten thousand times or whatever. because the actual the formation is in the doing of the thing. Mm-hmm. Mm-hmm. There's is I think that's true of any discipline. I don't think there is like a like the pure the pure theor theoretical sort of discipline has a little bit of that master apprentice sort of model. because it gets into the the curtain question forming. Now the thing is though, like a i there's a bunch of theory that you can just that is often necessary for the context there. so if I'm You know, I can go and be a better plumber if I know hydrodynamics and pressure and material science and all of those different things in a theoretical sort of vein. That could put me make it easier for me to learn some of the practical lessons as a result of that theoretical knowledge. That's a bit of a continuum. the slider goes either direction, like, you know, theoretical physics, for example. there's a that ha contains a whole bunch more theory before one actually has to get into kind of the practice of it. but it's precisely in working with you know, more people who are further along in their careers than you in that particular discipline where you're able to gather from them kind of the further pertinent questions of the way in which they look at the world that has patterned their experience for coming to insights in that domain. Mm. Yeah, that's really interesting the way you say it. I'll also add the career of our Lord and Savior before becoming a preacher was carpenter, which of course I mean that just when you when you were describing the training formation piece, right? I mean there there's the skill involved in carpentry and then and then also the formation and w making it your own and the beauty that can come out of it and but like you say it's true in really most most things. I mean, we don't get to the top of our profession and say, okay, I'm I'm done. We look for who's doing it better and who's done it more and what book c what book can I read. so that's yeah, that's interesting. That I like that. So so there's this piece here that you that you wrote in in the LinkedIn post that I'm referring to and it's it's really it's pretty meaty, so I'll I'll read it and then we'll kinda talk about what you meant by it. But But education's role is no longer to transfer expertise into stable markets, but to form people capable of navigating unstable ones with authenticity, imagination, and insight oriented to the good, the true and the beautiful. So tell us a little bit what you meant by that. Yeah. I I think that and we I may we may have touched on this in another conversation, but Universities have been around for a while and they're the way in which they operate kind of has ebbed and flowed in both in response to culture but also to the economy. and I think particularly after kinda kinda the Industrial Revolution and then you know, maybe the the booms with oil and gas and the rail and electricity in the United States too. There in order to be able to drive those economic profess professions forward, we've realized that coming to breakthroughs by partnering with universities end ended up being a great way of having somebody who was trained enough in the theory that they could also drive our business practice forward. I recently finished a biography of of Rockefeller, for example. Paul Titan, it was a really really well written But they realized that if you had a better way of refining petroleum, for example, your company could do much better. And that these research institutions called universities ended up being really a really valuable aspect of that. all kinds of money of course have gone into that a as a result. So a number of the universities in the United States of course were founded out of money in the in those sorts of veins, University of Chicago, Carnegie Mellon, like the list goes on. but what they realized there right was like, our Our training, our technay, our tool use is getting so complicated that you have to have a couple of years of theory in order to actually be able be useful for me in the way. Mm-hmm. I think this is also where the difference between technical schools and universities started to separate a bit too, whereas like, you know, plumbing you only need to learn how to use tools, you don't have a lot of theory behind it and and I'm purposely being a little bit pejorative because some people think of it in that pejorative sort of way, which I I makes no sense to me. But and but in a university, you know, you need more like intellectual formation and then then you're y you do a different set of things there. but I I think I think that that difference is great if you know what the jobs are. If you know what the industries are making money, how I need another hundred and fifty petroleum engineers because I I can count that. when you have a big technological shift though, like you know, which you've seen like in the in the industrial revolution or other veins, you don't entirely know what the new jobs are, you know. So it's not like, you know, the w we have to talk about the word the the origin of the word saboteur with the weavers putting their sabots into the industrial machinery. You don't quite know how many industrial machinists you need because demand for the thing is still changing and there's like a kind of a lot of economic p turmoil around that. So do I as a weaver go and get like learn how to work metal, or do like how do I think about that? The best way to think about that of course though is is by being a better thinker yourself and being able to kind of see the application of tools in a variety of different domains. And what that gets to, as we we were kind of touching on this session, is formation. Like if you're if you're good at understanding how at understanding qua understanding, or good at you know, applying your unrestricted desire to know and and of cap capacity for insight in a in a variety of different domains, it kind of helps you understand this new tool and how it can be used in in a in a wider variety of settings, which is exactly what is needed at the moment. the reason why of course we use this AI tool first and forem first and foremost in in code is because everybody who was working with it and building it were working in code. Could it be used in other places? a hundred percent. Do we quite know what that looks like yet? Not Really, because we don't have enough of those people doing it. You know, we don't know what the new job is quite there. but the people who are going to figure it out aren't necessarily going to be the the folks who are good at a you know, last year's or the previous generation set of tools. It's people who understand the application of this new tool, which we have to learn a lot about, to broad spheres of human endeavor. And therein lies that formation aspect that that goes about this. There's there's kind of a that's kind of the carrot way of looking at it perhaps. There's a stick way of looking at it as well. If you're an employer where all of a sudden you have in in the competitive market, you have people who are able to ten X or a hundred X individual productivity as a result of the incorporation of these tools. Well y while you're interested in that. How do I get that ten X, hundred X increase in productivity for my own workforce? Mm-hmm. But I want them to do it in the right way. And we don't know what the right way is, right? So there's a lot of this concern like we here have conferences all the time, like ethical use of AI or or how do I use AI not only in ways that don't harm my customer or you know, leak s important data. I mean this over the last week and this weekend in fact, just seeing how I think there's one point five million anthropic API credentials have been exposed as a result of this this claw bot. really I so d to a little bit of context from a technical standpoint. a researcher figured out how to kind of open up an aut autonomous agents on your own machine so you can you can have autonomous agents run your own computer. it's in a really kind of startup y hacky sort of vein where these agents are doing wild autonomous things on their own, forming little groups of agents out on the internet, like it's it's kind of this a fascinating tech phenomenon that's happened over the last like five days. but of course they have no information because they're just executing you know autonomously, leading to things like anthropic your API codes being exposed, which means other people could use your anthropic credits for their own API their own AI compute. So like things like that you don't want to happen inside your enterprise. You want people who are more circumspect. You don't want them you don't want to have to policy everybody saying, Hey, don't download something on your computer like and and use it in this fashion, right? And so you need people with that broader formation to understand what's the right decision in that in that context, given this new set of tools. You can't rely just on the training with regard to like here's how you use Excel, don't use it in bad ways. because these are much more complicated, nuanced and sophisticated tools that are not only kind of thinking on your behalf, but also acting on your behalf. That's that's a terrible, terrible thing from a firm's perspective because you have a lot less control. You have to rely on the formation of your employees much more. and therein lies the rub. And and but but not to you know create create additional fear. I mean this is really I I can't help but think of my mother-in-law retiring from the credit union when they went to a GUI interface and she just was very adamant with me that the DOS prompts were a much better tool. She's like, look, I can do it faster this way, and we went over it, you know, and she would show me. I mean she's right. You can't get back to the commandline. Turns out she's more technical than she realizes. I'll let her know. But she you know, she said, no, this this is so I've got to click here and click there and it's just too hard because Well, I mean, because of her habits. She had been formed in this one way of doing things and and she had learned it and she was fast and th the and successful every time. And the GUI interface actually slowed her down and made her think about different things and but that doesn't mean that someone new couldn't come in and and do that more quickly. But my my point is that sh she she quickly retired before she had to use it too much because of Really fear and and not getting it and not thinking that it that it was a she d really didn't want to deal with it and whether or not it was a a better system, but I I that is a fear that I have as you're describing some of these rogue bots that are going on, rogue agents, are that then we can we can have a fear set in that okay, it's too complicated, I can't get it, so I'm just gonna stay all the way away from it and not touch it. Well you know, turns out anyone who had to stay in the work well now my mother-in-law books rooms late, so she uses a good interface the whole time. But but the you can't you can't necessarily say, well, that's just you know, the tool is is beyond my scope. And so there th well, there are parts of it that always will be, right? There are parts of technology that, you know, advanced hackers would spend all day every day and many, many hours trying to do things will likely be smarter than the average user or the average prompt user or things like that. But but I but it still makes sense in a lot of ways, even if you can't understand fully all the ways that they're pulling things together, to understand what can I do with this tool? What a what is possible and capable. And and I think to your point around productivity in the workforce, there's almost a demand Like how can you 10x your job? Let's that's a thing you should now that used to be crazy talk. Hey, that's a cool only now it's it's a bit commonplace. You you have to be thinking about how can you 10x what what you're doing and and then how can you not cause harm. So I think about I I wrote a a blog recently in sales and marketing, it's only annoying if it doesn't have value. Right? You can create oodles of content. It's more content than you ever could want, which in the SEO game used to, you know, be the winning formula. But now you can create so much content, turns out if it's annoying, nobody cares, right? So so how are you creating content? You can create much more of it, but is that 10Xing? Not necessarily. Just because you're 10X in your output, it's not necessarily 10Xing the results. So these are things that as we talk about kind of the complexities and how how it can go awry. It's still important to talk about well, where can we be and and what can it accomplish i in in a at all different levels, beginner or intermediate or those of us who you know who are not coding every day or just using it. I think that's an important piece around there. Yeah, no, and a lot of it ends up being oriented towards its end, you know, as T loss. like, does this piece of content need to be created? Is it is it is the world better for it? and th that that right if if you're not driving your unrestricted desire to know in in the pursuit of those four transcendentals, the good, the true, the beautiful and and being then then so what? Like so you're, you know, ten X, a hundred X more productive on something that doesn't matter. to do, you and that's that's where that I think formation code comes in is not just, you know, AIFI and things for the sake of AIFI things or being productive for the sake of being productive. but really having a solid understanding of the the ends of what you're doing and then why this is a good way of achieving them. And and almost almost the tool requiring us to act in a more well formed way because we can create so much more havoc more easily. We can create so much more damage so that that 10x really I like the way you say that, right? Is a there's a world better off for for having it. That's that's a great way to think about it. So so we we touched on the university a little bit, but one one other idea that we wanted to explore was how can we explore Or can we explore the generalization of the pursuit of the good, the true and the beautiful in secular education? And an another way to think about that is what happens when a university substitutes optimization metrics for transcendentals? And an optimization metric might be retention or placement or rankings. Yeah, and part of the reason why they would do that, right, is because they're getting feedback from their customer, ostensibly the students, that the student is is is hoping to find just a job out of their time at university, right? And I think I mean Adam Smith had a concern about this when he wrote Wolf Wealth of Nations. he added something very hilarious to say if in particular about study abroad programs. he said something along the lines of parents tire of seeing their children deteriorate in front of their eyes and so they send them to deteriorate in front of somebody else. But what what his concern was there is that as when you put a a a degree on an amount of education then or or a certain kind of outcome for an individual in terms of formation or intellectual power. or something along those lines, that degree ends up being that that measure ends up becoming the name. So as a result, it it ceases being a good measure, right? and so I I think universities when they when they shift to that sort of credentialing, you know, have a good time for four years and get a good job out of it, they have to know what the jobs are. And so in this time right now we don't entirely know what the jobs are. This is why the hierarchy is and so that that model, y even though it's kind of been a little bit broken, you know, arguably at least for the last couple of decades, because of that mismatch between the measure and the and the and the aim, is is really coming to fruition now. It's like, well, we don't know what the jobs are, so we can't there's less of a this is what you're going to get with your university degree is a great paying job. it's is you know, the the model isn't completely broken. Clearly there are, you know, hundreds of thousands of students graduating and getting jobs still. But but is we're already starting to see that those headwinds in in strong strong ways even even for like you know, MI MIT graduates in computer science who which which is I think surprising to many given like the the tech booms right now. But but it it ends up being that that we missed part of the goal of the educ of education, which is to round out and enrich even like the interior lives of our students, where they they just have a better life as a result of their education, as a result of their understanding more about the world around them, about in all of those formational aspects that are ha really harder to get your your hands on, but end up being so important for for humans to be able to find meaning or to or to flourish in that same sort of vein. And so it's that understanding I think of the good, the true and the beautiful that y the secular institutions too can take well in hand. I mean you could almost just use Man's Search for Meaning by Victor Frankel as kind of the perspective there. Like if you don't have a good sense of meaning then Whatever whatever you have in terms of how ends up not doing the job. Now to be clear, you're not comparing the university system with concentration camps in during World War Two, correct? I think any sort of human institution where requires you to have and find meaning. And so whether whether that's a do love or you know a a lead crystal a walnut wainscoated Ivy League school the problem remains. Taylor sa says the doctorate to and further credentialed, yes. that's great. I was like, man, he's not gonna actually defend this, is he? Okay, good, good. Well, I mean you're hitting on all sorts of things. One, two of my children are studying abroad this summer, so I guess that's I don't know what that says about me. I guess I guess that's the piece. But you and I had talked about off camera before that my so my my freshman daughter is at Georgia Tech and she's she is studying business. I caveat that 'cause she she's wants to go to law school. She's taking her first law class and she's just a liberal heart. liberal arts, writer, thinker to the extreme. I mean, I could care less if she wants to be a lawyer. That sounds totally terrible to me, but you know, to each his own Taylor. but you know, that's that's her interest level and she has to take computer science at at Georgia Tech, which is a really interesting you know, that's interesting. I think one of the challenges that MIT and and actually Georgia Tech has this too, the computer science programs are overflowing. They're a dime a dozen. not so 2001 when I graduated. So so I'm curious, I'm maybe I don't know if I'm jumping, but I'll jump in. But so my undergrad's computer science, i is it worthless? Do I evaluate my degree? Yeah, so I I think that there's computer science like some other disciplines that require the use of tools. for their work, right? Without a computer, you can't be a computer scientist. And so there's a way in which you can think about you can think about being a computer scientist as just getting good at using a tool. Now if you if you can see of it in that fashion, like you could be learning cobalt and an a which is an ancient programming language. for coming up with that one. Yes, got it. Cobalt. Okay. Cobalt. And and like being really good at cobalt but not actually understanding like the the core computer science theory that goes into understanding why a recursive function works or why matrices are so important or how to think about you know building a building an application and all of the things that one would have to be concerned about there. Notice though how how that theory and praxis kind of come together really solidly in in that sort of in the computer science degree. Th i there there was a phenomenon though you know it maybe a decade ago of these kind of code boot camps though. Code boot camps really pulled out the tool part of it and had you just focus on the tool part of it. So that you could be, you know, a beast of Python or something like that. But not necessarily understand the two, three, four years of computer science theory that actually helps you understand when and how all of this works together on on the actual on the computer itself. And so so could I would say that your computer science degree ends up being less important because of the tools that you learned because we have a whole new set of tools. There's this thing called AI native engineering, which is a completely different way of programming. it's just it's it's vibe coding professionalized into actual real products and and you c you're able to do amazing things with it as a as a developer these days. But what remains the same it's all of the principles of computer science, all of that theory that also came along with your degree, so that you know how the thing should be evaluated once you send all those prompts into the world. So what you learned really is kind of a way in which the world operates in a kind of human formation sort of level. and you have to be a little bit more flexible with regard to what tools you're using to accomplish that set of understandings which still remain very powerful and valid. Mm-hmm. Well that's good. That's good to know. I that I it still has some validity to it. But I I think that the I think that the the rise of and and when you talk about AI native engineering that's that's that's you're still you were well you mentioned vibe coding. Why don't why don't we kind of cover it? I I I botched the question a little bit because you know the setup is that with tools like Replit and and base forty four and lovable, you you you can vibe code, you can prompt code. You can you can write code and I and I've done this recently. I I so for an update, I I don't write code every day. I do sales and marketing and technology and product stuff. So I I don't I really haven't written much code in quite a while. But but but turns out anyone can do replit or or vibe coding. But walk us through let's talk about a little bit about the tools and the different levels of tools. Yeah, certainly. So traditional programming, you had to learn a programming language. Python, Ruby, C, Rust. There's a variety of different languages out there. And they're languages in the in the real human sense of being able to convey meaning to the computer so that the computer would do stuff for you. Mm-hmm. vibecoding ends up being somebody i i which is kind of pejorative, kind of not, of using a a natural language tool like a copilot or like a replet, to natural language with an L L And then the LLM produces the code which executes in the way that you want it to, like building a website or a mobile application or some sort of computer program. The LLM takes all of the coding language work off of your plate, and so now you as a you know English major can say, Hey, I want a website that talks about, you tokens similarly and then I want it to be beautiful. And the LLM will figure out what that means and code it for you and launch it for you. And you have a website and all you had to do is kind of utter it into being using natural language. but of course unless you have some kind of understanding of computer science, you don't really know as a as an English major perhaps, like, does it need to look like this? Do are there security things I should be worried about? how do I tell if it's good or not from a technical standpoint. What is possible. Yeah. Right. What is possible. Exactly. Yeah. Yeah. And so that ends up kind of being the vibe coding sort of thing. The vibe coding thing though, if done by like computer science people or even often product people who have a little bit more of the overlap of natural language and what a product should look like and all of the considerations one might have around building a product, you're able to build real things fairly quickly as a result of as a result of that. You have a contextual knowledge for what good looks like at the end of a of a product being built. and now don't need to know the underlying code. Push that all the way to AI native engineering. AI native engineers are engineers who, you know, have been maybe working at Microsoft for twenty years. and before w knew a number of v languages to a very, very high degree of professional ability. but what they can do now, because of all of their software engineering general knowledge, they don't necessarily need to learn to they don't need necessarily to write code anymore. They can have the tools write code for them and have many of them writing it at the same time. Well to the extent that we have teams now that and this is this is in reference to a couple of research teams that I work with. I won't opine as to how far it is into the productionization of it. But you can have engineering teams not even look at the code at all. have the entire code base owned by their LLM tools and they only write and are concerned about the evals, the evaluations of the things that are created. Because in they've we've been able to abstract away caring about how the thing was implemented to just how the thing performs as a result of that. Whole different paradigm in in engineering. which has been super interesting to see. But notice too how that has kind of changed up the tool use significantly while while the same kind of computing paradigms are still necessary to understand w whether what good looks like at the other end of it. Mm-hmm. And and what is the don't answer if you can't, but what is the what does it look like when when you're thinking about the evaluation at the other end. What what is the w what is the human interplay? Where where does the human come come back in in that in that piece? Yeah. you security, performance. yeah, security and performance are first things that come to mind. ability to execute the task or perform the the job that was required of the of the tool. how well it thinks about the user experience as part of interacting with the yeah, there there's a there's a bunch of different different pieces in there. for sure. And the UX thing still remains a a more of a gnarly problem since we just we don't even know what the UX of of AI really should be yet. We're we're mapping it onto old design paradigms, and by we I mean tech in general. because we haven't wrapped around wrapped our heads around this like this, this new technological paradigm where you're act a lot of your development can be done by speaking natural language at the machine and what you see or hear in a order to do that better, we don't know. Right. Right. It it's almost like there's even more layers under the hood where than we had in in you know, as I was learning cobalt just putting I'm not that old, cobalt but the but the you know, in the object oriented languages of C plus plus and Java there's a there's an inherent wrapping around, you know, we can do more complex things than we can from could from previous and now we've got that paradigm. When you're describing that, when you're describing like what the UX looks like, it made me think of minority report. Do you remember that old movie with Tom Tom Cruise? Right? I mean is that what we're is that what we're in for? Is there any is there any world in which minority report is one of the UX pieces? For those of you who don't know there were images you'd walk into a store and it knew your preferences and there'd be holograms. Yeah. Yeah, ambient interfaces is ambient interfaces, yeah. Yeah, where I anticipate things. Yeah, because the I mean, part of the UX is just speaking. Part of the UX is just talking to you know, speaking what you want to come into existence. And again let me kinda come into that ambiguity piece. Okay, so that leads us to our our final double question is should our parents use AI? Why or why not? And then should our kids be allowed to use AI on their homework, for example, is more specific. So where do you stand on the parent child or no? Only people in their midlife or or or late adulthood can use it. It's just for us. No. Well I I think anybody really sh the the only thing to keep in mind there are w are like one's own human formation. so you I mean you don't want a your your parent to use it if they don't know what they're using, right? It's it's similar to you c it's easy to get burned if you don't know the thing gets hot, you know? and so there's but but you know, your parents are smart. I if you're able to you or, you know, s some trusted authority is able to kind of explain to them what it's good for or what it's not good for and and things to be aware of then then that's straightforward. where ch where children I think differ is that they still have intellectual development too. Like they're you know, they ha they have not only software problems but hardware problems. as as their brains develop, right? and and maybe that's true for for the other end of life as well, but that's something to take into account too. But I I tree for for my own kids I have kids ranging from three to fifteen. similar to in how we treat screens where it's used for certain kinds of things around and things that the tool itself is good for with a deep understanding of how it's affecting you as an as an intellect and as a human. Hmm that's good. I like that. Yeah, I think my my parents are pretty They're they're pretty young and young at heart. But I I do fear that just like you have people f calling the elderly and and you know, re extracting information that that the tool could just be another place to extract that. It's it's kinda like the the lowest human how how you can prey on the elderly is it's that's a pretty rough, low place to be. But but the but I think that is one piece is knowing knowing what And and there's a comfort there because they do online banking in in, you know, people who are born in the forties. And and and I I you and I joked a little bit that the formation dips a little at age sixteen, so you're you're re you're getting ready for it. There's a right there the foundation. But I I do know, you know, my son, my 13-year-old, he he prays before he turns on a screen. That's kind of the thing he talked to a priest about video games, and he doesn't even play video games, he just watches the people play the video games. My least favorite thing. I can barely tolerate it. But but we we limit time and things like that. And and he asked a priest and he said, But it's it's about you know, the virtue is in the middle. It's not about the extremes. And so I I never wanted to say no, you can never do any of that. I didn't think that that was a valid way to to to raise my kids of this world, but I also was probably more strict than than the average person on time. I just limit time on it. but I I do think it's important to understand the tools and and the way that they're that they're being used because other people are using them and and thinking about the way in the which the world works. So I d I do think that's important. I don't want my kids using it for to do their homework for them. I hope nobody does. But but but we c but I do use it, I will say this, I do use it to create quizzes and and prep tests for them. And I find it to be phenomenal in that and and an important part of their formation and their and their learning and and how they can grow. So Yeah, I'm excited in one of our future episodes to go through how to do that precisely in a variety of these different tools. because they can be great foils for intellectual development where you know engage you to in in a in a solid intellectual way, but it has to be used in a thoughtful approach. Absolutely. Taylor, thanks so much. Great to be with you today. Thank you, Ellen.
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As AI reshapes how we learn and work, how do we prepare for a future we can’t yet predict? Ellen Twomey and Taylor Black explore why formation of the whole person matters beyond technical training. Through a Catholic lens, they discuss education, the changing role of developers, and how families can use AI to strengthen learning while cultivating judgment, virtue, and a love of the good, the true, and the beautiful.
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