[MUSIC PLAYING] CHRISTINA SHIVERS: The act of drawing and design really has significant connections to music. I mean, even the process of musical notation, there are so many really fascinating connections between musical notation and architectural notation. They're both languages-- graphic languages. And in both cases, music, and architecture have significant commonalities because they both are disciplines that are conducted through the act of drawing. 

CHARLIE BENNETT: You are listening to WREK Atlanta, and this is Lost in the Stacks, the research library rock and roll radio show. I'm Charlie Bennett in the studio with everybody-- Alex McGee, Marlee Givens, Fred Rascoe, and Cody Turner. I can't say anybody's name. 

FRED RASCOE: Rascoe. 

CHARLIE BENNETT: Rascoe. Each week on Lost in the Stacks, we pick a theme and then use it to create a mix of music and library talk. Whichever you are here for, we hope you dig it. 

ALEX MCGEE: Our show today is called How to Train Your Algorithm. That's the title of an exhibit, you can visit in the Georgia Tech Library right now on the second floor of Crosland Tower. 

MARLEE GIVENS: It is a set of objects made from recycled paper, melted plastics, wood, Styrofoam, burlap, and probably a few other unexpected materials displayed on stands made from unpainted, unvarnished wood planks. 

FRED RASCOE: And it's all about AI. 

CHARLIE BENNETT: Yeah, this show is like a split single for Lost in the Stacks. One side is AI, and the other side is the material umph. 

ALEX MCGEE: How to Train Your Algorithm is an ongoing project exploring AI with material practices created by Professor Christina Shivers, the 2023 Ventulett NEXT fellow in the School of Architecture at Georgia Tech. 

MARLEE GIVENS: Charlie spoke with Dr. Shivers in the library's scholars event theater in front of a live audience during Media Arts Day 2025.. And our interview segments today come from that conversation. 

FRED RASCOE: And our songs today are about architecture and design, repetition, and getting machines to work well with humans and vice versa. No matter how many experimental technological tools we have at our disposal, the product of design still has to incorporate the human factor, right? Doesn't it? 

So let's start with human factor by Music for Pleasure right here on Lost in the Stacks. 

CHARLIE BENNETT: Be assertive, Fred. 

[MUSIC FOR PLEASURE, "HUMAN FACTOR"] 

That was Human Factor by Music for Pleasure. Our show today is called How to Train Your Algorithm. Our guest is Dr. Christina Shivers, an academic, architect, and musician whose research broadly focuses on the intersection of environmental and economic thought specifically within the design disciplines. 

ALEX MCGEE: Dr. Shivers discussed her work in an interview recorded live in the Georgia Tech Library. For our first question, we asked, was it a straight line from your work in urban landscapes and reclamation to this AI project? 

CHRISTINA SHIVERS: I think there's a couple steps in between. I mean, my background is in design and making, so music and design. So I always sort of had a somewhat applied approach to things, or to the world. And then through studying for a PhD, I had to start thinking about things very differently. 

So how do I write and do historical research, understand primary sources as almost my kind of material that I'm working with more so than the act of drawing. It's very kind of-- not a learning process, but just a different way of thinking or using my brain a little differently. And so in coming back into more of a design setting, as a professor and as the Ventulett NEXT fellow here, I began to start thinking about passion I have for making drawings, for making models, for really investigating architectural and craft questions, how do I begin to approach that through the lens of all of what I was doing with my dissertation and with my research? 

And I think there are many major environmental questions facing architects today, from what sort of materials do we use? how are the materials processed? what kind of chemicals are in them? how are they coming from point A to point B? where are they extracted from? Those are just some questions. I mean, there are other questions about the carbon emissions buildings produced. 

So beginning to approach my project last year, AI, as we all know, has really ballooned in terms of popularity in the last two years, three years. I guess ChatGPT emerged in January of 2022. 

CHARLIE BENNETT: Yeah, there seems to be a metaphorical starting gun. But every time we talk about it, there's always been the phrase, well, that had been happening before, but it just hit the popular consciousness somehow. 

CHRISTINA SHIVERS: Yeah. And so in architecture, I think it's been a bit of an open question about how one uses it. For many people, it has amazing potential to produce renderings. Renderings are one of the things architects kind of have to do to show the client what the building, what the project will look like. And many architects will approach renderings as like a sort of necessary evil. So with AI, you can just export renderings or out-- 

[CHUCKLING] 

CHARLIE BENNETT: Are renderings the pitch PowerPoint? 

CHRISTINA SHIVERS: A rendering is more of like a-- you model your building in a 3D modeling software, and then you use a rendering software to basically put all the materials, lighting, put it in its environment, make it look very realistic. Because a client will often not really want to look at plans, and sections, and elevations. They want to know what it's going to feel like in the building. So AI has a lot of potential for rendering uses in architecture. 

I was really interested in what other questions I posed, particularly because it has this-- it does have an immense environmental toll. But it also is, in many ways, a kind of reflection of ourselves, of our society, because it's trained with all of our data. There are many controversies around the use and acquisition of that data, but it's basically, in this way, a kind of mirror of our society. 

So I became interested in trying to understand, potential uses of like an AI platform, how that could maybe begin creating unexpected stories or unexpected ways of understanding our society. And I was interested in primarily in understanding the kind of environmental underside of that. 

CHARLIE BENNETT: So when you say AI is a reflection of society or the culture at large, were you interested in messing with how society was reflected? Were you interested in messing with society so that it was reflected differently, or just messing up the AI itself? 

CHRISTINA SHIVERS: So I'm interested in-- so AI has very particular ways in which it functions. It is trained to reproduce identifiable objects. And it has a really difficult time thinking abstractly or producing abstract images. 

CHARLIE BENNETT: Wait. Let me interrupt you there. Has a difficult time thinking, you said? 

CHRISTINA SHIVERS: Or I guess not thinking, but producing. 

CHARLIE BENNETT: But is that what you kind of-- the thinking of the AI is when it tries to produce something out of what raw materials it has or raw data it has? 

CHRISTINA SHIVERS: Yeah. So it will revert to something that looks like an object-- that table, something like that. And I was really interested in trying to say, what happens if you try to circumvent that process? What would these AI algorithms and softwares begin producing? 

And so I was really interested in developing a series of what are called-- what I called camouflage models. So noise algorithm can sometimes kind of mess with the image recognition parts of AI. There were-- 

CHARLIE BENNETT: I think we should unpack that real quick. So a noise algorithm-- what is that? 

CHRISTINA SHIVERS: Yeah, so if you think about static or an old TV when it just is static on the screen, that's noise, basically. It's just visual nothingness. It's the same with sound, so like white noise, brown noise, all these different noises. 

CHARLIE BENNETT: It's wild that static on a TV is not really a thing anymore, that there's a moment when people did not grow up with that. But white noise or pink noise is still totally in people's consciousness. 

CHRISTINA SHIVERS: Yeah, I have a white noise machine I use very frequently to sleep. 

[CHUCKLES] 

CHARLIE BENNETT: So a noise algorithm is something that generates that kind of static or disarray? 

CHRISTINA SHIVERS: Yeah, something-- so because of the way that the image producing AI systems work, they basic screen of noise, and they slowly whittle it down into something like an object. 

CHARLIE BENNETT: Oh, wow. 

CHRISTINA SHIVERS: Yeah. And so if you interfere with that process with noise, it can throw it off. So there were some artists fairly recently-- I don't remember how long ago, but in the last two or three years-- who were basically printing stickers with a noise image and putting it on their face so it wouldn't be able to recognize it. 

I'm pretty sure the algorithms and the companies that produce these AI algorithms are always updating. So I'm sure they've kind of circumvented that a bit. But I still was very interested in this process. So I created a sort of series of abstract three-dimensional models in a 3D software that had different noise algorithms applied to their materiality, to their surface. 

CHARLIE BENNETT: So if I can try to understand it in a very simple metaphor-- I know you know this phrase, but Michelangelo said the way to sculpt something was to look at the raw material and then take away anything that wasn't the sculpture. It sounds like you are throwing rocks at a sculpture while it's being sculpted. 

CHRISTINA SHIVERS: Yeah, so basically, I created these things. And I asked an AI program, what is this? And in all the cases, it would come up with really interesting answers. There's a caption generating software called Pallyy AI software is kind of in this process. But I asked it, what is this? or describe this? And it would say something along the lines of, this is a blue and green or turquoise and green plastic bag. I like to put my art supplies in it. 

CHARLIE BENNETT: Whoa. Where did that come from? That additional-- 

CHRISTINA SHIVERS: So that image or caption generator is for use for Instagram and for basically quickly generating captions that, I guess, you don't want to think of. 

CHARLIE BENNETT: I hate this so much. I'm so upset. I don't know if I can continue the interview. 

MARLEE GIVENS: This is Lost in the Stacks. We'll be back with more from Dr. Christina Shivers about messing with AI after a music set. 

FRED RASCOE: You can file this set under NA 2520.H73. 

[MANOR, "ARCHITECTURE"] 

[GENTLE GIANT, "DESIGN"] 

ALEX MCGEE: That was Design by the not-Welsh band Gentle giant. 

CHARLIE BENNETT: You don't know that. 

[CHUCKLING] 

ALEX MCGEE: There's a debate. 

CHARLIE BENNETT: Just sounds like it was recorded in a field near cows. 

ALEX MCGEE: And before that, Architecture by Manor. Songs about, well, design and architecture. 

[MUSIC PLAYING] 

MARLEE GIVENS: This is Lost in the Stacks, and today's show is called How to Train Your Algorithm. Dr. Christina Shivers from Georgia Tech's School of Architecture has been exploring AI and materiality using images, noise algorithms, and fabrication. You're listening to excerpts of an interview with her, recorded live in the library on Media Arts Day 2025. 

CHARLIE BENNETT: In the last segment, we talked about how this project works. Let's review. Dr. Shivers creates an image of an object obscured with visual noise, what she calls the camouflage model, and then asks an AI system to identify the object. That identification becomes the prompt for an AI generated image. 

FRED RASCOE: Then, the camouflage model and the AI image are blended into a new image. And that new hybrid image is used as part of a prompt to design an architectural pavilion. 

ALEX MCGEE: Which will eventually be built using recycled and unexpected materials. If you need more detail or want to see these images, the whole process is on christinashivers.com-- Christina spelled with a C-H. 

CHARLIE BENNETT: This AI system-- don't even have to name it-- you showed it this image, or it created this image from text? 

CHRISTINA SHIVERS: So I showed it the image on the left. It said it was a blue and green plastic bag. And then I took the sentence that it gave me and had it produce the blue and green plastic bag. Yeah, so it's like one step of translation from left to the next one. 

CHARLIE BENNETT: And how is it that it can make the plastic bag from an image that, if I can just describe it very quickly for anyone listening, it looks like a landscape with some popsicle sticks? I mean, I don't-- help me. I don't see how it can then say that that's a bag. 

CHRISTINA SHIVERS: That's why it's really fascinating. That's what I thought really became really fascinating about this process is the objects that it's-- the data that is trained with it reverts to something. And so something as ubiquitous as a plastic bag that we see everywhere that we use for everything, it's like, OK, I guess this is a plastic bag. 

CHARLIE BENNETT: So the AI was able to peel the noise off of that image and get a plastic bag? 

CHRISTINA SHIVERS: It said it was a plastic bag, yeah, through its computer vision image recognition process. 

CHARLIE BENNETT: So if I go back to my silly metaphor of the sculptor and throwing rocks at the sculpture, do you not like the sculptor? Are you tired of what he's creating? Are you messing with the AI in order to know it better, or are you trying to figure out ways to disrupt it? 

CHRISTINA SHIVERS: I'm trying to-- I think it's probably both. I think it has potential. With any tool, it's really interesting to use it in a way that it may not be intended to use. Many, many artists and musicians use things quite differently than maybe the way they were engineered and stumble upon, in the process, something new-- a way of using that medium that can reveal something that is unexpected. 

So I think that's part of it, so messing with the AI algorithm. A, I am trying to get under the surface to begin understanding what the data that it's trained with starts to-- what it starts to reveal about that data and, in turn, how it is this reflection of our world around us. So the plastic bag is so ubiquitous that it looks at that image on the left and it's like, I guess this is a bag. 

CHARLIE BENNETT: Wow. So there's the noisy image, and then the rendering of a prompt-- that noisy image, and then another landscape. So what's the next image then? 

CHRISTINA SHIVERS: That is a combination of those two images. So basically, just those two images were blended together to begin understanding-- starting to develop a process of how this can create an architectural application. 

CHARLIE BENNETT: And did you do that with an AI tool-- 

CHRISTINA SHIVERS: Yeah. 

CHARLIE BENNETT: --or is that-- OK. It's just digesting, digesting, digesting. 

CHRISTINA SHIVERS: Yeah, it's a kind of recursive process. And so that third step is the bridging point between the object that's been described, but then kind of incorporating what it originally was used to create that description. 

CHARLIE BENNETT: So again, I'm going to do for people listening. So I see what looks like a landscape with popsicle sticks stuck in it. And what AI describe that as used as a prompt produces a pretty realistic plastic bag photo. I mean, I'm looking at it now and I can tell, oh, yeah, that's not real. But I didn't until you told me. And then the next image is actually 3D, and it is another landscape, like maybe some rock strata with plastic bag handles straight up. Is that what you see? 

CHRISTINA SHIVERS: Yeah-- sort of also kind of melted plastic almost in some way. 

CHARLIE BENNETT: Yeah, it's got that texture to it. But I see rock in it too, like from a lava flow or something. And then the purple underneath-- well, let me not get too far into this. So then you blend them. And what does that tell you? 

CHRISTINA SHIVERS: It basically is just a process of making those two things that were created part of-- not allowing the bag to be the-- because basically, in AI softwares that create images, there's weights that can be assigned to an image that you put in. 

CHARLIE BENNETT: Oh, right. How much should this be used in the end product? 

CHRISTINA SHIVERS: Yeah, so trying to not allow the bag to be fully dominant because I wanted the original camouflage model to also be part of this process. 

CHARLIE BENNETT: I think we should get a t-shirt that says not allow the bag to be fully dominant. 

[CHUCKLING] 

CHRISTINA SHIVERS: Yeah, so that was sort of a process step in the creation of the final output on the right, which is an architectural, what I call, a sort of research pavilion. It's something that could be built given some time. In the exhibition I'm making, it's broken up into a series of modules. So I'm creating one module of what this would be. 

If you wanted to build this in reality, it would be one piece of it. So showing how, basically, through this process, creating an architectural object or pavilion that displays a potentially new-- or somewhat new-- not everything under the sun is not-- everything's a recombination of something else, especially when you're working with AI. But something that can become innovative in architectural construction techniques and processes. 

AI is really this interesting process where it's always giving you multiple variations of something. And so you have to work with images in this way. That's parametric almost, because you can change a number slider to change the height of a box, for instance. 

CHARLIE BENNETT: So I'm flashing on like Photoshop and using color levels, like desaturating. But this affects an entire rendering of an architectural idea? 

CHRISTINA SHIVERS: Yeah, and that's what's really interesting about AI is that it is inherently parametric, but through a kind of very different way of thinking about it. Instead of thinking about numbers, sliders or different ways of manually coding an interface, you are working with text descriptions, and in this instance, a series of images that are being combined, recreated. Again, it hearkens back to that analog method of photocopying, cutting up, recutting up. 

CHARLIE BENNETT: This seems like a very involved way of doing a conceptual model. 

ALEX MCGEE: --to Lost in the Stacks. And we'll hear more about the research pavilions and melted plastic on the left side of the hour. 

[MUSIC PLAYING] 

[MUSIC PLAYING] 

(SINGING) One, two 

One, two, three 

- Hi, I'm Joelle Dietrick, and I'm an artist that makes work about moving around. You are listening to Lost in the Stacks on WREK Atlanta. 

(SINGING) When you were a child, you were touched by the muse 

And she said you were on fire from your head to your shoes 

[PHONE RINGING] 

CHARLIE BENNETT: Today's show is called How to Train Your Algorithm, although it might be how to trick your algorithm. There's been new information brought into the studio. Named after the AI and architecture research project created by Dr. Christina Shivers of the Georgia Tech School of Architecture. 

You're hearing excerpts from an interview I recorded with Dr. Shivers. And for our mid-show break, I wanted to pull a minute from the interview when she talked about AI and intentionality. This is for you, Fred. 

[MUSIC PLAYING] 

CHRISTINA SHIVERS: What I also am trying to explore in this process is this blending between what agency me or the artist has and what agency is part of the AI program. And I think in many discussions about AI and art, many people are concerned about losing artistic agency. 

And I have many suspicions about AI just-- but I think it's something that's necessary to engage with because it's being engaged with as we speak. And so beginning to think about it critically and through an artistic and architectural lens is really important. 

But the process that I'm working with, and I think all processes in working with AI, there is actually a lot of agency that the artist or the user of AI has. But I do think you have to think about it intentionally because it's very easy to say, make this great. That's it. Where in reality, AI, in essence, just from a very basic standpoint or a basic level is a kind of form of curating. 

It always gives you variations when you say, which one is best? But then when you continue with this process of curating, but also combination blending, again, these parametric methods that always are going to create something a little bit different or drastically different, but you're not quite sure what it is, that is where you begin to have agencies. It's very process-based instead of planning based, I think. 

[MUSIC PLAYING] 

CHARLIE BENNETT: File this set under PA 4037.C25. 

[BOBBY DAY, OVER AND OVER] 

(SINGING) Doot, doot, doot, doot 

Well, I 

[PEEL DREAM MAGAZINE, "MACHINE REPEATING"] 

CHARLIE BENNETT: That's Machine Repeating by Peel Dream Magazine. And we started with Over and Over by Bobby Day. Those are songs about the three R's-- Repetition, Repetition, and Repetition. Or to put it another way, the three R's-- Repetition, Repetition and Repetition. Fred? 

FRED RASCOE: Repetition, repetition, repetition. 

CHARLIE BENNETT: That's right. What was that thing about vegetative electron microscopy? 

[MUSIC PLAYING] 

MARLEE GIVENS: This is Lost in the Stacks, and our show today is called How to Train Your Algorithm, which is also the name, we're pretty sure, of a research project by Dr. Christina Shivers of Georgia Tech's School of Architecture. 

CHARLIE BENNETT: What could the other name be? Marlee, what do you think? 

MARLEE GIVENS: How to trick your algorithm? 

CHARLIE BENNETT: Alex was jumping for the mic on that one. 

ALEX MCGEE: How to do repetition, repetition, repetition, your algorithm. 

[CHUCKLING] 

CHARLIE BENNETT: We're playing excerpts from an interview with Dr. Shivers that only happened once recorded live in the Georgia Tech Library this year on Media Arts Day. This last segment has to begin with the answer to the question, what have you learned? How is this project useful? 

CHRISTINA SHIVERS: --interesting, because the whole process-- it's doing something a little bit different each time. And again, it's hard to fully understand why it does that. You do multiple iterations-- or I did multiple iterations. And I'm like, why is it doing it this little way? And then you tweak it, and you understand certain parts of it. But it does have particular features that you just don't know what's going on underneath. 

CHARLIE BENNETT: This is the black box thing. It goes in and comes out, and you don't exactly know what happened. 

CHRISTINA SHIVERS: Yeah, you have no idea what's exactly going on. 

CHARLIE BENNETT: And so then the final results are, in some cases, less realistic than the blended images. But then you're calling those research pavilions. So why research and why pavilion? 

CHRISTINA SHIVERS: Yeah, so each of them is-- basically, I gave it a parameter of being a 10 by 10 cube, and something that has to exist as kind of an architectural object. It has to stand up, basically. 

CHARLIE BENNETT: Was that literally the thing you gave? You said it has to stand up, or did you say it in a different way? 

CHRISTINA SHIVERS: I'm trying to remember my prompt. It became very regular, but it was 10 by 10 cube in isometric view because those are each in isometric view-- a piece of architecture, a pavilion in the style of a certain architect. 

It's interesting because you continually give it very similar descriptions so you can get it-- 

CHARLIE BENNETT: But slightly [INAUDIBLE]. 

CHRISTINA SHIVERS: --yeah, slightly different in the process. That's where you kind of can begin exerting control, at least I found in this process a little more. So it will always give you a variation of something within the parameters that you want, which is an architectural 10 by 10 cube that has to be-- 10 by 10 by 10 cube that has to, again, stand up. I didn't use the word "stand up." 

CHARLIE BENNETT: Pavilion is what kind of made that. 

CHRISTINA SHIVERS: Yeah. 

CHARLIE BENNETT: So you said give me a pavilion to start with. 

CHRISTINA SHIVERS: Yeah, basically, and the dimensions of it and how it would produce the drawing. And using the features of these different materials or different objects that were made-- so in each of these pavilions, I said, using the kind of plastic combination bag-- is made out of that. So the material is connected to those images. 

CHARLIE BENNETT: And you can make these. That's the other piece of it? 

CHRISTINA SHIVERS: So that's the larger research question, is how AI begins to develop or allow architects to develop innovative uses of materials in their construction methods. 

CHARLIE BENNETT: The materials-- that's the most important part. Because what I see with an untrained eye is, oh, this is a sort of rendering of the feel of a building that you'd go for. But you're looking at what material it suggests. 

CHRISTINA SHIVERS: Yeah, so in each of these, they have been modeled and run through the process, I guess-- the ringer, where I model all of them, I do dimensioned drawings, and begin to create a process by which these are built. And that's been done with the larger question of beginning to develop a research or a kind of thesis of what AI can present for architects outside of simply creating renderings. 

CHARLIE BENNETT: And is the idea that these could be built at like a people-walking through scale? 

CHRISTINA SHIVERS: Yeah, so they're 10 by 10-- so they'd be 10 feet. Each module would be 2-- you could imagine it's cut every 2 feet in space-- every two feet this way. So they're all made of different 2 by 2 foot by 2 foot modules, so like bricks basically. 

CHARLIE BENNETT: And you want to fabricate those yourself? 

CHRISTINA SHIVERS: Yeah. 

CHARLIE BENNETT: How far along are you in the process of? 

CHRISTINA SHIVERS: Pretty far along. So the first one is made with recycled plastic bags, plastic sheets, basically. So you have to be very careful. Obviously, you have to your plastic appropriately. You don't want to just inhale any plastic that's melting. 

This is where it becomes really interesting. Plastic bags are very easy to be melted down and reformed into flat sheets and recycled, basically, and reused. I've been melting-- well, getting the process going. I've done some experiments. I'm still waiting for a piece of machinery to arrive to get the full fabrication going. Some hiccups, but I've still made test runs of this. 

But basically, melting plastic bags down into plastic sheets. So you do that process. You create a sheet. You let it cool. It takes a little bit of time. But then you have a building material from there to work with. 

To make one of these modules, you create a frame underneath. You reheat the sheet for just a little bit, so it becomes malleable. And then drill it. I haven't drilled anything yet, but that's the intention if you don't want it to move around. 

CHARLIE BENNETT: Were you hoping to get to a place where you could build something? 

CHRISTINA SHIVERS: Yes. 

CHARLIE BENNETT: And what does that do for you to be able to build these research pavilions? 

CHRISTINA SHIVERS: It helps concretize AI research and also present new means of obtaining something, quote, unquote, "sustainable." Because innovative materials are possibly one of the more promising directions with which architects probably need to be working to think about producing maybe more sustainable or environmentally less harmful buildings-- in many ways, something like almost a resource. Each of these is built out of some type of off-cast object. 

But yeah, in each of these-- or basically, each of these cases, the idea is to build them in some capacity to begin looking at the applied methods, which in architecture, it's building something or understanding how to build something. So using AI in a way of concretizing it as an applied thing more so than just producing a rendering. 

CHARLIE BENNETT: This is Lost in the Stacks. Today's show was How to Train Your Algorithm. It was inspired by an exhibit currently installed in the Georgia Tech Library on the second floor of the Crossland Tower. 

MARLEE GIVENS: And our guest was Dr. Christina Shivers, the creator of How to Train Your [INAUDIBLE] Georgia Tech. And you can learn more about this project and other work at christinashivers.com, and that's Christina spelled with a C-H. 

CODY TURNER: You can file this set under QA 76.9.I58I35. 

[TRICERATOPS, "MECHANICAL FRIEND"] 

[MANFRED MANN, "MACHINES"] 

MARLEE GIVENS: Machines by Manfred Mann. And before that, Mechanical Friend by Triceratops. Songs about humans trying to get machines to do what the humans want them to do. 

[MUSIC PLAYING] 

CHARLIE BENNETT: Today's episode is called How to Train Your Algorithm. And to finish the AI and art discussion, I'd like to ask everybody, what's some aspect of creative AI I you would like to interrogate? I'm waiting for the longitudinal study of a set of artists who use AI to see if the qualities of their work begin to become similar to each other. How about you, Marlee? 

MARLEE GIVENS: I'm not that deep today. I need something to do interior design. 

[LAUGHTER] 

CHARLIE BENNETT: You want to know if it works or not? 

MARLEE GIVENS: Well, I'm not really good at design, and I'm worse with 3D spaces. And so I just need something to-- if I give it a vibe, like create a room for me, that would be great. Fred? 

FRED RASCOE: So I think-- well, to start off with, I don't know a whole lot about art criticism, academic study of art. But I do know that no matter what process, or technique, or genre that people rise up and say, ugh, that's not art, it always, always, always turns out to be art in later years. So I'm interested to see where that tipping point comes in with AI-generated creative work. 

CODY TURNER: Yeah, Fred, I'll answer the next. I think AI is going to lead to this era of perfectionism, like everything's perfect. So I'm curious as to what conscious imperfections are going to creep back in once everyone gets used to everything being AI generated. What about you, Alex? 

ALEX MCGEE: Mine's kind of in a similar vein to Charlie's. I'm curious to see how much theft there is of other people's work in AI, especially with artists. I follow this cake decorator, actually, and she regularly calls out AI for then creating similar things that people are circulating and passing off as her own, and also creating outlandish expectations for people actually doing this work. 

CHARLIE BENNETT: That could be like a poetry degree-- the words we use to describe theft, and take, and use. 

[CHUCKLING] 

Let's just roll the credits, man. 

[MUSIC PLAYING] 

MARLEE GIVENS: Lost in the Stacks is a collaboration between WREK Atlanta and the Georgia Tech Library, written and produced by Alex McGee, Charlie Bennett, Fred Rascoe, and Marlee Givens. Legal counsel and a set of anti-surveillance noise masks were provided by the Burroughs Intellectual Property Law Group in Atlanta, Georgia. 

CHARLIE BENNETT: Special thanks to Christina for being on the show, to Kirk Henderson and Connor Lynch for inspiring the episode, and also for Connor running to see what the name of things were. To Quincy Thomas for the interview audio. And thanks, as always, to each and every one of you for listening. 

MARLEE GIVENS: Our web page is library.gatech.edu/lostinthestacks, where you'll find our most recent episode, a link to our podcast feed, and a web form if you want to get in touch with us. 

CHARLIE BENNETT: Next week's show is our last GT library guidebook episode for the semester. We're checking out the info desk. 

FRED RASCOE: It's time for our last song today. Humans will never be completely removed from the architectural design process. 

CHARLIE BENNETT: You hope. 

FRED RASCOE: Right? But automated tools like AI will inevitably be incorporated into our processes, into our designs, into our world. So let's close with a track about humans coexisting with technology and making the best of it. This is Our World by The Individuals right here on Lost in the Stacks. And have a great weekend, everybody. 

[MUSIC PLAYING]