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Peter Bauman: Hello everybody, and welcome to this Le Random discussion following the release of Chapter 8 of our Generative Art Timeline, and that was covering the decade of the 2000s. I'm your host, Peter Bauman, or Monk Antony, the editor-in-chief at Le Random. And joining us today are the artists and the thinkers and the writers who lived art history in the decade of the 2000s, and they include Christiane Paul, Casey Reas, Christa Sommerer and Golan Levin. And then also joining us from the Le Random team are our co-founder, thefunnyguys, and our collection lead, Conrad.
And today we're looking at digital expression in the 2000s, and we're zooming in on this particular decade because at Le Random I've been writing this Generative Art Timeline. Very thankful to Conrad, who's been helping out with adding images. This timeline goes back 70,000 years into pre-modern history. And so I'm going to start off by talking about the first chapter. We've had talks for each chapter so far, and two for the '60s, and this is our talk for the eighth chapter, so we are getting close to the finish. The eighth chapter covers the decade of the 2000s. And I keep calling it that because I'm not sure if there's another way that you refer to this decade, aughts or noughts, so please refer to it however you'd like.
And really we want these discussions to be opportunities to learn from the past and to speak to the people and the artists who were making the history that we're celebrating and learning about today.
So without further ado, those people are, our first guest is Christiane Paul. She is the curator of digital art at the Whitney Museum of American Art and Professor Emerita at the School of Media Studies at the New School. She has written extensively on new media arts and lectured internationally on art and technology. She literally wrote the book Digital Art, which was first published in 2003, and she has written many other texts as well, including A Companion to Digital Art, which came out in 2003. So I think we are very honored to have her as a guest today.
And then our next guest is Casey Reas. He is the co-founder of Processing, the art-centered computer language, which has become the foundation for a vast majority of today's generative art. And we'll talk about why that is today, and part of that is because of all of the time and dedication that Casey and others have put into education and keeping the program free and open source. But Casey is also an artist, and since the early 2000s his work has been showcased around the world with numerous solo and group exhibitions at institutions like MoMA, DAM, Christie's and others like bitforms in New York. Many of his most iconic pieces reside in the permanent collections of major museums, and we are extremely grateful to have him join us for our talk today.
And our next guest is Dr. Christa Sommerer, who is an artist and the professor of the Interface Cultures study program at the Institute for Media at the University of Art and Design in Linz, Austria. Her works have been created largely in collaboration with Laurent Mignonneau. We are really excited to have Christa on today because her work explores artificial life and the intermediate field of art, science and technology. A lot of it is based on simulations, and the work has been developed in creative environments for interaction and really involves participation from the audience and viewers. So in a lot of ways I think Christa and Laurent's work from the '90s and 2000s is the artistic forebear for a lot of today's AI art, and so we're really excited to have Christa on today.
And then Golan Levin. Golan Levin is the professor of electronic art at the School of Art at Carnegie Mellon University, where his pedagogy is concerned with reclaiming computation as a medium of personal expression. He has been active in software art since 1995 and his work has been included in the permanent collections of venues like [inaudible].
It's really great to learn more about our guests, but now it's time to hear more from them directly. Maybe we can start with Christiane. It's very convenient that, Christiane, you wrote a book, and the title of the book is Digital Art, and it came out originally, at least, in the decade that we're focusing on today. So I wonder if you could tell us about how did it end up in 2003 that you wrote that book, and what was the scope of the book back then, and why did you choose that particular scope? And again, thank you so much for joining us.
Christiane Paul: Thank you for inviting me, and it's such a pleasure to be here with artists I've been working with for a long time.
So I think in the early 2000s, we were once again in one of the upswings of digital art and a lot of interest in it, to a point where Thames & Hudson, the publisher of Digital Art, decided to include a volume on digital art and on internet art in their World of Art series. And that originally led to the publication of that book. And yeah, you mentioned it. It came out in its fourth edition last year in 2023, and also has been translated into six languages at this point. So it has longevity.
But in the original edition, I was looking at the history of digital art from the early days, from the algorithms of the 1960s and the generative art of that time until that point. If you look at the fourth edition, then you're seeing work up to, I think, 2022. So the scope has always been to trace digital art throughout the decades.
Peter Bauman: Yeah, thank you for the further introduction. And I have a question also for Casey. Casey, really, it's incredibly important to have you with us today as the co-founder of Processing. And it was also so instrumental in this decade, as it continues to be two decades later. And I wonder if you can talk about DBN, or Design by Numbers, and that transition to Processing at MIT when you were studying under John Maeda. What were you and Ben with Processing looking to expand upon from John's Design by Numbers?
Casey Reas: Sure, thanks Peter. I think an interesting thing about this group is I think we've all known each other for this full time, since around 2000, and been in dialogue for this entire time too, more or less. Golan was also at the Media Lab at the same time that I was there. He arrived a year before me.
John Maeda, who was the director of the Aesthetics and Computation Group, first released Design by Numbers, I think in 1999. And he was the author and engineer of the first version. And his vision for that was to make coding accessible. And one way he did that was through the language itself, but also making it more minimal. And so it was black and white only. It was 100 by 100 pixels. And because it was so minimal in the visual constructions you could make, the language was very short, was very quick to learn. We could sit down with someone who'd never coded before, and within a half hour, within an hour, people were making things. And I think that was the most extraordinary thing about Design by Numbers.
And then a lot of us started teaching with it. Me, Ben Fry, Elise Co, Golan, we started teaching with DBN. And we noticed that after that first day or the first week of people using it, they really wanted to express themselves in visual ways that extended beyond that 100 by 100 pixel grayscale box.
And so the idea of Processing, as Ben Fry and I were starting that in the spring of 2001, was really to make Processing as approachable as Design by Numbers, to have it be minimal, to allow people to start coding very quickly, but to continue to expand beyond that, to go full screen, to go into color, to go into 3D. That was the original idea. And I feel really confident saying that there's no way Processing would exist without Design by Numbers being there first, and also John really pushing Ben and I both into Design by Numbers.
So after John worked on DBN, then Tom White had another round at the engineering behind it, and then Ben picked it up. And it was through Ben picking up Design by Numbers at the code base level, and me originally writing what we called the courseware, which is the educational software around DBN. It was that direct engagement that John had moved us into that led to the ideas around Processing.
Golan Levin: I wanted to say something about Processing, but also more generally, what happened around the year 2000 with Processing and DBN that I think is important. Casey, I think, doesn't give himself enough credit in terms of just saying, oh, we wanted to add color and full screen graphics to DBN. Because I think what the insight was with DBN and Processing was a reaction, I think, to mid-1990s toolkits for artists. And I'm thinking specifically of Macromedia Director and Flash, and the kind of constraints on artists that those corporate tools basically made in terms of what the circumscribed artist is not being able to make.
With tools like Processing and DBN, suddenly you could make any arbitrary polygon, which was not possible with those earlier tools. You could suddenly have direct pixel access. You could say, make this pixel red. And previously those tools had a conceptual model for what an artist might want to make that was really, really limited, and basically involved the presentation of fixed media objects like ready-made videos, canned audio and ready-made digital images that were typically photographs that came out of 1990s CD-ROM multimedia.
And what we saw happening with DBN and Processing was a kind of, I think, clawing back of what the computer could actually do, in terms of allowing artists who were interested in [inaudible].
Peter Bauman: Processing has become, so its use has become so ubiquitous, but in a lot of ways, that's not giving Processing credit for the fact that it was free and open source and also solving a lot of those structural issues that you were talking about, Golan.
Conrad House: Yeah, I think it was a good transition to Christa here, and how she was at MIT during 2001 working at the Center for Advanced Visual Studies. And maybe Christa can touch on a bit more of what she was working on there. And it'll be interesting to know if any of you encountered each other or discussed what you were working on at the time, and if there was open dialogue between these areas of visual studies and computational design.
Christa Sommerer: Yeah, thank you, everybody. I'm very happy to be here with you. Yeah, it's a good question. Actually, our journey together with Laurent Mignonneau, a French artist and also developer, started in 1992 in Frankfurt, where we met at Peter Weibel's Institute for New Media. And there, artists like us were able to work with back then quite advanced computers called Silicon Graphics computers. And we could also use these computers and program visual graphics by ourselves. So in that sense, it was a very unique situation, because we could have access to these high-end graphic computers and also experiment with the technology there, and develop code by ourselves. And especially Laurent, who had already programmed since his early childhood, was able to work with growing algorithms.
Then at 1993, we were very lucky to be at Ars Electronica at the festival, which was dedicated to artificial life. And when we saw the projects there and also listened to the lectures by Christopher Langton, there was Larry Yaeger, there was Karl Sims, we really got [inaudible] some forms of artificial evolution. This was the starting point for Laurent and myself.
And the time that you refer to at MIT Media Lab, this was Steve Benton, who I think passed away long time ago. We were some artist in residency there for half a year, but I don't think that we actually met there, Casey and Golan. I think the time when we met was more at Ars Electronica, from what I remember, for sure at the Code festival in Ars Electronica, 2003.
Casey Reas: The 2003 Code festival at Ars Electronica was a big one for a lot of things, yeah.
Christa Sommerer: And I think, Golan, you were also an artist in residency at Ars Electronica Lab, at Future Lab, from what I remember.
Golan Levin: For the early 2000s, I spent my summers there doing various projects. That's right.
Christa Sommerer: Exactly. Yeah. So we kept meeting in different places and also exhibitions, of course. And Christiane, we know each other, I think, also since the early 1990s already, where we met at different festivals. And also, I remember that Christiane exhibited our Evolve, the interactive pool, in Boston. Was it Boston? Yeah, it was in Boston, I think. And that was also a really wonderful experience.
So yes, we have been meeting. And of course, we know very well the work of each other. And our students are also using Processing. So I think it's really a very awesome teaching tool, and also a very good way for artists who are not programming directly by themselves, a good way of getting into code and making really cool artwork. So it's a very wonderful, wonderful tool.
Christiane Paul: Yeah, zooming out a bit and connecting the dots between all of those great contributions. I think there were some significant shifts between the '90s and 2000s that also really put generative art into a new phase, a new category. Of course, there was the excitement of the web in the '90s. There were early AI projects that were happening, but not only due to computing power, but also the whole social environment, of social media coming about in 2003. And this focus on databases and database aesthetics, I think we entered a new phase.
And it's also indicative that during that period, I commissioned works by Casey and by Golan for the Whitney's Artport website. And once again, it was this time of data visualization gaining a lot of traction in the generative realm. And Golan did terrific pieces. The Dumpster, I think you were also included in the Whitney Biennial with one of them. Casey really connected the dots when it came to early generative art with the focus on conceptual art practices and the connection of generative art to that. And we commissioned his Software Structures.
I could not work with Christa at the Whitney Museum of American Art, but we did indeed work on a show together where Evolve was exhibited in the early 2000s, 2004, in Boston at a gallery there, which also included a lot of generative art. And this idea of artificial life really entered a new phase at that time.
Conrad House: While we're on topic with Artport, Christiane, and you've really helped lead that initiative since the early 2001, being one of the main curatorial visions for the project. And the internet is something that's ever evolving, and especially over the last two decades has drastically changed. So I'm just curious to see if there has been any change. How has that curatorial mission or vision changed for Artport throughout this time? And maybe some of your favorite highlights for your work that you've done at Artport.
Christiane Paul: So that's a great question. The curatorial mission has not changed at all, because we always saw Artport as a platform that would chronicle the evolution of art on the web. So basically, we put this platform into a position where it was an observer. But during that process of observation, a lot changed over the decades, definitely. And it's really interesting to look at the pieces.
We started with a series called Gate Pages, and that was the time of splash pages, before pop-up windows were being consistently blocked. There were so many art websites doing splash pages, and the gate pages were meant to be an introduction to artists' work, and many of the artists did really exciting mini pieces during that time for those pages.
And then if you look at Artport, which of course commissioned in the beginning only a couple of projects per year, now it's way more consistent, you can still make out certain types of narratives in the works, mentioning once again Casey's and Golan's works. And that's very different from the current biennial project that is on Artport curated by Meg Onli and Chrissie Iles, that is very much focused on AI and essentially is a LoRA for Stable Diffusion. Very different world from the early 2000s.
Casey Reas: So many things to jump in about. I think it was that time in the early 2000s also where code was able to run in the browser in a new way. I think through things like Java applets, through things like Flash. The idea of that was that people were making things, releasing it on a daily basis, on a weekly basis, and things were just spreading across the world. People were seeing generative art running in the browser in a really substantial way. There was this idea of view source, this idea of sharing the code with each other. And that just was a really strong ethos in the world. And I think allowed these things to grow very, very quickly.
I think before, like Christa mentioned, these Silicon Graphics machines, these are $50,000, $200,000 computers. The work could only be seen in the museum. And now all of a sudden people could see generative work anywhere they were, with an internet connection. And I think that allowed this stuff to spread very, very quickly. And that happened at scale in the early 2000s.
Golan Levin: I wanted to also emphasize, I mean, Artport was really significant in supporting and collecting this kind of work. But to underscore Christiane's point, what we started to see was not just that there could be interactive graphics in a rectangle in the browser, but also that all of those graphics started to use the internet as its subject as well. That the networked condition, the condition of being in a network and having connections to each other, was suddenly reflected as a subject matter of the material. And you would see this in works like Josh On's They Rule, or you'd see it in works like The Secret Lives of Numbers.
“The idea of that was that people were making things, releasing it on a daily basis, on a weekly basis, and things were just spreading across the world.” — Casey Reas 22:37
And you might call these works, I think, this kind of way of working where there's an interest also in very large databases, whether accessing them or creating them, was also something that, as Christiane pointed out, arose at that time. I think today there's a name for it. Sam Lavigne calls it scrapism, right? This kind of way of acquiring large amounts of data by hook and by crook and then presenting it back to the public as a mirror of society. But that really became possible at a very different scale in the early 2000s, where suddenly you could, like, I did write a program that would scrape a million numbers and then present it in a browser, and then people could experience it and understand something about society that they couldn't understand or see before.
Christiane Paul: Just a quick footnote. In the '90s, you had that, let's say, impulse too. There was a lot of recycling of information on the web going on. But to Golan's point, scale is really key here. In the early 2000s, this just entered a completely different scale compared to the '90s and its recycling of web pages. That wasn't yet scrapism. And at that point, data was wide open. It was pre-Snowden. It was pre-deep concerns about privacy and surveillance. And that was a huge difference at that moment than what's been happening in the last decade.
Christa Sommerer: Maybe if I could add to it from my observation, I would say that in the early '90s this was a very small group of people who was very internationally connected, but it was a small group of artists that met at the festivals, at SIGGRAPH, at ISEA, at Ars Electronica. And then in 2000, suddenly more people joined in. And it's certainly also due to the tools that were available. But also, I think at that time already the first graduates came out of the different universities. And so I think academia also played a big role, because suddenly we had more young people that were involved in computer art creation. And then, of course, later on at the end of 2000, these people were becoming professors themselves. So this whole academic field also, I think, had a huge impact on the sustainability and also on the diversification of media art and digital art.
Peter Bauman: One thing about the education, I think it's a really good point. And something I do want to talk about is I was talking to Karsten Schmidt, who's known as Toxi, and he was really telling me about the importance of what Processing did with education, is that it didn't make these institutions or these students reliant on commercial software anymore. So they had this free and open source software available, and how that really changed the way it was taught. Because now suddenly it can be taught basically for free. Before it was very expensive to acquire all those licenses. It was a very expensive tool for Macromedia and for Adobe.
Casey Reas: Just really briefly, I'd like to say I think even more important than the cost of that is that as artists, we're making our own tools and we're forming them based on what we want them to do, rather than relying on the corporate entities to imagine what we want to do and to release that. I think having control over our own tools is the most essential thing about that for me. Golan's very articulate about that.
Golan Levin: I'm an evangelist for a long time. I'm a fan of whatever Casey's doing. But yeah, no, I mean, the open source software tools for the arts really blossomed in that decade. Something that we should also not neglect is the birth of Arduino roughly in 2005 at Ivrea, which was students of Casey's at the time who were working on it. It came out of a system called Wiring before that.
I was just a couple of weeks ago talking to a very high placed person at the National Science Foundation here in the United States. And I mentioned, well, Arduino, which is widely used in every mechanical and engineering department, every robotics department, every STEM type makerspace. I was like, Arduino started as a project by artists, and they did not know that. And I felt like we should probably underscore that, because the way that Arduino, for example, has penetrated into STEM spaces, its history as having emerged from the arts, because tools like BASIC Stamp at the time did not meet the needs of artists, were not easy to learn to use, were not artist friendly, should not be forgotten. And I think we'll see this again when we start to see the Processing philosophy begin to really shape computer science education, which I think it's very, very well poised to do.
Peter Bauman: Yeah, Golan, I wonder if we could talk a little bit more about the work that you were doing in the early part of this decade that we're looking at. So what I love about it is just how unique and diverse the work was. I mean, work like Telesymphony, where you orchestrated an audience's mobile phones to ring in unison, or The Alphabet Synthesis Machine. These projects are all very different. They all involve a lot of audience participation, but they have software at their heart. And I'm wondering how you, what do you see as maybe tying those projects together, and how do you see them aligning with the major themes of the decade that we've talked about, which are these kind of increases in tooling but also things like interactivity and the rise of social and mobile phones, and any kind of theme from the decade?
Golan Levin: I'll try and keep this brief because I've already had the privilege of speaking a bunch, but I consider myself something of a generalist in new media. And for that reason, the work I do doesn't really fit well within any kind of one category. I've been interested in generativity, interactivity, the network condition, data visualization, live performance.
As I mentioned, I really felt the shackles of something like Macromedia Director in the mid-1990s. And I just wanted to make blobs, and there was no way of doing so. And so some of the work like my Audiovisual Environment Suite, which I made as my master's thesis with John Maeda at MIT, was about just kind of exploring or demonstrating or both the plasticity, the real plasticity of digital media in ways that I think the commercial tools didn't allow. And part of that was an aesthetic and formal kind of goal of sort of like, let's make really interesting blobs. And part of that was a kind of maybe almost a political statement about what the commercial tools couldn't do, and to kind of show another path.
Performances, I did a lot of performances in the early 2000s. And I think that one reason was because it was actually very difficult to do full screen impressive audiovisual, real time audiovisual synthesis and graphics in the browser. Even though it became newly possible to do some degree of that, to really make immersive experiences in the browser was still quite difficult, and maybe even is still kind of difficult today. And so performances became a way that I could do that.
I would say I never wanted to achieve the kind of aesthetic perfection that somebody like Ryoji Ikeda focuses on. But rather, I was sort of always interested in conceptual propositions about what form could do and what plastic media could achieve. And so Telesymphony was a sort of conceptual study about what happens if we can control the audience's mobile phones. I did a project with a Dutch, two performers, two musicians, two performers, Jaap Blonk and Joan La Barbara, sort of saying, what if we could visualize the voice in real time ways. And these performances were conceptual propositions sort of exposing what media could be like. And I mean, if I had to tie it all together, I would say I think what a job of a media artist can be is kind of exploring what future media might be like, or exposing the new aesthetics and new politics made possible by new technologies.
Casey Reas: It's a really interesting thing. And I think it's an interesting question how that gets shaped when, in the '60s, there's maybe 10 people making art with computers, in the '70s there's 100, in the '80s there's 1,000, and in the '90s there's 10,000. And what's expressed really changes when the number of people making art in this way is exponentially going up, and suddenly using computers is no longer such a special thing, or even such a kind of rejected thing as it was in 1968 or something.
Conrad House: Yeah. I really like how you describe yourself as a generalist of new media. You don't like to tie yourself down to any one particular thing, just kind of explore what you think is really fun. But I think one thing that is at least commonly seen is systems-based approaches to creating some type of interactive art or generative art, whatever it may be.
And maybe I think on this note, we can maybe jump to Christiane and talk about, I think you recently talked with Peter about how the interest in technology [inaudible] of apathy. And we kind of see this throughout the '60s, throughout the '80s, '90s. Do you see in today's contemporary space, do you see us having a broader interest that's growing? Or do you see us kind of having a correction to this highly, I guess, investor-interested spike that we saw with the 2021, 2022 wave of this NFT space having these drastic economic implications?
Christiane Paul: Yeah, you're absolutely right. There always are the waves of digital art and interest in digital art also, or mostly institutionally, because the practitioners, of course, keep going. It's more the art world per se or other entities paying attention or not. And I would say that we're definitely still very much in a high due to AI and for digital art. I don't see that going away anytime soon.
And what all of us have been seeing and preaching for decades is the continuous digitization of our lives that has always been ongoing, no matter who paid interest. And I think we probably reached a critical moment where that is just not going away.
Predictably, the whole NFT hype collapsed a lot. Good. I think that's what most of us were waiting for. That doesn't mean that artists aren't doing interesting work on the blockchain. I mean, I think it's a more interesting space now because artists working in that way are much more committed to generativity, to on-chain work. I mean, Casey did a great job with Feral File, putting great practitioners to the fore. It's not all about JPEGs and spinning MP4s hanging on the blockchain anymore.
And once again, I think it's just inextricably tied to economic factors. And at this point, I can see so many people, the trustees of museums, suddenly being very interested in the space, not only for art historical reasons, but because they see a real market impact of all of it. And I think that also uniquely positions digital art as a medium to critically reflect on that and provide a reality check. But yeah, I would say we're in a high upside of the curve, and I don't see it collapsing in the near future.
Conrad House: Yeah, that's great. I think the touch on the interest in AI and how that's really grown drastically recently. And we talked about Artport and Whitney working with Holly Herndon recently to showcase some of her work and collection, and even interactiveness with allowing viewers of the project to work with Stable Diffusion and come out with their own outputs. But maybe we can jump over to Christa and have her maybe expand a bit more on the projects we've talked about, Evolve and Life Writer and Mobile Feelings, and maybe how you see those as potential predecessors to what we see today with AI art. I think a big part of this also is the definition of AI art is ever changing. And there's kind of a lot of subcategories of what we see as AI art or artificial life, or whatever you want to call it. So maybe expand a bit more on that and how you see that as acting before what we see today.
Christa Sommerer: Yeah, thank you, Conrad, for your question. Yes, it's quite interesting. I think that's a good point, because in the early '90s we made these works that are very specifically dealing with generative algorithms and artificial life and evolution. And several of these works are now actually right now on display at our big retrospective exhibition, which was at the ZKM in Karlsruhe, then here in Linz at Ars Electronica, then in Brussels and right now in Bilbao.
And what we can observe is, from the perception of people when they experience this work, when they interact with the work, nothing has changed. And that's quite astonishing, because some of these works are 30 years old. And so what we are always really surprised about is digital art doesn't really age much, because when the code is working, or when the interaction is working, if you keep it presenting the way it was, it's actually still very fresh. And also the people's interaction or curiosity towards the work, or the way they engage with the work, is still the same. So in that sense, I think that's quite surprising to us and also astonishing.
But of course we have to see also that the context has changed now. Maybe Christiane, you remember probably quite well, at the beginning of the '90s people were in awe when something moved on the computer, or they were not used to have computers. Of course, nowadays everyone has mobile phone in their pocket and most people are super media savvy. So even though they are so used to have technology mostly invading, or in every part of their life, they are still in a way open to deal with media art that is talking about life, that talks about evolution, that talks about generativity, that talks about learning processes. So I think if you keep working on the concepts of the work and maybe the message in a way, then these works don't really age, and that's a big surprise to us.
And coming back to your question about AI and A-Life connection, I was just digging out some of the early publications on A-Life. There was a lot of conferences. Christopher Langton was the main editor of these books back then at the Santa Fe Institute. And if you read these texts here, for example, there's one from Charles Taylor, when you read the definitions that they gave and also the predictions that they made about the future, it's exactly what we see now with AI as well. So I think there's not that much difference between the discussions that we had in the early '90s about A-Life and the discussions we are having now about AI, because at the end of the day, I think it's about automatic processes. It's about creation. It's about how can we learn principles of creation, and how can artists, I mean, from an artistic point of view, how can artists use this?
What I see, however, and I don't know, this would be a very interesting question I have to Christiane, Golan and Casey, since you're all teaching. What I see now, however, is some kind of big fear among art students about AI. And I often heard, oh, my God, I think I'm going to give up my artistic practice because AI can do it much better, and I don't see any more need of doing anything. And this is for me a bit shocking to hear that from young media artists, that they are starting to feel overwhelmed by AI technology instead of trying to shape it and make it fit their needs. So this would be something I'm super curious. Maybe it's a very different situation in the United States. But here I see that more and more art students become quite critical about this automatic creation using AI systems.
Christiane Paul: Yeah. So I want to add to that on two fronts. First of all, coming back and adding to your points about the overlaps between A-Life and AI. I think those are mainly in several areas: both fields modeling life-like biological processes, which AI uses to develop neural networks and evolutionary algorithms; then the study of complex systems and the emergence of complex behaviors; and the use of optimization techniques, for example, to determine fitness. I think those are the main areas of overlap.
To your question in terms of practice, I would also say that I see not necessarily fear, but really students being turned off by AI software and technologies. First of all, I believe that still is a huge misunderstanding of what AI art is and can be. Because if you really see it as text-to-image models that generate output on the basics of a simple prompt, I would hardly call art in any way. They are insta-kitsch engines when it comes to that. And all the artists doing great work, such as Casey, for example, it requires a lot of training of models on specific data sets. It requires even working with prompts, a lot of tweaking and massaging of code, of models, to do something that is truly transformative and reflects on these systems. And I think there's huge potential in that.
What I have seen among students, and also young visitors to the Harold Cohen exhibition that I curated for the Whitney that is still on view, is them being completely turned off by the aesthetics of those softwares, which they absolutely hate, just because of the kind of blurry extrapolation, uncanny kind of feeling. And you can still see the training data sets and this normative aesthetics in them. But they loved Harold Cohen, for example. And so that was an expression of AI encoded by an artist that they were very much attracted to. And I think that's a really good example.
So I would definitely say that I have seen the same kind of criticality among students of the current softwares. And I think it would be unfortunate if they get turned away and do not realize that these are also very interesting tools to use, and that it's an area that badly needs them to reflect on these tools and their implications on all levels.
“Because if you really see it as text-to-image models that generate output on the basics of a simple prompt, I would hardly call art in any way. They are insta-kitsch engines when it comes to that.” — Christiane Paul 42:44
Casey Reas: And I think that the impact of AI is so multifaceted and so complicated. And there's such amazing, interesting things that are happening and such dreadful and awful things that I'm like, where to even begin. It's impacting culture in lots and lots of ways. And of course artists should be dealing with that. But it's all the best and all the worst all wrapped up in one. Yeah, I think I have a lot swimming around. I think that's a really vague.
But I think the 1960s was the moment for the birth of the ideas around AI. The 1990s were a huge surge in artificial life. I think a lot of artists, myself included, Christa's works that I've seen with Laurent, were really inspired by that '90s artificial life research. And for me, that was all expressed in the early 2000s. I had a class with a computer, sorry, a robotics professor named Rodney Brooks. He wrote this book called Cambrian Intelligence. And I think the fundamental idea of that book is, let's stop thinking about intelligence like chess playing intelligence, and let's think about behaviors and simulation of behaviors. And if we can get to the simulation of bugs and insects and things like that, we're actually going to be much closer to intelligence than if we focus on higher level processes. And so for me, that was the idea that cracked open a lot of things that I spent a decade exploring. And I believe a lot of Christa's installations were like that. What if art can mutate? What if art can evolve? These ideas, I think, which are very different from working with painting and drawing, were able to emerge through software as a medium at these moments.
Conrad House: Yeah. And I think Christiane really just hits the target perfectly. I think a lot of this contemporary stigma against it can be maybe driven towards those text-to-image prompts, and maybe seeing like the effort isn't always there sometimes, is what I think a lot of people critique it for. But I think what Christa just said is, if the message is strong in the work, it kind of creates a timeless environment around the piece. And if it's conceptually strong, I think it's really important. And just like Christiane also said, artists that are able to create their own neural networks and work with their own data sets. So looking at people like Sofia Crespo and Anna Ridler and Casey, I think just that little bit of effort and maybe more artist's hand in the work, not so much working with a black box system, can create a lot more appreciation for the work that's been created in it.
I want to maybe touch to Golan. You had this opening statement with your Creative Dialogue episode with Claire Hentschker, and you mentioned this idea that some people maybe see AI as an end to visual culture. And I feel like this is a stigma. And I think you also mentioned that this is a stigma that's constantly proven wrong over and over again. It's applied to many other things. But is this a stigma that you maybe felt in the 2000s from outside viewers or outside critics regarding not just AI art, but maybe any kind of computer digital art that you were creating at the time?
Golan Levin: In the early 2000s, I certainly felt like things were cracked wide open, because it suddenly became possible to do interactive, real-time, dynamic form. Certainly in 2D and also to an extent in 3D.
I think AI, one of the most positive experiences I've ever had with AI was actually with Casey. When Midjourney was brand new, we were both there in the Discord together. And we were just basically one-upping each other, riffing on each other's prompts. So I would say something like chocolate chip sculpture, and Casey would respond with, with sprinkles or something like that. And yes, it was amazing that it could make these things.
But to me, the really big innovation of Midjourney, which they've never sort of like, I mean, Joel Simon has kind of picked up on this more than they have, is this sort of the weird social space that it created of people kind of exchanging images back and forth for fun that were sort of made on the spot as they realized their imagination in pictures of ridiculous and nonsensical things that looked real enough to be funny.
Was that the end of visual? I think we're closer to the end of visual culture when we have a condition now that Christiane politely used the word normative. But it's just this regurgitated stuff that is this kind of every culture chopped up and pureed and kind of represented in this very average way.
I'm quite hopeful that culture will proceed. Nick Cave had a great quote about AI in his many articles, the singer, sort of saying, AI might make a good song, but it'll never make a great one because it literally lacks the nerve. What we like when we like a great song, and I'm kind of interpolating Nick Cave here, is we like the voice of the person that we're hearing. We like the connection to a real person.
And this goes back to what Christa said before. I might like a piece of AI art, but not because it's a pretty image. It's like, oh, that stimulates all my neurons in the right way. But rather because I'm actually hearing the voice of the creative person behind it, whether it might be an interesting conceptual proposition or unique aesthetic that they were able to achieve by working it in ways that other people didn't put in the time to do. I'm connecting with a human who is using a tool in an interesting way.
And I think one of the things I like best about the best digital artists, and I'm sitting in front of some of them, right, is they make work that is like nobody else's. I know the lion by the mark of their claw. I can see a piece of Casey's. For a while, Casey had an anonymous identity online. I didn't know, it was just this, didn't say who it was, but Casey was releasing work under this anonymous name. And I was like, that shit looks a lot like Casey's, to the point where no one else could make work like that. I was like, I know the lion by the mark of his claw. And I liked the work because it was attractive, but I also liked the work because it was Casey's voice. And I think there's lots of ways that we can appreciate people's voices, but I don't think there'll be any end to that.
“What we like when we like a great song, and I'm kind of interpolating Nick Cave here, is we like the voice of the person that we're hearing. We like the connection to a real person.” — Golan Levin 50:05
Christiane Paul: And I actually have been reading that same Nick Cave quote to my students often, and he specifically references Nina Simone and Kurt Cobain. And that kind of lived experience of a life that filters through in the music in this case, and that embodied experience and context and understanding is something AI just cannot have ever. And if you don't reinsert it through an artist, then it all becomes generic, or yeah, the imitation game.
Conrad House: It's just, these conversations around these decades are so fascinating, because a few conversations ago we were talking about mainframe computers with very limited computing power. Now we're talking about very advanced AI systems. And of course, as all of you know, this is powered through Moore's law, which has powered all these decades of digital art history.
And I have a question specifically for Casey. In this decade that we're in, the 2000s you were discussing, Moore's law also continues. There's a 20X increase in computing power. And I just wonder if this significant leap, if it increased the capabilities of the Processing software throughout the decades. Was there certain features that were possible at the end of the decades that weren't possible at the start? And if it also led to an increased expressivity for you as an individual artist working with software?
Casey Reas: Yes, for sure. I think a really huge shift happened in the very late 1990s with GPU technology. And so we talked a little, or I talked a little before, about these SGI machines that were very exclusive, very hard to get access to. And now all of a sudden a Windows box with a good graphics card and a GPU could produce equivalent work. And so that made it much easier for people to get access to the kinds of machines they needed to express themselves or build what they really wanted to build. And so these moments of access, technical access, are really essential.
When Processing was first begun in 2001, it was made as a sketching language. We called it a sketchbook. And I think that was one of the primary ideas of the software. But also you would make these really minimal kind of small sketches, and then you would take what you learned from that and you would port that code to C++ in order to really run it in a quick, high fidelity way. And then over the course of the 2000s, Processing became more and more capable as computers became more capable, as the software developed. And then it no longer was a sketching environment. It was sort of a full production environment where you could start sketching in Processing and then keep the software going and going and going to the final instance.
So that was a major shift in the way that I think I thought, and a lot of people thought, about Processing. But significantly the free software, the community part of Processing, really extended that. So making libraries for Processing was a really important early thing that allowed other people to contribute what they were experts in to the source code. So Ben and I were graphics people, but other people were computer vision people, audio people, simulation people, et cetera. People like Karsten Schmidt, Toxi, contributed a lot to the Processing source code.
And in my own work, if I needed to integrate, so I wanted to track people in the environment for doing an interactive performance piece, all of a sudden there were libraries for Processing that other people had made that I could use in my own work. So it allowed a lot of people to extend their practice through that sharing and through that community development.
Peter Bauman: Yeah, I mean, that ethos I think is so important and maybe doesn't get talked about enough. And again, yeah, it was something that Karsten, when I was speaking to him, really drove home, is that ethos that dates back to Ivan Illich and the early computer programmers and early computer theorists. And was that something that was explicitly on your mind with Processing, Casey, with that ethos that you've mentioned before? And I know that it was explicitly embedded into the kind of verbiage of Processing itself with FLOSS. And maybe you can explain that too.
But I also just think that you're talking about access, and this decade was so important with access, because it's when really smartphones were launched and when Processing too gave so many people more access to software. So yeah, I'm wondering if you could talk a bit more about that ethos, and then maybe we can all close with thinking about maybe what some of these major themes are from this decade, or what some of the main takeaways from this decade are.
Casey Reas: Yeah, no. Software code being open for people to read, have access to, is as long as code is being written, and it wasn't until later that code began to be launched. It's as if that code has been created as an incomplete version of your code, that your code has to be locked down and proprietary.
And so Processing wouldn't have been possible to make without other open-source code libraries that was built on top. The idea is that you have the set of modular pieces that can be put together in different ways. And so Processing has a free open-source license in the same way that lots of the software that comprise it do as well. And that kind of carries forward.
Christiane Paul: Yeah, it brought about major shifts technologically and what was accessible to people, new software tools that really expanded the range. As Christa pointed out, I think we also really saw a change in the landscape due to the new wave of students graduating from schools carrying that practice further. We saw at least the beginnings of big data, not as we are experiencing it today and really nurturing the current AI waves, but this whole idea of more massive data sets and what they meant for artistic practice or so really brought a change to generativity.
So I think the 2000s really brought about a new level, a new level of understanding technologies, also very much due to social media and connectivity, not necessarily communication, reaching a new level on different types of platforms with all of their potential and problems.
Golan Levin: I wanted to just toss in a really quick comment. A big difference between me now and me in the 2000s is I'm now the parent of teenagers. My kids were born in the same year as Twitter, and they've only known the internet to get worse and worse. So they actually hate computers, which is really interesting to me. My older kid hates computers, and like their grandfather, like grandfathers actually, is more like an engraver and an architect with traditional analog media, wants to learn real instruments and tools. So I do see a strange, interesting backlash coming against the kind of generation that does not have the tools to do that.
Maybe look, as we look back, to not only see how the seeds of today were planted then, but also to sort of check to see what sorts of concepts we've maybe left behind and kind of await rediscovery. I was looking at the timeline and I'm privileged to be in it, and I thought it was great, Peter. But I also thought, oh yeah, where's Blast Theory? Where's all that ephemeral stuff that was not, as someone recently put it, a proposition for interior decor or a financial instrument, but where's this kind of weird experience you have out in the streets of a city that technology made possible? So I wait, thinking about what did we lose from that decade that maybe we need to recover.
Christa Sommerer: Yeah, I agree with you, Golan. I think it's really, when I remember the '90s and also 2000, there was this very enthusiastic spirit, this idea of, oh, we are going to change the world, we are going to work with this cool technology and things got better. But now often we see that technology has not always been used in the positive way, and especially with social media, people get problems. Sometimes they are being bullied, or there's a lot of things that we could not anticipate. At least I could not anticipate it. I did not see this coming, I have to say.
So it's understandable that the younger generations are more critical about the technology and sometimes also a little bit more reluctant to use it, and generally feel like they view it with more suspicion than what we did back then. So I think that's interesting. But on the other hand, I think it also means that there is maybe some more bigger need for artists to deal with this sort of social topics on a critical level, but also on a technological level.
So I think Ars Electronica is a very good festival for this. This year, the topic is hope, which I think is very good, in times of war and in times of Ukrainian war and Israeli war and so on. A lot of young people feel like it's a negative spin. Things are kind of very bad, bad news being bombarded on them. And so I think this idea of hope and creating a better future, even though it's just through art and technology, I think is a really good topic that we should look at. So I'm quite hopeful in that sense.
Peter Bauman: Yeah, and I think it's a really good point that our relationship with technology also evolves, just like institutional interest in this kind of art evolves. Like our relationship with technology evolves. People from a different generation were fearful of it because of computers' relationship with war, and lots of movies that were against it. But yes, now we've kind of accepted it more. But now we may be, as Golan was saying, we may be trending in the opposite direction.
And it's probably a good spot to wrap it up. But thank you all, everybody. And what again, what a treat. I mean, what an honor to host such a distinguished panel. And we're really thankful for everybody's time and participation and your thoughts and what you've contributed, of course, as well.
I think Christiane summed it up really well from my perspective. I'm really grateful for bringing us together. Thank you so much. It's really good to see Christa, you. It's been a while. And Golan, we don't see each other enough, for sure.
Golan Levin: Take care, everyone.
Christa Sommerer: Thank you.
Christiane Paul: Thank you, everybody. Thank you so much. Bye bye.
