rewrite this title and make it good for SEO Making Art that Tells the Future — Interview with David Young | MakersPlace Editorial

David Young has built his career at the forefront of emerging technologies, from early internet projects to recent explorations in AI and quantum computing. His work uses technology to create new forms of beauty while encouraging reflection on “the new” and its obsolescence. Holding degrees from MIT’s Media Lab and UC Santa Cruz, Young’s art has been exhibited internationally and featured in collections like the GENAP Collection in Zurich. Based in New York, he continues to innovate at the intersection of art and technology.

In this MakersPlace Spotlight interview, David Young delves into how AI and quantum computing influence his art and challenge our understanding of these technologies. Through projects like Learning Nature and Hallucinations, Young explores how AI “sees” the world and invites us to consider its implications and limitations. In conversation with Brady Walker, Young reflects on his journey, inspirations, and views on today’s rapidly shifting tech landscape.

BW: Welcome to MakersPlace Spotlights. I’m here with AI-based artist David Young. David, thank you for joining us. Maybe you can start with a little about your journey as an artist.

DY: Sure. My background is in computer science, and I studied visual studies at MIT’s Media Lab. I’ve always been enthusiastic about technology’s potential for good, but in recent years, I’ve become concerned about AI’s impact. Social media, for instance, is destroying democracy. So, I began using art to spark deeper conversations about AI, bringing more diverse voices to the table. Art can act as a backdoor, intriguing people visually and leading them to think about the technology behind it.

BW: That’s interesting. In a 2018 essay, you asked, “Can beauty help us imagine new possibilities for AI?” How has your thinking evolved?

DY: We typically view technology in terms of efficiency, optimization, and growth. I wanted to shift that narrative. My Learning Nature series invited AI to explore nature, a setting far from corporate applications, hoping viewers would have a wordless aesthetic experience. That experience can act as a Trojan horse, encouraging people to learn about the technology behind the art. I’m optimistic that grassroots creativity can help shape the future of tech.

BW: How has working with AI influenced your creativity?

DY: Working with AI is funny; we often anthropomorphize it as an intelligent participant, but it’s just code on a machine. My background helps me see through the hype cycles and recognize the opportunism of some developers. We need to view AI for what it is, but we also can’t ignore the cultural excitement around it. My work plays with this duality, showing both AI’s “thinking” and its underlying mechanics. For instance, my Tabula Rasa series highlights the machine-like nature of AI.

BW: In a recent essay, you explored whether AI will truly revolutionize things, comparing it to blockchain’s initial hype.

DY: Exactly. There’s always an obsession with the latest “new thing,” and AI won’t be the last. I explored quantum computing for that reason—it could make technologies like blockchain and NFTs obsolete, turning them into digital dust. It’s another example of how we should approach hyped technologies thoughtfully.

BW: Regarding quantum computing: Are we doomed? From my perspective, the work in NFTs and blockchain has been about raising up artists, raising awareness, and giving digital artists a profile they didn’t have. So, if that work is done when quantum computing comes around and “squashes us,” something good will still have come out of it.

DY: I don’t think quantum computing is going to squash us all. I do agree that NFTs have been fantastic for artists to get their work in front of new audiences and build practices and successful careers. It’s been wonderful for creativity and the diversity of artistic voices. The only challenge with quantum computing is that it makes the underlying platform less secure. Eventually, we’ll need new fixes or patches to restore the security we need.

BW: What does studying Visual Studies at MIT involve? Is it like an art degree with computers?

DY: It was hands-on. I was in the Media Lab, founded by Nicholas Negroponte to invent the future of media. When I was there in the late ’80s and early ’90s, the group I was in invented anti-aliased text and explored the screen as a medium, which was revolutionary. Led by Muriel Cooper, we worked in a chaotic, open space with advanced tech and the directive to “invent something amazing.” My AI background had me thinking about how AI might impact visualizing information. Much of the tech we use today emerged from this early exploration.

BW: Has your aesthetic sensibility evolved since working with AI?

DY: Interesting question. Working with AI is different from writing traditional code. With code, you create an image through procedural, rule-based processes, so the results, however complex, are traceable. With AI, you feed it images, and it develops an understanding based on that—but its “thinking” remains impenetrable.

In terms of aesthetic evolution, I’ve developed an intuition for what the AI is doing and how to guide it. I approach AI as a user, not a technical expert, encouraging others to do the same. Creating with AI involves a unique collaboration—it’s not just code, but a tool you work with to explore new visual expressions.

BW: I use AI all the time for work and fun. It’s interesting—the relationship I’ve developed with it. In some ways, it’s like using a synthesizer; adjust one knob, and you get a different result.

DY: That’s a good analogy. AI is like any other tool—keyboard, camera, or paintbrush. The more skilled you are, the more you can bring out something unique.

BW: Let’s talk about your Hallucinations series. You trained an AI on a few images to explore its “confusion.” What were you hoping to learn?

DY: Hallucinations builds on my earlier work, exploring what it means for AI to “see.” Traditional AI-generated images look recognizable, but I wanted to bring out elements that were invisible at first but become clear when amplified, suggesting the AI sees something different from what we see. This series plays with the idea of AI “hallucinations,” where the machine creates something perceptible to it but not obvious to us.

BW: That reminds me of the book The Immense World, about how animals perceive things differently—like how a peahen experiences a male’s feather display as raucous sound.

DY: Exactly. We tend to think AI sees as we do, but I want to question that assumption. With Hallucinations, I took the idea further to add personal expression, exaggerating subtle patterns to make them visible. The term “hallucination” became popular around this time with systems like ChatGPT, where AI makes up facts by reshuffling learned data. I titled each piece with quotes from tech leaders, reflecting the “hallucinations” they have about AI’s power and infallibility. I wanted the images to be strange, reflecting the glitchiness and non-human vision of AI, showing how different they are from typical outputs.

BW: There’s talk about AI “hallucinations” as models start to get trained on their own output, possibly creating incoherent junk. What’s the future of AI if this continues?

DY: The idea of AI polluting the internet and relearning from it is interesting. We might be at peak AI now, with future models becoming less useful as they’re trained on junk. There’s already so much low-quality content online, AI-generated or clickbait. It feels like everything is shifting.

BW: I wonder if smaller, purpose-driven AI models would be better, avoiding the large-scale pollution issue.

DY: AI will continue to evolve, but we need awareness of its biases and who controls these technologies. My Manipulations series explores how AI “sees” differently. I amplify elements that may be invisible to us but obvious to the machine. The works you’re showing were generated by training AI on only a few solid colors instead of photographs. Limiting the data creates a mix of machine-like grids and organic shapes, revealing AI’s mechanical and organic sides.

My Tabula Rasa series follows the idea of treating AI like a blank mind, giving it minimal data to learn from. This image here was trained on just a couple of solid colors, and I then manipulated the output to reveal more hidden details.

BW: So, you’re saying this is kind of an underlying expression from the AI that you extracted and made your own?

DY: I did it backward. That Tabula Rasa animation you showed a moment ago—that’s from the Tabula Rasa series, where the machine was trained on just a handful of solid colors. It generates an animation of its learning process, moving through what’s called latent space. Its understanding of a few colors creates images that are both organic, with smoky and curvy patterns, and machine-like, with grid-like repetition.

Training the machine on just a couple of solid colors creates these strange, organic patterns. I take an image from this output and manipulate it to pull forward patterns or qualities that are obvious to the machine but invisible to us. That’s what that other image was that you had on the screen.

BW: This piece is just stunning—it’s like watching a machine Rothko its way through.

DY: That’s an interesting response. It raises the question: is there a shared sensibility that makes a machine create something with a quality like Rothko? Some might say there’s a universal consciousness that connects us, the machine, and everything else. But I trained this on a GAN that had just been turned on, with no prior exposure, so it only saw a few solid colors. This might reflect our tendency to see patterns rather than the machine capturing some universal awareness.

BW: You just released some pieces on Verse from your quantum computing investigation called Quantum Drawings. What sparked this series?

DY: Quantum Drawings came from my interest in quantum computing as an emerging technology, like AI, that’s “promised” to change everything. Quantum computing is radically different from any other type of computing—it’s almost incomprehensible. I wanted to experiment with it creatively to develop an intuition for what quantum computing might mean or become.

This approach is similar to my work with AI, where I use off-the-shelf code to explore. For Quantum Drawings, I run code on an IBM quantum computer, then use the output to create visuals.

BW: So you got your hands on a quantum computer? What is the IBM quantum computer?

DY: Now that I’ve noodled around with it, I can talk a bit more about it. Here’s the basic premise of what makes a quantum computer different from a regular computer, and I’ll keep it simple. In a normal computer, the smallest unit of data is a bit, which is either a one or a zero. In a quantum computer, you have a qubit, which exists as both zero and one simultaneously.

Quantum processing is unlike traditional computing because it operates on nearly every possibility at once. Only when you ask the computer, “What is the value of this qubit?” do you get either one or zero. So it’s very different. The promise is that with enough qubits, quantum computers could solve problems in moments that would take a normal computer longer than the age of the universe. Quantum computers will do things that normal computers can’t.

I thought, “This is weird, this is important.” Just as with AI, I don’t think people need to be technical experts in quantum computing. Hopefully, art and visual experiences can make this technology less intimidating and inspire people to want to participate in its future.

BW: I’m curious about your experience. What was the difference between working on an IBM quantum computer and a traditional computer? Like with AI, where you aim to give people an aesthetic experience—what’s different about this?

DY: What struck me about emerging technologies like AI and quantum computing is how awkward they are. When I worked with AI and GANs in 2018-2020, you’d start a program, but it could take days or even a week before you got an interesting output. It was slow and fragile—one small change could break everything. It made me take note of how slow and brittle this supposedly world-changing technology was.

With the quantum computer, there’s a similar retro quality. You write a program, submit it to run when the machine has time, and it could take minutes or even days to process. It reminded me of the early days when people coded on punch cards and waited for their results. There’s something retro-futuristic about it, like the early days of any new technology—all strung together in a jury-rigged way.

BW: So, you write the code, send it off, and they send you the output when they can?

DY: Exactly.

BW: What was the creative process like, not knowing what the output would be?

DY: At first, I didn’t fully understand what was happening on the quantum machine. I’d get back a data file and think, “What do I do with this?” Some early images were simple grids, but then I started treating it like a drawing—a line moving over time as the machine processed data.

As I researched quantum mechanics, I tried to visualize its strange qualities, like entanglement and the multiverse. For example, when a quantum bit is measured, it can split the universe into two outcomes. Each action could mean moving through an infinite number of universes. It’s fascinating, and as an artist, it’s a compelling concept to explore visually.

BW: I won’t keep you long. What’s your daily workflow like?

DY: Do you think digital artists have a more unified workflow than painters? I know many artists, and everyone has their own process—some treat it like a business, others follow inspiration. I’d like to say I have a regular approach, but I’m not disciplined enough. I have endless ideas and to-do lists, but most ideas get lost.

It’s a balance between production and creative modes. Creative mode is often unexpected—I’ll start something, fall into flow, especially when coding, and time disappears as I adjust and see results. That’s different from using an AI generator, which isn’t always flow-like but can spark new ideas. Not sure that’s a very satisfying answer.

BW: It seems like you’re often tackling something completely new. Can you stay consistent when you’re reinventing yourself from project to project?

DY: I’d like to say there’s a methodology—that each stage is logical and progressive. But I’m also exploring things aesthetically, letting them go in directions I might not have expected.

BW: Let’s say you’re alive at this stage of your career, but it’s 1924. What would you be working on?

DY: Good question. Technology was bringing about incredible changes back then. Photography was transforming creativity, allowing painting to become more expressive. Photography and early cinema were exploring abstract and generative techniques, even new ways of using time visually. It would’ve been an exciting period to experiment. It’s a reminder that everything we think is new has had versions throughout history.

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