Gerald Hushlak
Professor Gerald Hushlak was born in Alberta where he continues his practice as a photographer, painter, and digital artist.
After completing an MFA from the Royal College of Art, London, UK, Hushlak took up the position at the University of Calgary that has acted as the platform for his cross-disciplinary work in art and computer science. Hushlak has exhibited mural-size paintings in museums, built rapid prototype sculpture defined in a 3D modeling package titled Cinema 4-D, and plotted large lenticular and Giclee printed drawings derived from his evolutionary computing software.
He uses evolutionary computing techniques (BreederArt) to “breed” digital imagery from his photographs. The cutting-edge art technology journal Leonardo featured his work as its cover story in the summer of 2007. Since the beginning of his art career, Hushlak has participated in 40+ one-person exhibitions in public museums and art galleries and numerous group exhibitions. His most recent one-man exhibition was held at the Chentang Zhuang Art and Technology Museum in Tianjin, China in 2017.
Gerald, your work positions the computer not merely as a tool but as an autonomous creative partner. How do you negotiate authorship in this hybridized process, where agency is shared between human intuition and machine-driven evolution?
I work with four computers—but they’re not my only collaborators. I also work with two moose, four deer, shifting snow, and warm Chinook winds. Together, we shape temporary sculptures in my backyard, a space I call the Snow Graveyard.
In the summer, I build modular sculptural elements that become raw material for winter installations. These are arranged into snow-covered mounds—each about the size of a human grave—and left to interact with the elements.
The Snow Graveyard is always changing. In Calgary, Canada, the weather can shift dramatically in a single day. Chinook winds melt and reshape the forms; overnight freezes lock those changes in place. I intervene too—watering the mounds late at night, directing the flow to specific areas. Ice forms instantly, creating strange new textures. The result is an evolving, collaborative sculpture shaped by time, temperature, and chance.
Throughout the season, I photograph these transformations. The images feed into computer systems that remix and reinterpret the forms. Unlike AI models trained for specific results, these digital tools offer open-ended responses. They generate sparks—visual cues that guide the next stage of making.
The animals contribute as well. A nearby spring attracts moose and deer, and I embed scents inside the sculptures to lure them in. As they explore, their antlers shift the elements, unintentionally rearranging the work. Sometimes, their interaction marks the piece as finished—nature calling it complete before I do.
I don’t treat these collaborators—Billy the moose, Willie the deer, Helen the computer—as individual artists. But they’re active participants in a process that blends natural forces with human-made systems. From these shared gestures, new directions emerge—ones I could never have imagined on my own.
In your iterative digital breeding system, the emergence of “wild card hybrids” serves as a pivotal generative moment. Could you elaborate on how these unexpected forms influence your conceptual vocabulary and aesthetic trajectory?
Even though the winter sculptures sometimes look like finished art, I’m not thinking about aesthetics at that stage. They’re just raw material—inputs for the next step.
After photographing the sculptures, I sort the images into groups based on what they have in common—shapes, textures, lighting. Each group might have 200 to 300 images. Then I use a digital “breeding” system, where parts of one image are mixed with parts of another. It’s like matching puzzle pieces that weren’t meant to fit, but sometimes do.
This process creates hybrids—new images that carry parts of different parents. Most of them follow the logic of the source material. But sometimes, something odd slips through. These “wild card hybrids” don’t look like anything I expected. They might be strange or awkward—but often, they open new doors.
I see these surprises as important moments. They help shape the direction of the work, both in how it looks and what it might mean.
To stay honest, I always throw out the bottom third of what’s made—images that feel weak, boring, or too familiar.
I also choose to do this editing by hand. I don’t use AI to sort or score the images. I want to stay involved. It’s important to make those choices myself, not leave it up to a system.
Some of the images become large paintings later on. Painting adds a physical layer—brush marks, texture, surface—that brings a different kind of depth to the digital forms.
You draw an analogy between your digital process and the evolutionary work of Darwin and Mendel. To what extent do you consider your practice as a form of digital bio-art, and how does this framing inform your understanding of ‘creation’ in the 21st century?
The references to Darwin and Mendel are meant as a guide—not a literal link to biology. They help explain how traits or features from different sources can combine, evolve, and still keep their own identity. It’s about showing how transformation can happen through shared patterns and change over time.
But beyond that, I don’t really think of my work as bio-art. There’s no direct connection to genetics, DNA, or biology as a science. The natural world is a big part of the process—but more in the sense of weather, animals, and chance, not in a biological or lab-based way.
What interests me is how things evolve—visually, conceptually, and through time. Computers, weather systems, animals, and even ice all shape the work in ways I can’t fully predict. My role is to guide, react, and sometimes just step back and let the process unfold.
I’m not trying to copy science—I’m more interested in how forms can shift, combine, and surprise us, especially now that digital tools, machines, nature, and people all play a part in making art.
Clusters of drawings appear to function as visual ecosystems within your exhibitions. How do you curate or choreograph these constellations, and what role does inter-image dialogue play in the reading of the work?
I usually make the drawings and CNC-milled pieces in groups. Seeing them together invites comparison—how they were made, how they differ, and how they connect.
One image on its own can lead people to imagine a story, but I’m not trying to tell stories. I’m more interested in what happens when you see many images side by side. It changes how we look. We start to notice more.
I think of it like a group of people from different backgrounds. When we see them together, we compare—looking closely at what’s shared and what’s different. The drawings work in a similar way.
These clusters show contrasts—digital versus hand-drawn, soft versus sharp. But they aren’t meant to explain anything. They invite reflection. The images don’t tell a single story—they build a kind of visual space, where meaning comes from the relationships between them.
The metaphor of a stream “finding its path” beautifully captures the dynamic unpredictability of your process. How do you, as the artist, discern when to intervene and when to let the algorithmic flow take its course?
The stream metaphor works well because I use four different computers, each set up to follow its own path. Each one is programmed a little differently, and I let them run without stepping in too much. I want to see where they go on their own.
I don’t judge the results right away. Some images might feel strong, others not. But that mix is important. It tells me something about what’s working, what’s not, and where the next steps might be.
Sometimes I’ll make small changes to how the computer is processing things. Other times, I’ll start over and completely reimagine the setup. But the key is that the system needs to keep evolving. If it stays still, the process stops being useful.
So I try to stay open. I let the machines lead for a while, then step in when something catches my attention. It’s a balance—between control and letting go, between shaping the flow and watching where it wants to go on its own.
Given your extensive background in both traditional and computational art practices, how do you reflect on the historical anxiety surrounding machine aesthetics about your work? Has the critical discourse caught up to the reality of artistic co-creation with machines?
“Machine aesthetics” often focuses too much on surface—smooth, digital, screen-based—and not enough on material presence.
Traditional art, like oil painting, has texture, weight, and irregularity. That physical quality brings emotion and depth. In contrast, machine-made images can feel too perfect or flat—more like pictures than art.
Even when I use computers, I bring the work back into the physical world. Drawing, milling, or painting adds touch, texture, and meaning.The conversation around machine-made art is still catching up. It’s not just about what machines can make—it’s about how artists shape that work with real materials and human decisions.
Your collaborations span from fellow artists to scientists and institutions like the National Institute of Archeology and History in Mexico. How does interdisciplinary collaboration enrich or challenge the visual language of your practice?
Working with people from different fields and cultures pushes me to think in new ways. It challenges the habits we fall into when we work alone or within the same circle.
Interdisciplinary collaboration doesn’t always lead to better results—but it does open up possibilities. Sometimes we accept new ideas because they offer something we’ve never seen before. Other times we reject them—but even then, we have to ask why. That process of questioning helps us grow.
These exchanges don’t just add content—they shape how I see, think, and build the work. They stretch the visual language beyond what I might create on my own.
The inclusion of your work in seminal collections like the Victoria & Albert Museum and the San Francisco Museum of Modern Art speaks to its cultural resonance. What do you see as the enduring contribution of computer-generated art to the canon of contemporary visual culture?
The inclusion of computer-generated art in major collections is important—but the real challenge is whether these works will survive.
Decades ago, I was careful to print my work only on materials that were labeled “archival.” Some of those claims turned out to be false. Over time, certain prints faded—especially the yellows—just like old photographs. The ink companies blamed the paper, and the paper makers blamed the ink. But in the end, the art suffered.
I believe that when a computer-generated work is sold, the buyer should receive the original code. That way, if the print degrades, it can be reprinted properly. This isn’t about perfection—it’s about preservation.
Another big issue is storage. I have around 150 external hard drives holding millions of digital drawings. Some are now unreadable because the software has changed. Institutions rarely keep the old hardware needed to access this work. My earliest digital drawings were saved on reel-to-reel tape. That equipment is long gone—and those pieces are likely lost forever.
If we care about the future of computer art, we need serious support—standards for materials, funding to recover old files, and respect for digital art as cultural history. Without that, important chapters of art history could disappear.
You have spoken of “imagineering” new aesthetic relationships. Could you expand on this term in the context of your evolving relationship with emerging technologies such as AI, machine learning, and real-time generative systems?
To fully answer that would take a long essay—but in short, “imagineering” is my way of describing how new technologies open up space for unexpected relationships between forms, ideas, and systems.
It’s not just about using tools like AI or generative software—it’s about exploring how those tools shift our way of seeing and making. They suggest patterns I wouldn’t think of. They react in ways I can’t always predict.
“Imagineering” is about listening to those signals, shaping them, and letting them shape me back. It’s a kind of creative loop—part invention, part response—that continues to evolve as the technologies do. The tools are always changing, and so is the language. But for me, the goal remains the same: to find new ways to make meaning through form, structure, and surprise.
From the Glenbow Museum’s surveys of the 60s, 70s, and 80s to your exhibitions in China and Portugal, your career spans eras, geographies, and technologies. What have been the most radical shifts in how your work is received, and how do you envision your legacy in an art world increasingly shaped by post-humanist and post-digital paradigms?
One of the biggest shifts in my practice came when I moved from using vector-based drafting tools—like ink-pen plotters—to raster-based imaging. I started working with a medical scanning system at a local hospital, using it during off-hours, between midnight and morning. It allowed me to scan and manipulate images in entirely new ways.
Instead of creating single images, I began printing long strips of related images—like contact sheets. That opened the door to working in clusters or “families” of images, where each one influenced the others. I stopped thinking in terms of traditional composition and started exploring structural relationships between forms. A machine meant for medical diagnosis was now offering artistic direction.
Later, while preparing for a museum exhibition in China, I couldn’t afford to ship the work. So I decided to print everything on-site—on large sheets of silk. As viewers walked past, the silk moved with the air, introducing a kinetic, almost performative element I hadn’t planned for. That opened a new path for future work.
Even now, I look at the symmetry of car fronts and backs on the highway and think—this kind of familiar, accepted design language is also a way into my art. I try to build on that—using symmetry, repetition, and variation—to invite people into the work, wherever it’s shown.
Throughout your career, you've been the recipient of more than half a million dollars in funding from esteemed institutions such as the Canada Council, SSHRC, and the Alberta Foundation for the Arts. How has this sustained institutional support shaped the scope, ambition, and experimental freedom of your practice, particularly in the realm of technologically mediated art, where infrastructure and longevity are often critical but underfunded?
In the early stages of my career, working with computers in art meant I had to partner with people in science. I couldn’t do it alone. Funded support from institutions like the Canada Council and SSHRC allowed me to work with programmers, computer science colleagues, and even my wife, who was doing her master’s in computing. That teamwork was essential—we built tools that didn’t exist yet.
Long before software like Photoshop was available, we were already experimenting with medical imaging tools to scan and transform images. We didn’t commercialize it—but the creative foundation was there.
Grants also made it possible to travel with purpose. I would go to places specifically to find material—visual, environmental, or cultural—that could feed into the software processes I was developing. These new experiences often became source images for the sculpture installations I now create outdoors.
Sustained funding also gave me time to explore more abstract questions—like how transformation works in nature. For example, I studied how birds return to the same nest, leaving behind layered materials and waste. Over time, those deposits form new structures—shapes built from repetition, decay, and the environment.
That kind of organic change connects to how I work with computers now: layering, reshaping, clustering. I see it in drone swarms, in fireworks choreography, in natural patterns—and technology helps me observe and use those systems in new ways.
Without funding, most of that experimentation simply wouldn’t have happened.