Huichuan Wang Reimagines the Vision of Herbert W. Franke

For artist and educator Huichuan Wang technology is less of a tool and more of an artistic collaborator. This idea lies at the heart of a new research project with the art meets science - Foundation Herbert W. Franke, which Wang will lead.

The research will explore how one of the pioneers of computer and computational art might be reimagined through the possibilities of contemporary artificial intelligence and generative technologies. It is a timely project. As debates around AI continue to polarise artists and audiences alike, Wang's research returns to a much older question: what happens when humans and machines create together?

For MFA Computational Arts graduate Wang, the answer can be found in the work of Herbert W. Franke.

"I think there is this anxiety that comes from thinking about the computer as a replacement for the artist," she says. "In my daily experience the relationship is nothing like that. It is much closer to a collaboration between independent parties."

A pioneer before computer art existed

An Austrian scientist, writer and artist, Herbert W. Franke was creating machine-generated images in the early 1950s, decades before "computer art" entered common usage. Armed with expertise in physics, chemistry and mathematics, he experimented with oscilloscopes, analogue computers and photographic techniques to create luminous abstract images that explored the aesthetic possibilities of scientific instruments.

Rather than treating machines as passive devices, Franke saw them as active participants in the creative process. He believed mathematical structures generate beauty and argued that artists should work with the capabilities of technology rather than simply impose preconceived ideas upon it. In his 1957 book 'Art and Construction', he envisioned a future where humans and machine systems would create in partnership. That vision now feels remarkably prescient.

"Every artist working with generative AI today follows a similar methodology, whether they know his name or not," says Wang. "Establish a generative system, let it produce, then choose."

A natural fit

Wang's appointment to the project is no accident. Although trained in traditional fine art painting her practice has increasingly focused on computational and generative processes. After study at the Central Academy of Fine Arts in Beijing, she came to Goldsmiths for postgraduate study in Computational Art gaining an MFA. It was there that she began working extensively with code, AI and electronics.

Today she continues to work with Goldsmiths, alongside Professor William Latham and Dr Rachel Falconer in the School of Computing, and maintains her studio practice. Despite her embrace of digital technologies, Wang sees continuity rather than rupture between her painting background and her computational work.

"The most consistent thing about my practice is that I prefer to work with materials rather than over them," she explains. "What I have always been looking for is something that answers back, not a tool that obeys." That philosophy underpins what she calls "Techno-Craft" - an approach that treats technological systems as creative partners whose limitations, unpredictability and behaviours are part of the artistic process. It is also the reason that she strongly connects to Franke's methods.

"As I studied how the images were made, admiration turned into something closer to recognition. Franke worked the way I have always wanted to: he set up conditions, respected the autonomy of his instruments, and treated unpredictability as a source rather than an obstacle."

Reimagining Franke for the age of AI

The research centres on a substantial archive of Franke's early work. Around 2,000 high-definition images digitised from original slides supplied by the art meets science - Foundation Herbert W. Franke are being used to train custom AI systems capable of generating new visual material inspired by the artist's 1950s photographic experiments. But as Wang is keen to stress the project is not about reproduction. "What I am doing is better described as re-imagining: taking the processes behind the images seriously and asking what they can become with the systems of our own time."

Her research combines archival investigation with cutting-edge machine learning. Working closely with Susanne Päch, Franke's wife and a key steward of his legacy, Wang is studying not only the finished artworks but the mathematics and instruments, signal sources, cameras, experimental methods that produced them. The practical process involves training custom AI models on individual Franke series, generating thousands of image and video outcomes, selecting promising results and then constructing moving image works through careful sequencing and editing. Automation for Wang, rather than diminishing her role, means instead that her artistic judgement needs to become more focused. "The model produces far more images than I could ever use," she says. "The machine produces passages; the composition of the whole remains a human task."

What is computational art, really?

For many people, the phrase "computational art" sounds contradictory. Art is often seen as deeply human, while computation suggests automation and data. Wang though views this as a misunderstanding. Computational art is not about replacing human creativity with algorithms but instead about creating systems that generate unexpected possibilities. The artist establishes conditions, the machine responds, and meaning emerges through an ongoing dialogue between the two. In this sense, she argues, there is a direct line between Franke's analogue computer and today's generative AI models. Both involve working with systems that possess their own logic, behaviours and surprises. "The instruments have changed beyond recognition. The structure of the collaboration has barely changed at all," Wang says.

Beyond the image

Perhaps the most significant outcome of the research will not be the new AI-generated works themselves but the questions they raise. As Wang delved deeper into Franke's archive, she realised that both humans and AI often make the same mistake: they see only images, not the processes that created them. That insight has become central to the project.

"The shift from seeing images as images to seeing images as records of processes may be the most important thing the research has to teach," she says. By animating Franke's frozen traces of light and translating his analogue experiments into contemporary computational environments, Wang hopes to reveal the dynamic systems hidden inside the photographs. The resulting works will invite audiences to experience Franke's pioneering vision not as historical artefacts but as living processes still capable of generating new forms.

Seventy years after Herbert W. Franke first turned scientific instruments into artistic collaborators, Huichuan Wang is continuing that conversation. In doing so, she is exploring not only where computational art came from, but where it might go next.