Dan Tapper is an innovative artist and creative technologist interested in the intersection between information and experience. For Dan data is a raw material, as tactile and malleable as clay or paint, waiting to be translated into something we can feel. Working across installation, performance and software, Dan's practice lives in the space where invisible systems become visible. We spoke to Dan about AI, data and innovation.
How would you describe your artistic practice?
My practice sits somewhere between art, technology and research. I create installations, performances and software that explore how information changes as it moves between different systems, whether that's through radio transmissions, scientific data, machine learning or human communication. I'm fascinated by phenomena that exist just beyond our senses: electromagnetic fields, environmental signals, biometric data, or patterns hidden within large datasets.
Rather than treating data as something objective or purely scientific, I'm interested in how it can become expressive, poetic and experiential. Translation is at the heart of what I do. I think of every artwork as a process of transforming one form of information into another, allowing people to experience something that would otherwise remain invisible or unheard.
Alongside making artworks, I also develop creative tools and educational resources. I see teaching and open knowledge sharing as an extension of my artistic practice rather than something separate from it.
What interests you about working with data and generative technologies?
I think about data and generative technologies as a gigantic sandbox for play and experimentation. Because my interest lies in translation of information I can design environments that are powered by all sorts of data, quickly switching between rules and datasets to see what types of patterns emerge. I often see myself as a sort of curator, moving through lots of information to find the points that are most interesting.
I’m currently obsessed with the field of Artificial Life (ALife), exploring how lifelike behaviours can emerge from simple rules and interactions, creating systems that evolve, adapt and self-organise without being explicitly controlled. A lot of my recent works are based around ALife principles and it sometimes feels like an almost scientific practice of tweaking starting conditions, evaluating behaviour and saving and cataloguing states. As the simulations get more complex, generative systems have been great tools for storing and interpolating between parameter information.
What is your philosophy on art and technology?
For a long time my tagline was “I apply lo fi ideas to hi fi technologies”. I have a background in fine arts and have always been super inspired by conceptual and process based art (particularly movements like Dadaism and Fluxus). There’s a famous quote from the artist Sol Lewitt “The idea becomes the machine that makes the art” that sums up my process pretty well. A lot of my work stems from pretty crude lists and diagrams in notebooks, often inspired by nature walks. I use technology to flesh out these ideas into something more polished and tangible but I like to think at its core the works could be manifested as anything from participatory performance art to poetry.
As an artist, what excites you about AI and what concerns you?
I’ve worked with AI in various capacities for a long time and find it super exciting. I think it’s important to contextualise AI beyond the current landscape of LLMs and generative models - for example supervised classification learning models like Wekinator and Teachable Machine. These tools allow for an expanded, personalised toolset that focus on specific areas of control vs full authorship.
I’m also really inspired by the aesthetics of “old” AI from a few years ago. I’ve recently been reviving old experiments with StyleGan2, thinking about how to navigate the latent space using my current biological system interests (biological agents moving in latent space, controlling how the AI model is navigated). It’s resulted in some really fun and weird little pieces.
In terms of what concerns me. I do work with LLMs and other AI tools as part of my creative process. I feel in a lot of ways it allows me to think bigger picture around the types of systems I build, as well as allowing me to develop and iterate faster. On the flipside I find that in some areas my coding/critical problem solving skills diminish if I use AI a lot. Because of this I try and silo my AI use to specific periods or projects to keep my hand in with code and problem solving.
What do you want the viewer to take away from your work?
I want the viewer to take away a sense of playful exploration. The core of what I do is based around play, seeing what happens when I collide certain things together. I’ve been making work for a long time now so my toy box has got more sophisticated but the excitement of trying out a new system or combination or rules continues to be a delight.
