
| Photograph: Matthew Plummer-Fernández
Matthew Plummer-Fernández joined Camberwell College of Arts last year as the new course leader for BA Fine Art: Computational Arts.
Alongside his work at UAL, Matthew is a practicing artist with an interest in algorithmic systems, popular culture and contemporary issues. His work has been exhibited extensively, and commissioned by institutions including the Victoria & Albert Museum and Somerset House in London, AND Festival in Manchester and ZKM in Karlsruhe.
He received an MA from the Royal College of Art (RCA) in 2009, and completed his practice-based doctorate at Goldsmiths, University of London in 2019. He is also a senior lecturer at UAL’s Creative Computing Institute (CCI).
We spoke to him to find out more about his practice, and how his interests inform his vision for BA Fine Art: Computational Arts.
Well, I've been on a long journey through various courses and disciplines, so I guess you would say I have an interdisciplinary background.
I first went to study engineering, because I had an aptitude for computers, mathematics and physics. But I always had an interest in art too - I was even the illustrator at my university for the Student Union.
My course was quite a forward-thinking engineering course, because it combined elements of computing with digital fabrication, electronics, CGI and 3D modelling.
So from there I decided to do an MA at the Royal College of Art (RCA) in product design, where I thought I could naturally exchange some of those technical skills for more design-oriented ideas and thinking. The RCA, being an art institution, really opened me up to different practices that I hadn't really come across before. There were a lot of experimental media artists at the RCA and that sent me down a different pathway.
After that, I worked as a technologist in different capacities, first in a commercial setting, and then in an academic setting. I worked at Goldsmiths as a human-computer interaction (HCI) researcher. And alongside that I had ample time to develop my own art practice, which I didn't really get to do until a few years after being at the RCA.
My first passion is in producing 3D printed sculpture, perhaps as a natural extension of my design background. From then on, I really discovered a whole community of artists and technologists that were experimenting and with new emerging practices: everything from practitioners that make bots, to practitioners that use artificial intelligence (AI) in their artwork. Through that experience I discovered this field, and it’s quite nice to actually come full circle and be embedded again in academia, but on a course that really is the sort of sum of all those parts.
The interesting thing about technical services in the last 10 years is that they've become more accessible through online interfaces, so something like 3D printing is now something that is quite easy to order online.
That was my way in: instead of having everything under my own roof in my house, I had this distributed studio, if you like.
I still use it now: instead of using my own computer to render images using AI, for example, I'm accessing servers that Google run to do all the hard work for me. I really think of practice not as something that necessarily has to exist all in 1 space, but as something that is globally accessible.
This really helps emerging practitioners, because you may not have your own art practice within a studio setting, but you have all these tools at your disposal that you can access online.
At Goldsmiths I started as a researcher, but that role gave me a window of opportunity to start giving tutorials and lectures to students, often about using technology or doing coding to complement their practices.
From then on, it was only until UAL started the CCI that I really felt like there was a bespoke set of courses that were dedicated to my field. I felt more at home at a place like the CCI than when I was offering coding lessons to fashion or design students.
One of the approaches that I take as a tutor is to feel like I'm also embedded in the learning space, co-learning with students as we all explore emerging technologies and methodologies.
I'm constantly having to teach myself new skills, because they're constantly shifting and being updated, and I think it actually creates a more shared and inclusive environment in the classroom. Everyone has an equal contribution to make by discovering these tools and sharing them with others, so it definitely impacts on my practice. Some tools or techniques that I might otherwise overlook I pick up on through my teaching and find that, without even realising it, a couple of months later I'm using them in my own artwork.
Since March last year I've been developing a series called Cave Paintings. They depict fantastical-looking caves and are generated using AI.
There’s a new subset of AI tools that take text prompts or image prompts to guide and steer the AI towards producing a certain image.
Some of the first experiments with these tools were very trivial things such as ‘depict a person eating a pizza’. But I discovered that you could really push the parameters by finding just the right combination of words and references, for example, to an art movement or a particular painter, and through these very nuanced text prompts you'd be able to generate something radically different and visually interesting. The outcome is kind of an embodiment of all those references that you're giving it.
Cave Paintings is an ongoing series and I’m currently testing out a sub-series of works that are animated. This is created by tweaking the code to generate lots of stills that when in sequence, produce an animation.
This is something really inspired by my students because I taught them how to do the text-to-image prompt methods last year. A couple of my students found ways to make animations based on this technique - they kept feeding back more and more text prompts and images and 1 student in particular - Nikos Kourous - found ways to make whole narrative films by piecing together lots of these images. This is an emerging field that's coming straight out of our course.
The new online market spaces that are now open to digital artists for this invention of NFTs has been something I've investigated for the last year. I got really involved in it, not just because it was a way of producing and making money from my work, but I found the discussion around it quite interesting.
I tend to be attracted to technologies that have a heated debate around them: the research side of me just wants to be a fly on the wall listening to and participating in them, rather than having a particular viewpoint or making a stand for or against something.
I've enjoyed getting to understand those markets a lot better, and experiencing the highs and lows. And I feel like this will inform my teaching on the subject, because I think it is a topic that will be extremely exciting for students, but also something that could be quite precarious. Trading with a currency that fluctuates a lot naturally means you are taking a certain amount of risk and I think it’s important for me to be able to better prepare my students for such a marketplace.
One of the themes in my work is current societal issues, and I'm really interested in socially engaged practice, because I feel that, especially with new technologies, you can be right in the middle of a conversation that feels very current - whether it's online security, open source technologies, NFTs or the climate crisis.
A lot of these issues are heightened by technology, so as a practitioner that works with technology, it’s important to understand ethics and learn how to navigate their contentious uses.
For example, a lot of artists might want to use facial recognition technology, because it's great to make augmented reality (AR) filters and things like that. But there are controversial uses of that which are already applied. Being able to show an awareness of that in your work is essential, and something you have to learn to circumnavigate as a practitioner.
Yes. I think artists are naturally inquisitive and critical of the topics that they delve into.
When they work with AI, CGI, or game engines such as Unreal, they understand that there are histories to these technologies. We do discuss this in the classroom - for example, we were recently looking at the military use of game engines to train soldiers - topics like that are things that we definitely don't shy away from. If anything, they enrich other conversations and make the work more interesting and impactful.
It has been important for me to position the course and differentiate it from similar courses that might emerge from other disciplines such as computing or design.
One approach that has organically developed from work with the students is this idea that we're not ‘classically trained’ in the technology.
Using the analogy of learning how to use a musical instrument has helped me to easily communicate that we're picking things up off the shelf, sometimes very powerful tools and technologies, without having to go through an extensive, rigorous training that would, in a more classic model of learning, usually lead us up to being granted access to these tools.
At the CCI, for example, you might have a much more rigorous curriculum that goes through the basics of coding, leading all the way up to using machine learning by the 3rd year. Whereas on BA Computational Arts, you'll probably be using machine learning within the first couple of weeks - and having to figure out how to make it give a good tune, so to speak!
That punk approach, to me, really fits in with fine art methodologies: you might not be a total expert, but just by being inquisitive and patient, you'll find a totally new way of working with those tools.
I think that has been a really productive approach. We're seeing students do things that you don't normally do with AI, which is just exactly what we want. We want to see the innovation in ideas and approaches rather than technical innovations.
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