Making Art By Writing Code

I was asked to write a fifteen minute intro to De Montfort University‘s Computer Art Pioneers celebration, “Making Art By Writing Code”, organised by Sheffield’s Site Gallerywhich I chaired this weekend. The all-day event took the form of a series of conversations between four original algorithm artists and four younger members of the community, followed by a (fascinating) grand panel involving everyone, at the end. It coincided with the launch of Ernest Edmonds’ new exhibition at Site, and Manfred Mohr‘s new show at the Caroll Fletcher Gallery in London. All the pioneers have been good friends for decades, so the atmosphere was excellent. They were also, without exception, extremely fluent and interesting. The day was filmed and recorded, and if I see anything go up anywhere I will of course link to it from this blog. You can read about all four pioneers here; some of the work is really beautiful. “Fallen monk” Roman Verostko’s drawing machine paintings obviously pressed my buttons, and Frieder Nake is just brilliant. He carries all his work around in his head all the time, and was absolutely crackling with inspired philosophical gems.

A couple of people asked if I was going to put the text of my talk up anywhere, so here it is! I know some real nerds read my blog, so please bear in mind this was for a general audience…

Cybernetics has been defined as “the scientific study of control and communication in the animal and the machine”. The ‘systems art’ we will discuss today reminds us that mathematics and science are continuously implicated in our emotional experience of the world. In different ways, many of the works we will hear about today both represent and are derived from logical systems.

These works don’t shy away from the crucial facts about what it is to be human. By engineering encounters between humans and machines, in which a very fundamental sort of conversation takes place, systems art forces us to confront the possibility that we are not the centre of the universe. It’s reassuring and unsettling at the same time. We find ourselves to be creative and influential, but also limited ­– definitely part of something larger than we are.

The participatory art that we will be talking about today uses technology to sharpen the human experience. The language may be maths and logic, but the expression and interpretation derives from humans: the artists and the participating viewer, whose actions are implicated in the art, as they imprint themselves upon the system.

As we experience these works, we also create them – we find ourselves participating in an ideas-generating community where both people and machines have a role to play. In this sense, these works implicitly promote collaboration, and in the last 15 years or so, the notion of technology as a facilitator of collaboration, and the opportunities opened up by networked systems have become very familiar to all of us, thanks to the rise of the internet.

In very recent years, however, technology has become both mystical and domesticated. We carry around shiny, opaque, unopenable, objects with no comprehension of their workings, and because they are so fluent in our language, so in tune with our preferred vocabulary of images and signs, it is easy to imagine that our machines must think a bit like we do. It is a form of anthropomorphism of technology – and can certainly be useful. The printing devices James Jefferies and I developed earlier this year at this very gallery became widely known by their human names, Cathy and Heathcliff. Their behaviour started to make more sense when we began to treat them as petulant teenagers.

But while it’s seductive to meditate on how computers are like us, it’s just as interesting to think about how they are different. Machine minds are composed of linguistic strata: layers of signs – heiroglyphs that become more recognisable to us near the surface and more numerical and abstract on the descent.

There has undoubtedly been an upsurge of interest in these abstractions in the last few years. In the hope of demystifying their machinery, people are joining coding clubs and signing up to online courses and workshops in their thousands. Some may have an eye on their future work prospects, but for most of us the fascination stems from a need to understand our totally ubiquitous technology better, so that we can do more with it. In only a very, very slightly ‘Weird Science’ way, we are driven to develop a relationship with our equipment. Speaking to technology in its own language is powerful precisely because so much technology is no longer designed to be interrogated in this way – and the urge to hold a conversation with machines is as strong as ever.

But we have always had this impulse to interface with machines. In the 50s and 60s, computers were relatively unusual. They hadn’t yet learned our language, so we had to learn theirs. And in 2012, we find computers are silent again, for different reasons. They have evolved to mimic our thought patterns and habits so precisely, to respond with such sensitivity to every touch, to know our mind before we do, that their true processes can seem mysterious and unreachable.

Creating art through coding in the 60s replaced the subjectivity and elitism of conventional art-making with untouchable rationalism. Logic is a great leveller; entropy comes to us all eventually. And these days machines are useful as facilitators of social systems – technology is synonymous with the internet, and the internet is an enormous web of people. Tech is now being recognised as a far-reaching tool, it turns up in everyone’s life and can break down these kinds of barriers.

The days of punched cards may be over but there are more excellent reasons to find a common language to communicate with machines than ever, and there have been developments in this area even in the last year.

The Raspberry Pi computer launched in February. Designed with the intention of helping children learn to code, this credit-card sized computer has the graphics capability of an Xbox, boots up in the command line, and comes as an unapologetically bare circuitboard. The Raspberry Pi’s developer, Eben Upton, has cited the BBC Micro as his inspiration. The BBC was the first computer designed to educate – it’s familiar to any of us who were schoolchildren in the 1980s, and is cited as a hugely significant influence by a generation of adult coders in this country today. Eben Upton and the Raspberry Pi team want today’s kids to learn to code – to have to learn to code – just as we had to in order to communicate with those stubborn – yet totally rational home and school computers of the 1980s.

Whether you’re an artist or a technologist, a school child or a systems art pioneer, programming can be immensely creative, exciting and satisfying. It’s easy to forget, but all our interactions with any computer are a tantalising game of call and response. Whenever we touch a machine, we are effectively typing “input N$ semi colon…” And as with the Raspberry Pi’s bare circuit board – if we are to understand how machines work, it may be time to look again at computers for what they really are.

Nowadays, we have “Processing”: a programming language that allows artists working with technology to control modern devices – such as the Microsoft Kinect depth camera. Processing is not overly mathematical, but intuitive in that peculiar way that logic always is. Its accessibility means that artists are able to use it without extensive technical knowledge. Processing, and the Processing derivative used for the increasingly popular Arduino microprocessor, can bring artists closer to their equipment and help them exert a high level of control over their works.

“Processing” is an apt name for the language – because, as we look again at our machines, we find we are creating an art of procedures and events. With coding now beginning to be highly valued for its creative potential, audiences raised in a highly tech-literate society are as interested in the workings as the outcome.

Artists like Sheffield’s adopted Alex McLean have been turning code into the subject of their performance for years and even incorporating music – as some of the artists we will hear from today have done. But the notion of ‘seeing the workings’ has become much more mainstream since hacker culture and the “internet of things” phenomenon really took off, in the last few years.

When algorithmic art began, programming was an efficient, time-saving, way of making replicable, aesthetically beautiful and interesting works. Very quickly it ceased to be a matter of efficiency, and now there is a vast spectrum of creativity, with programmer at one end and artist at the other. The programmer-artist is no longer simply a pragmatist who assists an artist, like a tradesman, but is accepted as a craftsperson, him or herself. One reason we have such a breadth of work in this area now is due to the work and insights of the pioneers we have with us today.

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