The most beautiful, complex and apparently spontaneous creations are often produced by following a few very simple, very rigid rules.
In their talk, Eno and Wright show some computer animations in which each coloured cell on the screen is programmed to analyse the behaviour of the cells next to it, and alter its own behaviour in response.
For example: “If three of your neighbours are alive, you’ll survive into the next generation. Or if only one of them is alive, you’re going to die.”
When the program runs at high speed these rules change the colours of the cells in each ‘generation’, creating complex patterns of colours flickering across the screen.
Suppose you had to make this as a film, what we’re seeing here. It would be very complicated, that’s a lot of information if you had to specify it as a visual phenomenon like that.
But what actually has happened is that there’s this tiny little set of rules and this landscape for them to work in. And the set of rules is typically like a 2K document or something like that, and you get all that richness.
So this is the power of generative systems, that you make seeds rather than forests.
The full version of the talk (available on Fora.tv) references Richard Dawkins’ observation that a typical willow tree seed only contains 800K of data, which would fit on an old-fashioned floppy disk.
To extend this metaphor, it sounds as though Eno and Wright are suggesting that creators are more like gardeners than architects, planting and watering the seeds to help them grow, but with no control over the emerging forms.
And these [computer animations] are very much the type of thing where you have no idea what it’s going to look like, when you build the rules. You turn it on and it’s always just a total surprise.
Simple rules like this underly the phenomenal complexity of Wright’s classic game SimCity:
SimCity is underlaid by a series of very simple cellular automata like this, and they have a set of very simple rules for crime and traffic and pollution. And on top of that we overlay all these nice graphics of cars and factories and all that.
But really underneath it’s a very simple rule-based system like this, that allows us to simulate things, and it took a while to actually discover the rules but once we put together a few simple rules we got to the stage where we were seeing emergent phenomena.
We were seeing things like urban gentrification just with the simple interactions of the crime / land value rules and stuff like that. It seemed like it was a much more complex simulation than in fact it really was.
Something to bear in mind next time you try out the new organic shop in your area.
A brilliant example of a generative system in Eno’s work is 77 Million Paintings, in which he fed 300 of his own paintings into a remixing program:
(If you like this clip, get the software DVD and watch it on a high-resolution screen. It will take your breath away. NB it plays on a computer, not a DVD player.)
Play It Simple
A point that comes up repeatedly in the Eno/Wright talk is that complex results emerge from simple rules. No rules mean there is no system, so nothing is generated. But if you add too many rules and risk breaking the system. The trick is to find just enough rules to get the system under way without destroying it prematurely.
But introduce a simple rule such as ‘one of you is higher status and the other’, and it starts to come alive. Tweak the rules slightly – ‘one of you is the servant but acts higher status than the master’ – and you have a recipe for spontaneous comedy.
Twitter is another good example of a generative system. When I first tried Twitter, I didn’t see the point. There was so little I could do. Type a 140 character message? Get messages from other people? Is that all?
But when I was persuaded to persist with Twitter, I discovered the incredible richness of the conversations and connections it facilitates. Now you can find me there most days. It’s one of the very few web applications I would genuinely miss if it disappeared overnight.
I’m not the first one to be puzzled by Twitter’s lack of ‘obvious’ features that can be found in similar – but less successful – networks such as FriendFeed or Plurk. But Eno and Wright would probably argue that Twitter is so successful because its rules are so simple.
But how can you know in advance which rules will bring you the best creative results? Which ideas should you pursue and implement, and which should you leave on the drawing-board?
Which means you have to try things, play around with them, test quickly and test often. Allow failure to tag along as a daily playmate.
Isn’t that the beauty of real creativity, that you wake up every morning not knowing what you’re going to discover?
What Do You Think?
What do you make of the idea that complex phenomena are created and determined by simple rules?
What other examples of generative systems can you think of – in the arts, sciences, business and society?
What difference would it make to your work if you thought of yourself as making seeds rather than forests?
About the Author: Mark McGuinness is a poet and creative coach.