Anyone who can be replaced by a machine deserves to be.
~Dennis Gunton
A noteworthy popular intellectual trend in recent years might be called “How Everything Works, In Spite of Itself.” Roughly, the trajectory can be described by James Gleick’s Chaos, which appeared in 1988; M. Mitchell Waldrop’s Complexity in 1992; and Steven Johnson’s Emergence, debuting in 2001. On the even more popular side, one can glance at Gladwell’s Tipping Point and Surowiecki’s Wisdom of Crowds, although more serious readers ought to be referred to Stuart Kauffman’s The Origins of Order. What unites these works – or rather, the trend that these books represent – is a perennial desire to see our world defined in terms of simple rules that, once intuited, reveal themselves as pervasive and universal. What are the consequences of this point of view, as we attempt to better understand societies and urbanism?
In a very real sense, this desire for heuristic happiness can be drawn straight back to the Enlightenment, if not even earlier. One can imagine Kepler experiencing equal parts delight and relief when his (only three, and very simple) laws of planetary motion persisted in their universality; or Newton’s, when he was able to derive these laws from the inverse square law of gravity. Whew! Kind of a shame to have to leave those Platonic solids behind, but there is something to be said for simplicity.
The principles derived by scientists working in the fields of chaos and complexity offer similar mercies. The desired outcome is more or less as follows: create a game of as few rules as possible, that in turn creates outcomes that are intricate, beautiful and pleasingly lifelike. Computer-assisted simulations such as Tim Conway’s Game of Life and Mitchell Resnick’s StarLogo have catalyzed the demonstration of how lifelike patterns evolve from simple rules. These simulations not only provide legitimate insights into real world processes, but also speak to us in a titillating fashion, inviting us to observe and name the resulting shapes generated by generations of cellular automata interacting with one another.