Self-organizing models

To tame urban traffic, computer scientist Carlos Gershenson finds that letting transportation systems adapt and self-organize often works better than trying to predict and control them. He makes the argument that we assume that the world is predictable, and as a result we try to produce solutions that tie into this predictability. However, in Gershenson's view, such solutions are destined to fail, for the world is not truly predictable.

This points towards a broad shift in urban tech from predictive to adaptive approaches as the computational complexity of systems we seek to optimize grows exponentially with scale.