The modern city is awash in data. Cheap sensors on cars, roads, and people give us a real-time understanding of traffic. We can track pollution, temperature, and climate with unerring precision. Satellite photographs reveal shade cover, property values, and building development.
We infuse urban spaces with sensors, drinking from a torrent of data, making sense of city life. But this reliance on data has real risks: Complex systems often have unintended consequences, and it's hard to experiment.
Alistair Croll shares lessons from the past and explains how paving the cowpaths, examining the models, and iterating everything can mitigate these risks.