"Today, sensor-equipped boilers and tin cans report their data automatically, and in real time. And, just as Beer thought, data about our past behaviors can yield useful predictions. Amazon recently obtained a patent for “anticipatory shipping”—a technology for shipping products before orders have even been placed. Walmart has long known that sales of strawberry Pop-Tarts tend to skyrocket before hurricanes; in the spirit of computer-aided homeostasis, the company knows that it’s better to restock its shelves than to ask why.
Governments, with oceans of information at their disposal, are following suit. That’s evident from an essay on the “data-driven city,” by Michael Flowers, the former chief analytics officer of New York City, which appears in “Beyond Transparency: Open Data and the Future of Civic Innovation,” a recent collection of essays (published, tellingly, by the Code for America Press), edited by Brett Goldstein with Lauren Dyson. Flowers suggests that real-time data analysis is allowing city agencies to operate in a cybernetic manner. Consider the allocation of building inspectors in a city like New York. If the city authorities know which buildings have caught fire in the past and if they have a deep profile for each such building—if, for example, they know that such buildings usually feature illegal conversions, and their owners are behind on paying property taxes or have a history of mortgage foreclosures—they can predict which buildings are likely to catch fire in the future and decide where inspectors should go first. The appeal of this approach to bureaucrats is fairly obvious: like Beer’s central planners, they can be effective while remaining ignorant of the causal mechanisms at play. “I am not interested in causation except as it speaks to action,” Flowers told Kenneth Cukier and Viktor Mayer-Schönberger, the authors of “Big Data” (Houghton Mifflin), another recent book on the subject. “Causation is for other people, and frankly it is very dicey when you start talking about causation. . . . You know, we have real problems to solve.” (http://www.newyorker.com/magazine/2014/10/13/planning-machine)