Like other large law enforcement organizations around the country, the department had built up such an impressive arsenal of technologies for keeping tabs on citizens that it had reached the point of surveillance overload. To get a clear picture of an emergency in progress, officers often had to bushwhack through dozens of byzantine databases and feeds from far-flung sensors, including gunshot detectors, license plate readers, and public and private security cameras. This process of braiding together strands of information—“multi-intelligence fusion” is the technical term—was becoming too difficult. As one Chicago official put it, echoing a well-worn aphorism in surveillance circles, the city was “data-rich but information-poor.” What investigators needed was a tool that could cut a clean line through the labyrinth. What they needed was automated fusion.
He clicked “INVESTIGATE,” and Citigraf got to work on the reported assault. The software runs on what Genetec calls a “correlation engine,” a suite of algorithms that trawl through a city’s historical police records and live sensor feeds, looking for patterns and connections. Seconds later, a long list of possible leads appeared onscreen, including a lineup of individuals previously arrested in the neighborhood for violent crimes, the home addresses of parolees living nearby, a catalog of similar recent 911 calls, photographs and license plate numbers of vehicles that had been detected speeding away from the scene, and video feeds from any cameras that might have picked up evidence of the crime itself, including those mounted on passing buses and trains. More than enough information, in other words, for an officer to respond to that original 911 call with a nearly telepathic sense of what has just unfolded.