Cities Use Anti-Terrorism Funds to Ramp up Citizen Surveillance for other Purposes
Wednesday, October 16, 2013
With federal funding intended to thwart terrorism, many American cities have expanded surveillance and intelligence gathering that amounts to an assault on people’s privacy, according to critics.
A prime example is Oakland, California, whose crime-plagued streets prompted local officials and police to develop the Domain Awareness Center. Seven million dollars in federal grants meant to prevent terror attacks at the Oakland port will be used by police to collect and analyze volumes of surveillance data from throughout the city. The data can be gathered from a variety of sources, from gunshot-detection sensors to license plate readers mounted on patrol cars.
The Center is planned as a high-tech operation, fully staffed 24 hours a day, which will display its streams of data on banks of giant wall monitors.
Initially data collection will focus on the port, traffic camera coverage, license plate reading and 911 calls. Eventually, the system will add surveillance of schools, state highways and commuter rail.
Oakland’s efforts, which will begin next summer, demonstrate “how cities are compiling and processing large amounts of information, known as big data, for routine law enforcement,” Somini Sengupta wrote for The New York Times. “And the system underscores how technology has enabled the tracking of people in many aspects of life.”
In New York City, the police department—with the help of federal counterterrorism funding—utilizes a computer network linking information from 3,000 surveillance cameras with license plate readers, radiation sensors, criminal databases and terror suspect lists.
Massachusetts’ law enforcement also has used federal money to buy automated license plate scanners, while police in Arlington, Texas, and the sheriffs office in Montgomery County, Texas, bought drones with homeland security money.
Oakland tried to get its own drone too, but gave up on the idea after citizens spoke out in opposition.