EFF’s new database reveals what tech local police are using to spy on you

Updated: An interactive map shows you everything from Ring partnerships to predictive policing.
Written by Charlie Osborne, Contributing Writer

The Electronic Frontier Foundation (EFF) has debuted a new database that reveals how, and where, law enforcement is using surveillance technology in policing strategies. 

Launched on Monday in partnership with the University of Nevada's Reynolds School of Journalism, the "Atlas of Surveillance" is described as the "largest-ever collection of searchable data on police use of surveillance technologies."

The civil rights and privacy organization says the database was developed to help the general public learn about the accelerating adoption and use of surveillance technologies by law enforcement agencies. 

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The map pulls together thousands of data points from over 3,000 police departments across the United States. Users can zoom in to different locations and find summaries of what technologies are in use, by what department, and track how adoption is spreading geographically. 

Atlas of Surveillance also highlights specific technologies including body-worn cameras, drones, automated license plate readers, facial recognition, Ring partnerships, and predictive policing, in which data is used to 'predict' where and how crimes are likely to take place. 


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It is also possible to directly search the data to investigate local police departments, including what has been adopted in your area and any surveillance-related grants or awards they have received in the past.

"Atlas of Surveillance documents the alarming increase in the use of unchecked high-tech tools that collect biometric records, photos, and videos of people in their communities, locate and track them via their cell phones, and purport to predict where crimes will be committed," the EFF says.

For example, according to EFF's datasets, ShotSpotter gunshot detection technology has proven popular in many states. The solution uses a combination of sensors, algorithms, and machine learning (ML) to detect and alert law enforcement to gunfire in urban areas.

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The map has been built based on crowdsourced data and journalism over the past 18 months, including news articles, government meeting notes, press releases, and social media content.

Users are also able to submit new data points for inclusion. 

"The prevalence of surveillance technologies in our society provides many challenges related to privacy and freedom of expression, but it's one thing to know that in theory, and another to see hard data laid out on a map," Reynolds School Professor and Director of the Center for Advanced Media Studies Gi Yun commented.

Update 17.24 BST: EFF told ZDNet that there are no plans yet to expand the map, "since we've only done a fraction of the US and other countries may require other methodologies." However, the rights group is open to the idea in the future.

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