Street-Level Surveillance
US cities have deployed camera networks, facial recognition, and license plate readers unevenly — and the geography of that unevenness tells a story. An interactive investigation built on the Atlas of Surveillance dataset.
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Investigation
Method
An interactive map of where US police departments have deployed camera networks, facial recognition, and license plate readers — and where the vendors selling that hardware are based. The source is the EFF's Atlas of Surveillance.
Built in Laura Kurgan's Conflict Urbanism studio at Columbia GSAPP. The work is half data journalism, half mapmaking: the goal is to make the geography of surveillance something you can see, not just read about.
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Surveillance Technology Distribution
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Findings
- Surveillance doesn't distribute evenly. Camera density correlates with income and racial demographics — not crime rates alone.
- Facial recognition adoption accelerated post-2020. Cities that deployed protest-monitoring tools rarely rolled them back after the moment passed.
- License plate readers create movement histories. ALPRs passively log every vehicle that passes — building retroactive location databases without warrants.