AI Case Study

"Walking around downtown Orlando, you might not notice the lightbulb-sized camera affixed to one of the traffic signal poles along the city’s palm tree–studded avenues. But it’s there, scanning all the same. If it sees you, the camera will instantly send a live video feed over to Amazon's facial “Rekognition” system, cross-referencing your face against persons of interest. It’s one of three IRIS cameras in the Orlando area whose video feeds are processed by a system that could someday flag potential criminal matches — for now, all the “persons of interest” are volunteers from the Orlando police — and among a growing number of facial recognition systems nationally.

Amazon, however, declined to answer on-record several specific questions about Rekognition, among them: whether the system learns or otherwise improves from the video it ingests; whether Amazon provided Orlando law enforcement with hands-on training to help them understand how to use and interpret Rekognition (apart from emailed guidance and publicly available documentation); and how, exactly, the system processes and disregards faces that are not those of “persons of interest.”

To be clear, Orlando has not yet deployed a citywide facial recognition project. It is not currently processing the faces of pedestrians by comparing them to the faces of known criminals, nor are the alerts the system sends to police officers meant to detain suspicious “persons of interest.” But the city's Rekognition pilot is already testing how the technology would perform these kinds of tasks. Which means — to some extent — that the idea of a public-facing facial recognition database that automatically scans the city for possible criminal matches has already won.

Documents obtained by BuzzFeed News show the initial rollout of Orlando’s Amazon Rekognition pilot was marked by internal miscommunication that led to both the city of Orlando and Amazon Web Services — Amazon’s cloud computing arm that offers its facial recognition tools — presenting confusing and contradictory information about the pilot to the public.

After the contract between the City of Orlando and Amazon was finalized in December 2017, documents show that in mid-February a team from Amazon Web Services spent two days in Orlando connecting the city’s video feeds to AWS Rekognition for a “proof of concept” project. This was Orlando’s first-phase pilot of Amazon Rekognition: video streams from five cameras inside city buildings and three more outside in downtown Orlando, all working to identify the faces of the seven volunteer officers when they walked by.

Orlando PD uploads photos of "persons of interest" (officer volunteers) into the system; Rekognition analyzes their faces, maps their features, and indexes them. Then, faces from the city's eight designated live video streams — four from cameras inside Orlando police headquarters, three IRIS cameras in downtown Orlando, and one at another unnamed city facility — are sent to Rekognition and compared against the Orlando-provided collection of faces. If the system detects a match between a pedestrian's face and that of a "person of interest" in its index, it is supposed to instantly send a notification to police officers.

For Orlando’s second pilot, according to the July memo, the number of cameras “may be increased” from eight cameras to an unspecified number, “to ensure this technology can function as designed with a larger volume.” The city said it retains video footage for 30 days, after which it is overwritten."