"Flock, the automatic license plate reader and AI-powered camera company, uses overseas workers from Upwork to train its machine learning algorithms, with training material telling workers how to review and categorize footage including images people and vehicles in the United States, according to material reviewed by 404 Media that was accidentally exposed by the company. The findings bring up questions about who exactly has access to footage collected by Flock surveillance cameras and where people reviewing the footage may be based."
"Flock's cameras continuously scan the license plate, color, brand, and model of all vehicles that drive by. Law enforcement are then able to search cameras nationwide to see where else a vehicle has driven. Authorities typically dig through this data without a warrant, leading the American Civil Liberties Union and Electronic Frontier Foundation to recently sue a city blanketed in nearly 500 Flock cameras."
"Companies that use AI or machine learning regularly turn to overseas workers to train their algorithms, often because the labor is cheaper than hiring domestically. But the nature of Flock's business-creating a surveillance system that constantly monitors US residents' movements-means that footage might be more sensitive than other AI training jobs. Broadly, Flock uses AI or machine learning to automatically detect license plates, vehicles, and people, including what clothes they are wearing, from camera footage. A Flock patent also mentions cameras detecting "race.""
Flock employs overseas Upwork contractors to annotate and categorize camera footage that includes images of people and vehicles in the United States. The company’s training materials instruct reviewers on how to label license plates, vehicle color, brand, model, and clothing. Flock cameras are deployed across thousands of U.S. communities and continuously scan passing vehicles and people. Law enforcement can search camera data nationwide, often without warrants, and have performed ICE lookups. Automated detection includes plates, vehicles, and people, with a patent referencing race. An exposed panel revealed annotation metrics and remaining annotator tasks.
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