Revealed: a California city is training AI to spot homeless encampments
For the last several months, a city at the heart of Silicon Valley has been training artificial intelligence to recognize tents and cars with people living inside in what experts believe is the first experiment of its kind in the United States.
Last July, San Jose issued an open invitation to technology companies to mount cameras on a municipal vehicle that began periodically driving through the city’s district 10 in December, collecting footage of the streets and public spaces. The images are fed into computer vision software and used to train the companies’ algorithms to detect the unwanted objects, according to interviews and documents the Guardian obtained through public records requests.
Some of the capabilities the pilot project is pursuing – such as identifying potholes and cars parked in bus lanes – are already in place in other cities. But San Jose’s foray into automated surveillance of homelessness is the first of its kind in the country, according to city officials and national housing advocates. Local outreach workers, who were previously not aware of the experiment, worry the technology will be used to punish and push out San Jose’s unhoused residents.
City employees are driving a single camera-equipped vehicle through sections of district 10 “every couple weeks”, said Khaled Tawfik, director of the San Jose information technology department. The city sends the training footage to participating companies, which include Ash Sensors, Sensen.AI, Xloop Digital, Blue Dome Technologies and CityRover.
Some of the areas in district 10 targeted by the pilot, such as Santa Teresa Boulevard, are places where unhoused people congregate, sometimes with the city’s encouragement. The light rail station on Santa Teresa Boulevard, for example, is home to the city’s only designated safe parking location for RVs, often used as homes.
There’s no set end date for the pilot phase of the project, Tawfik said in an interview, and as the models improve he believes the target objects could expand to include lost cats and dogs, parking violations and overgrown trees.
“If the City were to productionize this technology, we envision the cameras to be on our fleet motor pool vehicles that regularly drive throughout