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By Chris Arsenault
TORONTO, Oct 15 (Thomson Reuters Foundation) – As makeshift tent cities spring up across Canada to house rough sleepers who fear using shelters due to COVID-19, one city is leveraging artificial intelligence (AI) to predict which residents risk becoming homeless.
Computer programmers working for the city of London, Ontario, 170km southwest of the provincial capital Toronto, say the new system is the first of its kind anywhere – and it could offer insights for other regions grappling with homelessness.
“Shelters are just packed to the brim across the country right now,” said Jonathan Rivard, London’s Homeless Prevention Manager, who works on the AI system.
“We need to do a better job of providing resources to individuals before they hit rock bottom, not once they do,” he told the Thomson Reuters Foundation.
Canada is seeing a second wave of coronavirus cases, with Ontario’s government warning the province could experience “worst-case scenarios seen in northern Italy and New York City” if trends continue.
Homeless people are particularly at risk of being infected and infecting others during the pandemic, due to weakened immune systems and poor access to shelter and sanitation, health experts say.
Launched in August, the AI system analyzes the personal data of participants to calculate who faces having nowhere to sleep for an extended period, said Matt Ross, an information technology (IT) expert with the city who helped build the program.
As a test the system, called the Chronic Homelessness Artificial Intelligence model (CHAI), tracked a group of individuals for six months before its formal launch in August.
Over that period, CHAI saw a 93% success rate in predicting when someone would become chronically homeless, Ross noted, adding it is now meeting or exceeding that rate.
By using the system to anticipate who is likely to become chronically homeless, the city can prioritize how it works with those individuals to try and get them into safe housing or get them access to health services they might need, Rivard said.
