Incident 290: False Negatives for Water Quality-Associated Beach Closures
Description: Toronto’s use of AI predictive modeling (AIPM) which had replaced existing methodology as the only determiner of beach water quality raised concerns about its accuracy, after allegedly conflicting results were found by a local water advocacy group using traditional means.
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Alleged: Toronto Public Health developed an AI system deployed by Toronto city government, which harmed Sunnyside beachgoers , Marie Curtis beachgoers and Toronto citizens.
A safe water advocacy group is concerned for the health of Toronto beachgoers after the city’s new water quality monitoring system appears to have repeatedly allowed contaminated beaches to remain open.
This summer, the city quietly adopted…
Earlier this year, Toronto's public health department quietly flipped the switch on an experiment targeting the city's most pollution-prone beaches.
Instead of relying on day-old laboratory tests to ensure that people don't swim in unsafe w…
Toronto recently used an AI tool to predict when a public beach will be safe. It went horribly awry.
The developer claimed the tool achieved over 90% accuracy in predicting when beaches would be safe to swim in. But the tool did much worse…
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.