An Algorithm Is Helping a Community Detect Lead Pipes

Wired
Sidney Fussell
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MORE THAN SIX years after residents of Flint, Michigan, suffered widespread lead poisoning from their drinking water, hundreds of millions of dollars have been spent to improve water quality and bolster the city’s economy. But residents still report a type of community PTSD, waiting in long grocery store lines to stock up on bottled water and filters. Media reports Wednesday said former governor Rick Snyder has been charged with neglect of duty for his role in the crisis.

Snyder maintains his innocence, but he told Congress in 2016, "Local, state and federal officials—we all failed the families of Flint.”

One tool that emerged from the crisis is a form of artificial intelligence that could prevent similar problems in other cities where lead poisoning is a serious concern. BlueConduit, an analytics startup that says it uses predictive modeling to find lead pipes, offered promising results in Flint, but the city’s complex politics ended its use prematurely.

Now, four years later and 100 miles away, officials in Toledo, Ohio, facing concerns about lead pipes, want to use the technology. They hope to avoid the problems that surfaced in Flint by expanding community outreach and involvement. The Ohio Department of Health estimates that as many 19,000 children in the state have elevated levels of lead; children in Toledo tested positive for lead poisoning at nearly double the statewide rate, according to a 2016 report from the Toledo Lead Poisoning Prevention Coalition.

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