An algorithm is helping cities locate pipes that could release highly toxic lead into drinking water.

What’s new: BlueConduit, a startup that focuses on water safety, is working with dozens of North American municipal governments to locate lead water lines so they can be replaced, Wired reported.

How it works: For each city, the company develops a custom model that ranks the likelihood that any given property has lead pipes.

  • The company starts by collecting comprehensive data on building locations, ages, market values, occupants, and other variables, BlueConduit executives told The Batch. It works with the local government to gather details from a representative set of properties, including known pipe materials and results of water tests if they’re available.
  • It trains a gradient boosted tree on the data, tuning the model to account for uncertainties in the dataset.
  • The model’s output is used to produce maps that officials can use to prioritize removal of potentially hazardous pipes and residents can use to request removal.

Behind the news: Founded by faculty at Georgia Tech and University of Michigan, BlueConduit developed its technology to help manage a wave of lead poisoning in Flint, Michigan, between 2014 and 2019. There it achieved 70 percent accuracy in classifying properties with lead pipes. Contaminated water in Flint exposed thousands of people to dangerously high levels of lead.

Why it matters: Lead exposure can impair development in children, and it’s linked to heart, kidney, and fertility problems in adults. Yet digging up older water lines that may use lead pipes can cost thousands of dollars. Cities can save millions if they can focus on the most dangerous locations and avoid replacing pipes in houses that are already safe.

We’re thinking: Flint stopped using BlueConduit’s system in 2018 partly because some residents complained they were being passed over by the AI-driven replacement strategy — a sign of how little they trusted their local government and the unfamiliar technology. The city reinstated the system the following year under pressure from the state and legal actions, but the lesson remains: When you’re deploying a major AI system, establishing trust is as important as tuning parameters.


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