Fire Forecasting Could Reshape California
Bloomberg Businessweek|August 30, 2021
AI that predicts wildfires could keep many homeowners from losing their insurance. How else could it help?
Joshua Brustein and Mark Milian

Climate change is making California’s fire seasons more severe, but the conditions that lead to any single fire remain consistent: dry weather, overgrown brush, wind speed, and wind direction. Private companies and public agencies are racing to develop technology to monitor these conditions, in the hopes of understanding how wildfires spread—and predicting them before they happen.

As a bigger proportion of the country’s most populous state burns, the stakes of getting those predictions right goes up, too. Six of the seven largest fires in California’s history have occurred since August of last year, and extreme drought throughout the American West has experts concerned that this year’s season is shaping up to be particularly bad. Human lives are on the line. So are billions of dollars.

There’s demand for wildfire forecasting from both the public sector and commercial interests. As of now much of the innovation is coming from technology companies looking to serve insurers grappling with increasingly costly and erratic blazes—a trend that could determine not only how predictive software is used but how it’s designed. These dynamics are on display with Kettle, a startup that’s created a predictive system by using artificial intelligence to help it design reinsurance policies that protect insurance companies against wildfire risk. Andrew Engler, who has spent years in the insurance industry, first as a sales lead at Allstate and then a vice president at Argo Group, and Nathaniel Manning, former chief executive officer of the humanitarian communication crowdsourcing app Ushahidi, founded Kettle in 2020.

Reinsurers have traditionally used a technique called stochastic modeling, which analyzes historical data to determine the likelihood of random events. That doesn’t work when the changing climate system behaves in ways that humans have not yet seen, Engler says.

“If the way you price risk is you go, ‘OK, how many times has a wildfire hit Los Angeles in the past 500 years? Well, it’s happened twice, so we’ll peg all of our pricing this year at a 1-in-250 chance that Los Angeles will burn,’ you’re going to be wildly wrong, because the next 15 years are going to look nothing like the past 500,” he says. “So understanding that, there’s a major opportunity here.”

Kettle is looking to analyze enormous amounts of geospatial imagery to find emerging patterns. It pulls in data from satellites and weather data maps to predict the areas in California most at risk for wildfire.

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