Cornell University computer scientist Emma Pierson uses AI and emerging data science models to reveal how health disparities arise between sexes, races, socioeconomic groups, and other demographic categories. "These are fancy ways of saying I use math to find patterns in large data sets, and the specific types of patterns I'm looking for are attempting to answer sort of old questions in health and social sciences," she says.The "old questions" she's investigating range widely in their specifics, but she focuses on uncovering how systemic inequalities in public health come to be, and pointing atways to dismantle them. For example, by analyzing mobile-phone data, she recently showed that particular "superspreader" locations were primarily responsible for transmitting covid-19 across populations, and that low-income and minority communities suffered greater risk of exposure.
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