Solving the World’s Problems with Data Science

Street connectivity in the above map of Mexico City is one measure Espino used to infer neighborhood poverty levels. Data science is helping companies maximize profits, but it can also be a powerful tool for solving social problems. The Data Science for Social Good conference held last month in Chicago highlighted new work in this field, with two Data Science Institute Master’s students—Carlos Espino and Amir Imani —presenting research of their own. Imani’s project used natural language processing techniques to show that ethics rules governing chemists from country to country are more similar than many politicians realized. Espino used crowdsourced data, including cellphone records, to infer urban poverty levels in neighborhoods across Milan and Mexico City. Predicting Poverty Levels with Crowdsourced Data Most countries have some version of the U.S. Census Bureau…

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