Using Data For Good

by David J. Craig Published Spring 2018
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Portrait by Jörg Meyer

So what does it take to be a data scientist? Advanced skills in computer science, statistics, or math is a sound start — but it’s only a start. Intellectual versatility is essential, since data scientists often collaborate with experts in fields as varied as business, medicine, law, finance, journalism, and urban planning. And then there is the need to navigate the tricky ethical implications of one’s work. Are data scientists prepared to ensure the responsible use of data through the entire data life cycle, from collection to analysis to interpretation? Or might a project jeopardize people’s privacy, as occurred when the political-consulting firm Cambridge Analytica misused data from tens of millions of Facebook profiles in the lead-up to the 2016 presidential election?

Jeannette M. Wing, the director of Columbia’s Data Science Institute, says that she came to Columbia last year in part to promote discussion among faculty and students about these types of complex issues. A former corporate vice president of Microsoft Research, she notes that the nascent field of data science, which she defines elegantly as “the extraction of value from data,” has yet to establish best practices for handling such challenges. And she thinks that Columbia, which created its Data Science Institute in 2012 — years before similar research centers began to pop up at other universities — is poised to lead the conversation.

“In addition to being five years ahead of the curve in promoting interdisciplinary data-science projects, Columbia has an advantage in that lots of our scholars in the social sciences and humanities want to be a part of this dialogue,” she says. “And if the field of data science is going to evolve in a socially responsible way, you have to include their perspectives.”

Wing has certainly succeeded in raising the visibility of data science at Columbia since arriving here. The Data Science Institute, initially based in the engineering school, has been elevated to a University-wide research center; its 250 affiliated faculty and researchers are engaged in projects that touch nearly every academic discipline. Wing has also launched a postdoctoral fellowship program in data science, an undergraduate research program for promising young talent in the field, a seed-grant program to support new research collaborations, and a fundraising initiative aimed at creating new data-science faculty positions.

In all of her efforts, Wing says, she is guided by a simple mantra: “data for good.”

“I always say that at Columbia, we are harnessing the power of data science across all fields to drive exploration, provide insights, and make predictions to inform better decisions,” she says. “‘Data for good’ means using the power responsibly and ethically to tackle society’s greatest challenges.”


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