Theoretical computer science can be as remote and abstract as pure mathematics, but new research often begins in response to concrete, real-world problems. Such is the case with the work of Cynthia Dwork.
Over the course of a distinguished career, Dwork has crafted rigorous solutions to dilemmas that crop up at the messy interface between computing power and human activity. She is most famous for her invention in the early to mid-2000s of “differential privacy,” a set of techniques that safeguard the privacy of individuals in a large database. Differential privacy ensures, for example, that a person can contribute their genetic information to a medical database without fear that anyone analyzing the database will be able to figure out which genetic information is hers—or even whether she has participated in the database at all. And it achieves this security guarantee in a way that allows researchers to use the database to make new discoveries.
Dwork’s latest work has a similar flavor to it. In 2011 she became interested in the question of fairness in algorithm design. As she observes, algorithms increasingly control the kinds of experiences we have: They determine the advertisements we see online, the loans we qualify for, the colleges that students get into. Given this influence, it’s important that algorithms classify people in ways that are consistent with commonsense notions of fairness. We wouldn’t think it’s ethical for a bank to offer one set of lending terms to minority applicants and another to white applicants. But as recent work has shown—most notably in the book “Weapons of Math Destruction,” by the mathematician Cathy O’Neil—discrimination that we reject in normal life can creep into algorithms.
Privacy and ethics are two questions with their roots in philosophy. These days, they require a solution in computer science. Over the past five years, Dwork, who is currently at Microsoft Research but will be joining the faculty at Harvard University in January, has been working to create a new field of research on algorithmic fairness. Earlier this month she helped organize a workshop at Harvard that brought together computer scientists, law professors and philosophers.
Quanta Magazine spoke with Dwork about algorithmic fairness, her interest in working on problems with big social implications, and how a childhood experience with music shaped the way she thinks about algorithm design today. An edited and condensed version of the interview follows.
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