Work in the Data Privacy Lab consists of two competing teams. The first team involves developing ways to learn sensitive information from disparate and seemingly innoncent information. Results from this team are termed semantic learning algorithms and members of this team are called "data detectives." Being good at learning sensitive information from data allows the Data Privacy Lab to better understand what is needed to be "data protectors," which is name given to members of the second team. By constructing solutions that can provably control what can be learned, the Data Privacy Lab provides effective privacy technology for real-world problems. For more information, see Privacy is a Learning Problem" and related essays by our director, Dr. Latanya Sweeney.
The Data Privacy Lab seeks balanced, integrated solutions that weave technology and policy together.
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