This project takes a new approach to problems involving sensitive data, by focusing on rigorous mathematical modeling and characterization of the value of private information. By focusing on quantifying the loss incurred by affected individuals when their information is used -- and quantifying the attendant benefits of such use -- the approaches advanced by this work enable concrete reasoning about the relative risks and rewards of a wide variety of potential computations on sensitive data.
Specifically, this work has four main technical thrusts. The first is the development of new models and definitions, enabling privacy considerations to be incorporated into agent utility functions. The second is analysis of the feasibility and costs of eliciting sensitive information, in light of these models. The third focus is on enabling more sophisticated computations in settings where individuals value their privacy. Finally, more complex settings incorporate the interests of additional actors.
One of the goals of this project is not only to develop a science of the value of private information, but to build bridges between computer science and economics that will enable such work. Further, the models and algorithms developed by this project could inform future regulation regarding the use, exchange, and monetization of sensitive data. The project supports and is supported by a wide variety of educational goals, including significant research involvement of students at a range of stages, development of a course series with a substantial research component, and assessment of a pedagogical technique created to facilitate meaningful engagement with research literature.
