At the first White House public workshop on Big Data, Latanya Sweeney, a leading privacy researcher at Carnegie Mellon and Harvard who is now the chief technologist for the Federal Trade Commission, was quoted as asking about privacy and big data, “computer science got us into this mess; can computer science get us out of it?”
There is a lot computer science and other technology can do to help consumers in this area. Some examples:
• The same predictive analytics and machine learning used to understand and manage preferences for products or content and improve user experience can be applied to privacy preferences. This would take some of the burden off individuals to manage their privacy preferences actively and enable providers to adjust disclosures and consent for differing contexts that raise different privacy sensitivities.
Computer science has done a lot to improve user interfaces and user experience by making them context-sensitive, and the same can be done to improve users’ privacy experience.
• Tagging and tracking privacy metadata would strengthen accountability by making it easier to ensure that use, retention, and sharing of data is consistent with expectations when the data was first provided.
• Developing features and platforms that enable consumers to see what data is collected about them, employ visualizations to increase interpretability of data, and make data about consumers more available to them in ways that will allow consumers to get more of the benefit of data that they themselves generate would provide much more dynamic and meaningful transparency than static privacy policies that few consumers read and only experts can interpret usefully.
In a recent speech to MIT’s industrial partners, I presented examples of research on privacy-protecting technologies.
