With the emergence of the Internet of Things and a data-centric economy, where a growing number of products, services and business processes rely on the collection and processing of user data, people are increasingly confronted with an unmanageable number of privacy decisions. What is needed is a new, more scalable paradigm that empowers them to regain control over their data. Over the past ten years, my group at CMU has been working towards the development of personalized privacy assistants. To be effective, these assistants will have to be capable of incrementally learning the privacy preferences of their users, semi-automatically configure many privacy settings on their behalf and generally alert their users about privacy practices they may not be expecting. These assistants will have to be minimally disruptive, limiting their interactions with us to the bare minimum, yet knowing enough about us to make many decisions on our behalf.
Through these very selective interactions, they will alert us about practices we may not feel comfortable with, confirm privacy settings they are not sure how to configure, refine models of our preferences, and occasionally nudge us to carefully (re)consider the implications of some of our privacy decisions.
As part of this presentation, I will summarize our progress in this area, focusing in particular on a series of pilot studies conducted to evaluate personalized privacy assistant functionality developed to help smartphone users manage their mobile app privacy settings. I will also review some of the ethical and business challenges that the development of this type of technology needs to consider.
Norman Sadeh is a Professor in the School of Computer Science at Carnegie Mellon University. His research interests span mobile and pervasive computing, cybersecurity and privacy, human computer interaction, machine learning and personal assistants. Norman is director of the School of Computer Science’s Mobile Commerce Lab and also co-founder and co-director of the School of Computer Science’s Master’s Program in Privacy Engineering. He also co-founded and served as co-director of the School’s PhD Program in Societal Computing during its first ten years.
Dr. Sadeh is also co-founder, chairman and chief scientist of Wombat Security Technologies, a CMU spinoff that sells a unique suite of cybersecurity training products and anti-phishing filtering technologies. Norman has been on the faculty at Carnegie Mellon since 1991 and is also well-known for his work on the livehoods project as well as earlier work in scheduling, constraint satisfaction and constrained optimization, supply chain management and Semantic Web technologies. In the late nineties, he served as Chief Scientist of the European Union’s $600M e-Work and e-Commerce program, which at the time included all pan-European research in cyber security and online privacy.
Norman received his PhD in computer science from Carnegie Mellon University, an MSc, also in computer science, from the University of Southern California, and a BS/MSc in Electrical Engineering and Applied Physics from Brussels Free University.