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Designing programmable privacy logic frameworks that correspond to social, ethical, and legal norms has been a fundamentally hard problem. The theory of Contextual integrity (CI) (Nissenbaum 2010) offers a model for conceptualizing privacy that is able to bridge technical design with ethical, legal, and policy approaches. While CI is capable of capturing the various components of contextual privacy in theory, it is challenging to discover and formally express these norms in operational terms. This talk will discuss our work in designing a framework for crowdsourcing privacy norms based on the theory of contextual integrity.

Bio:
Yan Shvartzshanider is a postdoctoral research associate at CITP and a postdoctoral researcher in the Department of Media, Culture, and Communication at New York University. He is also affiliated with Open Networks and Big Data Lab in the Courant Institute of Mathematical Sciences at NYU. Yan received his Ph.D. in Engineering from the University of Sydney, Australia and is currently working on architectures and algorithms for privacy-preserving information systems. In particular, his work focused on developing a privacy framework based on the theory of Contextual Integrity. Before NYU, Yan held postdoctoral positions in Princeton (Edge lab) and Cambridge University (OCaml lab) where he worked on designing networked systems architectures for the Internet of Things and Fog networks. In general, Yan is passionate about solving fundamental problems that have real-world impact as well as fascinated by the commercial side of transferring ideas into viable business propositions.