In his talk, Alessandro Acquisti links two streams of research he is conducting at Carnegie Mellon University: the “behavioral economics of privacy,” and the study of privacy and disclosure behavior in online social networks. First, he highlights how research in behavioral economics can help us make sense of apparent inconsistencies in privacy (and security) decision-making, and presents results from a variety of experiments in this area he conducted at Carnegie Mellon University. Then, he discusses the technical feasibility and privacy implications of combining publicly available Web 2.0 images with off-the-shelf face recognition technology, for the purpose of large-scale, automated individual re-identification. Combined, the results highlight the behavioral, technological, and legal challenges raised by the convergence of new information technologies, and raise questions about the future of privacy in an augmented reality world.