Context, Causality, and Information Flow: Implications for Privacy Engineering, Security, and Data Economics
The creators of technical infrastructure are under social and legal pressure to comply with expectations that can be difficult to translate into computational and business logics. The dissertation presented in this talk bridges this gap through three projects that focus on privacy engineering, information security, and data economics, respectively. These projects culminate in a new formal method for evaluating the strategic and tactical value of data. This method relies on a core theoretical contribution building on the work of Shannon, Dretske, Pearl, Koller, and Nissenbaum: a definition of information flow as a channel situated in a context of causal relations.
Sebastian Benthall is a security scientist working at the intersection of computer science, economics, law, and philosophy. He is a research fellow at the Digital Life Initiative at Cornell Tech and a data scientist for Ion Channel, a Washington, D.C., based cybersecurity company. Before becoming a scientist, Sebastian managed the development of spatial data infrastructure for global coordination around disaster risk reduction. He holds a B.A. in cognitive science from Brown University and is completing his Ph.D. at the UC Berkeley School of Information.