Security

What can machines know about the mind? This dissertation seeks to understand people’s beliefs about this question: how these beliefs affect and arise from interactions with digital sensors, from prior beliefs about the mind and the body; and how these beliefs may shape the design of technical systems in the future.

The purpose of this dissertation is twofold. First, it surfaces that the boundary between sensing bodies and sensing minds is unstable, deeply entangled with social context and beliefs about the body and mind. Second, it proposes the porousness of this boundary as a site for studying the role that biosensing devices will play in near future. As biosensors creep into smart watches, bands, and ingestibles, their ability to divine not just what these bodies do, but what they think and feel, presents an under-explored avenue for understanding and imagining how thesetechnologies will come to matter in the course of life.

We investigate cybersecurity toolkits, collections of public facing materials intended to help users achieve security online. We look at design dimensions of these toolkits, and investigate how the toolkits construct security as a value and how they construct people as (in)secure users.

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. This dissertation 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: data games. This method relies on a core theoretical contribution building on the work of Shannon, Dretske, Pearl, Koller, and Nissenbaum: a definition of situated information flow as causal flow in the context of other causal relations and strategic choices.