Social & Cultural Studies

Professionals tasked with preserving online security hope to use new machine-learning based techniques to develop a “fairer” system to determine patterns of “good” and “bad” usage, moving beyond regional blocking. However, we argue that these systems may continue to embed unequal treatments, and troublingly may further disguise such discrimination behind more complex and less transparent automated assessment.

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.