Human-centered research on emerging technological applications can inform the development of secure, privacy-preserving, products and procedures that align with social and legal standards. Directly engaging with stakeholders situated in particular contexts can provide detailed perspectives that reveal limitations, problems, or unmet needs in security approaches, data collection, data use, and accuracy of technologies.

This thesis demonstrates how direct engagement with stakeholders illuminates crucial problems and perspectives, consisting of four research studies consulting potential users or data subjects of technologies with broad social implications, focusing on four emerging technological applications: 1) AR glasses with advanced sensor capabilities, 2) AI analysis of voice data for decision-making in employment and education, 3) the convergence of information technology (IT) and operational technology (OT) in energy grid infrastructure, and 4) patient-facing medical translation tools. We first consider current AR users' context-sensitive privacy attitudes, preferences, and concerns regarding how future hypothetical AR glasses could collect and use data. Second, we report on how speakers of four US English dialects perceived potential benefits and harms of AI-enabled voice analysis in high-stakes employment and educational contexts. Third, we compare approaches to vulnerability impact assessment among experts in critical infrastructure and computer security, identifying notable differences in the self-reported approaches to assessing risk in energy systems between these two groups. Finally, we present attitudes, preferences, and concerns of Mandarin- and Spanish-speaking individuals with limited English proficiency (LEP) towards existing and emerging translation services and technologies in medical contexts.

We contribute an interdisciplinary approach to eliciting and analyzing firsthand stakeholder insights about privacy and security problems with emerging technologies. We use human-computer interaction methods to obtain rich, qualitative data and apply thematic coding, discourse analysis, and sociocultural anthropological considerations to contextualize participants' responses. Our approach elucidates context-sensitive and socially situated perceptions and attitudes regarding the privacy and security of various technologies, highlighting social dimensions often overlooked in usable privacy and security literature and revealing broader implications for policy and technology design.

213 pages

Thesis Committee:
Lujo Bauer (Co-chair)
Lorrie Cranor (Co-chair)
Emma Strubell
Renee Shelby (Google, Inc.)
Robert Erbes (Idaho National Laboratory)

Nicolas Christin, Head, Software and Societal Systems Department
Martial Hebert, Dean, School of Computer Science

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