Bringing together interdisciplinary faculty from the iSchool, economically disadvantaged/low socioeconomic status (SES) families, and public library partners may help minimize privacy and security challenges that librarians face and risks that low-SES families face using internet and communication technologies (ICTs).
Jessica Vitak

Jessica Vitak
Dr. Jessica Vitak is an associate professor in the College of Information Studies at the University of Maryland and an affiliate professor in the Communication Department. In addition, she is director of the Center for the Advanced Study of Communities and Information (CASCI) and associate director of the Human Computer Interaction Lab (HCIL).
Focus
Dr. Vitak's research evaluates the benefits and drawbacks of mediated communication technologies by focusing on the role that social and technical affordances shape interactions online.
Current Research Interests
- Data privacy and security
- Pervasive data ethics
- Generation, collection, and analysis of large-scale user data
Education
- PhD, Michigan State University
Enhancing Digital Privacy and Security Skills for Low-Socioeconomic Families: Resources for Librarians and Patrons
Mapping Privacy and Surveillance Dynamics in Emerging Mobile Ecosystems: Practices and Contexts in the Netherlands and US
Mobile devices are efficient and convenient, but also increase the potential for more pervasive forms of digitally mediated surveillance by media companies, marketers, governments, employers, and Internet Service Providers. This project evaluates mobile users’ mental models of privacy.
Collaborative Research: Pervasive Data Ethics for Computational Research (PERVADE)
Increasingly pervasive data about people enables fundamentally new computational research. Simultaneously, changes in scale, scope, speed, and depth of data availability require reconsideration of ethics for computational research. Much work addressing ethics for big and pervasive data proceeds from first principles, applying traditional tenets of research ethics to computational data research.