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CSIS Seminar

Privacy, security, and ethical challenges in the era of ubiquitous data collection

Speaker:   Dr. Jessica Vitak, University of Maryland, College Park
When:   February 23, 2018, 11:00 am - 12:00 pm
Where:   Engineering Building, Room 1602


Over the past decade, the Internet of Things has pushed its way into our workplaces and homes by making regular products "smarter." We now wear watches to track our steps, heart rate, and sleep patterns. Our thermostats learn over time about our heating and cooling preferences. Our refrigerator can detect when we run out of milk. And our intelligent personal assistants passively listen for a voice cue ("Alexa!") to respond to our questions and commands. In many ways, we are living in the science fiction future we dreamed of decades ago. On the other hand, the influx of devices meant to collect constant data about your movement and location, health, and purchasing patterns raise significant questions about the privacy and security of that data. In this talk, I'll share early results from two NSF grants, one looking at privacy and surveillance on smartphones and intelligent personal assistants like Siri and Alexa, and the other collaborative project on pervasive data ethics. I'll also raise questions for researchers working in this space to consider as they work with large, public datasets to ensure they are taking adequate steps to protect the data and the users behind that data.

Speaker Bio

Jessica Vitak (PhD, Michigan State University) is an assistant professor in the College of Information Studies at the University of Maryland and associate director of the Human Computer Interaction Lab (HCIL). Her research evaluates the benefits and drawbacks of mediated communication technologies by focusing on the role that social and technical affordances shape interactions online. Specifically, she focuses on questions around data privacy and security, as well as pervasive data ethics, around the generation, collection, and analysis of large-scale user data. She is currently PI or Co-PI on three federal grants on these topics (NSF-SES-1640640, NSF-IIS-1704369, and IMLS-LG-81-16-0154-16). For more information, see https://pearl.umd.edu.