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Saturday, September 28 • 9:00am - 9:35am
Mobile Privacy Expectations in Context

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An increasing amount of social activity and commerce is performed using mobile devices such as phones and tablets. These devices collect and transfer many types of mobile data, including location information, activities, motion information, text, and sound. In addition, individuals interact with mobile devices in new ways by integrating the phone in their daily activities. With new forms of data collection, consumers, organizations, and regulators struggle to address privacy expectations across a diverse set of activities on mobile devices.

This paper will describe findings from empirical research employing a context-based survey to understand consumers? privacy expectations for mobile devices across diverse real-world contexts. The study asks:
1) How do individuals? privacy expectations change between mobile application contexts?
2) What factors change these expectations?

To answer these questions, the project will test the hypotheses that (a) individuals hold different privacy expectations based on the context of their mobile activity, and (b) contextual factors such as who (the data collection actor, e.g. the application developer or mobile phone provider), what (data attributes, e.g. the type of information received or tracked by the primary organization), why (application context, e.g. games, weather, social networking, navigation, music, banking, shopping, and productivity) and how (the use of data, e.g. the amount of time data is stored or how that data is reused) affect individuals? privacy expectations. A promising direction of privacy scholarship ? privacy as contextual integrity (Nissenbaum, 2009) ? provides the theoretical backbone for the empirical work and posits that expectations about use and transmission of information are dependent upon the context. Individuals exchange information with particular people for a specific purpose, and expectations around what constitutes appropriate flows of information vary across such contexts. The theory suggests that tactics to address privacy expectations with mobile devices should depend on the context of the exchange.

To test the hypotheses and investigate whether and how privacy expectations vary across contexts in mobile activity, the researchers are conducting a survey using factorial vignette methodology (Wallander, 2009), in which respondents answer questions based on a series of hypothetical vignettes. This method allows the researchers to simultaneously examine multiple factors ? e.g. changes in context and types of information sharing ? by providing respondents with rich vignettes which are systematically varied. The mobile privacy survey is being piloted using Amazon?s Mechanical Turk to recruit respondents. After initial pilot runs, we will gather participants who use mobile applications using snowball sampling with a reward for completion.

This paper will report on survey findings that identify contextual factors of importance in the mobile data ecosystem. Because addressing privacy expectations for mobile devices is an explicit goal of US regulatory bodies, understanding how consumer privacy expectations change in different data use and business contexts can help regulators identify contexts that may require stricter privacy protections and help firms and managers better meet privacy expectations of users. Study results will be responsive to pressing government needs and societal concerns about mobile privacy and will have direct implications for researchers, business leaders, policy experts, and consumers. Finally, the study?s results will be compared to results from a parallel survey on online privacy and context to give guidance as to whether and how policies and practices about managing privacy should differ for the mobile ecosystem.

Nissenbaum, H. (2009). Privacy in Context: Technology, Policy, and the Integrity of Social Life. Stanford, CA: Stanford Law Books.
Wallander, L. (2009). 25 years of factorial surveys in sociology: A review. Social Science Research, 38(3), 505?520.


Katie Shilton

Associate Professor & Doctoral Program Director, University of Maryland
Katie Shilton is an Associate Professor at College of Information Studies and leads the Ethics & Values in Design (EViD) Lab at the UMD iSchool. Her research and teaching explores ethics and policy for the design of information collections, systems and technologies, and digital c... Read More →

Saturday September 28, 2013 9:00am - 9:35am PDT
GMUSL Room 332

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