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Abstract:
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Helen Nissenbaum’s theory of privacy as contextual integrity provides a useful framework for thinking about how and why privacy violations occur. Rather than treat privacy as a binary (i.e., you have it or you don’t), contextual integrity argues that whether an action violates one’s privacy depends on the norms of information flows in that context. We can identify numerous examples of data flows that are acceptable in one context (e.g., sharing medical details with your doctor) but are viewed as unacceptable in other contexts (e.g., your doctor sharing those medical details with your supervisor). In this presentation, I’ll share several examples of how contextual integrity can help us move beyond the privacy paradox to consider a range of contextual factors that influence people’s decisions to disclose personal information when sharing digital trace data. Using a diverse set of methods, including factorial vignettes and card sorting activities, can help reveal how even small changes in the attributes associated with an information disclosure can significantly influence whether one perceives that data sharing to be acceptable—or as a privacy violation.
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