Martin, Kirsten E. and Nissenbaum, Helen, Measuring Privacy: Using Context to Expose Confounding Variables (December 31, 2015). Available for download at SSRN: http://ssrn.com/abstract=2709584
“Past privacy surveys often omit important contextual factors and yield cloudy, potentially misleading results about how people understand and value privacy. We revisit two historically influential measurements of privacy that have shaped discussion about public views and sentiments as well as practices and policies surrounding privacy: (1) Alan Westin’s series of surveys establishing that people in their valuations of privacy persistently fall into three categories: fundamentalists, pragmatists, and unconcerned and (2) Pew Foundation’s survey of individuals’ ratings of ‘sensitive’ information. We find, first, the relative importance of types of sensitive information on meeting privacy expectations is highly dependent on the contextual actor receiving the information as well as the use of information. Respondents differentiate between contextual, appropriate use of information and the commercial use of information. Second, Westin’s privacy categories were a relatively unimportant factor in judging privacy violations of different scenarios. Even privacy unconcerned respondents rated the vignettes to not meet privacy expectations on average, and respondents across categories had a common vision of what constitutes a privacy violation. While groups differed slightly, contextual factors explained the tremendous variation within Westin’s groups. In sum, respondents were highly nuanced in their judgments about information by taking into consideration the context, actor, and use as well as the type of information. In addition, respondents had common concerns about privacy across Westin’s privacy categories. Significant for public policy we demonstrate that teasing out confounding variables, reveals significant commonality across respondents in their privacy expectations. For firms, our work reveals that respondents’ judgments of privacy violation are highly sensitive to how the information is shared and used after disclosure.”
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