Search for: All records

We present an empirical study exploring how privacy influences the acceptance of vaccination certificate (VC) deployments across different realistic usage scenarios. The study employed the privacy framework of Contextual Integrity, which has been shown to be particularly effective in capturing people’s privacy expectations across different contexts. We use a vignette methodology, where we selectively manipulate salient contextual parameters to learn whether and how they affect people’s attitudes towards VCs. We surveyed 890 participants from a demographically-stratified sample of the US population to gauge the acceptance and overall attitudes towards possible VC deployments to enforce vaccination mandates and the different information flows VCs might entail. Analysis of results collected as part of this study is used to derive general normative observations about different possible VC practices and to provide guidance for the possible deployments of VCs in different contexts. 

Privacy expectations during disasters differ significantly from nonemergency situations. This paper explores the actual privacy practices of popular disaster apps, highlighting location information flows. Our empirical study compares content analysis of privacy policies and government agency policies, structured by the contextual integrity framework, with static and dynamic app analysis documenting the personal data sent by 15 apps. We identify substantive gaps between regulation and guidance, privacy policies, and information flows, resulting from ambiguities and exploitation of exemptions. Results also indicate gaps between governance and practice, including the following: (a) Many apps ignore self-defined policies; (b) while some policies state they “might” access location data under certain conditions, those conditions are not met as 12 apps included in our study capture location immediately upon initial launch under default settings; and (c) not all third-party data recipients are identified in policy, including instances that violate expectations of trusted third parties.