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1. Disaster privacy/privacy disaster

   https://doi.org/10.1002/asi.24353  

   Sanfilippo, Madelyn R.; Shvartzshnaider, Yan; Reyes, Irwin; Nissenbaum, Helen; Egelman, Serge (March 2020, Journal of the Association for Information Science and Technology)
2. Disaster Privacy/Privacy Disaster

   https://doi.org/10.1002/asi.24353  

   Sanfilippo, M.; Shvartzshnaider, Y.; Reyes, I.; Nissenbaum, H.; Egelman, S. (January 2020, Journal of the Association for Information Science and Technology)

   null (Ed.)

   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. 

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3. Transparent Privacy is Principled Privacy

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   https://doi.org/10.1109/TIFS.2022.3177953  

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5. Do Privacy Labels Answer Users’ Privacy Questions?

   Zhang, S.; Sadeh, N. (February 2023, Workshop on Usable Security and Privacy)

   Inspired by earlier academic research, iOS app privacy labels and the recent Google Play data safety labels have been introduced as a way to systematically present users with concise summaries of an app’s data practices. Yet, little research has been conducted to determine how well today’s mobile app privacy labels address people’s actual privacy concerns or questions. We analyze a crowd-sourced corpus of privacy questions collected from mobile app users to determine to what extent these mobile app labels actually address users’ privacy concerns and questions. While there are differences between iOS labels and Google Play labels, our results indicate that an important percentage of people’s privacy questions are not answered or only partially addressed in today’s labels. Findings from this work not only shed light on the additional fields that would need to be included in mobile app privacy labels but can also help inform refinements to existing labels to better address users’ typical privacy questions. 

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