“It would probably turn into a social faux-pas”: Users’ and Bystanders’ Preferences of Privacy Awareness Mechanisms in Smart Homes

Parth Kirankumar Thakkar, Shijing He, Shiyu Xu, Danny Yuxing Huang, and Yaxing Yao. 2022. “It would probably turn into a social faux-pas”: Users’ and Bystanders’ Preferences of Privacy Awareness Mechanisms in Smart Homes. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI '22). Association for Computing Machinery, New York, NY, USA, Article 404, 1–13. https://doi.org/10.1145/3491102.3502137

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Abstract

The opaque data practices in smart home devices have raised significant privacy concerns for smart home users and bystanders. One way to learn about the data practices is through privacy-related notifications. However, how to deliver these notifications to users and bystanders and increase their awareness of data practices is not clear. We surveyed 136 users and 123 bystanders to understand their preferences of receiving privacy-related notifications in smart homes. We further collected their responses to four mechanisms that improve privacy awareness (e.g., Data Dashboard) as well as their selections of mechanisms in four different scenarios (e.g., friend visiting). Our results showed the pros and cons of each privacy awareness mechanism, e.g., Data Dashboard can help reduce bystanders’ dependence on users. We also found some unique benefits of each mechanism (e.g., Ambient Light could provide unobtrusive privacy awareness). We summarized four key design dimensions for future privacy awareness mechanisms design.