Internet of Things in Context: Discovering Privacy Norms with Scalable Surveys
by Noah Apthorpe, Yan Shvartzshnaider, Arunesh Mathur, Nick Feamster
Privacy concerns surrounding disruptive technologies such as the Internet of Things (and, in particular, connected smart home devices) have been prevalent in public discourse, with privacy violations from these devices occurring frequently. As these new technologies challenge existing societal norms, determining the bounds of “acceptable” information handling practices requires rigorous study of user privacy expectations and normative opinions towards information transfer.
To better understand user attitudes and societal norms concerning data collection, we have developed a scalable survey method for empirically studying privacy in context. This survey method uses (1) a formal theory of privacy called contextual integrity and (2) combinatorial testing at scale to discover privacy norms. In our work, we have applied the method to better understand norms concerning data collection in smart homes. The general method, however, can be adapted to arbitrary contexts with varying actors, information types, and communication conditions, paving the way for future studies informing the design of emerging technologies. The technique can provide meaningful insights about privacy norms for manufacturers, regulators, researchers and other stakeholders. Our paper describing this research appears in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.