Search for: All records

The platformization of households is increasingly possible with the introduction of “intelligent personal assistants” (IPAs) embedded in smart, always-listening speakers and screens, such as Google Home and the Amazon Echo. These devices exemplify Zuboff’s “surveillance capitalism” by commodifying familial and social spaces and funneling data into corporate networks. However, the motivations driving the development of these platforms—and the dataveillance they afford—vary: Amazon appears focused on collecting user data to drive personalized sales across its shopping platform, while Google relies on its vast dataveillance infrastructure to build its AI-driven targeted advertising platform. This paper draws on cross-cultural focus groups regarding IPAs in the Netherlands and the United States. It reveals how respondents in these two countries articulate divergent ways of negotiating the dataveillance affordances and privacy concerns of these IPA platforms. These findings suggest the need for a nuanced approach to combating and limiting the potential harms of these home devices, which may otherwise be seen as equivalents. 

Voice-controlled intelligent personal assistants (IPAs) have seen tremendous growth in recent years on smartphones and as standalone devices in people’s homes. While research has examined the potential benefits and drawbacks of these devices for IPA users, few studies have empirically evaluated the role of privacy and trust in individual decision to adopt IPAs. In this study, we present findings from a survey of IPA users and non-users (N=1160) to understand (1) the motivations and barriers to adopting IPAs and (2) how concerns about data privacy and trust in company compliance with social contract related to IPA data affect acceptance and use of IPAs. We discuss our findings in light of social contract theory and frameworks of technology acceptance. 

Fitness trackers are an increasingly popular tool for tracking one’s health and physical activity. While research has evaluated the potential benefits of these devices for health and well-being, few studies have empirically evaluated users’ behaviors when sharing personal fitness information (PFI) and the privacy concerns that stem from the collection, aggregation, and sharing of PFI. In this study, we present findings from a survey of Fitbit and Jawbone users (N=361) to understand how concerns about privacy in general and user- generated data in particular affect users’ mental models of PFI privacy, tracking, and sharing. Findings highlight the complex relationship between users’ demographics, sharing behaviors, privacy concerns, and internet skills with how valuable and sensitive they rate their PFI. We conclude with a discussion of opportunities to increase user awareness of privacy and PFI.