Collective feedback can support an individual's decision-making process. For instance, individuals often seek the advice of friends, family, and co-workers to help them make privacy decisions. However, current technologies often do not provide mechanisms for this type of collaborative interaction. To address this gap, we propose a novel model of Community Oversight for Privacy and Security ("CO-oPS"), which identifies mechanisms for users to interact with people they trust to help one another make digital privacy and security decisions. We apply our CO-oPS model in the context of mobile applications ("apps"). To interrogate and refine this model, we conducted participatory design sessions with 32 participants in small groups of 2-4 people who know one another, with the goal of designing a mobile app that facilitates collaborative privacy and security decision-making. We describe and reflect on the opportunities and challenges that arise from the unequal motivation and trust in seeking support and giving support within and beyond a community. Through this research, we contribute a novel framework for collaborative digital privacy and security decision-making and provide empirical evidence towards how researchers and designers might translate this framework into design-based features.

Older adults are increasingly becoming adopters of digital technologies, such as smartphones; however, this population remains particularly vulnerable to digital privacy and security threats. To date, most research on technology used among older adults focuses on helping individuals overcome their discomfort or lack of expertise with technology to protect them from such threats. Instead, we are interested in how communities of older adults work together to collectively manage their digital privacy and security. To do this, we surveyed 67 individuals across two older adult communities (59 older adults and eight employees or volunteers) and found that the community's collective efficacy for privacy and security was significantly correlated with the individuals' self-efficacy, power usage of technology, and their sense of community belonging. Community collective efficacy is a group's mutual belief in its ability to achieve a shared goal. Using social network analysis, we further unpacked these relationships to show that many older adults interact with others who have similar technological expertise, and closer-knit older adult communities that have low technology expertise (i.e., low power usage and self-efficacy) may increase their community collective efficacy for privacy and security by embedding facilitators (e.g., employees or volunteers) who have more technical expertise within their communities. Our work demonstrates how both peer influence and outside expertise can be leveraged to support older adults in managing their digital privacy and security.

People often rely on their friends, family, and other loved ones to help them make decisions about digital privacy and security. However, these social processes are rarely supported by technology. To address this gap, we developed an Android-based mobile application ("app") prototype which helps individuals collaborate with people they know to make informed decisions about their app privacy permissions. To evaluate our design, we conducted an interview study with 10 college students while they interacted with our prototype. Overall, participants responded positively to the novel idea of using social collaboration as a means for making better privacy decisions. Yet, we also found that users are less inclined to help others and may be only willing to partake in conversations that directly affect themselves. We discuss the potential for embedding social processes in the design of systems that support privacy decision-making, as well as some of the challenges of this approach. I.

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