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  1. Smart home cameras raise privacy concerns in part because they frequently collect data not only about the primary users who deployed them but also other parties -- who may be targets of intentional surveillance or incidental bystanders. Domestic employees working in smart homes must navigate a complex situation that blends privacy and social norms for homes, workplaces, and caregiving. This paper presents findings from 25 semi-structured interviews with domestic childcare workers in the U.S. about smart home cameras, focusing on how privacy considerations interact with the dynamics of their employer-employee relationships. We show how participants’ views on camera data collection, and their desire and ability to set conditions on data use and sharing, were affected by power differentials and norms about who should control information flows in a given context. Participants’ attitudes about employers’ cameras often hinged on how employers used the data; whether participants viewed camera use as likely to reinforce negative tendencies in the employer-employee relationship; and how camera use and disclosure might reflect existing relationship tendencies. We also suggest technical and social interventions to mitigate the adverse effects of power imbalances on domestic employees’ privacy and individual agency. 
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  2. Commitment devices are a technique from behavioral economics that have been shown to mitigate the effects of present bias—the tendency to discount future risks and gains in favor of immediate gratifications. In this paper, we explore the feasibility of using commitment devices to nudge users towards complying with varying online security mitigations. Using two online experiments, with over 1,000 participants total, we offered participants the option to be reminded or to schedule security tasks in the future. We find that both reminders and commitment nudges can increase users’ intentions to install security updates and enable two-factor authentication, but not to configure automatic backups. Using qualitative data, we gain insights into the reasons for postponement and how to improve future nudges. We posit that current nudges may not live up to their full potential, as the timing options offered to users may be too rigid. 
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