Session:「Stay safe out there!」

Keeping a Low Profile?: Technology, Risk and Privacy among Undocumented Immigrants

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173688

論文アブストラクト: Undocumented immigrants in the United States face risks of discrimination, surveillance, and deportation. We investigate their technology use, risk perceptions, and protective strategies relating to their vulnerability. Through semi-structured interviews with Latinx undocumented immigrants, we find that while participants act to address offline threats, this vigilance does not translate to their online activities. Their technology use is shaped by needs and benefits rather than risk perceptions. While our participants are concerned about identity theft and privacy generally, and some raise concerns about online harassment, their understanding of government surveillance risks is vague and met with resignation. We identify tensions among self-expression, group privacy, and self-censorship related to their immigration status, as well as strong trust in service providers. Our findings have implications for digital literacy education, privacy and security interfaces, and technology design in general. Even minor design decisions can substantially affect exposure risks and well-being for such vulnerable communities.

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“That Really Pushes My Buttons”: Designing Bullying and Harassment Training for the Workplace

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3173809

論文アブストラクト: Workplace bullying and harassment have been identified as two of the most concerning silent and unseen occupational hazards of the 21st century. The design of bespoke training addressing domain-specific job roles and relations presents a particular challenge. Using the concept of data-in-place where data is understood as being bound and produced by a particular place, this paper describes how locally-situated accounts can be used to engage employees in workplace-specific training seminars. Using higher education as a case study, we describe a four-stage design process for future training efforts: (1) in-depth interviews for further understanding of bullying and harassment; (2) design of digital probes for capturing contextual data; (3) probe deployment and subsequent data analysis; (4) data-driven discussion-based seminars. We outline the potential for digital probes in promoting the denormalization of toxic workplace cultures, considerations for novel sensitive data governance models, and the discussion of data-in-place's temporal dimension.

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Unpacking Perceptions of Data-Driven Inferences Underlying Online Targeting and Personalization

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174067

論文アブストラクト: Much of what a user sees browsing the internet, from ads to search results, is targeted or personalized by algorithms that have made inferences about that user. Prior work has documented that users find such targeting simultaneously useful and creepy. We begin unpacking these conflicted feelings through two online studies. In the first study, 306 participants saw one of ten explanations for why they received an ad, reflecting prevalent methods of targeting based on demographics, interests, and other factors. The type of interest-based targeting described in the explanation affected participants' comfort with the targeting and perceptions of its usefulness. We conducted a follow-up study in which 237 participants saw ten interests companies might infer. Both the sensitivity of the interest category and participants' actual interest in that topic significantly impacted their attitudes toward inferencing. Our results inform the design of transparency tools.

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“A Stalker's Paradise”: How Intimate Partner Abusers Exploit Technology

論文URL: http://dl.acm.org/citation.cfm?doid=3173574.3174241

論文アブストラクト: This paper describes a qualitative study with 89 participants that details how abusers in intimate partner violence (IPV) contexts exploit technologies to intimidate, threaten, monitor, impersonate, harass, or otherwise harm their victims. We show that, at their core, many of the attacks in IPV contexts are technologically unsophisticated from the perspective of a security practitioner or researcher. For example, they are often carried out by a UI-bound adversary - an adversarial but authenticated user that interacts with a victim»s device or account via standard user interfaces - or by downloading and installing a ready-made application that enables spying on a victim. Nevertheless, we show how the sociotechnical and relational factors that characterize IPV make such attacks both extremely damaging to victims and challenging to counteract, in part because they undermine the predominant threat models under which systems have been designed. We discuss the nature of these new IPV threat models and outline opportunities for HCI research and design to mitigate these attacks.

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