Abstract Apps like Life 360 and Apple’s Find My have made continuous map-based location-sharing common and convenient. Yet, knowledge of how location-sharing is used in day-to-day life remains limited – especially in relation to young adults. Through a combination of interviews with participants and the deployment of daily mini-questionnaires among college-aged users (i. e. 18-22, $$n=15$$ n = 15 ) in the New York City area, we identify and present three salient aspects of location-sharing practices: (i) orchestration of social activities; (ii) management of social membership; and (iii) production of a “sense” of safety for oneself and others. Our findings point to new social norms emerging in relation to the proliferation of location-sharing apps among New York college students. We discuss such new norms through the lenses of self-disclosure, privacy, and trust-building. Our research scaffolds a more holistic understanding of location-sharing practices among a generation of digital natives and, in return, provides insights into future of designs of location-based technology.

Social media apps present personalized content to users. Such content is often described as “for you,” raising questions about the relationship between users’ sense of “self” and the “you” that is represented. Answering such questions is pressing in the case of teen users whose identities are still forming. Thus we ask, “What do teens think about the relationship between personalized content and their sense of self?” We interviewed teens aged 13 to 17 (n = 15) about their experiences with personalized content on social media. Participants so routinely saw themselves accurately reflected in personalized content that they noted the occasional inaccuracy with surprise, while simply scrolling past it. Our findings point to: the normalization of data doubles in the form of personalized content; and teens’ indifference to inaccuracies presented by such data doubles.

This study investigates people's perceptions of AI decision-making as compared to human decision-making within the job application context.It takes into account both favorable and unfavorable outcomes, employing a 2 � 2 experimental design (decision-making agent: AI algorithm vs. human; outcome: favorable vs. unfavorable).Upon evaluating a job seeker's suitability for a position, participants viewed algorithmic decisions as fairer, more competent, more trustworthy, and more useful than those made by humans.Interestingly, when a candidate was deemed unsuitable for hiring, people reacted more negatively to the verdict given by a human than to the same judgment offered by AI.Moreover, participants credited algorithmic decisions with greater sensitivity to both quantitative and qualitative qualifications, thus indicating algorithmic appreciation.Our findings shed light on the psychological basis of perceptions surrounding Algorithmic Decision-Making (ADM) and the responses to the decisions rendered by ADM systems.

Research involving sensitive data often leads to valuable human-centered insights. Yet, the effects of participating in and conducting research about sensitive data with youth are poorly understood. We conducted meta-level research to improve our understanding of these effects. We did the following: (i) asked youth (aged 13-21) to share their private Instagram Direct Messages (DMs) and flag their unsafe DMs; (ii) interviewed 30 participants about the experience of reflecting on this sensitive data; (iii) interviewed research assistants (RAs, n=12) about their experience analyzing youth's data. We found that reflecting about DMs brought discomfort for participants and RAs, although both benefited from increasing their awareness about online risks, their behavior, and privacy and social media practices. Participants had high expectations for safeguarding their private data while their concerns were mitigated by the potential to improve online safety. We provide implications for ethical research practices and the development of reflective practices among participants and RAs through applying trauma-informed principles to HCI research.

Digital privacy is confusing. As such, technology companies deploy anthropomorphic metaphors to simplify what digital privacy means. By leveraging the familiarity of the body, such metaphors ostensibly make the intangible complexity of digital privacy graspable. Yet by anthropomorphizing technologies involved in the transformation of the discourse of privacy into a discourse of digital privacy, such metaphors confound the promise of ''more-than-human'' ontology. Through constant comparative analysis of the role that human embodiment plays in historical and contemporary discourses of privacy, this paper weighs the philosophical costs of using anthropomorphic metaphors to simplify the discourse of digital privacy. I argue that anthropomorphic metaphors problematically align contemporary technologies with an anachronistic discourse of the human, rather than productively surfacing more-than-human possibilities for understanding entangled modes of being. I provide theoretical implications for research in computing that hopes to harness the non-anthropocentric sensitivity of the ''more-than-human'' to effect responsible change in the world.

Well-being apps promise to improve people's lives. Yet evidence shows that the data-hungry app culture that contextualizes well-being apps normalizes the user experience of affective discomfort. This apparent contradiction raises a difficult question: Is it responsible to ask people to improve their well-being by engaging further with an app culture that normalizes affective discomfort? We approached this question by deploying an online, scenario-based survey (n=688) about a fictional, but realistic well-being app called "Thalia." Thalia represents a novel class of well-being apps that are envisioned to: (i) utilize AI-driven facial recognition and analysis; and (ii) collect data for use in medical contexts. We found that people perceived Thalia to be affectively discomfiting even as they judged Thalia to be beneficial. Such findings imply a trade-off between 'better living through technology' and the negative affective implications of surveillance capitalistic app culture. Such a trade-off necessitates high-level analysis of just what "well-being" means in the context of contemporary app culture. Through analysis and discussion, we explore a troubling interplay between novel well-being apps and affective discomfort that requires careful attention from HCI researchers if human-centered well-being -- flourishing -- is truly what our products are intended to foster.

Drawing on insights from focus group interviews (n = 82) conducted during the development of Long Beach, California’s Smart City Strategic Initiative (SCSI), we examine the extent to which the four guiding principles of the SCSI correspond to Long Beach residents’ perceptions and concerns about the smart city: design for equity; earn public interest; cultivate local expertise; build civic resilience. Participants expressed widespread wariness of the fairness of smart city technologies. We find that Bernard De Koven’s theory of the well-played game constitutes a promising framework for the fair deployment and maintenance of smart city technologies. Based on De Koven’s work and participant insights, we provide a series of empirically-grounded and theoretically informed implications for design intended to leverage the collaborative spirit of play communities in the design of smart cities.

It is not well understood why people continue to use privacy-invasive apps they consider creepy. We conducted a scenario-based study (n = 751) to investigate how the intention to use an app is influenced by affective perceptions and privacy concerns. We show that creepiness is one facet of affective discomfort, which is becoming normalized in app use. We found that affective discomfort can be negatively associated with the intention to use a privacy-invasive app. However, the influence is mitigated by other factors, including data literacy, views regarding app data practices, and ambiguity of the privacy threat. Our findings motivate a focus on affective discomfort when designing user experiences related to privacy-invasive data practices. Treating affective discomfort as a fundamental aspect of user experience requires scaling beyond the point where the thumb meets the screen and accounting for entrenched data practices and the sociotechnical landscape within which the practices are embedded.

Pandemic-tracking apps may form a future infrastructure for public health surveillance. Yet, there has been relatively little exploration of the potential societal implications of such an infrastructure. In semi-structured interviews with 23 participants from India, the Middle East and North Africa (MENA), and the United States, we discussed attitudes and preferences regarding the deployment of apps that support contact tracing to contain the spread of COVID-19. Through interpretive analysis, we examined the relationship between persistent discomfort and vulnerability when using such apps. Such an examination yielded three temporal forms of vulnerability: real, anticipatory, and speculative. By identifying and defining the temporalities of vulnerability through an analysis of people's pandemic-related thoughts and experiences, we develop the overlapping discourses of humanistic infrastructure studies and infrastructural speculation. In doing so, we explore the concept of vulnerability itself and present implications for the study of vulnerability in Human-Computer Interaction (HCI) and for the oversight of app-based public health surveillance.

Pandemic-tracking apps could be a viable pandemic-mitigation technique, although their efficacy has been weakened by limited adoption in many places. Therefore, it is important to investigate how the perceptions of such apps are formed in different regions, which may help explain the differences in adoption. We replicated prior work on the adoption of pandemic-tracking apps in the United States with participants from India (n = 236). We identified that the perceptions of pandemic-tracking apps are connected to social orientation, familiarity with health-related technology, and demographics. We found that the perceptions and expected use were uncorrelated with privacy concerns, suggesting that privacy may not necessarily be the most suitable lens for studying the adoption of pandemic-tracking apps in India. Based on the findings, we make several recommendations for future pandemic-preparedness campaigns and identify the need to continue the trend toward contextualizing privacy-centered research with privacy-adjacent individual factors across multiple regions.

“There’s an app for that” is perhaps the definitive rhetoric of our times. To understand how users navigate the trade-offs involved in using apps that support a variety of everyday activities, we conducted scenario-based semi-structured interviews (n = 25). Despite the technical and regulatory mechanisms that are supposedly meant to empower users to manage their privacy, we found that users express an overarching feeling of resignation regarding privacy matters. Because these apps provide convenience and other benefits, as one participant put it, “there is a very fine line” that marks the divide between feeling empowered in the use of technology and coping with the discomfort and creepiness arising from invasive app behavior. Participants consistently expressed being resigned to disclose data even as they accepted personal responsibility for their own privacy. We apply the findings to discuss the limits of empowerment as a design logic for privacy-oriented solutions.

The deployment of technologies to track and mitigate the spread COVID-19 has surfaced tensions between individual autonomy and the collective good. These tensions reflect a conflict between two central concerns: (i) effectively controlling the spread of the pandemic and (ii) respecting individual rights, values, and freedoms. We explored these tensions in an online experiment (n = 389) designed to identify the influence of social orientation and communicative framing on perceptions and expected use of pandemic-tracking apps. We found that social orientation is a statistically significant predictor of app perception and expected use, with collectivist social orientation associated with higher levels and individualist social orientation with lower levels for both aspects. We found interactions between social orientation and communicative framing, as well as a connection between privacy concerns and expected duration of app use. Our findings hold important implications for the design, deployment, and adoption of technology for the public good. Shaping the post-pandemic social contract requires considering the long-term sociocultural impact of these technological solutions.