huashen218/convxai-cia-dataset huggingface dataset:
Title: Monitoring Pets, Deterring Intruders, and Casually Spying on Neighbors: Everyday Uses of Smart Home Cameras
Authors: family: H. Tan
given: Neilly; family: Y. Wong
given: Richmond; family: Desjardins
given: Audrey; family: A. Munson
given: Sean; family: Pierce
given: James
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: design, surveillance, personal data, tracking, privacy, Internet of Things (IoT), smart cameras

Abstract: The increased adoption of smart home cameras (SHCs) foregrounds issues of surveillance, power, and privacy in homes and neighborhoods. However, questions remain about how people are currently using these devices to monitor and surveil, what the benefits and limitations are for users, and what privacy and security tensions arise between primary users and other stakeholders. We present an empirical study with 14 SHC users to understand how these devices are used and integrated within everyday life. Based on semi-structured qualitative interviews, we investigate users’ motivations, practices, privacy concerns, and social negotiations. Our findings highlight the SHC as a perceptually powerful and spatially sensitive device that enables a variety of surveillant uses outside of basic home security—from formally surveilling domestic workers, to casually spying on neighbors, to capturing memories. We categorize surveillant SHC uses, clarify distinctions between primary and non-primary users, and highlight under-considered design directions for addressing power imbalances among primary and non-primary users.
Title: Machine-Mediated Teaming: Mixture of Human and Machine in Physical Gaming Experience
Authors: family: Maekawa
given: Azumi; family: Saito
given: Hiroto; family: Uriu
given: Daisuke; family: Kasahara
given: Shunichi; family: Inami
given: Masahiko
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: sports design, physical interaction, augmentation, human-machine collaboration

Abstract: Technological advancement has opened up opportunities for new sports and physical activities. We introduce a concept called machine-mediated teaming, in which a human and a surrogate machine form a team to participate in physical sports games. To understand the experience of machine-mediated teaming and the guidelines for designing the system to achieve the concept, we built a case study system based on tug-of-war. Our system is a sports game played by two against two. One team consists of a player who actually pulls the rope and another player who participates in the physical game by controlling the machine’s actuators. We conducted user studies using this system to investigate the sport experience in this form and to reveal insights to inform future research on machine-mediated teaming. Based on the data obtained from the user studies, we clarified three perspectives, machine stamina, action space, and explicit feedback, that should be considered when designing future machine-mediated teaming systems. The research presented in this paper offers a first step towards exploring how humans and machines can coexist in highly dynamic physical interactions.
Title: “I’m Surprised So Much Is Connected”
Authors: family: Hammann
given: Sven; family: Crabb
given: Michael; family: Radomirovic
given: Sasa; family: Sasse
given: Ralf; family: Basin
given: David
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: security setup, user interviews., Account Graph

Abstract: A person’s online security setup is tied to the security of their individual accounts. Some accounts are particularly critical as they provide access to other online services. For example, an email account can be used for external account recovery or to assist with single-sign-on. The connections between accounts are specific to each user’s setup and create unique security problems that are difficult to remedy by following generic security advice. In this paper, we develop a method to gather and analyze users’ online accounts systematically. We demonstrate this in a user study with 20 participants and obtain detailed insights on how users’ personal setup choices and behaviors affect their overall account security. We discuss concrete usability and privacy concerns that prevented our participants from improving their account security. Based on our findings, we provide recommendations for service providers and security experts to increase the adoption of security best practices.
Title: “Okay, whatever”: An Evaluation of Cookie Consent Interfaces
Authors: family: Habib
given: Hana; family: Li
given: Megan; family: Young
given: Ellie; family: Cranor
given: Lorrie
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: GDPR, privacy notice, privacy choice, cookie consent

Abstract: Many websites have added cookie consent interfaces to meet regulatory consent requirements. While prior work has demonstrated that they often use dark patterns — design techniques that lead users to less privacy-protective options — other usability aspects of these interfaces have been less explored. This study contributes a comprehensive, two-stage usability assessment of cookie consent interfaces. We first inspected 191 consent interfaces against five dark pattern heuristics and identified design choices that may impact usability. We then conducted a 1,109-participant online between-subjects experiment exploring the usability impact of seven design parameters. Participants were exposed to one of 12 consent interface variants during a shopping task on a prototype e-commerce website and answered a survey about their experience. Our findings suggest that a fully-blocking consent interface with in-line cookie options accompanied by a persistent button enabling users to later change their consent decision best meets several design objectives.
Title: Field Evidence of the Effects of Privacy, Data Transparency, and Pro-social Appeals on COVID-19 App Attractiveness
Authors: family: Dooley
given: Samuel; family: Turjeman
given: Dana; family: Dickerson
given: John P; family: Redmiles
given: Elissa M.
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Pro-Social, Transparency, Field Study, Privacy, COVID-19

Abstract: COVID-19 exposure-notification apps have struggled to gain adoption. Existing literature posits as potential causes of this low adoption: privacy concerns, insufficient data transparency, and the type of appeal – collective- vs. individual-good – used to frame the app. As policy guidance suggests using tailored advertising to evaluate the effects of these factors, we present the first field study of COVID-19 contact tracing apps with a randomized, control trial of 14 different advertisements for CovidDefense, Louisiana’s COVID-19 exposure-notification app. We find that all three hypothesized factors – privacy, data transparency, and appeals framing – relate to app adoption, even when controlling for age, gender, and community density. Our results offer (1) the first field evidence supporting the use of collective-good appeals, (2) nuanced findings regarding the efficacy of data and privacy transparency, the effects of which are moderated by appeal framing and potential users’ demographics, and (3) field-evidence-based guidance for future efforts to encourage pro-social health technology adoption.
Title: To Self-Persuade or be Persuaded: Examining Interventions for Users’ Privacy Setting Selection
Authors: family: Krsek
given: Isadora; family: Wenzel
given: Kimi; family: Das
given: Sauvik; family: Hong
given: Jason I.; family: Dabbish
given: Laura
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Reflective Writing, Individual Differences, Privacy, Social Cybersecurity, Social Influence, Privacy Behaviors, Qualitative Methods, Social Proof, Surveys, Quantitative Methods, Authority, Decision Making

Abstract: User adoption of security and privacy (S&P) best practices remains low, despite sustained efforts by researchers and practitioners. Social influence is a proven method for guiding user S&P behavior, though most work has focused on studying peer influence, which is only possible with a known social graph. In a study of 104 Facebook users, we instead demonstrate that crowdsourced S&P suggestions are significantly influential. We also tested how reflective writing affected participants’ S&P decisions, with and without suggestions. With reflective writing, participants were less likely to accept suggestions — both social and Facebook default suggestions. Of particular note, when reflective writing participants were shown the Facebook default suggestion, they not only rejected it but also (unknowingly) configured their settings in accordance with expert recommendations. Our work suggests that both non-personal social influence and reflective writing can positively influence users’ S&P decisions, but have negative interactions.
Title: Online Terms and Conditions: Improving User Engagement, Awareness, and Satisfaction through UI Design
Authors: family: Kitkowska
given: Agnieszka; family: Högberg
given: Johan; family: Wästlund
given: Erik
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: terms & conditions, replication studies, online decision-making, UI design

Abstract: Too often, while interacting with online technologies, we blindly agree to services’ terms and conditions (T&Cs). We often disregard their content—believing it is not worth engaging with the long, hard-to-understand texts. The inconspicuous display of online T&Cs on the user interface (UI) adds to our lack of engagement. Nevertheless, certain information included in T&Cs could help us make optimal decisions. In this replication research, we investigate this issue in the purchasing context. We confirm and extend previous findings through an online experiment (N = 987), showing that differently presented T&Cs (icons, scroll, and cost-cue) compared to hyperlinked text affect whether people open them, becoming aware. We also show the effect of decision-making style on the relationship between awareness and satisfaction. We discuss the possible use of these findings to improve users’ informed decisions. We also highlight problems that different designs may pose, potentially increasing the information gap between users and service providers.
Title: Putting scientific results in perspective: Improving the communication of standardized effect sizes
Authors: family: Kim
given: Yea-Seul; family: Hofman
given: Jake M; family: Goldstein
given: Daniel G
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: perception, visualization, statistics, effect size

Abstract: How do people form impressions of effect size when reading scientific results? We present a series of studies on how people perceive treatment effectiveness when scientific results are summarized in various ways. We first show that a prevalent form of summarizing results—presenting mean differences between conditions—can lead to significant overestimation of treatment effectiveness, and that including confidence intervals can exacerbate the problem. We attempt to remedy potential misperceptions by displaying information about variability in individual outcomes in different formats: statements about variance, a quantitative measure of standardized effect size, and analogies that compare the treatment with more familiar effects (e.g., height differences by age). We find that all of these formats substantially reduce potential misperceptions and that analogies can be as helpful as more precise quantitative statements of standardized effect size. These findings can be applied by scientists in HCI and beyond to improve the communication of results to laypeople.
Title: Toward User-Driven Algorithm Auditing: Investigating users’ strategies for uncovering harmful algorithmic behavior
Authors: family: DeVos
given: Alicia; family: Dhabalia
given: Aditi; family: Shen
given: Hong; family: Holstein
given: Kenneth; family: Eslami
given: Motahhare
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Qualitative Methods, Algorithmic Harm, Fair Machine Learning, Search, Sensemaking, Collective Work, User-Driven Algorithm Auditing, Auditing Algorithms, Algorithmic Bias

Abstract: Recent work in HCI suggests that users can be powerful in surfacing harmful algorithmic behaviors that formal auditing approaches fail to detect. However, it is not well understood how users are often able to be so effective, nor how we might support more effective user-driven auditing. To investigate, we conducted a series of think-aloud interviews, diary studies, and workshops, exploring how users find and make sense of harmful behaviors in algorithmic systems, both individually and collectively. Based on our findings, we present a process model capturing the dynamics of and influences on users’ search and sensemaking behaviors. We find that 1) users’ search strategies and interpretations are heavily guided by their personal experiences with and exposures to societal bias; and 2) collective sensemaking amongst multiple users is invaluable in user-driven algorithm audits. We offer directions for the design of future methods and tools that can better support user-driven auditing.
Title: Where Should We Put It? Layout and Placement Strategies of Documents in Augmented Reality for Collaborative Sensemaking
Authors: family: Luo
given: Weizhou; family: Lehmann
given: Anke; family: Widengren
given: Hjalmar; family: Dachselt
given: Raimund
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Mixed Reality, collaborative sensemaking, qualitative user study, sensemaking, content organization, spatial layout, spatiality, Augmented Reality, affordance

Abstract: Future offices are likely reshaped by Augmented Reality (AR) extending the display space while maintaining awareness of surroundings, and thus promise to support collaborative tasks such as brainstorming or sensemaking. However, it is unclear how physical surroundings and co-located collaboration influence the spatial organization of virtual content for sensemaking. Therefore, we conducted a study (N=28) to investigate the effect of office environments and work styles during a document classification task using AR with regard to content placement, layout strategies, and sensemaking workflows. Results show that participants require furniture, especially tables and whiteboards, to assist sensemaking and collaboration regardless of room settings, while generous free spaces (e.g., walls) are likely used when available. Moreover, collaborating participants tend to use furniture despite personal layout preferences. We identified different placement and layout strategies, as well as the transitions in-between. Finally, we propose design implications for future immersive sensemaking applications and beyond.
Title: Characterizing Practices, Limitations, and Opportunities Related to Text Information Extraction Workflows: A Human-in-the-loop Perspective
Authors: family: Rahman
given: Sajjadur; family: Kandogan
given: Eser
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Human-AI collaboration, Information extraction, Data science workflows

Abstract: Information extraction (IE) approaches often play a pivotal role in text analysis and require significant human intervention. Therefore, a deeper understanding of existing IE practices and related challenges from a human-in-the-loop perspective is warranted. In this work, we conducted semi-structured interviews in an industrial environment and analyzed the reported IE approaches and limitations. We observed that data science workers often follow an iterative task model consisting of information foraging and sensemaking loops across all the phases of an IE workflow. The task model is generalizable and captures diverse goals across these phases (e.g., data preparation, modeling, evaluation.) We found several limitations in both foraging (e.g., data exploration) and sensemaking (e.g., qualitative debugging) loops stemming from a lack of adherence to existing cognitive engineering principles. Moreover, we identified that due to the iterative nature of an IE workflow, the requirement of provenance is often implied but rarely supported by existing systems. Based on these findings, we discuss design implications for supporting IE workflows and future research directions.
Title: Supporting Real-time Peer-Mentoring of Rural Volunteers
Authors: family: Varghese
given: Delvin; family: Bartindale
given: Tom; family: Montague
given: Kyle; family: Baillie Smith
given: Matt; family: Olivier
given: Patrick
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: volunteers, rural development, global south, mentoring, ICTD, international development, HCI4D

Abstract: Telephone-driven community forums have been a widely proposed solution to address the unreliable internet connectivity and large geographic scope that characterizes many international NGO contexts. Primarily, these applications support asynchronous activities, such as information portals or forums to access rural journalism, but opportunities for real-time experience sharing remain largely under-explored. In this paper, we explore the potential of such forums to support remote mentoring of NGO volunteers, a practice that requires synchronous, dialogical formats for experience sharing and peer discussion. We engaged 28 participants from a rural Indian NGO in the design of peer-mentoring sessions that leverage synchronous audio discussions, using the structure and format of traditional talk-show radio as a starting point. The participants favored an entertaining approach to mentoring and discussed the logistics required to achieve this within their resource constraints. We conclude with design implications for designing media-driven community engagement platforms and the ethical challenges around protecting marginalized community interests.
Title: Understanding AR Activism: An Interview Study with Creators of Augmented Reality Experiences for Social Change
Authors: family: Silva
given: Rafael M. L.; family: Principe Cruz
given: Erica; family: Rosner
given: Daniela K.; family: Kelly
given: Dayton; family: Monroy-Hernández
given: Andrés; family: Liu
given: Fannie
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: augmented reality, activism, social change

Abstract: The rise of consumer augmented reality (AR) technology has opened up new possibilities for interventions intended to disrupt and subvert cultural conventions. From defacing corporate logos to erecting geofenced digital monuments, more and more people are creating AR experiences for social causes. We sought to understand this new form of activism, including why people use AR for these purposes, opportunities and challenges in using it, and how well it can support activist goals. We conducted semi-structured interviews with twenty people involved in projects that used AR for a social cause across six different countries. We found that AR can overcome physical world limitations of activism to convey immersive, multilayered narratives that aim to reveal invisible histories and perspectives. At the same time, people experienced challenges in creating, maintaining, and distributing their AR experiences to audiences. We discuss open questions and opportunities for creating AR tools and experiences for social change.
Title: Care Workers Making Use of Robots: Results of a Three-Month Study on Human-Robot Interaction within a Care Home
Authors: family: Carros
given: Felix; family: Schwaninger
given: Isabel; family: Preussner
given: Adrian; family: Randall
given: Dave; family: Wieching
given: Rainer; family: Fitzpatrick
given: Geraldine; family: Wulf
given: Volker
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: Social Robot, Robotic Support, Social Service, Long-term, Appropriation, Work Practices, Residential Care, Practice-based, CSCW, Participatory Design, Pandemic, Empirical Study, Humanoid, Usage Patterns, Covid-19, HRI, Nurse, Sustainable Technology Integration, Care Work, HCI, Care Robot, Empowerment

Abstract: Research on social robots in care has often focused on either the care recipients or the technology itself, neglecting the care workers who, in and through their collaborative and coordinative practices, will need to work with the robots. To better understand these interactions with a social robot (Pepper), we undertook a 3 month long-term study within a care home to gain empirical insights into the way the robot was used. We observed how care workers learned to use the device, applied it to their daily work life, and encountered obstacles. Our findings show that the care workers used the robot regularly (1:07 hours/day) mostly in one-to-one interactions with residents. While the robot had a limited effect on reducing the workload of care workers, it had other positive effects, demonstrating the potential to enhance the quality of care.
Title: Something Personal from the Metaverse: Goals, Topics, and Contextual Factors of Self-Disclosure in Commercial Social VR
Authors: family: Sykownik
given: Philipp; family: Maloney
given: Divine; family: Freeman
given: Guo; family: Masuch
given: Maic
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: self-disclosure, online social interaction, social virtual reality

Abstract: Current Social VR literature provides limited insight on one of the most critical behaviors for developing and maintaining interpersonal relationships: self-disclosure. Therefore, we present an online survey (N = 126) investigating how users disclose personal information to each other in Social VR. Our results indicate that many participants see in Social VR access to authentic connections with others despite tending towards skepticism and privacy concerns. Most users disclose sexuality-related information, lifestyle preferences, and personal goals. In contrast, information that breaks anonymity, such as real names and more intimate aspects of oneself, are shared less commonly. Thereby, self-disclosure decisions depend on factors like the relationship to or age of disclosure recipients, the privacy of a virtual environment, the group size, or the activity context, and is driven by different goals, i.a., relational development or exploration of oneself. These insights advance the understanding of current Social VR users and their behavior by directing future research on self-disclosure-based relationship building in Social VR and outlying broader design implications for the future metaverse.
Title: The Effect of the Vergence-Accommodation Conflict on Virtual Hand Pointing in Immersive Displays
Authors: family: Batmaz
given: Anil Ufuk; family: Barrera Machuca
given: Mayra Donaji; family: Sun
given: Junwei; family: Stuerzlinger
given: Wolfgang
Venue: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
Keywords: selection, virtual hand, Fitts’ Law, vergence-accommodation conflict, 3D pointing

Abstract: Previous work hypothesized that for Virtual Reality (VR) and Augmented Reality (AR) displays a mismatch between disparities and optical focus cues, known as the vergence and accommodation conflict (VAC), affects depth perception and thus limits user performance in 3D selection tasks within arm’s reach (peri-personal space). To investigate this question, we built a multifocal stereo display, which can eliminate the influence of the VAC for pointing within the investigated distances. In a user study, participants performed a virtual hand 3D selection task with targets arranged laterally or along the line of sight, with and without a change in visual depth, in display conditions with and without the VAC. Our results show that the VAC influences 3D selection performance in common VR and AR stereo displays and that multifocal displays have a positive effect on 3D selection performance with a virtual hand.