bluuebunny/crossref_metadata_2025 huggingface dataset:
Toward a Feminist Social Media Vulnerability Taxonomy
Authors: Barta Kristen , Pyle Cassidy , Andalibi Nazanin
Published: April 2023

Vulnerability intimately shapes the lived human experience and continues to gain attention in computer-supported cooperative work and human-computer interaction scholarship broadly, and in social media studies specifically. Social media comprise sociotechnical affordances that may uniquely shape lived experiences with vulnerability, rendering existing frameworks inadequate for comprehensive examinations of vulnerability as mediated on social media. Through interviews with social media users in the United States (N = 20) and drawing on feminist conceptualizations of vulnerability and social media disclosure and privacy scholarship, we propose a feminist taxonomy of social media vulnerability (FSMV). The FSMV taxonomy reflects vulnerabilitysources, states, andvalences, within which we introduce the state ofnetworked vulnerability andambivalent, desired, andundesired valences. We describe how social media enable forms of vulnerability different from in-person settings, challenge framings that synonymize vulnerability with risk/harm, and facilitate interdisciplinary theory-building. Additionally, we discuss hownetworked, ambivalent, andun/desired vulnerability extend and diverge from prior work to create a theoretically rich taxonomy that is useful for future work on social media and vulnerability. Finally, we discuss implications for design related to granular control over profile, content, and privacy settings, as well as implications for platform accountability, as they pertain to social media vulnerability.
Transparency, Trust, and Security Needs for the Design of Digital News Authentication Tools
Authors: Francis Errol , Monroe Ayana , Sidnam-Mauch Emily , Ivancsics Bernat , Washington Eve , McGregor Susan E. , Bonneau Joseph , Caine Kelly
Published: April 2023

Americans' trust in news is declining, and authenticity and transparency challenges in digital publishing contexts pose unique challenges to the ability to effectively gratify their information-seeking needs via online media. Cryptographic technologies and web-based provenance indicators have the potential to enhance the trustworthiness and transparency of digital communication, but better understandings of news consumers practices and needs are required to develop practical tools. Through a representative online survey of 400 digital news consumers and 19 follow-up interviews, we investigate how users authenticate and assign trust to news content, and identify specific needs pertaining to news transparency and authentication that could be met by digital news authentication tools. While many users currently rely on political ideology to assess news trustworthiness, we find that users of all political orientations see value in independent provenance and authentication tools for digital news.
Trigger or Treat: Using Technology to Facilitate the Perception of Cravings and Corresponding Cues for Achieving Clinical-friendly Drug Psychotherapy
Authors: You Chuang-Wen , Hung Min-Wei , Hou Chi-Ting , Ho Chieh-Jui , Yuan Chien Wen (Tina) , Bi Nanyi , Huang Ming-Chyi
Published: April 2023

Drug addiction is a chronic condition, marked by compulsive drug use. In previous research, cue exposure and biofeedback technologies proved effective in drug psychotherapy sessions; however, the focus has generally been on the awareness of cravings and the identification of cues. There has been relatively little research on methods aimed at facilitating therapist-patient communication, particularly from a user-centered perspective. In this paper, we describe a qualitative technology probe study exploring the means by which patients identify cues and perceive cravings as well as the way that they communicate with therapists. Our analysis considers the difficulties in cue identification and craving perception, the interactions between the two, and the means by which these characteristics could impact the design of VR support systems in the future.
Tweet Trajectory and AMPS-based Contextual Cues can Help Users Identify Misinformation
Authors: Zade Himanshu , Woodruff Megan , Johnson Erika , Stanley Mariah , Zhou Zhennan , Huynh Minh Tu , Acheson Alissa Elizabeth , Hsieh Gary , Starbird Kate
Published: April 2023

Well-intentioned users sometimes enable the spread of misinformation due to limited context about where the information originated and/or why it is spreading. Building upon recommendations based on prior research about tackling misinformation, we explore the potential to support media literacy through platform design. We develop and design an intervention consisting of a tweet trajectory-to illustrate how information reached a user-and contextual cues-to make credibility judgments about accounts that amplify, manufacture, produce, or situate in the vicinity of problematic content (AMPS). Using a research through design approach, we demonstrate how the proposed intervention can help discern credible actors, challenge blind faith amongst online friends, evaluate the cost of associating with online actors, and expose hidden agendas. Such facilitation of credibility assessment can encourage more responsible sharing of content. Through our findings, we argue for using trajectory-based designs to support informed information sharing, advocate for feature updates that nudge users with reflective cues, and promote platform-driven media literacy.
Twitter has a Binary Privacy Setting, are Users Aware of How It Works?
Authors: Keküllüoglu Dilara , Vaniea Kami , Wolters Maria K. , Magdy Walid
Published: April 2023

Twitter accounts are public by default, but Twitter gives the option to create protected accounts, where only approved followers can see their tweets. The publicly visible information changes based on the account type and the visibility of tweets also depends solely on the poster's account type which can cause unintended disclosures especially when users interact. We surveyed 336 Twitter users to understand users' awareness of account information visibility, as well as the tweet visibility when users interact. We find that our participants are aware of the visibility of their profile information and individual tweets. However, the visibility of followed topics, lists, and interactions with protected accounts is confusing. Only 31% of the participants were aware that a reply by a public account to a protected account's tweet would be publicly visible. Surprisingly, having a protected account does not result in a better understanding of the account information or tweet visibility.
Understanding Motivational Factors in Social Media News Sharing Decisions
Authors: Wang Luping , Rzeszotarski Jeffrey M.
Published: April 2023

News sharing has become prevalent on many social media platforms. Users are not only exposed to news shared by others, but also actively share information with a diverse set of motivations. In this work, we propose five news sharing motivations based on the intrinsic and extrinsic factors found in prior literature. Through an online experiment, we further examine how a host of factors, including motivations, influence participants' decision to share news online. We then prompt participants to switch their original decision for extra compensation, observing how different news types, motivational and demographic factors may affect the switch. Our analysis suggests that sharing decisions can be reversed when a strong external stimulus (higher bonus) is presented. Further, there are motivational factors that independently influence participants' reversal decisions. Finally, using our work as an empirical basis, we propose designs for future new sharing systems.
Understanding Platform Mediated Work-Life: A Diary Study with Gig Economy Freelancers
Authors: Alvarez de la Vega Juan Carlos , Cecchinato Marta E. , Rooksby John , Newbold Joseph
Published: April 2023

Online freelancing platforms, such as Upwork, hold great promise in enabling flexible work opportunities where freelancers can combine their work with other life responsibilities, hereafter work-life. However, prior research suggests that platform features and self-managing demands of freelance work can jeopardise this apparent flexibility. In this paper, we report findings from a qualitative study, combining a 14-diary and semi-structured interview with 15 Upwork freelancers. We explored online freelancers' work practices, challenges, and the impact of platform features on their everyday lives. Our qualitative data suggest that platform features and individual context shape online freelancers' work-life practices. Freelancers develop strategies to mitigate platforms' constraints and balance their individual preferences and responsibilities. Further, our findings illustrate how platform features challenge freelancers' availability expectations, work autonomy, and work detachment. This paper contributes an empirical understanding of the factors influencing online freelancers' work-life practices by drawing upon Wanda J. Orlikowski's Structuration Model of Technology. This theoretical lens renders the interplay of freelancers, platforms, and instituted norms of freelance work.
Understanding Postpartum Parents' Experiences via Two Digital Platforms
Authors: Yao Xuewen , Mikhelson Miriam , Micheletti Megan , Choi Eunsol , Watkins S. Craig , Thomaz Edison , de Barbaro Kaya
Published: April 2023

Digital platforms, including online forums and helplines, have emerged as avenues of support for caregivers suffering from postpartum mental health distress. Understanding support seekers' experiences as shared on these platforms could provide crucial insight into caregivers' needs during this vulnerable time. In the current work, we provide a descriptive analysis of the concerns, psychological states, and motivations shared by healthy and distressed postpartum support seekers on two digital platforms, a one-on-one digital helpline and a publicly available online forum. Using a combination of human annotations, dictionary models and unsupervised techniques, we find stark differences between the experiences of distressed and healthy mothers. Distressed mothers described interpersonal problems and a lack of support, with 8.60% - 14.56% reporting severe symptoms including suicidal ideation. In contrast, the majority of healthy mothers described childcare issues, such as questions about breastfeeding or sleeping, and reported no severe mental health concerns. Across the two digital platforms, we found that distressed mothers shared similar content. However, the patterns of speech and affect shared by distressed mothers differed between the helpline vs. the online forum, suggesting the design of these platforms may shape meaningful measures of their support-seeking experiences. Our results provide new insight into the experiences of caregivers suffering from postpartum mental health distress. We conclude by discussing methodological considerations for understanding content shared by support seekers and design considerations for the next generation of support tools for postpartum parents.
Understanding the Use of Images to Spread COVID-19 Misinformation on Twitter
Authors: Wang Yuping , Ling Chen , Stringhini Gianluca
Published: April 2023

While COVID-19 text misinformation has already been investigated by various scholars, fewer research efforts have been devoted to characterizing and understanding COVID-19 misinformation that is carried out through visuals like photographs and memes. In this paper, we present a mixed-method analysis of image-based COVID-19 misinformation in 2020 on Twitter. We deploy a computational pipeline to identify COVID-19 related tweets, download the images contained in them, and group together visually similar images. We then develop a codebook to characterize COVID-19 misinformation and manually label images as misinformation or not. Finally, we perform a quantitative analysis of tweets containing COVID-19 misinformation images. We identify five types of COVID-19 misinformation, from a wrong understanding of the threat severity of COVID-19 to the promotion of fake cures and conspiracy theories. We also find that tweets containing COVID-19 misinformation images do not receive more interactions than baseline tweets with random images posted by the same set of users. As for temporal properties, COVID-19 misinformation images are shared for longer periods of time than non-misinformation ones, as well as have longer burst times. %\ywi added "have'' %\ywFor RQ2, we compare non-misinformation images instead of random images, and so it is not a direct comparison. When looking at the users sharing COVID-19 misinformation images on Twitter from the perspective of their political leanings, we find that pro-Democrat and pro-Republican users share a similar amount of tweets containing misleading or false COVID-19 images. However, the types of images that they share are different: while pro-Democrat users focus on misleading claims about the Trump administration's response to the pandemic, as well as often sharing manipulated images intended as satire, pro-Republican users often promote hydroxychloroquine, an ineffective medicine against COVID-19, as well as conspiracy theories about the origin of the virus. Our analysis sets a basis for better understanding COVID-19 misinformation images on social media and the nuances in effectively moderate them.
Values in Emotion Artificial Intelligence Hiring Services: Technosolutions to Organizational Problems
Authors: Roemmich Kat , Rosenberg Tillie , Fan Serena , Andalibi Nazanin
Published: April 2023

Despite debates about emotion artificial intelligence's (EAI) validity, legality, and social consequences, EAI is increasingly present in the high stakes context of hiring, with potential to shape the future of work and the workforce. The values laden in technology play a significant role in its societal impact.We conducted qualitative content analysis on the public-facing websites (N=229) of EAI hiring services. We identify the organizational problems that EAI hiring services claim to solve and reveal the values emerging in desired EAI uses as promoted by EAI hiring services to solve organizational problems. Our findings show that EAI hiring services market their technologies as technosolutions to three purported organizational hiring problems: 1) hiring (in)accuracy, 2) hiring (mis)fit, and 3) hiring (in)authenticity. We unpack these problems to expose how these desired uses of EAI are legitimized by the corporate ideals of data-driven decision making, continuous improvement, precision, loyalty, and stability. We identify the unfair and deceptive mechanisms by which EAI hiring services claim to solve the purported organizational hiring problems, suggesting that they unfairly exclude and exploit job candidates through EAI's creation, extraction, and affective commodification of a candidate's affective value through pseudoscientific approaches. Lastly, we interrogate EAI hiring service claims to reveal the core values that underpin their stated desired use: techno-omnipresence, techno-omnipotence, and techno-omniscience. We show how EAI hiring services position desired use of their technology as a moral imperative for hiring organizations with supreme capabilities to solve organizational hiring problems, then discuss implications for fairness, ethics, and policy in EAI-enabled hiring within the US policy landscape.
Vizdat: A Technology Probe to Understand the Space of Discussion Around Data Visualization on Reddit
Authors: Almahmoud Jumana , Karger David R.
Published: April 2023

Visualizations play a considerable role in explaining trends or providing evidence when consuming data online. Whether those visualizations are shared on news outlets or social networks, platforms usually allow readers to discuss their stories in comments sections. For the scope of this work, we studied the online communityr/dataisbeautiful on Reddit. We found that chart creators were using a variety of authoring tools to share their content. Readers of these posts,commenters, used text mainly to discuss and critique the visual content. We noticed a need for a richer mode of communication that would show instead of telling authors what to do. Based on our findings, we introducedVizdat, a lightweight tool and extension to allow users to visualize and reproduce charts in the comments sections of data stories. We usedVizdat as atechnology probe with 11 Reddit users to create data visualization and discuss charts onr/dataisbeautiful. During the four-week field deployment period, we observed howVizdat was used and interviewed the participants. We found thatcommenters saw value in accessing the visualization specifications throughVizdat and used those charts to structure their replies with richer modalities. As a result, visualizationauthors appreciated the feedback and less toxic discussion provided through comments embedded with modified versions of their charts. In our paper, we share these findings and other insights to understand the dynamics of forum discussion around charts.
"We are half-doctors": Family Caregivers as Boundary Actors in Chronic Disease Management
Authors: Bhat Karthik S. , Hall Amanda K. , Kuo Tiffany , Kumar Neha
Published: April 2023

Computer-Supported Cooperative Work (CSCW) and Human--Computer Interaction (HCI) research is increasingly investigating the roles of caregivers as ancillary stakeholders in patient-centered care. Our research extends this body of work to identify caregivers as key decision-makers and boundary actors in mobilizing and managing care. We draw on qualitative data collected via 20 semi-structured interviews to examine caregiving responsibilities in physical and remote care interactions within households in urban India. Our findings demonstrate the crucial intermediating roles family caregivers take on while situated along the boundaries separating healthcare professionals, patients and other household members, and online/offline communities. We propose design recommendations for supporting caregivers in intermediating patient-centered care, such as through training content and expert feedback mechanisms for remote care, collaborative tracking mechanisms integrating patient- and caregiver-generated health data, and caregiving-centered online health communities. We conclude by arguing for recognizing caregivers as critical stakeholders in patient-centered care who might constitute technologically assisted pathways to care.
What makes virtual intimacy...intimate? Understanding the Phenomenon and Practice of Computer-Mediated Paid Companionship
Authors: Li Weijun , Chen Shi , Sun Lingyun , Yang Changyuan
Published: April 2023

Virtual romance service (VRS), as a notable commodification of intimacy, is currently emerging in China. Such service is not similar to the kind of intimacy that fans and idols generate through parasocial relationships, but behaves as the direct dyadic intimacy between service providers (virtual lovers) and buyers (customers). To gain a deep understanding of computer-mediated paid companionship, we study emerging user behaviors in VRS through a mixed-method study, including a survey (N = 178) and a follow-up semi-structured interview (N = 22) with both virtual lovers and customers to learn about their motivations, perceptions, and how virtual lovers provide online paid companionship to meet customers' emotional needs. We found three behavioral strategies of virtual lovers and the fact that they provide service in surface and deep acting and real feeling. Customers see VRS as a way to obtain affective benefits with reduced affective cost. We also found that VRS customers paid for the tangible benefits of an idealized romantic partner, rather than long-term commitment and emotional investment, and we identified key characteristics that VRS reduces from intimate relationships that fit its pay-per-use feature. We conclude by discussing the nature of virtual lovers and design implications for computer-mediated paid companionship.
What Mid-Career Professionals Think, Know, and Feel About Phishing: Opportunities for University IT Departments to Better Empower Employees in Their Anti-Phishing Decisions
Authors: Tally Anne C. , Abbott Jacob , Bochner Ashley , Das Sanchari , Nippert-Eng Christena
Published: April 2023

Phishing attacks, in which deceptive messages purporting to be from a legitimate contact are used to trick recipients and acquire sensitive information for the purposes of committing fraud, are a substantial and growing problem for organizations. IT departments and professionals may put in place a variety of institutional responses to thwart such attacks, but an organization's susceptibility to phishing also depends on the decisions and actions of individual employees. These employees may have little phishing expertise but still need to react to such attempts on a daily basis. Based on 24 semi-structured interviews with mid-career office workers (70.8% women, averaging 44 years old, with a bachelor's degree or more) at two universities in the midwestern United States, we find that employees self-describe a wide range of levels of awareness of, and confidence, competency and investment in, the organization's proscribed anti-phishing policies and practices. These employees also describe variation in the ways they would prefer to increase their perceived performance levels in all of these areas. In this paper, we argue that in order to empower employees to be better collaborators in an organization's anti-phishing efforts, organizations should embrace a range of efforts akin to the range of expertise among the users themselves. We make four such empowering recommendations for organizations to consider incorporating into their existing anti-phishing policies and practices, including suggestions to 1) embrace educating non-expert users more fully on organizational processes and consequences, 2) provide employees with a standing one-to-one communication channel between them and an IT phishing point-of-contact, 3) keep employees in the loop once phishing reports are made, and 4) avoid testing employees with "gotcha" assessments.
"When the Beeping Stops, you Completely Freak Out" - How Acute Care Teams Experience and Use Technology
Authors: Hohm Anna , Happel Oliver , Hurtienne Jörn , Grundgeiger Tobias
Published: April 2023

Technology use in acute care has so far been studied with a predominant focus on safety and efficiency rather than the experience of acute care staff. In the present paper, we report a qualitative study including 130 hours of participant observation on acute care teams and retrospective interviews with nine anesthesiologists on their experiences with technology. Our approach is theoretically guided by four modern HCI perspectives, namely psychological need satisfaction, activity theory, embodied interaction, and media equation theory. We analyzed the interview and observation data using a reflexive thematic analysis and identified four themes. Technology as necessary (evil) describes the pervasiveness of technology and how acute care teams depend on technology. While technology as second patient covers the additional load for anesthesiologists on a functional and emotional level, technology as problem solver and safety net highlights relieving aspects of technology use. Technology as artificial limb focuses on so-called transparent tools that extend the body and capabilities of users. We then discuss the identified themes concerning the previously presented theories. Based on our findings and theoretical perspectives, we report general insights for research and design in acute care, such as the benefits of mixed methods or the importance of the gut feelings of experts. Finally, we propose possible directions for future work, such as developing a UX questionnaire adapted to the context of safety-critical domains, such as acute care.
Wizundry: A Cooperative Wizard of Oz Platform for Simulating Future Speech-based Interfaces with Multiple Wizards
Authors: Hu Siying , Yen Hen Chen , Yu Ziwei , Zhao Mingjian , Seaborn Katie , Liu Can
Published: April 2023

Wizard of Oz (WoZ) as a prototyping method has been used to simulate intelligent user interfaces, particularly for speech-based systems. However, as our societies' expectations on artificial intelligence (AI) grows, the question remains whether a single Wizard is sufficient for it to simulate smarter systems and more complex interactions. Optimistic visions of 'what artificial intelligence (AI) can do' places demands on WoZ platforms to simulate smarter systems and more complex interactions. This raises the question of whether the typical approach of employing a single Wizard is sufficient. Moreover, while existing work has employed multiple Wizards in WoZ studies, a multi-Wizard approach has not been systematically studied in terms of feasibility, effectiveness, and challenges. We offer Wizundry, a real-time, web-based WoZ platform that allows multiple Wizards to collaboratively operate a speech-to-text based system remotely. We outline the design and technical specifications of our open-source platform, which we iterated over two design phases. We report on two studies in which participant-Wizards were tasked with negotiating how to cooperatively simulate an interface that can handle natural speech for dictation and text editing as well as other intelligent text processing tasks. We offer qualitative findings on the Multi-Wizard experience for Dyads and Triads of Wizards. Our findings reveal the promises and challenges of the multi-Wizard approach and open up new research questions.
Working With AI to Persuade: Examining a Large Language Model's Ability to Generate Pro-Vaccination Messages
Authors: Karinshak Elise , Liu Sunny Xun , Park Joon Sung , Hancock Jeffrey T.
Published: April 2023

Artificial Intelligence (AI) is a transformative force in communication and messaging strategy, with potential to disrupt traditional approaches. Large language models (LLMs), a form of AI, are capable of generating high-quality, humanlike text. We investigate the persuasive quality of AI-generated messages to understand how AI could impact public health messaging. Specifically, through a series of studies designed to characterize and evaluate generative AI in developing public health messages, we analyze COVID-19 pro-vaccination messages generated by GPT-3, a state-of-the-art instantiation of a large language model. Study 1 is a systematic evaluation of GPT-3's ability to generate pro-vaccination messages. Study 2 then observed peoples' perceptions of curated GPT-3-generated messages compared to human-authored messages released by the CDC (Centers for Disease Control and Prevention), finding that GPT-3 messages were perceived as more effective, stronger arguments, and evoked more positive attitudes than CDC messages. Finally, Study 3 assessed the role of source labels on perceived quality, finding that while participants preferred AI-generated messages, they expressed dispreference for messages that were labeled as AI-generated. The results suggest that, with human supervision, AI can be used to create effective public health messages, but that individuals prefer their public health messages to come from human institutions rather than AI sources. We propose best practices for assessing generative outputs of large language models in future social science research and ways health professionals can use AI systems to augment public health messaging.
You Know What I Meme: Enhancing People's Understanding and Awareness of Hateful Memes Using Crowdsourced Explanations
Authors: Bi Nanyi , Huang Yi-Ching (Janet) , Han Chao-Chun , Hsu Jane Yung-jen
Published: April 2023

Good explanations help people understand hateful memes and mitigate sharing. While AI-enabled automatic detection has proliferated, we argue that quality-controlled crowdsourcing can be an effective strategy to offer good explanations for hateful memes. This paper proposes a Generate-Annotate-Revise workflow to crowdsource explanations and presents the results from two user studies. Study 1 evaluated the objective quality of the explanation with three measurements: detailedness, completeness, and accuracy, and suggested that the proposed workflow generated higher quality explanations than the ones from a single-stage workflow without quality control. Study 2 used an online experiment to examine how different explanations affect users' perception. The results from 127 participants demonstrated that people without prior cultural knowledge gained significant perceived understanding and awareness of hateful memes when presented with explanations generated by the proposed multi-stage workflow as opposed to single-stage or machine-generated explanations.
Youths' Usage of an Informal Chatting Tool in an After-school 3D Print Shop
Authors: Easley William , Hurst Amy , Mentis Helena M. , Hamidi Foad
Published: April 2023

Digital technological advancements have been a driving force in the continued evolution of the modern workplace. One notable change is an increased reliance on informal chatting tools in support of both distributed and co-located work. However, while researchers have recognized the growing prominence of these tools in work, little is known about how to best support youth who have grown up with access to interconnected technologies in acquiring and practicing the relevant skills needed to effectively communicate using these tools. In this study, we studied youth's utilization of Slack, a popular workplace chatting tool, in an after-school 3D print shop. Using in-depth semi-structured interviews, we uncovered the factors that supported or hindered youth employees' Slack use in a technical work context. This work offers implications for how to design youth workplace communication and coordination protocols that support the needs of this population.
Advocacy as Access Work: How People with Visual Impairments Gain Access to Digital Banking in India
Authors: Kameswaran Vaishnav , Y Vidhya , Marathe Megh
Published: April 2023

Research in accessibility and assistive technology often assumes that technology is within easy reach, that is, people with disabilities are able to obtain technologies so long as they are accessible. As a result, less is understood about the challenges that people with disabilities face in obtaining technology in the first place and how they work around these challenges. We reduce this gap by examining the technology access challenges of people with visual impairments in India in the context of digital banking. Through a qualitative study consisting of 30 interviews, we find that participants routinely encountered social and technical challenges that made it difficult to access and use digital banking. To address these challenges, people with visual impairments engaged in advocacy work which consisted of five dimensions: 1) creating awareness, 2) demonstrating competence, 3) escalation, 4) gathering support, and 5) seeking sighted help. We expand on the idea of advocacy as a form of access work performed by people with visual impairments to secure and maintain access to digital banking.
"All of the White People Went First": How Video Conferencing Consolidates Control and Exacerbates Workplace Bias
Authors: Houtti Mo , Zhou Moyan , Terveen Loren , Chancellor Stevie
Published: April 2023

Workplace bias creates negative psychological outcomes for employees, permeating the larger organization. Workplace meetings are frequent, making them a key context where bias may occur. Video conferencing (VC) is an increasingly common medium for workplace meetings; we therefore investigated how VC tools contribute to increasing or reducing bias in meetings. Through a semi-structured interview study with 22 professionals, we found that VC features push meeting leaders to exercise control over various meeting parameters, giving leaders an outsized role in affecting bias. We demonstrate this with respect to four core VC features---user tiles, raise hand, text-based chat, and meeting recording---and recommend employing at least one of two mechanisms for mitigating bias in VC meetings---1) transferring control from meeting leaders to technical systems or other attendees and 2) helping meeting leaders better exercise the control they do wield.
Capturing the Dynamics of Trust and Team Processes in Human-Human-Agent Teams via Multidimensional Neural Recurrence Analyses
Authors: Eloy Lucca , Spencer Cara , Doherty Emily , Hirshfield Leanne
Published: April 2023

As collaborative technologies evolve from supportive tools to interactive teammates, there is a growing need to understand how trust and team processes develop in human-agent teams. To contribute effectively, these systems must be able to support human teammates in a task without disrupting the delicate interpersonal states and team processes that govern successful collaboration. In order to break down the complexity of monitoring multiple actors in human-agent collaborations, there is a need to identify interpretable, generalizable measures that can monitor the emergence of interpersonal and team-level processes that underlie effective teaming. We address this gap by using functional Near-Infrared Spectroscopy to concurrently measure brain activity of two individuals in a human-human-agent team during a complex, ecologically valid collaborative task, with a goal of identifying quantitative markers of cognition- and affect-based trust alongside team processes of coordination, strategy formulation, and affect management. Two multidimensional extensions of recurrence quantification analysis, a nonlinear method based in dynamical systems theory, are presented to quantify interpersonal coupling and team-level regularity as reflected in the hemodynamics of three cortical regions across multiple time-scales. Mixed-effects regressions reveal that neural recurrence between individuals uniquely reflects changes in self-reported trust, while team-level neural regularity inversely predicts self-reported team processes. Additionally, we show that recurrence metrics capture temporal dynamics of affect-based trust consistent with existing theory, showcasing the interpretability and specificity of these metrics for disentangling complex team states and processes. This paper presents a novel, interpretable, and computationally efficient model-free method capable of differentiating between latent trust and team processes a complex, naturalistic task setting. We discuss the potential applications of this technique for continuous monitoring of team states, providing clear targets for the future development of adaptive human-agent teaming systems.
Crossing the Threshold: Pathways into Makerspaces for Women at the Intersectional Margins
Authors: Hedditch Sonali , Vyas Dhaval
Published: April 2023

In this paper, we focus on makerspace practices that can hinder or enable access for under-resourced women of colour who are novices to making, predominantly migrants and refugee women. We report on a 21 month long ethnographic fieldwork at nine makerspaces across two metropolitan Australian cities. The findings present barriers and opportunities around access of under-resourced women of colour into makerspaces. We present these findings through four themes: first impressions and visual representations; dimensions of the enabling environment; role of community partnerships; and intersectional identities of women. We conclude by discussing three contributions this paper makes to the HCI and CSCW literature, with supporting lessons and recommendations so that makerspaces no longer encode the involvement of only certain types of users (predominantly well-educated white males or white females), to the exclusion of women at the intersectional margins. If makerspaces can facilitate an enabling environment appropriate to be inclusive of women who face intersecting oppressions, the benefits of the maker movement can expand substantially.
Data Subjects' Perspectives on Emotion Artificial Intelligence Use in the Workplace: A Relational Ethics Lens
Authors: Corvite Shanley , Roemmich Kat , Rosenberg Tillie Ilana , Andalibi Nazanin
Published: April 2023

The workplace has experienced extensive digital transformation, in part due to artificial intelligence's commercial availability. Though still an emerging technology, emotional artificial intelligence (EAI) is increasingly incorporated into enterprise systems to augment and automate organizational decisions and to monitor and manage workers. EAI use is often celebrated for its potential to improve workers' wellbeing and performance as well as address organizational problems such as bias and safety. Workers subject to EAI in the workplace are data subjects whose data make EAI possible and who are most impacted by it. However, we lack empirical knowledge about data subjects' perspectives on EAI, including in the workplace. To this end, using a relational ethics lens, we qualitatively analyzed 395 U.S. adults' open-ended survey (partly representative) responses regarding the perceived benefits and risks they associate with being subjected to EAI in the workplace. While participants acknowledged potential benefits of being subject to EAI (e.g., employers using EAI to aid their wellbeing, enhance their work environment, reduce bias), a myriad of potential risks overshadowed perceptions of potential benefits. Participants expressed concerns regarding the potential for EAI use to harm their wellbeing, work environment and employment status, and create and amplify bias and stigma against them, especially the most marginalized (e.g., along dimensions of race, gender, mental health status, disability). Distrustful of EAI and its potential risks, participants anticipated conforming to (e.g., partaking in emotional labor) or refusing (e.g., quitting a job) EAI implementation in practice. We argue that EAI may magnify, rather than alleviate, existing challenges data subjects face in the workplace and suggest that some EAI-inflicted harms would persist even if concerns of EAI's accuracy and bias are addressed.
Deliberating with AI: Improving Decision-Making for the Future through Participatory AI Design and Stakeholder Deliberation
Authors: Zhang Angie , Walker Olympia , Nguyen Kaci , Dai Jiajun , Chen Anqing , Lee Min Kyung
Published: April 2023

Research exploring how to support decision-making has often used machine learning to automate or assist human decisions. We take an alternative approach for improving decision-making, using machine learning to help stakeholders surface ways to improve and make fairer decision-making processes. We created "Deliberating with AI", a web tool that enables people to create and evaluate ML models in order to examine strengths and shortcomings of past decision-making and deliberate on how to improve future decisions. We apply this tool to a context of people selection, having stakeholders---decision makers (faculty) and decision subjects (students)---use the tool to improve graduate school admission decisions. Through our case study, we demonstrate how the stakeholders used the web tool to create ML models that they used as boundary objects to deliberate over organization decision-making practices. We share insights from our study to inform future research on stakeholder-centered participatory AI design and technology for organizational decision-making.
Discovering the Hidden Facts of User-Dispatcher Interactions via Text-based Reporting Systems for Community Safety
Authors: Liu Yiren , Mayfield Ryan , Huang Yun
Published: April 2023

Recently, an increasing number of safety organizations in the U.S. have incorporated text-based risk reporting systems to respond to safety incident reports from their community members. To gain a better understanding of the interaction between community members and dispatchers using text-based risk reporting systems, this study conducts a system log analysis ofLiveSafe, a community safety reporting system, to provide empirical evidence of the conversational patterns between users and dispatchers using both quantitative and qualitative methods. We created an ontology to capture information (e.g., location, attacker, target, weapon, start-time, and end-time, etc.) that dispatchers often collected from users regarding their incident tips. Applying the proposed ontology, we found that dispatchers often asked users for different information across varied event types (e.g.,Attacker forAbuse andAttack events,Target forHarassment events). Additionally, using emotion detection and regression analysis, we found an inconsistency in dispatchers' emotional support and responsiveness to users' messages between different organizations and between incident categories. The results also showed that users had a higher response rate and responded quicker when dispatchers provided emotional support. These novel findings brought significant insights to both practitioners and system designers, e.g., AI-based solutions to augment human agents' skills for improved service quality.
Do Streamers Care about Bystanders' Privacy? An Examination of Live Streamers' Considerations and Strategies for Bystanders' Privacy Management
Authors: Wu Yanlai , Gui Xinning , Wisniewski Pamela J. , Li Yao
Published: April 2023

Live streaming has become a popular activity world-wide that has warranted research attention on its privacy related issues. For instance, bystanders' privacy, or the privacy of third-parties captured by streamers, has been increasingly studied as live streaming has become almost ubiquitous in both public and private spaces in many countries. While prior work has studied bystanders' privacy concerns, a gap exists in understanding how streamers consider bystanders' privacy and the steps they take (or do not take) to preserve it. Understanding streamers' considerations towards bystanders' privacy is vital because streamers are the ones who have direct control over whether and how bystanders' information is disclosed. To address this gap, we conducted an interview study with 25 Chinese streamers to understand their considerations and practices regarding bystanders' privacy in live streaming. We found that streamers cared about bystanders' privacy and evaluated possible privacy violations to bystanders from several perspectives. To protect bystanders from privacy violations, streamers primarily relied on technical, behavioral, and collaborative strategies. Our results also indicated that current streaming platforms lacked features that helped streamers seamlessly manage bystanders' privacy and involved bystanders into their privacy decision-making. Applying the theoretical lens of collective privacy management, we discuss implications for the design of live streaming systems to support streamers in protecting bystanders' privacy.
Don't Let Netflix Drive the Bus: User's Sense of Agency Over Time and Content Choice on Netflix
Authors: Schaffner Brennan , Stefanescu Antonia , Campili Olivia , Chetty Marshini
Published: April 2023

Users often turn to subscription video on demand (SVOD) platforms for entertainment. However, these platforms sometimes employ manipulative tactics that undermine a user's sense of agency over time and content choice to increase their share of a user's attention. Prior research has investigated how interface designs affect a user's sense of agency on social media and YouTube. For example, YouTube's autoplay left users feeling like they had less control over their time. We extend this work by investigating the design elements of Netflix, the most used SVOD, for the impact they have on users' senses of agency. We conducted interviews with 20 participants that used Netflix regularly, asking about their experiences and perceptions of features in the Netflix platform design that may affect their sense of agency. We found that a user's sense of agency was at odds with the platform's design. Users, who were often seeking entertainment for mood management, were met with features that encouraged watching more than they originally planned to and watching content they may not otherwise watch. We discuss design recommendations that Netflix could employ to reaffirm their users' agency.
Explanations Can Reduce Overreliance on AI Systems During Decision-Making
Authors: Vasconcelos Helena , Jörke Matthew , Grunde-McLaughlin Madeleine , Gerstenberg Tobias , Bernstein Michael S. , Krishna Ranjay
Published: April 2023

Prior work has identified a resilient phenomenon that threatens the performance of human-AI decision-making teams: overreliance, when people agree with an AI, even when it is incorrect. Surprisingly, overreliance does not reduce when the AI produces explanations for its predictions, compared to only providing predictions. Some have argued that overreliance results from cognitive biases or uncalibrated trust, attributing overreliance to an inevitability of human cognition. By contrast, our paper argues that people strategically choose whether or not to engage with an AI explanation, demonstrating empirically that there are scenarios where AI explanations reduce overreliance. To achieve this, we formalize this strategic choice in a cost-benefit framework, where the costs and benefits of engaging with the task are weighed against the costs and benefits of relying on the AI. We manipulate the costs and benefits in a maze task, where participants collaborate with a simulated AI to find the exit of a maze. Through 5 studies (N = 731), we find that costs such as task difficulty (Study 1), explanation difficulty (Study 2, 3), and benefits such as monetary compensation (Study 4) affect overreliance. Finally, Study 5 adapts the Cognitive Effort Discounting paradigm to quantify the utility of different explanations, providing further support for our framework. Our results suggest that some of the null effects found in literature could be due in part to the explanation not sufficiently reducing the costs of verifying the AI's prediction.
Exploring Challenges to Inclusion in Participatory Design From the Perspectives of Global North Practitioners
Authors: Elsayed-Ali Salma , Bonsignore Elizabeth , Chan Joel
Published: April 2023

Participatory Design (PD) aims to promote inclusivity by involving users throughout the design process. However, Human-Computer Interaction (HCI) and social computing research have pointed to instances where PD as practiced can, paradoxically, be exclusive. We aim to understand some of the challenges that could lead to exclusivity in order to design more inclusive PD practices. To investigate this, we conducted interviews with ten expert PD practitioners based in the Global North whose focus is on inclusion. Synthesizing practitioners' accounts, we advance understandings of challenges surrounding: 1) instantiating shared spaces that empower partners; 2) developing common ground among stakeholders; and 3) balancing funding needs with open-ended PD. We contribute theoretical and empirical insights into these challenges and close by articulating potential implications for addressing these challenges to inclusion in PD.
From Bias to Repair: Error as a Site of Collaboration and Negotiation in Applied Data Science Work
Authors: Lin Cindy Kaiying , Jackson Steven J.
Published: April 2023

Managing error has become an increasingly central and contested arena within data science work. While recent scholarship in artificial intelligence and machine learning has focused on limiting and eliminating error, practitioners have long used error as a site of collaboration and learning vis-à-vis labelers, domain experts, and the worlds data scientists seek to model and understand. Drawing from work in CSCW, STS, HCML, and repair studies, as well as from multi-sited ethnographic fieldwork within a government institution and a non-profit organization, we move beyond the notion of error as an edge case or anomaly to make three basic arguments. First, error discloses or calls to attention existing structures of collaboration unseen or underappreciated under 'working' systems. Second, error calls into being new forms and sites of collaboration (including, sometimes, new actors). Third, error redeploys old sites and actors in new ways, often through restructuring relations of hierarchy and expertise which recenter or devalue the position of different actors. We conclude by discussing how an artful living with error can better support the creative strategies of negotiation and adjustment which data scientists and their collaborators engage in when faced with disruption, breakdown, and friction in their work.