We present an experimental study that investigates how LLM-driven conversational AI tools might be weaponized to facilitate, exacerbate, or commoditize coercive control. Inspired by speculative design, we construct four scenarios that combine well-known coercive control tactics with the current capabilities of conversational AI tools. Then, we explore these scenarios via interactions with popular AI agents (ChatGPT, Gemini). We find that although AI tools refuse straightforward requests for harmful content, their guardrails can be circumvented via strategies such as gradual persuasion, splitting conversations, pre-prompting, and manipulating the AI agent’s settings. Collectively, these strategies enable AI agents to be leveraged in ways that facilitate harassment, intimidation, gaslighting, monitoring, surveillance, and other coercive control tactics. To make these tools safer for everyone, we discuss opportunities for AI agents to resist being abused for coercive control via analysis of users’ conversational patterns, and ensuring that pre-programmed settings are clearly visible to prevent covert manipulation.

This paper presents a qualitative study with 17 participants that uses video elicitations to investigate how conversational AI agents driven by large language models might support “shared care,” or coordination of home-based care among family caregivers (FCs) and home care workers (HCWs) who care for the same care recipient (CR). Participants saw conversational AI as a promising tool that might help streamline communication, coordinate shift handovers, bridge language gaps, and support onboarding of new or substitute caregivers. That said, caregivers assumed AI agents would inevitably make mistakes and should thus be designed to signal uncertainty and make it easy to report errors. More broadly, participants discussed how AI agents designed for sensitive home care contexts will need to explicitly preserve the human essence of care, minimize extra data work that might distract from caregiving, and always complement—not replace—human judgment.

This paper explores opportunities and challenges for data-driven advocacy to support home care workers, an often overlooked group of low-wage, frontline health workers.First, we investigate what data to collect and how to collect it in ways that preserve privacy and avoid burdening workers.Second, we examine how workers and advocates could use collected data to strengthen individual and collective advocacy efforts.Our qualitative study with 11 workers and 15 advocates highlights tensions between workers' desires for individual and immediate benefits and advocates' preferences to prioritize more collective and long-term benefits.We also uncover discrepancies between participants' expectations for how data might transform advocacy and their on-the-ground experiences collecting and using real data.Finally, we discuss future directions for data-driven worker advocacy, including combining different kinds of data to ameliorate challenges, leveraging advocates as data stewards, and accounting for workers' and organizations' heterogeneous goals.

We present a qualitative study that investigates the implications of current and near-future AI deployment for home care workers (HCWs), an overlooked group of frontline healthcare workers. Through interviews with 22 HCWs, care agency staff, and worker advocates, we find that HCWs do not understand how AI works, how their data can be used, or why AI systems might retain their information. HCWs are unaware that AI is already being utilized in their work, primarily via algorithmic shift-matching systems adopted by agencies. Participants detail the risks AI poses in sensitive care settings for HCWs, patients, and agencies, including threats to workers' autonomy and livelihoods, and express concerns that workers will be held accountable for AI mistakes, with the burden of proving AI's decisions incorrect falling on them. Considering these risks, participants advocate for new regulations and democratic governance structures that protect workers and control AI deployment in home care work.

This paper describes a qualitative study that interrogates the types of technology-facilitated coercive control faced by survivors of human trafcking and uncovers potential interventions to aid survivors' recovery.Via semi-structured interviews with 21 participants, including trafcking survivors and professional advocates, we show how trafckers use technology as a lever for control, engaging in surveillance, blackmail, impersonation, and harassment as they compel survivors to stay in the trafcking situation.In recovery, digital footprints keep survivors tethered to their traffcking experience, impacting their digital autonomy, economic mobility, and feelings of safety.Nevertheless, technology can also be a valuable tool for survivors' recovery, connecting them to essential resources and support systems.We discuss the need for interventions and services that account for the specifcity of the trafcking context to help survivors attain digital safety and autonomy, including the potential to adapt existing tech safety services designed for other contexts to human trafcking. CCS Concepts• Human-centered computing → Empirical studies in HCI ; • Security and privacy → Human and societal aspects of security and privacy.

Hospitals and care homes devote significant resources to placing post-acute patients from hospitals into long-term care. This paper describes a two-phase experiment over SMS, conducted with a hospital in Hawai'i, in which care homes express preferences, indicate availability to accept patients, and express interest in patients. In the first phase, the treatment asks care homes to reconsider their stated preferences to better support matching. The second phase measures whether resulting changes in preferences increased how often homes express interest in patients that match newly stated preferences. First, to motivate and inform experiment design, we explore factors contributing to extended hospital stays for patients, uncovering how care homes' preferences play a major role in what patients they consider accepting. Second, we conduct a 16-week randomized controlled trial with 960 homes, where we experimentally probed, via SMS messages, homes' willingness to change their preferences to improve potential patient match recommendations. We show that inducing homes to reflect on their preferences increased the number of homes who changed their preferences by over 50%: 9.8% of homes who received our treatment changed their preference compared to 6.0% of homes in the control group (p-value = 0.0421).Third, followup interviews with 22 home operators highlight how preference malleability is shaped by a combination of design constraints and on-the-ground realities, such as load-balancing existing patient rosters. Finally, we discuss implications for real-world systems like ours that must balance constrained communication with situational complexity towards improving outcomes.

As the US population ages, a growing challenge is placing hospital patients who require long-term post-acute care into adult foster care facilities: small long-term nursing facilities that care for those unable to age in place because their care requirements exceed what can be delivered at home. A key challenge in patient placement is the dynamic matching process between hospital discharge coordinators looking to place patients and facilities looking for residents. We designed, built, deployed, and maintain a system to support decision making among a team of six discharge coordinators assisting in the discharge of 127 patients across 1,047 facilities in Hawai'i. Our system collects vacancy and capability data from facilities via conversational SMS and processes it to recommend facilities that discharge coordinators might contact. Findings from a 14-month deployment provide evidence for how timely, accurate information positively impacts matching efficacy. We close with lessons learned for information collection systems and provisioning platforms in similar contexts.

This paper investigates how to incorporate trauma-informed principles into organizational and coordination processesin a high-stakes context: computer security clinics for survivors of intimate partner violence (IPV). IPV survivors often face complex technology-facilitated abuse and computer security clinics aim to assist by connecting survivors with trained experts who help them work toward digital safety. We analyze how clinics' referral processes constitute key sites for trauma-informed, inter-organizational coordination work, especially in light of stakeholders' asymmetrical knowledge of technology. Via semi-structured interviews, we uncover the potential for misalignment between survivors' needs and clinics' services, leading to potentially negative consequences for both survivors and clinic staff. We then design new referral and assessment tools that enable trauma-informed care and improve coordination by functioning as a guide for people seeking services and enabling clinic staff to determine if a survivor is a good fit for the services available. Finally, we show how the new tools improve coordination and outcomes by analyzing 97 referrals received by a clinic over a six month period. We close by discussing the role of structured communication mechanisms in trauma-informed inter-organizational coordination in high-stakes contexts.

Home care workers (HCWs) are an important group of frontline workers that deliver essential at-home care services to enable older adults to age in place. Despite their importance in patient care, research has shown that HCWs are an overlooked and undervalued workforce: HCWs work in isolated conditions, are paid low wages, experience high levels of stress and burnout, and more. As a result, despite being motivated to try and be healthy, this essential workforce suffers from poor physical and mental health outcomes. This paper combines data from focus groups, interviews, and a month-long field study with HCWs to investigate the feasibility and utility of using activity tracking devices to provide HCWs with fine-grained awareness and insights into daily activities that affect their health and wellbeing. We explore HCWs' reactions to both their individual and collective data, discussing their efforts towards positive behavior change, but also highlighting systemic and occupational factors that may limit HCWs' agency and control over their own activities. Finally, we discuss the potential for HCWs' collective data to raise awareness about their working conditions and provide data-driven evidence to aid advocacy efforts towards improved policies, better wages, or greater protections for this vital workforce.

Researchers increasingly look to understand experiences of pain, harm, and marginalization via qualitative analysis. Such work is needed to understand and address social ills, but poses risks to researchers' well-being: sifting through volumes of data on painful human experiences risks incurring traumatic exposure in the researcher. In this paper, we explore how the principles of trauma-informed computing (TIC) can be applied to reimagine healthier tools and workflows for qualitative analysis. We apply TIC to create a design provocation called TIQA, a system for qualitative coding that leverages language modeling, semantic search, and recommendation systems to measure and mitigate an analyst's exposure to concepts they find traumatic. Through a formative study of TIQA with 15 participants, we illuminate the complexities of enacting TIC in qualitative knowledge infrastructure, and potential roles for machine assistance in mitigating researchers' trauma. To assist scholars in translating the high-level principles of TIC into sociotechnical system design, we argue for: (a) a conceptual shift from safety as exposure reduction towards safety as enablement; and (b) renewed attention to evaluating the trauma-informedness of design processes, in tandem with the outcomes of designed objects on users' well-being.

From ELIZA to Alexa, Conversational Agents (CAs) have been deliberately designed to elicit or project empathy. Although empathy can help technology better serve human needs, it can also be deceptive and potentially exploitative. In this work, we characterize empathy in interactions with CAs, highlighting the importance of distinguishing evocations of empathy between two humans from ones between a human and a CA. To this end, we systematically prompt CAs backed by large language models (LLMs) to display empathy while conversing with, or about, 65 distinct human identities, and also compare how different LLMs display or model empathy. We find that CAs make value judgments about certain identities, and can be encouraging of identities related to harmful ideologies (e.g., Nazism and xenophobia). Moreover, a computational approach to understanding empathy reveals that despite their ability to display empathy, CAs do poorly when interpreting and exploring a user’s experience, contrasting with their human counterparts.

AI technologies are increasingly deployed to support community health workers (CHWs) in high-stakes healthcare settings, from malnutrition diagnosis to diabetic retinopathy. Yet, little is known about how such technologies are understood by CHWs with low digital literacy and what can be done to make AI more understandable for them. This paper examines the potential of explorable explanations in improving AI understanding for CHWs in rural India. Explorable explanations integrate visual heuristics and written explanations to promote active learning. We conducted semi-structured interviews with CHWs who interacted with a design probe in which AI predictions of child malnutrition were accompanied by explorable explanations. Our findings show that explorable explanations shift CHWs’ AI-related folk theories, help develop a more nuanced understanding of AI, augment CHWs’ learning and occupational capabilities, and enhance their ability to contest AI decisions. We also uncover the effects of CHWs’ sociopolitical environments on AI understanding and argue for a more holistic conception of AI explainability that goes beyond cognition and literacy.

This paper presents Saharaline, an intervention designed to provide collective social support for teachers in low-income schools. Implemented as a WhatsApp-based helpline, Saharaline enables teachers to reach out for personalized, long-term assistance with a wide range of problems and stressors, including pedagogical, emotional, and technological challenges. Depending on the support needed, teachers’ requests are routed to appropriate domain experts— staff employed by educational non-profit organizations who understand teachers’ on-the-ground realities—who offer localized and contextualized assistance. Via a three-month exploratory deployment with 28 teachers in India, we show how Saharaline’s design enabled a collective of diverse education experts to craft and deliver localized solutions that teachers could incorporate into their practice. We conclude by reflecting on the efficacy of our intervention in low-resource work contexts and provide recommendations to enhance collective social support interventions similar to Saharaline.

Research involving at-risk users—that is, users who are more likely to experience a digital attack or to be disproportionately affected when harm from such an attack occurs—can pose significant safety challenges to both users and researchers. Nevertheless, pursuing research in computer security & privacy (S&P) is crucial to understanding how to meet the digital-safety needs of at-risk users and to design safer technology for all. To standardize and bolster safer research involving such users, we offer an analysis of 196 academic works to elicit 14 research risks and 36 safety practices used by a growing community of researchers. We pair this inconsistent set of reported safety practices with oral histories from 12 domain experts to contribute scaffolded and consolidated pragmatic guidance that researchers can use to plan, execute, and share safer digital-safety research involving at-risk users. We conclude by suggesting areas for future research regarding the reporting, study, and funding of at-risk user research.

Home care workers (HCWs) are professionals who provide care to older adults and people with disabilities at home. However, HCWs are vulnerable and especially susceptible to wage theft, or not being paid their legally-entitled wages in full by their employers. Prior work has examined other low-wage work settings to show how technology is designed and deployed has the potential to both cause and address wage theft. We extend this work by examining the relationship between technology and wage theft in the home care context. We collaborated closely with a local grassroots organization to conduct interviews with workers and labor, legal, and payroll experts. We uncovered how the complex, volatile, and diverse nature of home care complicates the errors in time-tracking systems. Through design provocations and focus groups with workers and experts, we also investigated the potential of technology as a part of broader efforts to curb wage theft through educating and empowering isolated HCWs. While we found that approachable design could reduce errors in existing systems, make employer processes more transparent, and help workers exchange knowledge to build collective power, we also discuss concerns around burden, privacy, and accountability when designing technologies for HCWs and other low-wage workers.

AI-driven tools are increasingly deployed to support low-skilled community health workers (CHWs) in hard-to-reach communities in the Global South. This paper examines how CHWs in rural India engage with and perceive AI explanations and how we might design explainable AI (XAI) interfaces that are more understandable to them. We conducted semi-structured interviews with CHWs who interacted with a design probe to predict neonatal jaundice in which AI recommendations are accompanied by explanations. We (1) identify how CHWs interpreted AI predictions and the associated explanations, (2) unpack the benefits and pitfalls they perceived of the explanations, and (3) detail how different design elements of the explanations impacted their AI understanding. Our findings demonstrate that while CHWs struggled to understand the AI explanations, they nevertheless expressed a strong preference for the explanations to be integrated into AI-driven tools and perceived several benefits of the explanations, such as helping CHWs learn new skills and improved patient trust in AI tools and in CHWs. We conclude by discussing what elements of AI need to be made explainable to novice AI users like CHWs and outline concrete design recommendations to improve the utility of XAI for novice AI users in non-Western contexts.

The mass collection and reuse of social data requires a reimagining of privacy and consent, with particular attention to the (in)equitable distribution of benefits and burdens between researchers and subjects. Instrumenting frontline clinical services to collect and steward data might mitigate the exploitation inherent to data collection---with attention to how subjects can meaningfully participate in stewardship. We explore participatory data stewardship in the context of clinical computer security for survivors of intimate partner violence (IPV). Via semi-structured interviews with IPV support workers, we explore how data are produced within the IPV care ecosystem at the Clinic to End Tech Abuse (CETA). We then conduct design provocations with clients of IPV services and their support workers, exploring possibilities for participatory data mechanisms like open records and dynamic consent. We find participation in data stewardship may benefit clients through improved agency, self-reflection, and control of self-narrative, and that incurred burdens may be alleviated by enlisting trusted stewards. We close with future work for CSCW interrogating how knowledge of digital-safety harms can and should be produced from clinical encounters, towards more equitable ways of knowing.

We focus on the stories of five older adults who became voice assistant users through our study, and with whom we speculated about future interfaces through two design probes, one for health data reporting and one for positive reminiscing. We delivered a voice-first ambient interface (VFAI) to each participant, and closely observed participants’ journeys through periodic themed interviews (16 hours, 21 minutes of transcribed recordings), usage log reviews (4,657 entries), and phone and text support. Participants’ lived experiences impacted their perceptions and interactions with their VFAI, fueling rich insights about how to design for diverse needs. For example, while one participant saw increased potential in the VFAI after interacting with the design probe for health data reporting, another was skeptical of using it to communicate with her doctor. We contribute an in-depth exploration of VFAIs to support aging in place, implications for design, and areas for future work for tailoring VFAIs towards enabling continuity of care in people’s homes.

This paper explores how the design of interactive voice assistants (IVAs) might be tailored to support home health aides’ important work in complex home care contexts. We designed two custom IVAs: one that looks like an aide’s medical kit and one that blends into the home environment. We also designed a voice-based application that provides aides with guidance for day-to-day tasks and for performing a medical assessment. Via a lab-based study with 25 aides and seven patients, we explore how tailoring the IVAs’ design to home health care might impact its acceptability as a work device, enabling cooperative work among aides and clients, while potentially causing conflict that will require IVA designers to decide whose values to prioritize. We also highlight limits in aides’ power to control IVAs in clients’ homes. Finally, we discuss implications for designing privacy-preserving IVAs, including leveraging IVAs’ physical design to enact privacy mechanisms and opportunities to build ‘always on’ IVAs for privacy-sensitive contexts like home health care.

Home care workers (HCWs) deliver essential health services within patients’ homes and are an important part of the US healthcare system. Yet, they are a marginalized workforce, whose physical isolation and lack of access to support structures make them vulnerable to exploitation. Computer-mediated support programs may help bridge this gap and, through critical and liberatory pedagogies, foster material social change. However, such pedagogies typically assume the involvement of a professional facilitator when, in practice, support programs are often led by peers with little to no facilitation training. Based on a three-month study with HCWs, this paper explores how peers can perform critical and liberatory facilitation practice in an online support program. We illustrate the challenges peers faced learning this practice and performing this role in an online environment. Our findings can improve the design of computer-mediated support programs and how to prepare peer leadership, particularly for addressing the needs of marginalized populations.

Home health aides are paid professionals who provide long-term care to an expanding population of adults who need it. However, aides' work is often unrecognized by the broader caregiving team despite being in demand and crucial to care---an invisibility reinforced by ill-suited technological tools. In order to understand the invisible work aides perform and its relationship to technology design, we interviewed 13 aides employed by home care agencies in New York City. These aides shared examples that demonstrated the intertwined nature of both types of invisible work (i.e., emotions- and systems-based) and expanded the sociological mechanisms of invisibility (i.e., sociocultural, sociolegal, sociospatial) to include the sociotechnical. Through these findings, we investigate the opportunities, tensions, and challenges that could inform the design of tools created for these important, but often overlooked, frontline caregivers.

Home care workers (HCWs) provide essential care in patients' homes but are often underappreciated and work in stressful and isolated environments with diverse and intersecting support needs. This paper describes a computer-mediated peer support program that centers around sharing circles: spaces for personal, narrative storytelling to encourage HCWs to collaboratively reflect on their home care experiences and build rapport and shared identity with their peers. We describe the design of this program and a 12-week deployment that we conducted to evaluate the program with 42 HCWs in New York City. Our findings show that participants engaged in multiple types of peer support including emotional validation, learning how to navigate the workplace and patient care, defining and enabling good home care praxis, and building understanding around purpose and identity as HCWs. We discuss how these findings inform the design of technology and use of holistic pedagogies, such as storytelling, to enable this support in computer-mediated peer support programs. Such programs can help researchers and practitioners interested in addressing diverse needs that occur in intersectional contexts, such as that of HCWs and other marginalized populations.

Home health aides are a vulnerable group of frontline caregivers who provide personal and medically-oriented care in patients’ homes. Their work is difficult and unpredictable, involving a mix of physical and emotional labor as they adapt to patients’ changing needs. Our paper presents an exploratory, qualitative study with 32 participants, that investigates design opportunities for Interactive Voice Assistants (IVAs) to support aides’ essential care work. We explore challenges and opportunities for IVAs to (1) fill gaps in aides’ access to information and care coordination, (2) assist with decision making and task completion, (3) advocate on behalf of aides, and (4) provide emotional support. We then discuss key implications of our work, including how materiality may impact perceived ownership and usage of IVAs, the need to carefully consider tensions around surveillance, accountability, data collection, and reporting, and the challenges of centering aides as essential workers in complex home health care contexts.

Trauma is the physical, emotional, or psychological harm caused by deeply distressing experiences. Research with communities that may experience high rates of trauma has shown that digital technologies can create or exacerbate traumatic experiences. Via three vignettes, we discuss how considering the possible effects of trauma and traumatic stress reactions provides an explanatory lens with new insights into people’s technology experiences. Then, we present a framework—trauma-informed computing—in which we adapt and show how to apply six key principles of trauma-informed approaches to computing: safety, trust, peer support, collaboration, enablement, and intersectionality. Through specific examples, we describe how to apply trauma-informed computing in four areas of computing research and practice: user experience research & design, security & privacy, artificial intelligence & machine learning, and organizational culture in tech companies. We conclude by discussing how adopting trauma-informed computing will lead to benefits for all users, not only those experiencing trauma.

Survivors of intimate partner violence (IPV) face complex threats to their digital privacy and security. Prior work has established protocols for directly helping them mitigate these harms; however, there remains a need for flexible and pluralistic systems that can support survivors’ long-term needs. This paper describes the design and development of sociotechnical infrastructure that incorporates feminist notions of care to connect IPV survivors experiencing technology abuse with volunteer computer security consultants. We present findings from a mixed methods study that draws on data from an 8-month, real-world deployment, as well as interviews with 7 volunteer technology consultants and 18 IPV professionals. Our findings illuminate emergent challenges in safely and adaptively providing computer security advice as care. We discuss implications of these findings for feminist approaches to computer security and privacy, and provide broader lessons for interventions that aim to directly assist at-risk and marginalized people experiencing digital insecurity.

Frontline health workers provide essential services for their communities, but much of their work remains invisible—undervalued and underappreciated. Examining this invisible work ensures new technologies do not amplify or reinforce inequitable power structures, especially as governments and organizations push to digitize health work processes. We build on a burgeoning conversation by studying how invisible work manifests and how this invisibility can be challenged in two contexts of frontline health: home health aides in New York City, USA and Accredited Social Health Activists (ASHAs) in Uttar Pradesh, India. We highlight three shared manifestations of invisible work: (1) work done outside of the workers’ boundaries (2) work done to gain and share knowledge and (3) work done to manage relationships. These common categories are experienced differently in the two contexts, raising nuances to consider when designing technology for frontline health workers. We discuss these nuances and other tensions through concrete examples of how workers can escalate feedback and conflicts, quantify implicit expertise about patients, or build more awareness of their situation. Our paper guides the creation of technologies that take into account a more comprehensive understanding of the frontline health workers’ processes and highlight more of their contributions.

Artificial intelligence (AI) and machine learning (ML) are quickly becoming pervasive in ways that impact the lives of all humans across the globe. In an effort to make otherwise ”black box” AI/ML systems more understandable, the field of Explainable AI (XAI) has arisen with the goal of developing algorithms, toolkits, frameworks, and other techniques that enable people to comprehend, trust, and manage AI systems. However, although XAI is a rapidly growing area of research, most of the work has focused on contexts in the Global North, and little is known about if or how XAI techniques have been designed, deployed, or tested with communities in the Global South. This gap is concerning, especially in light of rapidly growing enthusiasm from governments, companies, and academics to use AI/ML to “solve” problems in the Global South. Our paper contributes the first systematic review of XAI research in the Global South, providing an early look at emerging work in the space. We identified 16 papers from 15 different venues that targeted a wide range of application domains. All of the papers were published in the last three years. Of the 16 papers, 13 focused on applying a technical XAI method, all of which involved the use of (at least some) data that was local to the context. However, only three papers engaged with or involved humans in the work, and only one attempted to deploy their XAI system with target users. We close by reflecting on the current state of XAI research in the Global South, discussing data and model considerations for building and deploying XAI systems in these regions, and highlighting the need for human-centered approaches to XAI in the Global South.

Older adults around the world lack access to a wide range of potentially life-changing digital applications, services, and information that could be provided by voice assistants (such as Amazon’s Alexa, Google’s Assistant, or Apple’s Siri). However, older adults’ needs are underrepresented in the design of voice assistants. Because of this, we are missing opportunities for digital inclusion, and increasing risks of excluding older adults as these devices permeate public settings. In this work, we video record older adults (n=26) interacting with a multi-modal voice assistants while waiting in line at food pantries, and use Interaction Analysis to draw insights from these recordings. We find that by being agnostic to body language, audio-prosodic features, and other contextual factors, voice assistants fail to capture and react to some important aspects of interactions. We discuss design (e.g, interpreting users’ posture as a cue to wake the device when they are leaning towards the device) and research (e.g., surveillance trade-offs) implications, and argue for the use of multi-modal inputs with attention to privacy. Designing and training voice assistants to take in and appropriately respond to non-verbal cues may increase their inclusivity, helping them fulfill important needs of our aging population.

Recent advances in Artificial Intelligence (AI) suggest that AI applications could transform healthcare delivery in the Global South. However, as researchers and technology companies rush to develop AI applications that aid the health of marginalized communities, it is critical to consider the needs and perceptions of the community health workers (CHWs) who will have to integrate these AI applications into the essential healthcare services they provide to rural communities. We describe a qualitative study examining CHWs’ perceptions of an AI application for automated disease diagnosis. Drawing on data from 21 interviews with CHWs in rural India, we characterize (1) CHWs’ knowledge, perceptions, and understandings of AI; and (2) the benefits and challenges that CHWs anticipate as AI applications are integrated into their workflows, including their opinions on automation of their work, possible misdiagnosis and errors, data access and surveillance issues, security and privacy challenges, and questions concerning trust. We conclude by discussing the implications of our work for HCI and AI research in low-resource environments.

The shutdown measures necessary to stop the spread of COVID-19 have amplified the role of technology in intimate partner violence (IPV). Survivors may be forced to endure lockdowns with their abusers, intensifying the dangers of technology-enabled abuse (e.g. stalking, harassment, monitoring, surveillance). They may also be forced to rely on potentially compromised devices to reach support networks: a dangerous dilemma for digital safety. This qualitative study examines how technologists with computer security expertise provided remote assistance to IPV survivors during the pandemic. Findings from 24 consults with survivors and five focus groups with technologist consultants show how remote delivery of technology support services raised three fundamental challenges: (1) ensuring safety for survivors and consultants; (2) assessing device security over a remote connection; and (3) navigating new burdens for consultants, including emotional labor. We highlight implications for HCI researchers creating systems that enable access to remote expert services for vulnerable people.

Although WhatsApp-based communication is playing an increasingly large role in the professional lives of teachers in low-income schools, the nature of the interactions that occur and how these interactions enable cooperative work are not well understood. We contribute a qualitative analysis of 26 existing WhatsApp groups (35,567 messages) that examines (1) the strategies used to encourage interaction within teacher-focused WhatsApp groups, and (2) how these interactions are sustained by teachers, management, and organizations over a period of time. We use teacher networks and activity awareness model to make sense of WhatsApp-based interactions and show how WhatsApp narrows the gap between management and teachers, leading to additional work and stress for teachers. WhatsApp was also used to circulate polarizing and malicious information, leading to a variety of interesting content moderation strategies. Our findings expand the scope of research on teacher networks to low-income contexts and will inform future interventions that enable cooperative work among teachers.

Low-income merchants in India, who conduct business via makeshift shops and handcarts, are increasingly using digital payment systems for business operations. Although these merchants are a key stakeholder in digital payment ecosystems, they have not yet received much attention from the research community. We present a qualitative study consisting of observations and interviews with 24 low-income merchants and 10 agents that explores the vulnerabilities merchants experience as they adopt and use digital payments. Using the notion of vulnerability as a lens, we show how socio-technical interactions between merchants and agents contribute to at least four different types of vulnerabilities: access-based, identity-based, financial, and informational vulnerabilities. We discuss how agents, customers, and fraudsters take advantage of merchants’ vulnerabilities to commit different types of fraud that lead to serious harm for merchants. We show how merchants developed strategies to combat fraud that lead to more work and extra burdens for merchants. Our research suggests a cyclic model of vulnerability that exposes the cumulative effects of vulnerabilities, frauds, and harms experienced by merchants. We end by providing practical recommendations for digital payment companies to break this cycle and better serve low-income merchants.

We argue that existing security, privacy, and antiabuse protections fail to address the growing threat of online hate and harassment. In order for our community to understand and address this gap, we propose a taxonomy for reasoning about online hate and harassment. Our taxonomy draws on over 150 interdisciplinary research papers that cover disparate threats ranging from intimate partner violence to coordinated mobs. In the process, we identify seven classes of attacks—such as toxic content and surveillance—that each stem from different attacker capabilities and intents. We also provide longitudinal evidence from a three-year survey that hate and harassment is a pervasive, growing experience for online users, particularly for at-risk communities like young adults and people who identify as LGBTQ+. Responding to each class of hate and harassment requires a unique strategy and we highlight five such potential research directions that ultimately empower individuals, communities, and platforms to do so.

This paper describes how village-level officials, relatively new to the Internet, use popular digital platforms on smartphones to supplement and extend long-standing patterns of information control and authoritarian power in rural Cambodia. They use these tools to monitor local affairs, report to the central government, and promote local government activities, practices which intimidate villagers and encourage their political withdrawal and self-censorship. This paper makes three contributions to the literature on networked authoritarianism and rural governance. First, technological changes currently underway in the Cambodian rural bureaucracy reflect a generational transition, as long-standing officials struggle to use new media easily or effectively, leading to new anxieties and breakdowns for these traditional holders of power. Second, bureaucratic information practices in these villages rely on material practices ranging from paper, face to face meetings, and loudspeakers, to new tools such as Facebook and smartphones - underlining significant continuities in mechanisms of bureaucratic power and control. Third, networked authoritarian practices conjure for villagers the historical links between information control and violence, and the effectiveness of these tactics on chilling speech is often rooted in villagers' memories of fear.

Home care workers (HCWs) are increasingly central to post-acute and long-term health services in the United States. Despite being a critical component of the day-to-day care of home-dwelling adults, these workers often feel underappreciated and isolated on the job and come from low-income and marginalized backgrounds. Leveraging the support of peers is one potential way to empower HCWs, but peer support encompasses a broad range of activities and aspects. Traditional conceptions of workplace support may not be appropriate to the home care context, as HCWs are a distributed workforce who have few opportunities to interact with each other. In this study, we explore how HCWs value and conceptualize peer support. Our findings demonstrate the importance of peer support in performing the emotional labor of home care work and ongoing attempts to strategically frame the home care profession as essential and medical in nature. Our results ground design implications for technology-enabled peer support based on the power dynamics of our participants' context and allow us to engage with issues where technology design for empowerment intersects with exploitation in distributed or crowd work, emotional labor, and tacit knowledge.

Smartphones play an increasingly large role in the professional lives of teachers in low-income contexts, creating an urgent need to better understand the role of technology-related stress (technostress) in teachers' smartphone use for work. We contribute a mixed methods study analyzing the impact of smartphone use on teachers' work lives in low-income Indian schools. Findings from 70 interviews and 1,361 survey responses suggest that although smartphones aid teaching and administrative functions, smartphone use also significantly predicts burnout among teachers, with technostress providing a major explanation for this relationship. We reveal how teachers' work is constantly surveilled and monitored via technology and how teachers' personal smartphones were controlled and repurposed through socio-technical structures by the higher management to serve management's goals, substantially increasing the work teachers were required to perform outside of work hours. Our work extends technostress research to HCI4D contexts and highlights the need to develop better support structures for teachers and rethink how smartphones are used in their work.

HCI researchers have increasingly studied how technology might improve the lives of marginalized workers. We explored this question through a qualitative study with home health aides in New York City, a vulnerable group of frontline caregivers whose work with patients is poorly paid and highly stressful, often involving life-or-death situations. To elicit the perspectives of aides and their supervisors on how technology interventions might contribute to moving aides towards a better future, we created a design provocation that centers aides' needs and suggests more equitable roles for them within the home care ecosystem. Findings from design sessions with 16 aides, nurses, and aide coordinators illuminate the ethical and pragmatic dilemmas inherent in this complex ecosystem, and show that designing technology for equity requires attention to structural problems in addition to workers' stated needs. We analyze our findings through the lens of social justice-oriented interaction design, and discuss how our work extends key strategies within this framework.

In Cameroon, no exam is more important than the baccalauréat, which serves as the gateway to adulthood and professional and higher-education aspirations. We build on existing literature on the benefits of practice tests to evaluate how SMS-based quizzes could help students in their final year of secondary school prepare for the baccalauréat. Students in 23 schools across Yaoundé, the capital of Cameroon, received multiple-choice questions four times per week for nine weeks leading up to the exam date. We examined baccalauréat pass rates and student feedback through 11 focus groups. We find that students used our practice tests for formative assessment and as a prompt for recall and review of study material. SMS-based quizzes were not isolated artifacts but were shared in the students' networks, built a distributed learning environment, and used as a focus of collaborative study sessions.

Current ICTD best practices call on practitioner organizations that deploy technology interventions with marginalized communities to commit to long-term engagements and provide continuous support. This paper describes a qualitative study that examines the challenges and issues that arise for organizations that have tried to answer this call: a set of education-focused non-profit organizations in India that have invested heavily in building long-term relationships with low-income schools and that are deeply committed to providing ongoing support, both in-person and via technology. Interviews and observations with 71 participants (51 from eight organizations, and 15 teachers and five principals from 12 schools) reveal (1) the challenges and issues that arise as organizations integrate smartphones into teacher support programs, and (2) the strategies that teachers and organizations use to ease smartphone adoption in teacher support programs. Our findings uncover the effects of organizations' smartphone-oriented support programs on teachers' workloads, efficacy, and stress, and highlight opportunities for organizations to improve their programs and support structures.

Technology increasingly facilitates interpersonal attacks such as stalking, abuse, and other forms of harassment. While prior studies have examined the ecosystem of software designed for stalking, there exists an unstudied, larger landscape of apps-what we call creepware-used for interpersonal attacks. In this paper, we initiate a study of creepware using access to a dataset detailing the mobile apps installed on over 50 million Android devices. We develop a new algorithm, CreepRank, that uses the principle of guilt by association to help surface previously unknown examples of creepware, which we then characterize through a combination of quantitative and qualitative methods. We discovered apps used for harassment, impersonation, fraud, information theft, concealment, and even apps that purport to defend victims against such threats. As a result of our work, the Google Play Store has already removed hundreds of apps for policy violations. More broadly, our findings and techniques improve understanding of the creepware ecosystem, and will inform future efforts that aim to mitigate interpersonal attacks.

A growing body of research suggests that intimate partner abusers use digital technologies to surveil their partners, including by installing spyware apps, compromising devices and online accounts, and employing social engineering tactics. However, to date, this form of privacy violation, called intimate partner surveillance (IPS), has primarily been studied from the perspective of victim-survivors. We present a qualitative study of how potential perpetrators of IPS harness the emotive power of sharing personal narratives to validate and legitimise their abusive behaviours. We analysed 556 stories of IPS posted on publicly accessible online forums dedicated to the discussion of sexual infidelity. We found that many users share narrative posts describing IPS as they boast about their actions, advise others on how to perform IPS without detection, and seek suggestions for next steps to take. We identify a set of common thematic story structures, justifications for abuse, and outcomes within the stories that provide a window into how these individuals believe their behaviour to be justified. Using these stories, we develop a four-stage framework that captures the change in a potential perpetrator's approach to IPS. We use our findings and framework to guide a discussion of efforts to combat abuse, including how we can identify crucial moments where interventions might be safely applied to prevent or deescalate IPS.

People in South Asia frequently share a single device among multiple individuals, resulting in digital privacy challenges. This paper explores a design concept that aims to mitigate some of these challenges through a 'tiered' privacy model. Using this model, a person creates a 'shared' account that contains data they are willing to share and that is assigned a password that will be shared. Simultaneously, they create a separate 'secret' account that contains data they prefer to keep secret and that uses a password they do not share with anyone. When a friend or family member asks to check their device, the user can tell them the password for their shared account, with their private data secure in the secret account that the other person is unaware of. We explore the benefits and trade-offs of our design through a three-week deployment with 21 participants in Bangladesh, presenting findings that show how our work aids digital privacy while also exposing the challenges that remain.

We created a quiz-based intervention to help secondary school students in Cameroon with exam practice. We sent regularly-spaced, multiple-choice questions to students' own mobile devices and examined factors which influenced quiz participation. These quizzes were delivered via either SMS or WhatsApp per each student's preference. We conducted a 3-week deployment with 546 students at 3 schools during their month of independent study prior to their graduating exam. We found that participation rates were heavily impacted by trust in the intervening organization and perceptions of personal security in the socio-technical environment. Parents also played a key gate-keeping role on students' digital activities. We describe how this role - along with different perceptions of smartphones versus basic phones - may manifest in lower participation rates among WhatsApp-based users as compared to SMS. Finally, we discuss design implications for future educational interventions that target students' personal cellphones outside of the classroom.

Home health aides (HHAs) increasingly being used by adults with heart failure for long-term assistance and post-hospitalization care. Despite being heavily involved in numerous aspects of heart failure management, most HHAs have not received heart failure training. They also struggle to get in touch with supervising nurses or other members of the care team when they have clinical questions, which may result in unnecessary visits to the emergency room. In addition, despite serving as a backbone in the health system for patients, HHAs, who are mostly women and minorities, are a marginalized and vulnerable group of frontline caregivers, enduring erratic employment, low wages, discrimination, and high levels of burnout. Although digital technologies could help to address many of the challenges HHAs face, little is known about the current impact of technology on HHAs work practices. To this end, we conducted a multi-stakeholder qualitative study with 38 participants in New York City using semi-structured interviews and focus groups. We uncover the ways in which technology is used, the complex socio-technical factors that underpin heart failure care, and stakeholder suggestions for how technology could improve HHAs work. Building on these insights, we synthesize design opportunities for researchers and designers interested in developing tools that support the delivery of home health care for patients suffering from life-threatening diseases like heart failure.

This paper examines refugees' experiences with and perspectives on the digital identity systems used by humanitarian organizations to collect, manage, and share their personal data. Through a qualitative study with 198 refugees in Lebanon, Jordan, and Uganda, we show how existing humanitarian identity systems present numerous challenges for refugees. For example, we find that refugees have little to no knowledge of the institutional systems and processes through which their personal data is managed and used. In addition, refugees are typically not able to exercise agency with regard to data that is collected about them (e.g., given choices about the data collected). At the same time, we show how refugees make active efforts to negotiate the various identities available to them, consciously weighing the benefits and constraints associated with different statuses to maximize their access to services, eligibility for employment, and spatial mobility. We use Bardzell's lens of feminist interaction design [8] to make sense of these findings and suggest a path forward that engages refugees in the design of improved identity management systems.

This paper explores the design space of feedback systems that connect care recipients to the community health feedback loop. While related work in this vein has often emphasized gathering feedback for the sake of transparency alone, our study emphasizes opportunities to integrate the collection and use of feedback in ways that may improve the quality or equity of routine health services. We conducted a qualitative study using semi-structured interviews and focus groups with 23 participants in Kenya. Our field study makes current feedback practices visible; and reveals barriers faced by beneficiaries, community health workers, and their supervisors. Our findings identify relevant socio-technical complexities, and we outline concrete opportunities to design feedback systems that support and augment current practices. These contributions to the ICTD literature hold potential to inform the design of feedback systems that engage underserved populations in a systematic and equitable manner.

People's content choices are ideally driven by their intentions, aspirations, and plans. However, in reality, choices may be modulated by recommendation systems which are typically trained to promote popular items and to reinforce users' historical behavior. As a result, the utility and user experience of content consumption can be affected implicitly and undesirably. To study this problem, we conducted a 2 × 2 randomized controlled field experiment (105 urban college students) to compare the effects of intention informed recommendations with classical intention agnostic systems. The study was conducted in the context of spoken word web content (podcasts) which is often consumed through subscription sites or apps. We modified a commercial podcast app to include (1) a recommender that takes into account users' stated intentions at onboarding, and (2) a Collaborative Filtering (CF) recommender during daily use. Our study suggests that: (1) intention-aware recommendations can significantly raise users' interactions (subscriptions and listening) with channels and episodes related to intended topics by over 24%, even if such a recommender is only used during onboarding, and (2) the CF-based recommender doubles users' explorations on episodes from not-subscribed channels and improves satisfaction for users onboarded with the intention-aware recommender.

Intimate partner abusers use technology to track, monitor, harass, and otherwise harm their victims, and prior work reports that victims have few resources for obtaining help with such attacks. This paper presents a qualitative analysis of data from a field study of an approach to helping survivors of intimate partner violence (IPV) with technology abuse. In this approach, called clinical computer security, a trained technologist performs a face-to-face consultation with an IPV survivor to help them understand and navigate technology issues. Findings from consultations with 31 survivors, as well as IPV professionals working on their behalf, uncovered a range of digital security and privacy vulnerabilities exacerbated by the nuanced social context of such abuse. In this paper we explore survivor experiences with, and reactions to, the consultations, discussing (1) the ways in which survivors present their tech concerns, (2) the cooperative work required to guide survivors towards understanding probable causes of tech insecurity, (3) survivors' reactions to the consultations, particularly when security vulnerabilities or spyware are discovered, and (4) the role we play as consultants and interventionists in the complex socio-technical systems involved in mitigating IPV. We conclude by discussing some of the broad ethical and sustainability challenges raised by our work, and provide design opportunities for tech platforms to better support survivors of IPV.

Privacy scholarship has shown how norms of appropriate information flow and information regulatory processes vary according to environment, which change as the environment changes, including through the introduction of new technologies. This paper describes findings from a qualitative research study that examines practices and perceptions of privacy in Cambodia as the population rapidly moves into an online environment (specifically Facebook, the most popular Internet tool in Cambodia today). We empirically demonstrate how the concept of privacy differs across cultures and show how the Facebook platform, as it becomes popular worldwide, catalyzes change in norms of information regulation. We discuss how the localization of transnational technology platforms provides a key site in which to investigate changing cultural ideas about privacy, and to discover misalignments between different expectations for information flow. Finally, we explore ways that insufficient localization effort by transnational technology companies puts some of the most marginalized users at disproportionate information disclosure risk when using new Internet tools, and offer some pragmatic suggestions for how such companies could improve privacy tools for users who are far -geographically or culturally - from where the tools are designed.

Community health programs in low-resource settings (like rural Kenya) aim to provide essential health services to vulnerable populations. However, to date, there has been limited research that explores the design of mechanisms that enable care recipients to provide feedback regarding their satisfaction with the services they receive. Such feedback has the potential to increase the motivation of community health workers (CHWs), enhance training procedures, detect fraudulent behavior, and inform key performance indicators for health programs. Our paper explores the design and deployment of a USSD-based system that allows anyone who possesses a basic mobile phone to provide feedback regarding the health services and quality of care they received from a CHW or during a hospital visit. Our system was designed through iterative fieldwork in rural Kenya that engaged with multiple stakeholder groups, including care recipients, CHWs, and high-level decision makers. After designing and testing the system, we deployed it for seven weeks in Siaya, Kenya, collecting both quantitative system usage data and qualitative data from six focus groups with 42 participants. Findings from our deployment show that 168 care recipients engaged with the system, submitting 495 reports via USSD. We discuss the broader factors impacting deployment, including the feasibility of USSD, actionability of feedback, scalability, and sustainability. Taken together, our findings suggest that USSD is a promising approach for enabling care recipients to submit feedback in a way that balances privacy, equity, and sustainability.

The proliferation of mobile devices around the world, combined with falling costs of hardware and Internet connectivity, have resulted in an increasing number of organizations that work to introduce educational technology interventions into low-income schools in the Global South. However, to date, most prior HCI research examining such interventions has focused on interventions that target students. In this paper, we expand prior literature by examining an intervention, called Meghshala, that targets teachers in low-income schools as its primary users. Through interviews and observations with 39 participants from 12 government schools in India, we show how the introduction of a teacher-focused technology intervention causes teachers to reconfigure their work practices, including lesson preparation, in-classroom teaching practices, bureaucratic work processes, and post-teaching feedback mechanisms. We use the concept of material agency to analyze our findings with respect to teacher agency and reconfiguration, and use theories of teacher knowledge to highlight the kinds of knowledge production that teachers in our research context tend to focus on (e.g., content knowledge). Finally, we offer design opportunities for future teacher-focused technology interventions.

Indirect resource exchange (IRE), where individuals share physical items with one another but do not receive direct benefits (e.g. payment), has the potential to increase communities' access to resources, reduce consumption and waste, and bootstrap social ties. Although social technologies could play a key role in realizing this potential, significant barriers have emerged to the adoption of IRE services, including concerns related to trust, reciprocity, and coordination. To explore these issues, we designed and iterated on a concept called ShareBox, a system that enables IRE through a smart lockbox. We developed ShareBox as a technology probe following a set of design guidelines including: creating a physical-virtual system, enabling asynchronous and anonymous exchange, allowing for low-entry-barrier interactions, and emphasizing affordability and flexibility. We explore the benefits and trade-offs of these design guidelines through short deployments and semi-structured interviews with community members, and present findings that highlight both the potential and the remaining challenges of our design.

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.

This paper examines the opportunities and issues that arise in designing technologies to support low-income rural women in Bangladesh. Through a qualitative, empirical study with 90 participants, we reveal systemic everyday challenges that women face that form the backdrop against which technology design could potentially happen. We discuss how technology is already impacting women's lives, sometimes by reinforcing their subservient role in society and sometimes used tactically by women to gain a measure of agency. The issues raised by our participants concerning technology's place in their lives provide HCI researchers with valuable guidance about what might (or might not) be appropriate to design for them. We also show how prevalent HCI research and design strategies may fit more poorly than expected into rural women's lives, and we discuss possible alternative design directions, and the ethical and pragmatic trade-offs that they entail. Our contribution is not to "solve" the problem of designing for low-income rural women, but to expand the HCI community's understanding of technology design within deeply patriarchal societies.

Evaluations of technological artifacts in HCI4D contexts are known to suffer from high levels of participant response bias---where participants only provide positive feedback that they think will please the researcher. This paper describes a practical, low-cost intervention that uses the concept of social proof to influence participant response bias and successfully elicit critical feedback from study participants. We subtly exposed participants to feedback that they perceived to be provided by people 'like them', and experimentally controlled the tone and content of the feedback to provide either positive, negative, or no social proof. We then measured how participants' quantitative and qualitative evaluations of an HCI artifact changed based on the feedback to which they were exposed. We conducted two controlled experiments: an online experiment with 245 MTurk workers and a field experiment with 63 women in rural India. Our findings reveal significant differences between participants in the positive, negative, and no social proof conditions, both online and in the field. Participants in the negative condition provided lower ratings and a greater amount of critical feedback, while participants in the positive condition provided higher ratings and a greater amount of positive feedback. Taken together, our findings demonstrate that social proof is a practical and generalizable technique that could be used by HCI researchers to influence participant response bias in a wide range of contexts and domains.

Digital overuse on mobile devices is a growing problem in everyday life. This paper describes a generalizable mobile intervention that combines nudge theory and negative reinforcement to create a subtle, repeating phone vibration that nudges a user to reduce their digital consumption. For example, if a user has a daily Facebook limit of 30 minutes but opens Facebook past this limit, the user's phone will issue gentle vibrations every five seconds, but the vibration stops once the user navigates away from Facebook. We evaluated the intervention through a three-week controlled experiment with 50 participants on Amazon's Mechanical Turk platform with findings that show daily digital consumption was successfully reduced by over 20%. Although the reduction did not persist after the intervention was removed, insights from qualitative feedback suggest that the intervention made participants more aware of their app usage habits; and we discuss design implications of episodically applying our intervention in specific everyday contexts such as education, sleep, and work. Taken together, our findings advance the HCI community's understanding of how to curb digital overload.

Survivors of intimate partner violence increasingly report that abusers install spyware on devices to track their location, monitor communications, and cause emotional and physical harm. To date there has been only cursory investigation into the spyware used in such intimate partner surveillance (IPS). We provide the first in-depth study of the IPS spyware ecosystem. We design, implement, and evaluate a measurement pipeline that combines web and app store crawling with machine learning to find and label apps that are potentially dangerous in IPS contexts. Ultimately we identify several hundred such IPS-relevant apps. While we find dozens of overt spyware tools, the majority are "dual-use" apps - they have a legitimate purpose (e.g., child safety or anti-theft), but are easily and effectively repurposed for spying on a partner. We document that a wealth of online resources are available to educate abusers about exploiting apps for IPS. We also show how some dual-use app developers are encouraging their use in IPS via advertisements, blogs, and customer support services. We analyze existing anti-virus and anti-spyware tools, which universally fail to identify dual-use apps as a threat.

Our paper provides an enriched understanding of the relationship between research and practice through the study of practitioners variously engaged in field research on technology interventions in the context of global development. By conducting a qualitative inquiry with 33 practitioners from 26 global development organizations, we highlight how these practitioners have different goals, work practices, incentive structures, and expectations than researchers, making it challenging to co-create and coordinate productive and effective partnerships. Despite these challenges, practitioners in global development do appear to value and engage with research as they strive for positive impact across their target communities. Our analysis suggests that the domain of human-computer interaction for development (HCI4D) might benefit from engaging in "informed practice" through alignment with design-based implementation research (DBIR), which unites researchers and practitioners in their shared commitment to both research and practice, even if research and practice respectively remain their primary commitments. Our work provides CSCW and HCI4D researchers with new ways to conceptualize and navigate the above research-practice divide. We also emphasize the contribution such an approach might make to CSCW researchers beyond the context of global development, and more broadly concerned with making a positive societal impact with their work.

With the rapid growth of ICT adoption in the Global South, crimes over and through digital technologies have also increased. Consequently, governments have begun to undertake a variety of different surveillance programs, which in turn provoke questions regarding citizens' privacy rights. However, both the concepts of privacy and of citizens' corresponding political rights have not been well-developed in HCI for non-Western contexts. This paper presents findings from a three-month long ethnography and online survey (n=606) conducted in Bangladesh, where the government recently imposed mandatory biometric registration for every mobile phone user. Our analysis surfaces important privacy and safety concerns regarding identity, ownership, and trust, and reveals the cultural and political challenges of imposing biometric registration program in Bangladesh. We also discuss how alternative designs of infrastructure, technology, and policy may better meet stakeholders' competing needs in the Global South.

Our research aims to support community health workers (CHWs) in low-resource settings by providing them with personalized information regarding their work. This information is delivered through a combination of voice- and web-based feedback that is derived from data already collected by CHWs. We describe the in situ participatory design approach used to create usable and appropriate feedback for low-literate CHWs and present usage data from a 12-month study with 71 CHWs in India. We show how the system supported and motivated CHWs, and how they used both the web- and voice-based systems, and each of the visualizations, for different reasons. We also show that the comparative feedback provided by the system introduced elements of competition that discouraged some CHWs while motivating others. Taken together, our findings suggest that providing personalized voice- and web-based feedback could be an effective way to support and motivate CHWs in low-resource settings.

Prior research on technology use in the Global South suggests that people in marginalized communities frequently share a single device among multiple individuals. However, the data privacy challenges and tensions that arise when people share devices have not been studied in depth. This paper presents a qualitative study with 72 participants that analyzes how families in Bangladesh currently share mobile phones, their usage patterns, and the tensions and challenges that arise as individuals seek to protect the privacy of their personal data. We show how people share devices out of economic need, but also because sharing is a social and cultural practice that is deeply embedded in Bangladeshi society. We also discuss how prevalent power relationships affect sharing practices and reveal gender dynamics that impact the privacy of women's data. Finally, we highlight strategies that participants adopted to protect their private data from the people with whom they share devices. Taken together, our findings have broad implications that advance the CSCW community's understanding of digital privacy outside the Western world.

Digital technologies, including mobile devices, cloud computing services, and social networks, play a nuanced role in intimate partner violence (IPV) settings, including domestic abuse, stalking, and surveillance of victims by abusive partners. However, the interactions among victims of IPV, abusers, law enforcement, counselors, and others --- and the roles that digital technologies play in these interactions --- are poorly understood. We present a qualitative study that analyzes the role of digital technologies in the IPV ecosystem in New York City. Findings from semi-structured interviews with 40 IPV professionals and nine focus groups with 32 survivors of IPV reveal a complex set of socio-technical challenges that stem from the intimate nature of the relationships involved and the complexities of managing shared social circles. Both IPV professionals and survivors feel that they do not possess adequate expertise to be able to identify or cope with technology-enabled IPV, and there are currently insufficient best practices to help them deal with abuse via technology. We also reveal a number of tensions and trade-offs in negotiating technology's role in social support and legal procedures. Taken together, our findings contribute a nuanced understanding of technology's role in the IPV ecosystem and yield recommendations for HCI and technology experts interested in aiding victims of abuse.

Nutrient-based meal recommendations have the potential to help individuals prevent or manage conditions such as diabetes and obesity. However, learning people’s food preferences and making recommendations that simultaneously appeal to their palate and satisfy nutritional expectations are challenging. Existing approaches either only learn high-level preferences or require a prolonged learning period. We propose Yum-me , a personalized nutrient-based meal recommender system designed to meet individuals’ nutritional expectations, dietary restrictions, and fine-grained food preferences. Yum-me enables a simple and accurate food preference profiling procedure via a visual quiz-based user interface and projects the learned profile into the domain of nutritionally appropriate food options to find ones that will appeal to the user. We present the design and implementation of Yum-me and further describe and evaluate two innovative contributions. The first contriution is an open source state-of-the-art food image analysis model, named FoodDist . We demonstrate FoodDist’s superior performance through careful benchmarking and discuss its applicability across a wide array of dietary applications. The second contribution is a novel online learning framework that learns food preference from itemwise and pairwise image comparisons. We evaluate the framework in a field study of 227 anonymous users and demonstrate that it outperforms other baselines by a significant margin. We further conducted an end-to-end validation of the feasibility and effectiveness of Yum-me through a 60-person user study, in which Yum-me improves the recommendation acceptance rate by 42.63%.

We present an empirical analysis of HCI for development (HCI4D), a growing research area aimed at understanding and designing technologies for under-served, under-resourced, and under-represented populations around the world. We first present findings from our survey of 259 HCI4D publications from the past six years and summarize how this research has evolved, with an overview of the geographies it covers, technologies it targets, and its varied epistemological and methodological underpinnings. We then discuss qualitative findings from interviews we conducted with 11 experienced HCI4D researchers, reflecting on the ground covered so far Including computing and research trends, community-building efforts, and thoughts about 'development' - as well as challenges that lie ahead and suggestions for future growth and diversification. We conclude by summarizing the contributions our paper makes to HCI researchers inside the HCI4D community as well as those outside of it, with the goal of enriching discussions on how HCI can further benefit populations around the world.

This paper presents an analysis of the privacy issues associated with the practice of repairing broken digital objects in Bangladesh. Historically, research in Human-Computer Interaction (HCI), Information and Communication Technologies for Development (ICTD), and related disciplines has focused on the design and development of new interventions or technologies. As a result, the repair of old or broken technologies has been an often neglected topic of research. The goal of our work is to improve the practices surrounding the repair of digital artifacts in developing countries. Specifically, in this paper we examine the privacy challenges associated with the process of repairing digital artifacts, which usually requires that the owner of a broken artifact hand over the technology to a repairer. Findings from our ethnographic work conducted at 10 repair markets in Dhaka, Bangladesh, show a variety of ways in which the privacy of an individual's personal data may be compromised during the repair process. We also examine people's perceptions around privacy in repair and its connections with broader social and cultural values. Finally, we discuss the challenges and opportunities for future research to strengthen the repair ecosystem in developing countries. Taken together, our findings contribute to the growing discourse around post-use cycles of technology in ICTD and HCI.

Accredited Social Health Activists (ASHAs) have been shown to have a positive impact on health outcomes of the households they visit, particularly in maternal and neonatal health. As the first line of the public health system in many countries, they are a critical link to the broader public health infrastructure for community members. Yet they do this all with minimal training and limited support infrastructure. To a pregnant woman, an ASHA is a trusted ally in navigating the health system---information gathered is returned by appropriate advice and counseling. To the health system, the ASHA is a key channel of valuable householdlevel information for the public health system, yet she generally receives minimal guidance in return. In this paper we present ASTA---the ASHA Self-Tracking Application---a system that provides ASHAs with timely, on-demand information regarding their own performance compared to their peers. Using ASTA, ASHAs access comparative performance data through both a web-based and voice-based interface on demand. We evaluated ASTA through a 12-month deployment with 142 ASHAs in Uttar Pradesh, India, assessing the impact of providing feedback on ASHA performance. We find that ASHAs with access to the ASTA system made significantly more client visits, with average monthly visits 21.5% higher than ASHAs who had access to a control system. In addition, higher ASHA performance was correlated with increased usage of ASTA. However, the performance improvement was front-loaded, with the impact of the system decreasing toward the end of the study period. Taken together, our findings provide promising evidence that studying and incorporating tools like ASTA could be cost effective and impactful for ASHA programs.

We present the first analysis of the use and non-use of social media platforms by low-income blind users in rural and peri-urban India. Using a mixed-methods approach of semi-structured interviews and observations, we examine the benefits received by low-income blind people from Facebook, Twitter and WhatsApp and investigate constraints that impede their social media participation. We also present a detailed analysis of how low-income blind people used a voice-based social media platform deployed in India that received significant traction from low-income people in rural and peri-urban areas. In eleven-weeks of deployment, fifty-three blind participants in our sample collectively placed 4784 voice calls, contributed 1312 voice messages, cast 33,909 votes and listened to the messages 46,090 times. Using a mixed-methods analysis of call logs, qualitative interviews, and phone surveys, we evaluate the strengths and weaknesses of the platform and benefits it offered to low-income blind people.

A growing body of HCI4D research studies the use of SMS communication to deliver health and information services to underserved populations. This paper contributes a novel dimension to this field of study by examining if a hybrid computer-human SMS system can engage pregnant women in Kenya in health-related communication. Our approach leverages the different strengths of both the computer and the human. The computer automates the bulk-sending of personalized messages to patients, allowing the human to read patients' replies and respond to those in need of attention. Findings from a 12-month deployment with 100 women show that our approach is capable of engaging the majority of participants in health-related conversations. We show that receiving messages from the system triggers participant communication and the amount of communication increases as participants approach their expected due date. In addition, analysis of participants' messages shows that they often contain sensitive health information conveyed through a complex mixture of languages and 'txting' abbreviations, all of which highlight the benefits of including a human in the workflow. Our findings are relevant for HCI researchers and practitioners interested in understanding or engaging underserved populations.

Global development organizations rely on the essential affordances provided by both paper and digital materials to navigate hurdles posed by poor infrastructure, low connectivity, linguistic differences, and other socioeconomic constraints that render communication and collaboration challenging. This paper examines the collaborative practices around paper-digital workflows within global development organizations operating in low-resource environments. We use a mixed methods approach to gather data from 23 organizations in 16 countries. Our findings show the tensions that arise between the ubiquitousness of paper and the desirability of digitized data, and highlight the challenges associated with transitioning information several times between paper and digital materials. We also reveal design opportunities for new tools to bridge the gap between paper-based and digital information in low-resource settings. Finally, we contribute a nuanced understanding of the cross-cultural and infrastructural challenges that influence the paper-digital lifecycle. Our findings will be useful for researchers and practitioners interested in understanding or participating in the workflows that drive global development.

The worldwide adoption of mobile devices presents an opportunity to build mobile systems to support health workers in low-resource settings. This paper presents an in-depth field evaluation of a mobile system that uses a smartphone's built-in camera and computer vision to capture and analyze diagnostic tests for infectious diseases. We describe how health workers integrate the system into their daily clinical workflow and detail important differences in system usage between small clinics and large hospitals that could inform the design of future mobile health systems. We also describe a variety of strategies that health workers developed to overcome poor network connectivity and transmit data to a central database. Finally, we show strong agreement between our system's computed diagnoses and trained health workers' visual diagnoses, which suggests that our system could aid disease diagnosis in a variety of scenarios. Our findings will help to guide ministries of health and other stakeholders working to deploy mobile health systems in similar environments.

We describe our experiences integrating ODK Scan into the community health worker (CHW) supply chain in Mozambique. ODK Scan is a mobile application that uses computer vision techniques to digitize data from paper forms. The application automatically classifies machine-readable data types, like bubbles and checkboxes, and assists users with the manual entry of handwritten text and numbers. We designed an intervention that uses paper forms in conjunction with ODK Scan to monitor CHW usage of essential health commodities, finding that the application is capable of providing supervisors and stakeholders with important information regarding health commodity availability in the field. Specifically, we (1) detail our experiences integrating ODK Scan into the health worker supply chain in Mozambique, with particular emphasis on the critical (and often under-reported) role of practitioners; (2) evaluate the impact of the technology at multiple levels of the information hierarchy, providing quantitative and qualitative data that exposes the benefits, challenges and limitations of the technology; and (3) share lessons learned and provide actionable guidance to researchers and practitioners interested in ODK Scan or other systems that bridge the gap between paper-based and digital data collection.

Although HCI researchers and practitioners frequently work with groups of people that differ significantly from themselves, little attention has been paid to the effects these differences have on the evaluation of HCI systems. Via 450 interviews in Bangalore, India, we measure participant response bias due to interviewer demand characteristics and the role of social and demographic factors in influencing that bias. We find that respondents are about 2.5x more likely to prefer a technological artifact they believe to be developed by the interviewer, even when the alternative is identical. When the interviewer is a foreign researcher requiring a translator, the bias towards the interviewer's artifact increases to 5x. In fact, the interviewer's artifact is preferred even when it is degraded to be obviously inferior to the alternative. We conclude that participant response bias should receive more attention within the CHI community, especially when designing for underprivileged populations.