When Code Governs Community

We present a qualitative study of governance in the community of League of Legends, a popular Multiplayer online battle arena (MOBA) game developed by Riot Games. To cope with toxic behaviors such as griefing and flaming, Riot Games initially implemented a crowdsourcing system inviting players to participate in governing their own community. However, in May, 2014, they automated the system, relying heavily on code while minimizing the level of human participation. We analyzed both players’ and Riot Games’ narratives to understand their attitudes towards the relationship between human judgment and automation, as well as between alienation and community. We found stark differences between players and Riot Games in terms of attitudes towards code and value in designing online governance. We discuss how the design of governance might impact online community

Resisting the Censorship Infrastructure in China

China’s censorship infrastructure is widely recognized as sophisticated, strict, and comprehensive. We conducted a qualitative study to understand Chinese citizens’ practices to navigate the censored Chinese Internet. We found that participants’ practices were closely related to their understanding of and resistance to the censorship infrastructure. Participants switched between public and private channels based on the information they desired to seek. They communicated in ways that were considered less vulnerable to censorship examination. They broadened their information search to mitigate the impact of censored content consumption. Through these practices, participants reportedly coped with the censorship infrastructure in an effective manner. We discuss how this case of resistance to censorship in China may further our understanding of such infrastructure

The Medical Authority of AI: A Study of AI-enabled Consumer-facing Health Technology

Recently, consumer-facing health technologies such as Artificial Intelligence (AI)-based symptom checkers (AISCs) have sprung up in everyday healthcare practice. AISCs solicit symptom information from users and provide medical suggestions and possible diagnoses, a responsibility that people usually entrust with real-person authorities such as physicians and expert patients. Thus, the advent of AISCs begs a question of whether and how they transform the notion of medical authority in everyday healthcare practice. To answer this question, we conducted an interview study with thirty AISC users. We found that users assess the medical authority of AISCs using various factors including automated decisions and interaction design patterns of AISC apps, associations with established medical authorities like hospitals, and comparisons with other health technologies. We reveal how AISCs are used in healthcare delivery, discuss how AI transforms conventional understandings of medical authority, and derive implications for designing AI-enabled health technology

With Help from Afar: Cross-Local Communication in an Online COVID-19 Pandemic Community

Crisis informatics research has examined geographically bounded crises, such as natural or man-made disasters, identifying the critical role of local and hyper-local information focused on one geographic area in crisis communication. The COVID-19 pandemic represents an understudied kind of crisis that simultaneously hits locales across the globe, engendering an emergent form of crisis communication, which we term cross-local communication. Cross-local communication is the exchange of crisis information between geographically dispersed locales to facilitate local crisis response. To unpack this notion, we present a qualitative study of an online migrant community of overseas Taiwanese who supported fellow Taiwanese from afar. We detail four distinctive types of cross-local communication: situational updates, risk communication, medical consultation, and coordination. We discuss how the current pandemic situation brings new understandings to crisis informatics and online health community literature, and what role digital technologies could play in supporting cross-local communication

Exploring and Promoting Diagnostic Transparency and Explainability in Online Symptom Checkers

Online symptom checkers (OSC) are widely used intelligent systems in health contexts such as primary care, remote healthcare, and epidemic control. OSCs use algorithms such as machine learning to facilitate self-diagnosis and triage based on symptoms input by healthcare consumers. However, intelligent systems’ lack of transparency and comprehensibility could lead to unintended consequences such as misleading users, especially in high-stakes areas such as healthcare. In this paper, we attempt to enhance diagnostic transparency by augmenting OSCs with explanations. We first conducted an interview study (N=25) to specify user needs for explanations from users of existing OSCs. Then, we designed a COVID-19 OSC that was enhanced with three types of explanations. Our lab-controlled user study (N=20) found that explanations can significantly improve user experience in multiple aspects. We discuss how explanations are interwoven into conversation flow and present implications for future OSC designs

Designing for and Reflecting upon Resilience in Health and Wellbeing

Resilience has been a long-standing theme in HCI research and design. However, prior work has different conceptualizations of resilience, tackles resilience at different scales, and focuses on resilience as the ability to adapt to adversity. This one-day workshop will bring together HCI researchers, interaction designers, healthcare professionals, healthcare service users, and carepartners to critically reflect upon the epistemological stances on resilience and foreground the notion of resilience in health and wellbeing research. Our workshop themes include: 1) reflecting upon the diverse conceptualizations of resilience; 2) designing for resilience from a social justice perspective; 3) designing for multi-stakeholder resilience for individuals, families, communities, and society

Navigating the Healthcare Service “Black Box”: Individual Healthcare Consumers’ Practices and Design Opportunities

The U.S. healthcare system is known to be complex and fragmented. It presents as a black box to consumers as they often encounter a variety of challenges in obtaining the healthcare services they desire. To obtain a single service, patients often need to coordinate with multiple organizations, such as their employer, an insurance company, a physician practice, and a hospital. Such complexity and fragmentation manifests in isolation between patients, caregivers, organizations, and institutions. Yet little research has been done to understand how patients navigate the black box healthcare system. My dissertation research concerns the practices of parents of young children who navigated the multi-institutional healthcare system on behalf of their children in the United States. Through a narrative interview study of 32 parents from diverse racial, educational, and geographical backgrounds, I document how my participants as organizational outsiders navigated a complex system composed of diverse organizations and gain navigational competence. Building upon the empirical evidence, I conceptualize navigation practices and competence, and demonstrate multiple aspects of navigation practices. I further explore navigation practice in a concrete scenario that is choosing a provider, highlighting several factors that participants considered while making decisions. Lastly, I explore one specific type of navigation practice: the ongoing work that individual healthcare consumers engage in to make the fragmented healthcare infrastructure work for them, as a form of infrastructuring work. Building upon these findings, I discuss how navigation practice mediates the interaction between individual healthcare consumers and the “black box” healthcare system, and how design could better such interaction and help them obtain desired healthcare service