Artificially Intelligent (AI) agent systems such as robots are increasingly integrated into the workplace and gaining more power in collaborating with humans. Yet studies on robot power and compliance report mixed findings. To address these inconsistencies, we introduced legitimacy as people’s psychological acceptance of power. Three preregistered experiments were conducted (N = 431). In Experiment 1 and 2, we manipulated power assignment (robot power vs. human power), and legitimacy of power (legitimate, illegitimate, no explanation) through competence and procedural fairness. The results showed that participants complied more to the legitimate robot power than illegitimate one. In Experiment 3, we examined whether perceptions of legitimacy would emerge naturally in more ecologically valid collaboration. Results of multigroup mediation model showed that the robot leader was perceived as less legitimate than the human leader, which accounted for the reduced compliance to the robot’s decisions. In all three experiments, people’s perceived social attributes of robots with power and their affective responses after the interaction were negatively affected. This study underscores the importance of legitimacy in understanding power and compliance in human-robot collaboration.

While resuscitation training is critical, healthcare workers (HCWs) with high workload have limited chance to get trained and re-trained due to time and resource constraints. To address this gap, we engaged in a co-design process of robots that facilitate and prepare HCWs for resuscitation procedures (i.e., codes). First, we investigated what resuscitation training consists of, including challenges faced by trainees and trainers. Second, we collaboratively explored how a crash cart robot, that guides users to medical supplies and equipment, could assist trainers and trainees synchronously–during team-based clinical simulations and asynchronously–during one-on-one training. We found that robots could 1) serve as a learning assistant by providing real-time feedback and supporting personalized training needs; and 2) an evaluating assistant by monitoring multiple trainees and tracking critical timing of interventions in the training. Through this new training paradigm, we hope to demonstrate opportunities for crash cart robots to aid HCWs for their sustainable training and reskilling. We discuss the role of robots in training beyond cognitive knowledge, situating them within two underexplored contexts: practical skill training and team-based training.

International students in emerging adulthood face unique challenges as they navigate life transitions and adapt to new environments. These challenges significantly affect their mental well-being. While previous HRI studies have explored robotic solutions to address anxiety through therapeutic guidance, positive psychology, and mood recognition, little is known about design features tailored to the challenges of transition. By deploying co-design probes with 18 international students experiencing mild symptoms of anxiety and depression, we investigate their lived experiences and coping strategies and translate these insights into design implications for social robots. Our findings indicate that participants envisioned robots that create a welcoming living environment through seamless design and provide a sense of agency through achievable tasks. These features were seen as particularly helpful in relieving day-to-day tension in effortless ways. Based on these findings, we discuss how social robots can better support transitions in emerging adulthood.

Automation technologies are increasingly adopted in industrial workplaces, reshaping organizational structures and labor dynamics. Drawing on a community-based research study with production workers and union representatives from a large U.S. automotive manufacturing facility, this study shows that workers’ challenges with robots and the underlying causes of these challenges are closely tied to a historically developed division of labor. This division separates planning and decision-making, dominated by management and engineers, from execution, which is left to workers. These findings indicate that such challenges cannot be addressed through technological interventions alone but require sociopolitical approaches. We therefore propose integrating workers’ embodied knowledge into HRI research, alongside automation literacy education, as pathways to reconfigure existing labor relations.

HRI scholars envision a future of work where human-robot collaboration brings mutual gains: organizations benefit from increased efficiency and productivity, and laborers benefit when tasks are redistributed between humans and robots based on their respective strengths. Yet, ironically, this collaboration in real-world contexts can lead to the opposite effect-workers' efficiency may decrease due to the additional tasks they must undertake to manage unexpected errors caused by robots. This “stop-gap” labor, often viewed as temporary and naturally manageable over time, can have significant and persistent impacts on workers. Drawing from observations across multiple robot deployment sites, this paper highlights the overlooked burden of this labor, challenging idealized visions of seamless human-robot collaboration. We argue that attending to stop-gap labor presents an opportunity for the HRI community to make genuine improvements for workers as primary stakeholders within complex socio-economic networks.

Designing robots to support high-stakes teamwork in emergency settings presents unique challenges, including seamless integration into fast-paced environments, facilitating effective communication among team members, and adapting to rapidly changing situations. While teleoperated robots have been successfully used in high-stakes domains such as firefighting and space exploration, autonomous robots that aid high-stakes teamwork remain underexplored. To address this gap, we conducted a rapid prototyping process to develop a series of seemingly autonomous robots designed to assist clinical teams in the Emergency Room. We transformed a standard crash cart-which stores medical equipment and emergency supplies into a medical robotic crash cart (MCCR). The MCCR was evaluated through field deployments to assess its impact on team workload and usability, identified taxonomies of failure, and refined the MCCR in collaboration with healthcare professionals. Our work advances the understanding of robot design for high-stakes, time-sensitive settings, providing insights into useful MCCR capabilities and considerations for effective human-robot collaboration. By publicly disseminating our MCCR tutorial, we hope to encourage HRI researchers to explore the design of robots for high-stakes teamwork.

As families increasingly live apart due to reasons such as education, employment, or personal independence, they rely on computer-mediated communication (CMC) tools to stay connected. While tools like audio and video calls help bridge the distance, they often fall short in fostering social presence. This study explores how telepresence robots, with their physicality and mobility, may enhance social presence in remote family communication. We hypothesize that telepresence robots will increase perceived social presence compared to current CMC tools. To test this, we conducted a within-subjects study with eight families, deploying telepresence robots in their homes for two weeks. The results show that among the five factors encompassed by social presence—perceived presence, psychological closeness, seamless communication, and conversational involvement—four were significantly increased after using telepresence robots, while communication privacy showed no effect.

Healthcare workers (HCWs) encounter challenges in hospitals, such as retrieving medical supplies quickly from crash carts, which could potentially result in medical errors and delays in patient care. Robotic crash carts (RCCs) have shown promise in assisting healthcare teams during medical tasks through guided object searches and task reminders. Limited exploration has been done to determine what communication modalities are most effective and least disruptive to patient care in real-world settings. To address this gap, we conducted a between-subjects experiment comparing the RCC’s verbal and non-verbal communication of object search with a standard crash cart in resuscitation scenarios to understand the impact of robot communication on workload and attitudes toward using robots in the workplace. Our findings indicate that verbal communication significantly reduced mental demand and effort compared to visual cues and with a traditional crash cart. Although, frustration levels were slightly higher during collaborations with the robot compared to a traditional cart. These research insights provide valuable implications for human-robot teamwork in high-stakes environments.

Many emerging technologies are expected to reconfigure workplaces, and serious concerns have already been raised about their impact on workers, especially those who are already precarious. This study explores what roles designers can play to address power issues regarding workplace automation. Following Marxist researchers addressing the importance of analyzing “struggle” as an event that reveals power relations in workplaces, this study examines conflicting views between stakeholders regarding the value of newly adopted robots, and the value of the human labor that the robots could displace. In this study, workers—even those who perform the same tasks—have conflicting views regarding how their work can be automated: the collective voice of workers is not naturally formed. This observation can be seen as closely related to the weakened solidarity among workers not only in the US but internationally, due to the neoliberal restructuring of labor market and corporations. Considering the unique countervailing power of worker solidarity, this study proposes a new role for designers: facilitator of “inclusive collective imaginaries” by bridging workers’ divided opinions, addressing the importance of inclusive solidarity, and mobilizing them to successfully contribute to shaping automation technologies as a way to intervene in automation-related issues.

Healthcare workers (HCWs) face many challenges during bedside care that impede team collaboration and often lead to poor patient outcomes. Robots have the potential to support medical decision-making, help identify medical errors, and deliver supplies to clinical teams in a timely manner. However, there is a lack of knowledge about using robots to support clinical team dynamics despite being used in surgery, healthcare operations, and other applications. To address this gap, we engaged in a co-design process of robots that support clinical teamwork. We collaboratively explore how robots can support clinical teamwork with HCWs. This collaborative process includes understanding the challenges they face during bedside care and envisioning robots that can help mitigate these issues. Our study shows that robots can act as a shared mental model for clinical teams, help close communication gaps, and provide procedural steps to assist HCWs with limited in-hospital experience. This research highlights new ways HRI researchers can deploy robots in acute care settings, as well as define appropriate levels of autonomy to maintain human control in safety-critical settings.

Sleep has been studied as an individual activity, with the interconnected behaviors among family members being rarely considered. In this study, by incorporating the identified themes from the previous phase, we designed and tested two types of family-based sleep management systems: Bedtime Pal and Caring Heart. These systems redistributed sleep-relevant tasks among family members, so that they would have the chance to reflect on the difficulties and values involved in those tasks. We deployed the two prototypes and performed an in-the-wild study with 12 families in their homes. This study empirically revealed the importance of considering social dynamics as a design factor for family sleep management technologies. Design implications for sleep management technologies are discussed.

Informal caregivers are the main source of dementia care. Considering the importance of both family caregivers and persons living with dementia (PwDs), this paper explores how these two parties go through their dementia journey and how they envision robots to support them. We adopt a person-centered care approach which views these couples as reciprocal carepartners, rather than as care-givers and care-receivers. We conducted a community-based participatory research study with a dementia advocacy organization to imagine how robots can support these dementia dyads. The contribution of this paper is threefold: First, we introduce a person-centered care approach and show how this new approach reveals the issues of PwDs and carepartners (CPs) as partners and citizens. For example, PwDs' main challenges were not dementia symptoms but the concomitant stigma such as fears of being considered abnormal. This issue has rarely been discussed in HRI. Second, we suggest slow communication as an important robot design feature. When robots can wait for PwDs to proceed with information without judging PwDs' relatively slow response, PwDs feel respected and less stigmatized. Third, we address the importance of paying attention to disagreements between PwDs and CPs about robot design preferences. Considering the interdependency of the two parties, robot design processes should allow the two to negotiate.

Human-robot collaboration has been an important topic in the HRI communities. In this paper, we explore how robots can contribute to gas pipeline inspection work, and how they can support one of the most important elements of energy transportation infrastructure. To situate robots in the gas energy industry, we conducted a collaborative design study, where our co-designers were diverse stakeholders: from pipeline researchers to utility workers. The contribution of this paper is threefold: First, we explore gas pipeline work settings as a new context where robots can provide significant benefit, considering that public infrastructure is vast but understudied. Second, we collaboratively envisioned the design and use cases together with workers who are not often invited to human-robot collaboration research. Lastly, we address the importance of viewing humans in human-robot collaboration as “workers” whose roles and expertise are shaped within organizational dynamics. This study aims to shed light on the importance of a more nuanced understanding of work contexts and the positionality of robots within organizations.

Although the concept of wisdom is ancient, empirical research on it has only recently received attention in gerontology. This coincides with a critical turn away from a deficit model of aging, viewing aging as a series of losses, toward a more supportive and developmental model. This article draws on this recent work to consider how wisdom can be a critical lens for human-robot interaction (HRI) researchers and other technology design researchers to pay more attention to the coping strategies that older adults accumulated throughout their lives. We engaged in a 6-month collaborative design process with community-dwelling older adults. The contributions of this article are twofold. First, we found that wisdom as a design concept helps researchers to critically examine how they define knowledge. Wisdom as an accumulation of experiential knowledge of older adults helps researchers rethink the definition of knowledge—valuing computational and technological knowledge—in the field of HRI. Second, wisdom leads researchers to the past experiences of older adults. Although past experiences are as important as current experiences, they are not actively considered in robot design studies for older adults. We hope wisdom as a critical lens could allow researchers to integrate the invisible aspects of older adults’ aging experiences into the existing practices of designing robots for aging users.

Sleep is a vital health issue. Continued sleep deficiency can increase the chance of stroke, cardiovascular disease, obesity, and diabetes. Previous studies have investigated sleep as an individual activity performed within bedrooms at night. In this study with twenty parents of young children, we identify sleep as a complex experience entangled with social dynamics between family members. For example, children's sleep means not just time for children to rest, but time for self-care for parents. This paper's contributions are twofold. First, we show how the boundaries that define sleep in terms of time (at night), space (in bedrooms), and unit of analysis (individual-focused) limit designers' opportunities to tackle the deeper sleep issues of families. Second, we suggest "division of labor" as an important but rarely discussed design concept to enhance family sleep, and as a design theme for home technologies that address issues emerging from social dynamics between householders.

As more than half of the U.S. population is identified as a video gamer, a growing number of studies have investigated the health issues of gamers who spend prolonged times playing games. Potential health issues of gamers include eye fatigue, neck/back pain, wrist pain, mental stress and other issues. To alleviate potential health issues of gamers, this paper investigates how robots can help gamers better manage their health issues. We conducted three studies with gamers, including an informal interview, an online survey, and a co-design session. In the three studies with gamers, we found that gamers focused on the robot design factors-how robots get the gamers ’ attention, and how they force gamers to pause their play, while still seeming friendly. Our preliminary results indicate substantial promise regarding the role of robots in gamers ’ health management, which we will investigate in our future research.

Humans are an essential part of human-robot interaction (HRI), but what roles do they play in HRI research? Analysis of the role of human subjects in research can serve as an indicator of how the HRI community engages with society. In this paper, we examine humans' roles in the HRI studies published at the ACM HRI conference over the course of 16 years (between 2006–2021). We categorize the studies into three groups. The studies in the first group investigated human nature and studied humans as interchangeable subjects; the studies in the second group addressed humans as users of robots in certain contexts; the third group of studies approached humans as social actors who are closely connected to other actors and thereby generate social dynamics. The contributions of this paper are twofold: First, we reveal the patterns of how humans have been included in HRI studies. Specifically, we find that more than half of the studies limited the role of humans to interchangeable and generalizable actors. Second, we outline three opportunities for the HRI community that arise if human subjects are given more diversified roles in HRI research - opportunities for diversity, social justice, and reflexivity. On this basis, we call for a more socially -engaged research in HRI.

Family caregivers of patients with chronic conditions often subject themselves to drastic life changes. The quality of life of the caregivers often decreases noticeably at the beginning of the caregiving trajectory, because they typically reorient their lives to focus on the patient's health status. As a result, previous studies viewed caregivers primarily as people who need help and focused on how technologies can support them. However, in our study, we found that caregivers are also capable of developing their own experiential knowledge and strategies, which have been invisible in previous caregiver studies. By conducting in-home interviews with fourteen family caregivers, we present the types of new knowledge and coping strategies family caregivers have developed from their lived experiences during everyday caregiving tasks. These include 1) establishing new mindsets, 2) developing mindful activities, 3) building relationship management strategies, and 4) sharing experiences with people in their own networks. Based on our findings, we call for an asset-based approach that will help researchers notice the capabilities of caregivers. This approach could enable researchers to be more reflexive in the incorporation of caregivers' devalued knowledge within their system designs.

The Social Robots in Therapy workshop series aims at advancing research topics related to the use of robots in the contexts of Social Care and Robot-Assisted Therapy (RAT). Robots in social care and therapy have been a long time promise in HRI as they have the opportunity to improve patients life significantly. Multiple challenges have to be addressed for this, such as building platforms that work in proximity with patients, therapists and health-care professionals; understanding user needs; developing adaptive and autonomous robot interactions; and addressing ethical questions regarding the use of robots with a vulnerable population. The full-day workshop follows last year's edition which centered on how social robots can improve health-care interventions, how increasing the degree of autonomy of the robots might affect therapies, and how to overcome the ethical challenges inherent to the use of robot assisted technologies. This 2ndedition of the workshop will be focused on the importance of equipping social robots with socio-emotional intelligence and the ability to perform meaningful and personalized interactions. This workshop aims to bring together researchers and industry experts in the fields of Human-Robot Interaction, Machine Learning and Robots in Health and Social Care. It will be an opportunity for all to share and discuss ideas, strategies and findings to guide the design and development of robot-assisted systems for therapy and social care implementations that can provide personalize, natural, engaging and autonomous interactions with patients (and health-care providers).

Robots are being increasingly developed as social actors, entering public and personal spaces such as airports, shopping malls, care centres, and even homes, and using human or animal-like social techniques to work with people. Some even aim to engineer social situations, or are designed specifically for an emotional response (e.g., comforting a person). However, if we consider these robots as social interventions, then it is important to recognize that the robots design - its behavior, its application, its appearance, even its marketing image - will have an impact on the society and in the spaces it enters. While in some cases this may be a positive effect, social robots can also contribute negatively, e.g., reinforcing gender stereotypes or promoting ageist views. This full-day workshop aims to offer a forum for Human-Robot Interaction (HRI) researchers to explore this issue, and to work toward potential opportunities for the field. Ultimately, we want to promote robots for social good that can contribute to positive social changes for socio-political issues (e.g., ageism, feminism, homelessness, environmental issues). The political aspects of technologies have long been scrutinized in related areas such as Science and Technology Studies (STS) and Human-Computer Interaction (HCI). In particular, critical design explicitly targets the design of technologies that can contribute to our understanding of how technology can impact society. This workshop aims to strengthen this discussion in the HRI community, with the goal of working toward initial recommendations for how HRI designers can include elements of critical design in their work.

Many new technologies are being built to support people with dementia. However, they largely focus on the people with dementia; consequently, informal caregivers, one of the most important stakeholders in dementia care, remain invisible within the technology design space. In this paper, we present a six-month long, community-based design research process where we collaborated with dementia caregiver support groups to design robots for dementia caregiving. The contributions of this paper are threefold. First, we broaden the context of dementia robot design to give a more prominent role to informal family care-givers in the co-design process. Second, we provide new design guidelines that contextualize robots within the family caregiving paradigm, which suggest new roles and behaviors of robots. These include lessening emotional labor by communicating information caregivees do not want to hear (e.g., regarding diet or medication) or providing redirection during emotionally difficult times, as well as facilitating positive shared moments. Third, our work found connections between certain robot attributes and their relationship to the stage of dementia a caregivee is experiencing. For example, caregivers wanted their robots to facilitate interaction with their caregivees in early stages of dementia, yet be in the background. However, for later stages of dementia, they wanted robots to replace caregiver-caregivee interaction to lessen their emotional burden, and be foregrounded. These connections provide important insights in to how we think about adaptability and long-term interaction in HRI. We hope our work provides new avenues for HRI researchers to studying robots for dementia caregivers by engaging in community-based design.

Patient safety errors account for over 400,000 preventable deaths annually in US in hospitals alone, 70% of which are caused by team communication breakdowns, stemming from hierarchical structures and asymmetrical power dynamics between physicians, nurses, patients, and others. Nurses are uniquely positioned to identify and prevent these errors, but they are often penalized for speaking up, particularly when physicians are responsible. Nevertheless, empowering nurses and building strong interdisciplinary teams can lead to improved patient safety and outcomes. Thus, our group has been developing a series of intelligent systems that support teaming in safety critical settings, Robot-Centric Team Support System (RoboTSS), and recently developed a group detection and tracking system for collaborative robots. In this paper, we explore how RoboTSS can be used to empower nurses in interprofessional team settings, through a three month long, collaborative design process with nurses across five US-based hospitals. The main findings and contributions of this paper are as follows. First, we found that participants envisioned using a robotic crash cart to guide resuscitation procedures to improve efficiency and reduce errors. Second, nurses discussed how RoboTSS can generate choreography for efficient spatial reconfigurations in co-located clinical teams, which is particularly important in time-sensitive situations such as resuscitation. Third, we found that nurses want to use RoboTSS to "stop the line," and disrupt power dynamics by policing unsafe physician behavior, such as avoiding safety protocols using a robotic crash cart. Fourth, nurses envisioned using our system to support real-time error identification, such as breaking the sterile field, and then communicating those errors to physicians, to relieve them of responsibility. Finally, based on our findings, we propose robot design implications that capture how nurses envision utilizing RoboTSS. We hope this work promotes further exploration in how to design technology to challenge authority in asymmetrical power relationships, particularly in healthcare, as strong teams save lives.

We are living in an exciting time, as people are living longer, more active lives. This is reshaping how we think about aging. Rather than viewing aging as a problem to be fixed (i.e., a deficit model of aging), many aging researchers are viewing aging as a developmental stage of life to be celebrated and supported, that is, “successful aging.” In this article, we embrace this approach and consider it in the context of assistive robot design in an aim to steer the conversation away from deficit models that have limited robot design possibilities. To explore an alternative design approach to the study of aging in human-robot interaction (HRI), we invited five aging researchers (three geriatricians, one gerontologist, and one epidemiologist) and nine older adults to participate in our research. In the study, participants illustrated their interpretations of aging and suggested potential assistive robots. We found that while all participants perceived the importance of potential disabilities due to aging, they considered potential disabilities as only one aspect of the experience of aging. They highlighted other key themes to consider in designing robots to support successful aging, such as older adults’ autonomy and resilience. We discuss these findings for the HRI community and call for “robots for successful aging.”

HCI researchers investigating the politics of technology design have recently focused on how design practice can tackle "Matters of Concern" - complex social issues perceived and experienced in multiple ways. These researchers suggest design research can generate new networks of human and non-human actors to express and act on these issues. Prior studies, however, tend to restrict their networks within traditional boundaries (e.g. existing organizations, local communities) and categories (e.g. human/nonhuman binary) without examining their significance for participants. We suggest collaborative map making as a reflexive method for understanding current Matters of Concern from the perspectives of diverse actors, not just researchers. As case studies of the method's use, we present two studies of domestic computing technologies in the US and South Korea, which show how collaborative map making allows salient networks to expand beyond the individual actors in the home to local and global power issues outside of boundaries (e.g. physical house) and categories (e.g. private/public space) commonly recognized in HCI. Our methodology provides HCI researchers with a way to understand existing Matters of Concern, so they can position themselves to address and act on these issues.

This paper presents the results of research aimed at developing a methodology for the participatory design of social robots, which are meant to be incorporated into various social contexts (e.g. home, work) and establish social relations with people. In contrast to the dominant technologically driven robot development process, we aim to develop a socially robust and responsible approach to robot design using Participatory Design (PD) methods. The PD process builds on participants' self-identified issues and concerns, and develops robot concepts according to participants' interpretations of the capabilities and potential applications of robotic technologies. We present methodological insights from an ongoing PD project aimed at designing socially assistive robots with older adults diagnosed with depression and their therapists, and identify remaining challenges in this project. We particularly focus on supporting mutual learning between researchers and participants and on promoting active participation of older adults as "designers" (rather than consumers) as foundational aspects of PD. We conclude with reflections regarding how this work can contribute to the further development of social robots and relevant PD methodologies.

Assistive robots designed to support independently living older adults are expected to solve diverse physical, social and mental challenges related to aging. This paper presents how older adults-the potential users of assistive robots-interpret robotic technologies in terms of their usefulness and fit in their everyday lives. We interviewed 7 older adults aged 57-72, showing them photos and videos of assistive robots designed with their age group in mind. Most participants saw the robots as potentially useful in general terms, yet also commented that “those robots are not for me.” An analysis of their discussion about the robots identified several aspects of robot design that participants found problematic, particularly negative representations of aging depicted in robot use scenarios. Participants saw issues related to aging as important daily problems, but did not appreciate the manner in which robotics was expected to address those issues. They were particularly sensitive to the dominance of stereotypes defining aging primarily in terms of disability in robotics discourse and design. Based on participant feedback, we suggest a broader understanding of the experience of aging as the basis for future assistive robot design for this population, and conclude by discussing related robot design possibilities.

In recent years, HCI researchers have increased their focus on studying the power relationships between researchers and users, and developing methodologies for eliciting design ideas that are sensitive to existing epistemic hierarchies in technology design. The differential value given to expert versus lay knowledge is a central factor in these debates. We apply Artifact Analysis, developed to help designers handle the complexity of digital artifacts, as a method to explore how experts and non-experts understand and frame robots, a technology characterized by significant complexity. Our results show that both non-expert users and expert researchers have knowledge that is significant to future robot development, but they focus on different aspects of the technology - users address mediated and interaction complexity while researchers focus on internal and external complexity. We also found that robots function as boundary objects between experts and users, and suggest that one task designers can perform is to "stay on the boundary" and mediate between the different ways in which experts and non-experts frame emerging technology to develop designs that benefit from insights from both user and researcher perspectives.

Based on the results of an online survey conducted with participants in South Korea (N=73), Turkey (N=46), and the United States (N=99), we show that people's perceptions and preferences regarding acceptable designs and uses for robots are culturally variable on a number of dimensions, including general attitudes towards robots, preferences for robot form, interactivity, intelligence, and sociality. We also explore correlations between these design and use characteristics and factors cited as having an effect on user perceptions and acceptance of robots, such as religious beliefs and media exposure. Our research suggests that culturally variable attitudes and preferences toward robots are not simply reducible to these factors, rather they relate to more specific social dynamics and norms. In conclusion, we discuss potential design and research implications of culturally variable and universally accepted user preferences regarding robots.

Following Bell and Dourish's call for a "ubicomp of the present," we visited 14 households in Korea, where Weiser's dreams come true, to study their social dynamics and domestic technologies as a part of these dynamics. We used a participatory research approach in which participants, acting as collaborative ethnographers and co-designers, chose how to describe their homes to us and which existing technologies to discuss. A qualitative analysis of the conversations identified two main themes. The first finding is the highly gendered nature of roles in the Korean home, influenced by traditional Confucian values and reinforced by contemporary neo-liberal norms. The second finding is that domestic technologies are used, adopted, and imagined in the context of these gendered social dynamics rather than just according to functional needs. In conclusion, we emphasize the need to attend to the social dynamics of the home in the design of politically sensitive domestic technologies, which will enable the inclusion of marginalized voices, such as women, in design.

As HCI researchers have designed tools to promote wellness, disease has often been approached as a general problem. In contrast, public health research argues for an activist approach focused on how certain groups disproportionately experience disease and eliminating these disparities. Taking this activist stance, we examine how technology can reduce health inequalities by disrupting power relationships and helping communities pursue social change. We discuss our tool, Community Mosaic (CM), which allows individuals to share their healthy eating ideas with one another as a means of advocating behavior change. Our results characterize how CM helped facilitate activism (i.e., collective efforts to counter local challenges to healthy living) and shift users' attitudes regarding their role as advocates for health. We contribute to the field of HCI by using our findings to present a set of recommendations for future research focused on designing and evaluating health promotion tools using an activist lens.

In this paper, we describe the results of a comparative analysis of user-created designs for future domestic robots made by participants in Korea and the US. We identify their culturally variable expectations and preferences. We use a generative design methodology, which includes users visualizing their designs followed by semi-structured interviews. We describe our results in four areas of design: the look and feel of the robot, interaction mode, social role, and desired task. We identify variable cultural models relating to robotic technology and the cultural meaning of the domestic context as central factors. Finally, we discuss the design implications of our findings to culturally situated robot design.