As Pakistan’s population ages and traditional care structures evolve, there is increasing interest in technological solutions for supporting older adults at home. This study investigates the potential of social assistive robots (SARs) in Pakistani homes, focusing on cultural values, inter-generational living, and limited access to such technologies. In a 3-day mixed-methods home study, 14 older adults interacted with a SAR communicating in Urdu. Through observations, interviews, and questionnaires, we evaluated the robot’s acceptability, engagement, and cultural compatibility. The results highlighted the need for culturally sensitive design, emphasising the role of robots as companions rather than replacements for human care, and the importance of robot’s ability to communicate in Urdu. We discuss how SARs could be designed to reflect the characteristics of Pakistani households, including faith, family values, everyday routines, and environmental factors. Our design considerations can benefit research on deploying SARs to support older adults in Pakistan and similar cultures.

As robots are increasingly becoming part of daily life worldwide, it is important to ensure that they are inclusive and culturally sensitive to accommodate users from different backgrounds. In particular, many countries in the Global South (GS) have yet to explore the integration and benefits of robots, especially for underrepresented language groups such as Urdu. We present an exploratory mixed-methods study that investigates how robots' language affects the social interaction, acceptability and overall perception of robots within Pakistani Urdu-speaking individuals. The findings highlight the importance of language and cultural adaptation, and how these factors influence the acceptance of robots, emphasising the need for more inclusive and religion sensitive technologies designed for the GS users.

In this paper, we explore how humans communicate with teammates from an explainable-AI perspective, comparing how they interact with both human and AI-controlled robot teammates under a number of different strategies in scenarios such as disaster relief. We find that while humans do adapt their communication based on which strategy they are following, they consistently communicate differently with AI teammates than human teammates, tending to give explicit orders to the former while sending more vague messages with implicit understanding to the later. However, we also find that modern Large Language Models (LLMs) are capable of understanding the explainability intent of messages to the same level as humans, implying that such differences may not be required if LLMs are fully integrated into AI agents.

Abstract Pregnant women in the Global South face significant challenges due to lack of resources and informational gaps. In this paper, we take an assets-based lens to examine the experiences of pregnant women in a low-resource setting in Ghana, focusing on the role of information and technology in prenatal care. Through interviews and co-design workshops, we sought to understand the perspectives of multiple stakeholders including pregnant women, their family members, and healthcare professionals. We highlight the complexities involved in making decisions during pregnancy, including the challenges arising from the tensions between traditional healthcare practices and modern Western health services. We discuss opportunities in digital maternal health where we argue for the importance of attending to local needs and values and advocate for recognising community strengths and integrating rural care practices as valuable assets in prenatal intervention design. Our work aims to bridge some of the gaps between the theoretical understanding of digital health and the practical realities of prenatal care in low-resource settings.

The global aging population is growing, leading to an increased need for unpaid carers to support older adults. Socially Assistive Robots (SARs) can play an important role in supporting unpaid carers. However, as with any socio-technical system, building and maintaining trust is critical for achieving full potential and adoption of a SAR. Despite the growing interest in robotics across various domains, there has been limited research on time-dependant patterns of trust during Human Robot Interactions (HRI) and how unpaid carers perceive SARs as a support tool for care. We present a study in which we a) investigate the level of trust that unpaid carers have in using SARs for taking care of older adults, b) qualitatively explore the factors that influence trust considering the dynamic and context dependant nature of care. To explore SARs as a support tool from the perspective of unpaid carers we recruited 15 caregivers, we conducted co-design sessions, interviews and carers interacted with a Pepper robot evaluating trust before and after interaction. We discuss how the level of trust of unpaid carers in SARs increases after interaction and how unpaid carers trust in SARs is impacted by socially and culturally intelligent robots. Our work contributes to identify factors influencing trust that are important for carer’s while interacting with SARs, offering insights for the development and implementation of future SAR-based as a support tool that can assist them in taking care of older adults.

Mobile devices, including activity trackers and smartwatches, can help older adults monitor health parameters passively and unobtrusively. Most user interactions with small devices consist of brief glances at the time or notifications. Consuming information from small displays poses challenges, which have been seldom studied from the perspective of older users. In this paper, we worked with older adults towards creating health data visualizations for them for small devices. We conducted a mixed-methods study with 30 older adults, in which we (1) conducted group discussions to understand participants’ opinions, (2) measured times taken to interpret health data visualizations with and without progress information, (3) measured how much information they could manage to see during brief glances. When data was visualized without progress indicators, participants took less time to understand the data and made fewer errors. Participants preferred health data visualizations that featured peaceful, and positive pictorial representations. We present design opportunities for older adults’ data visualizations in small devices.

The Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced in/about LATAM; a set of driving forces and tensions with a heavy reliance on diasporic dynamics; and a set of professional demands and associated structural limitations. We also offer a roadmap towards building connections across HCI communities, in an attempt to rebuild HCI as a pluriverse.

Predictions of people's behaviour increasingly drive interactions with a new generation of IoT services designed to support everyday life in the home, from shopping to heating. Based on the premise that such automation is difficult due to the contingent nature of people's practices, in this work we explore the nature of these contingencies in depth. We have designed and conducted a technology probe that made use of simple linear predictions as a provocation, and invited people to track the life of their household essentials over a two-month period. Through a mixed-method approach we demonstrate the challenges of simple predictions, and in turn identify eight categories of contingencies that influenced prediction accuracy. We discuss strategies for how designers of future predictive IoT systems may take the contingencies into account by removing, hiding, revealing, managing, or exploiting the system uncertainty at the core of the issue.

This paper examines ‘the routine shop’ as part of a project that is exploring automation and autonomy in the Internet of Things. In particular we explicate the ‘work’ involved in anticipating need using an ethnomethodological analysis that makes visible the mundane, ‘seen but unnoticed’ methodologies that household members accountably employ to organise list construction and accomplish calculation on the shop floor. We discuss and reflect on the challenges members’ methodologies pose for proactive systems that seek to support domestic grocery shopping, including the challenges of sensing, learning and predicting, and gearing autonomous agents into social practice within the home.

Informal caregivers take care of someone (usually a close family member) who suffers from a chronic illness. In this stressful situation, caregivers have a high risk of depression or loneliness, because their social network is weakened. Most existing proposals focus on helping caregivers fulfill caregiving tasks, instead of providing support for their mental wellbeing (e.g. identifying early stages of social isolation). We present a prototype ambient interface, called EmoTree, that makes communication frequency tangible by using a metaphor of a tree, and investigate user perception and motivation of use. People found Emotree to be interesting and enjoyable (78%), and useful (54%) unless the user does not suffer some type of problem (69%). Our preliminary results show the interface is easy to use and has an adequate representation of communication frequency. Our next step will make a second assessment with informal caregivers in their real context.

Mother caregivers of children with cancer are often unaware of how the tasks of caregiving interfere in their social relationships and lifestyle. This article explores how persuasive mobile technologies may promote the self-reflection and introspection of communication practices, emotions, and lifestyle. The article describes the design of EmotionMingle, a mobile system running in a situated display showing an ambient visualization using the metaphor of a tree to represent the status of an individual’s social network that, used in tandem with downloaded Facebook photographs, may help caregivers avoid social isolation. EmotionMingle also informs caregivers of how their emotions correlate with their communication practices and lifestyle. The results of a qualitative evaluation of the EmotionMingle prototype reveal that mother caregivers perceived it as useful and its visualizations as appropriate. The findings from this study reveal emergent practices of using mobile persuasive applications for self-reflection to discover wellness trends, possibly inducing behavior change.