arXiv subjects

Wijnand IJsselsteijn

Publications and source records attributed to Wijnand IJsselsteijn.

5 recordsLinked to original sources

arXiv2026

Caring Over Computing: An Ethical and Sociotechnical Perspective on Generative AI for Social Connectedness in Dementia Care

People with dementia in residential care often experience reduced social connectedness. Person-centered care approaches foreground meaningful social interactions to support well-being, but staff and time pressures increasingly constrain opportunities for such care. Generative AI (GenAI) technologies offer possibilities for helping care professionals facilitate social connectedness, despite increasing care pressures. Yet, the meaningful integration of such technologies into the complex sociotechnical setting of residential dementia care is not straightforward. To responsibly design GenAI technologies for dementia care, we need to investigate how care professionals recognize and foster social connectedness and how technologies intersect with those approaches in care contexts. We conducted five workshops with 15 care professionals from three care organizations to pursue this objective. Our findings show that fostering social connectedness involves ongoing interpretation, negotiation, and adaptation to residents' individual needs. Technology was used by care professionals to support communication, interaction, and shared activities, yet remained largely peripheral to everyday care routines and required active mediation for use in practice. Drawing on an ethics of care framework, we derive ethical and sociotechnical implications for the responsible design and positioning of GenAI in residential dementia care.

cs.HC↗

arXiv2026

Navigating Transitions: Envisioning Conversational User Interfaces to Support International Students

International students face struggles when adapting to the host country. They are more susceptible to mental health problems than domestic students. While Conversational User Interfaces (CUIs) are increasingly researched and implemented, research on how they may help international university students is still scarce. Thus, we conducted participatory design workshops with international students who shared their perspectives and struggles of studying abroad, in which they also envisioned CUIs as aids to support their transitions. Participants proposed features of a CUI to address uncertainty, loneliness, and misunderstandings of cultural differences. Our paper reveals international students' needs and provides design implications for CUIs to support their well-being.

cs.HC↗

arXiv2026

Social Robots for People Living with Dementia: A Scoping Review on Deception from Design to Perception

As social robots are increasingly introduced into dementia care, their embodied and interactive design may blur the boundary between artificial and lifelike entities, raising ethical concerns about robotic deception. However, it remains unclear which specific design cues of social robots might lead to social robotic deception (SRD) in people living with dementia (PLwD), and which perceptions and responses of PLwD might indicate that SRD is taking place. To address these questions, we conducted a scoping review of 26 empirical studies reporting PLwD interacting with social robots. We identified three key design cue categories that might contribute to SRD and one that might break the illusion. However, the available literature does not provide sufficient evidence to determine which specific design cues lead to SRD. Thematic analysis of user responses reveals six recurring patterns in how PLwD perceive and respond to social robots. However, conceptual limitations in existing definitions of robotic deception make it difficult to identify when and to what extent deception actually occurs. Building on the results, we propose a dual-process interpretation that clarifies the cognitive basis of false beliefs in human-robot interaction and distinguishes SRD from anthropomorphism or emotional engagement.

cs.HC↗

arXiv2026

An Intent of Collaboration: On Agencies between Designers and Emerging (Intelligent) Technologies

Amidst the emergence of powerful intelligent technologies such as LLMs and text-to-image AIs that promise to enhance creative processes, designers face the challenges of remaining empowered and creative while working with these foreign digital partners. While generative AIs offer versatile, informative, and occasionally poetic outcomes, their lack of embodied knowledge presents an even greater challenge to designers in gaining fruitful outcomes, such as in the field of Digital Craftsmanship. In this project, three designers embarked on a three-month experimental journey with an intention to co-create with Google's LLM as a potential intelligent partner to investigate how it will influence the designers' creativity. We found that a power dynamic of agencies exists between the LLM and the designer, in which the designer can easily lose their creative agency. Regaining the designer's creative agency involves introspection into their own creative process, a structural understanding of the specific emerging technology involved, and deliberate adjustments to the dynamics of the human-technology relationship. We propose paying attention to the designer's inner world and parties of agencies when engaging with emerging intelligent technologies through three aspects: the sensitivity towards a creative process as cognitive activities; the active investigation into specific technology's capability; and the adjustment towards an appropriate working relationship between the designer and the emerging technology.

cs.HC↗

arXiv2026

A Bayesian Framework for Active Tactile Object Recognition, Pose Estimation and Shape Transfer Learning

As humans can explore and understand the world through active touch, similar capability is desired for robots. In this paper, we address the problem of active tactile object recognition, pose estimation and shape transfer learning, where a customized particle filter (PF) and Gaussian process implicit surface (GPIS) is combined in a unified Bayesian framework. Upon new tactile input, the customized PF updates the joint distribution of the object class and object pose while tracking the novelty of the object. Once a novel object is identified, its shape will be reconstructed using GPIS. By grounding the prior of the GPIS with the maximum-a-posteriori (MAP) estimation from the PF, the knowledge about known shapes can be transferred to learn novel shapes. An exploration procedure based on global shape estimation is proposed to guide active data acquisition and terminate the exploration upon sufficient information. Through experiments in simulation, the proposed framework demonstrated its effectiveness and efficiency in estimating object class and pose for known objects and learning novel shapes. Furthermore, it can recognize previously learned shapes reliably.

cs.RO↗