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.

We use the "social shaping of technology and society" framework to qualitatively analyze data collected through observation of human-robot interaction (HRI) between social actors in a nursing home (staff, residents, visitors) and the socially assistive robot PARO. The study took place over the course of three months, during which PARO was placed in a publicly accessibly space where participants could interact with it freely. Social shaping focuses attention on social factors that affect the use and interpretation of technology in particular contexts. We therefore aimed to understand how different social actors make sense of and use PARO in daily interaction. Our results show participant gender, social mediation, and individual sense making led to differential use and interpretation of the robot, which affected the success of human-robot interactions. We also found that exposure to others interacting with PARO affected the nursing staff's perceptions of robots and their potential usefulness in eldercare. This shows that social shaping theory provides a valuable perspective for understanding the implementation of robots in long-term HRI and can inform interaction design in this domain.

To explore the development and maintenance of human-robot interaction (HRI) in a real-world setting, we conducted a three-month long field study with the socially assistive robot PARO in a nursing home. We placed PARO a public area in the institution and observed naturally occurring interactions of nursing home residents, staff, and visitors with the robot. We collected both quantitative (on-site behavioral coding and interactor counts) and qualitative (observational field notes) data. The results of behavioral analysis complemented with information from our field notes show that interaction with PARO was often not spontaneous and that mediation from staff and family members was integral to successful interactions between residents and PARO. We also observed that individual interactors engaged with the robot in diverse ways based on their needs. We conclude by discussing design and methodological implications for in situ HRI studies.

This paper contributes to the study of interaction between groups of people and groups of robots by examining the effect of group size on people's attitudes and behaviors toward robots as interaction partners. Our work is motivated by psychological research on human intergroup dynamics, particularly the interindividual-intergroup discontinuity effect, which suggest that interactions among groups are more competitive than interactions among individuals. To test the discontinuity effect in the context of human-robot interaction, we conducted a between-subjects experiment with four conditions, derived by differentiating the ratio of humans to robots in the interaction (one or two humans interacting with one or two robots). Participants played a game with robots in which they were given a chance to exhibit competitive and cooperative behaviors, which we tracked. We also measured changes in participants' attitudes toward robots following gameplay. Our results show that people playing in groups behave more competitively towards the robots than individual human players. However, participants' attitudes toward robots did not change after the short-term interaction.