How did COVID-19 pandemic affect the older adults' needs for robot technologies in Japan?: comparison of participatory design workshops during versus after the COVID-19 pandemic.

Social technology can improve the quality of social lives of older adults (OAs) and mitigate negative mental and physical health outcomes. When people engage with technology, they can do so to stimulate social interaction (stimulation hypothesis) or disengage from their real world (disengagement hypothesis), according to Nowland et al.'s model of the relationship between social Internet use and loneliness. External events, such as large periods of social isolation like during the COVID-19 pandemic, can also affect whether people use technology in line with the stimulation or disengagement hypothesis. We examined how the COVID-19 pandemic affected the social challenges OAs faced and their expectations for robot technology to solve their challenges. We conducted two participatory design (PD) workshops with OAs during and after the COVID-19 pandemic. During the pandemic, OAs' primary concern was distanced communication with family members, with a prevalent desire to assist them through technology. They also wanted to share experiences socially, as such OA's attitude toward technology could be explained mostly by the stimulation hypothesis. However, after COVID-19 the pandemic, their focus shifted towards their own wellbeing. Social isolation and loneliness were already significant issues for OAs, and these were exacerbated by the COVID-19 pandemic. Therefore, such OAs' attitudes toward technology after the pandemic could be explained mostly by the disengagement hypothesis. This clearly reflect the OA's current situation that they have been getting further digitally excluded due to rapid technological development during the pandemic. Both during and after the pandemic, OAs found it important to have technologies that were easy to use, which would reduce their digital exclusion. After the pandemic, we found this especially in relation to newly developed technologies meant to help people keep at a distance. To effectively integrate these technologies and avoid excluding large parts of the population, society must address the social challenges faced by OAs.

"If you weren't connected to the Internet, you were not alive": experience of using social technology during COVID-19 in adults 50.

Introduction: Loneliness and social isolation reduce physical and mental wellbeing. Older adults are particularly prone to social isolation due to decreased connection with previous social networks such as at workplaces. Social technology can decrease loneliness and improve wellbeing. The COVID-19 pandemic prompted quarantine and social distancing for many people, creating a context of widespread social isolation. Method: In the current study, we interviewed middle-aged and older adults' (n = 20) about their use of social technology when social isolation was common: during the early part of the pandemic while social isolation and masking were still required in the United States, between August 2020 and June 2021.We analyzed the data using three-phase coding. We compare our results against the model of the bidirectional and dynamic relationship between social internet use and loneliness. Results: We found that during the COVID-19 pandemic, our participants experienced decreased social interaction and moved toward online interaction. Participant use of social technology supported the stimulation hypothesis - that is, they used it to maintain existing relationships and social connection. The findings also add novel evidence that the stimulation hypothesis endures for older adults during enforced isolation (in this case due to the COVID- 19 pandemic). Discussion: Based on our data, we also propose adding the presence or realism of connection via social technology as a main factor to the model and engaging with construal level theory of social presence to fill in critical variables of this relationship. We further find that digital exclusion acts as a barrier to obtaining benefits from stimulation via social technology and recommend that further research examined digital exclusion in relation to the bidirectional and dynamic model. Finally, we discuss recommendations for improving social technology to benefit middle-aged and older adults.

Group trust dynamics during a risky driving experience in a Tesla Model X.

The growing concern about the risk and safety of autonomous vehicles (AVs) has made it vital to understand driver trust and behavior when operating AVs. While research has uncovered human factors and design issues based on individual driver performance, there remains a lack of insight into how trust in automation evolves in groups of people who face risk and uncertainty while traveling in AVs. To this end, we conducted a naturalistic experiment with groups of participants who were encouraged to engage in conversation while riding a Tesla Model X on campus roads. Our methodology was uniquely suited to uncover these issues through naturalistic interaction by groups in the face of a risky driving context. Conversations were analyzed, revealing several themes pertaining to trust in automation: (1) collective risk perception, (2) experimenting with automation, (3) group sense-making, (4) human-automation interaction issues, and (5) benefits of automation. Our findings highlight the untested and experimental nature of AVs and confirm serious concerns about the safety and readiness of this technology for on-road use. The process of determining appropriate trust and reliance in AVs will therefore be essential for drivers and passengers to ensure the safe use of this experimental and continuously changing technology. Revealing insights into social group-vehicle interaction, our results speak to the potential dangers and ethical challenges with AVs as well as provide theoretical insights on group trust processes with advanced technology.

Socially facilitative robots for older adults to alleviate social isolation: A participatory design workshop approach in the US and Japan.

Social technology can improve the quality of older adults' social lives and mitigate negative mental and physical health outcomes associated with loneliness, but it should be designed collaboratively with this population. In this paper, we used participatory design (PD) methods to investigate how robots might be used as social facilitators for middle-aged and older adults (age 50+) in both the US and Japan. We conducted PD workshops in the US and Japan because both countries are concerned about the social isolation of these older adults due to their rapidly aging populations. We developed a novel approach to participatory design of future technologies that spends 2/3 of the PD session asking participants about their own life experiences as a foundation. This grounds the conversation in reality, creates rapport among the participants, and engages them in creative critical thinking. Then, we build upon this foundation, pose an abstract topic, and ask participants to brainstorm on the topic based on their previous discussion. In both countries, participants were eager to actively discuss design ideas for socially facilitative robots and imagine how they might improve their social lives. US participants suggested design ideas for telepresence robots, social distancing robots, and social skills artificial intelligence programs, while Japanese participants suggested ideas for pet robots, robots for sharing experiences, and easy-to-operate instructor robots. Comparing these two countries, we found that US participants saw robots as tools to help facilitate their social connections, while Japanese participants envisioned robots to function as surrogate companions for their parents and distract them from loneliness when they were unavailable. With this paper, we contribute to the literature in two main ways, presenting: (1) A novel approach to participatory design of future technologies that grounds participants in their everyday experience, and (2) Results of the study indicating how middle-aged and older adults from the US and Japan wanted technologies to improve their social lives. Although we conducted the workshops during the COVID-19 pandemic, many findings generalized to other situations related to social isolation, such as older adults living alone.

Together We can Figure It out: Groups Find Hospitality Robots Easier to Use and Interact With Them More than Individuals.

As robots are becoming more prevalent and entering hospitality settings, understanding how different configurations of individuals and groups interact with them becomes increasingly important for catering to various people. This is especially important because group dynamics can affect people's perceptions of situations and behavior in them. We present research examining how individuals and groups interact with and accept a humanoid robot greeter at a real-world café (Study 1) and in an online study (Study 2). In each study, we separately examine interactions of individuals, groups that participants formed after they arrived at the café (new-formed groups), and groups that participants arrived with at the café (pre-formed groups). Results support prior findings that groups are more likely to interact with a public robot than individuals (Study 1). We also report novel findings that new-formed groups interacted more with the robot than pre-formed groups (Study 1). We link this with groups perceiving the robot as more positive and easier to use (Study 2). Future research should examine perceptions of the robot immediately after interaction and in different hospitality contexts.

Lessons Learned About Designing and Conducting Studies From HRI Experts.

The field of human-robot interaction (HRI) research is multidisciplinary and requires researchers to understand diverse fields including computer science, engineering, informatics, philosophy, psychology, and more disciplines. However, it is hard to be an expert in everything. To help HRI researchers develop methodological skills, especially in areas that are relatively new to them, we conducted a virtual workshop, Workshop Your Study Design (WYSD), at the 2021 International Conference on HRI. In this workshop, we grouped participants with mentors, who are experts in areas like real-world studies, empirical lab studies, questionnaire design, interview, participatory design, and statistics. During and after the workshop, participants discussed their proposed study methods, obtained feedback, and improved their work accordingly. In this paper, we present 1) Workshop attendees' feedback about the workshop and 2) Lessons that the participants learned during their discussions with mentors. Participants' responses about the workshop were positive, and future scholars who wish to run such a workshop can consider implementing their suggestions. The main contribution of this paper is the lessons learned section, where the workshop participants contributed to forming this section based on what participants discovered during the workshop. We organize lessons learned into themes of 1) Improving study design for HRI, 2) How to work with participants - especially children -, 3) Making the most of the study and robot's limitations, and 4) How to collaborate well across fields as they were the areas of the papers submitted to the workshop. These themes include practical tips and guidelines to assist researchers to learn about fields of HRI research with which they have limited experience. We include specific examples, and researchers can adapt the tips and guidelines to their own areas to avoid some common mistakes and pitfalls in their research.

Our Robots, Our Team: Robot Anthropomorphism Moderates Group Effects in Human-Robot Teams.

Past research indicates that people favor, and behave more morally toward, human ingroup than outgroup members. People showed a similar pattern for responses toward robots. However, participants favored ingroup humans more than ingroup robots. In this study, I examine if robot anthropomorphism can decrease differences between humans and robots on ingroup favoritism. This paper presents a 2 × 2 × 2 mixed-design experimental study with participants (N = 81) competing on teams of humans and robots. I examined how people morally behaved toward and perceived players depending on players' Group Membership (ingroup, outgroup), Agent Type (human, robot), and Robot Anthropomorphism (anthropomorphic, mechanomorphic). Results replicated prior findings that participants favored the ingroup over the outgroup and humans over robots-to the extent that they favored ingroup robots over outgroup humans. This paper also includes novel results indicating that patterns of responses toward humans were more closely mirrored by anthropomorphic than mechanomorphic robots.

Positive Emotions, More Than Anxiety or Other Negative Emotions, Predict Willingness to Interact With Robots.

Like early work on human intergroup interaction, previous research on people's willingness to interact with robots has focused mainly on effects of anxiety. However, existing findings suggest that other negative emotions as well as some positive emotions also have effects. This article systematically examines the roles of positive and negative emotions in predicting willingness to interact with robots, using an integrative analysis of data across five studies that use diverse interaction conditions and several types of robots. We hypothesize and find that positive emotions account for more variance than negative emotions. Practically, the findings suggest new strategies for interventions, aimed at increasing positive emotions to increase willingness to engage in intergroup interaction. No existing work has examined whether positive emotions are stronger predictors than negative emotions for willingness for human intergroup interaction, an important topic for future research.

Human Group Presence, Group Characteristics, and Group Norms Affect Human-Robot Interaction in Naturalistic Settings.

As robots become more prevalent in public spaces, such as museums, malls, and schools, they are coming into increasing contact with groups of people, rather than just individuals. Groups, compared to individuals, can differ in robot acceptance based on the mere presence of a group, group characteristics such as entitativity (i.e., cohesiveness), and group social norms; however, group dynamics are seldom studied in relation to robots in naturalistic settings. To examine how these factors affect human-robot interaction, we observed 2,714 people in a Japanese mall receiving directions from the humanoid robot Robovie. Video and survey responses evaluating the interaction indicate that groups, especially entitative groups, interacted more often, for longer, and more positively with the robot than individuals. Participants also followed the social norms of the groups they were part of; participants who would not be expected to interact with the robot based on their individual characteristics were more likely to interact with it if other members of their group did. These results illustrate the importance of taking into account the presence of a group, group characteristics, and group norms when designing robots for successful interactions in naturalistic settings.