Participatory design is increasingly used to address the negative social impacts of artificial intelligence (AI), aiming for more inclusive and equitable innovation. However, it can inadvertently reproduce injustice and reinforce power imbalances, even with good intentions. While the HCI community is critical of these issues, the existing knowledge is often fragmented, making it challenging for AI researchers and policymakers to navigate. This paper presents a scoping review of participatory AI research in HCI focused on justice. We detail how participatory AI unfolds in practice and offers methodological insights on the roles of researchers and partnership with communities, the practical and contextual challenges, the role of reflexivity and situatedness and the essential but not so central role of artefacts in participatory processes. We conclude with recommendations for engaging in participatory design to promote justice in AI systems.

This full-day workshop is dedicated to mapping and building a community toward shaping sustainable futures of robot-assisted work, with and for workers. The program encompasses lightning keynotes from HRI experts, talks from selected participants bringing case studies, and a hands-on mapping activity for understanding the landscape of robotics innovation at work - in order to foster knowledge exchange and learning. The workshop culminates in a facilitated conversation with workers and managers from a particular case study, providing real-world insights into the challenges, complexities and opportunities for our HRI community in shaping the future of work. With this rich set of activities, the program aims to bridge the gap between academics and practitioners, and to promote a holistic understanding of our roles in shaping the future of work, with particular attention to systemic challenges and value-driven approaches. The workshop will conclude with a synthesis of key takeaways and potential directions for future research and community building.

We propose a workshop stemming from ongoing conversations about the role of design methods and designed artefacts within the field of Human-Robot Interaction (HRI). Given the growing interest in understanding what the field can learn from design explorations, the workshop focuses on hands-on annotating activity where participants (researchers and practitioners from HRI, Human-Computer Interaction, and Design Research) will analyze and reflect upon selected collections of robotic artefacts. Ultimate goal of the workshop is to explicate values, concepts and perspectives that usually remain tacitly embedded in the designed artefacts and, as such, hard to appreciate as proper HRI contributions. The expected outcome of the workshop is a set of methodological recommendations and concrete examples of what kind of knowledge can be generated through robotic artefacts.

HRI is an interdisciplinary field that requires researchers to be knowledgeable in broad areas ranging from social sciences to engineering. Study design is a multifaceted aspect of HRI that is hard to develop and perfect. Thus, the second edition of the “Workshop Your Study Design” workshop aims to improve the quality of future HRI studies by training researchers and boosting the accessibility of HRI as a field. Participants will have the opportunity to receive guidance and feedback on their study from an expert mentor. Researchers from all avenues of HRI will be invited to submit a 2–4 page paper on an HRI study they are currently designing, including a brief introduction and a complete methods section. Accepted submissions will be discussed in small groups led by mentors with relevant expertise. Prior to the workshop, papers will be shared within each group. Participants will be encouraged to read other submissions. During the workshop, attendees will work within their menteementor groups to discuss each paper and provide feedback. There will also be a session where mentors lead mini discussions on topics important to study design, such as balancing qualitative and quantitative design, power analysis, and research ethics. The workshop will end with a session where all participants can share important lessons that they learned with fellow attendees.

This paper is a methodological replication of Barendregt et al. [11], who urged Child-Computer Interaction field to embrace Intermediate Level Knowledge as a meaningful and valid way of generating knowledge. We extend this epistemological gap to the Human-Robot Interaction (HRI). Currently, artefact-centered papers—papers that present the development of an artefact—seem to be one of the primary ways that the HRI field generates knowledge. In this paper, we made an analysis of all papers presented at the HRI Conference from 2006 to 2020. Our results indicate that the 41,2 % of the papers were artefact-centered; and the impact of them, measured in the number of citations, was significantly lower than other kinds of papers. We used 23 artefact-centered papers to formulate two strong concepts and investigate how the foundational design epistemology about intermediate-level knowledge and RtD can contribute to other design-related disciplines to produce useful and valuable knowledge.

We present a vision for conversational user interfaces (CUIs) as probes for speculating with, rather than as objects to speculate about. Popular CUIs, e.g., Alexa, are changing the way we converse, narrate, and imagine the world(s) to come. Yet, current conversational interactions normatively may promote non-desirable ends, delivering a restricted range of request-response interactions with sexist and digital colonialist tendencies. Our critical design approach envisions alternatives by considering how future voices can reside in CUIs as enabling probes. We present novel explorations that illustrate the potential of CUIs as critical design material, by critiquing present norms and conversing with imaginary species. As micro-level interventions, we show that conversations with diverse futures through CUIs can persuade us to critically shape our discourse on macro-scale concerns of the present, e.g., sustainability. We reflect on how conversational interactions with pluralistic, imagined futures can contribute to how being human stands to change.

Interest in design methods and tools has been steadily growing in HRI. Yet, design is not acknowledged as a discipline with specific epistemology and methodology. Designerly HRI work is validated through user studies which, we argue, provide a limited account of the knowledge design produces. This paper aims to broaden current understanding of designerly HRI work and its contributions by unpacking what designerly knowledge is and how to produce it. Through a critical analysis of current HRI design literature, we identify a lack of work dedicated to understanding the conceptual implications of robotic artifacts. These, in fact, are implicit carriers of crucial HRI knowledge that can challenge established assumptions about how a robot should look, act, and be like. We conclude by discussing a set of practices desirable to legitimize designerly HRI work, and calling for further research addressing the conceptual implications designerly HRI work.

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.

Fast-paced contemporary life full of planned interaction usually makes people miss out on wonderful moments. We here present BubbleBot, a speculative robot designed to support serendipity of interactions in public space. After observations in public spaces and embodied design workshops, we have designed BubbleBot to be a peripheral public-space robot, bursting bubbles at passersby to invite serendipitous interactions. BubbleBot is a speculative robot to create magical moments among people with minimal peripheral social interaction. With this project, we aim at generating a conversation about the future roles and interaction paradigms of robots in public space.

In this note, we present minimal robot movements for robotic technology for children. Two types of minimal gaze movements were designed: social-gaze movements to communicate social engagement and deictic-gaze movements to communicate task-related referential information. In a two (social-gaze movements vs. none) by two (deictic-gaze movements vs. none) video-based study (n=72), we found that social-gaze movements significantly increased children's perception of animacy and likeability of the robot. Deictic-gaze and social-gaze movements significantly increased children's perception of helpfulness. Our findings show the compelling communicative power of social-gaze movements, and to a lesser extent deictic-gaze movements, and have implications for designers who want to achieve animacy, likeability and helpfulness with simple and easily implementable minimal robot movements. Our work contributes to human-robot interaction research and design by providing a first indication of the potential of minimal robot movements to communicate social engagement and helpful referential information to children.

Developing systems that motivate people to change their behaviors, such as an exercise application for the smartphone, is challenging. One solution is to implement motivational strategies from existing behavior change theory and tailor these strategies to preferences based on personal characteristics, like personality and gender. We operationalized strategies by collecting representative motivational text messages and aligning the messages to ten theory-based behavior change strategies. We conducted an online survey with 350 participants, where the participants rated 50 of our text messages (each aligned to one of the ten strategies) on how motivating they found them. Results show that differences in personality and gender relate to significant differences in the evaluations of nine out of ten strategies. Eight out of ten strategies were perceived as either more or less motivating in relation to scores on the personality traits Openness, Extraversion, and Agreeableness. Four strategies were perceived as more motivating by men than by women. These findings show that personality and gender influence how motivational strategies are perceived. We conclude that our theory-based behavior change strategies can be more motivating by tailoring them to personality and gender of users of behavior change systems.

Many researchers have started to explore natural interaction scenarios for children. No matter if these children are normally developing or have special needs, evaluating Child-Robot Interaction (CRI) is a challenge. To find methods that work well and provide reliable data is difficult, for example because commonly used methods such as questionnaires do not work well particularly with younger children. Previous research has shown that children need support in expressing how they feel about technology. Given this, researchers often choose time-consuming behavioral measures from observations to evaluate CRI. However, these are not necessarily comparable between studies and robots.

We present initial findings from an experiment where we used Semantic Free Utterances - vocalizations and sounds without semantic content - as an alternative to Natural Language in a child-robot collaborative game. We tested (i) if two types of Semantic Free Utterances could be accurately recognized by the children; (ii) what effect the type of Semantic Free Utterances had as part of help-giving behaviors with in situ child-robot interaction. We discuss the potential benefits and pitfalls of Semantic Free Utterances for child-robot interaction.

Since children (5-9 years old) are still developing their emotional and social skills, their social interactional behaviors in small groups might differ from adults' interactional behaviors. In order to develop a robot that is able to support children performing collaborative tasks in small groups, it is necessary to gain a better understanding of how children interact with each other. We were interested in investigating vocal turn-taking patterns as we expect these to reveal relations to collaborative and conflict behaviors, especially with children behaviors as previous literature suggests. To that end, we collected an audiovisual corpus of children performing collaborative tasks together in groups of three. Through automatic turn-taking analyses, our results showed that speaker changes with overlaps are more common than without overlaps and children seemed to show smoother turn-taking patterns, i.e., less frequent and longer lasting speaker changes, during collaborative than conflict behaviors.