Robot failures in Human-Robot Interaction (HRI), though often stemming from technical limitations, can have severe effects on the interactional dynamics between humans and robots. Prior empirical research has led to conflicting findings on how such failures influence user perceptions and the overall success of the interaction. In this study, we investigate how human participants respond to robot failures on a moment-to-moment basis, with a particular focus on how social roles, responsibilities, and agency are negotiated as these episodes unfold. We examine how responses and helping behaviors are instantiated, and which factors facilitate or hinder recovery strategies. We focus on kinematic failures, such as interruptions in motion, unsuccessful grasping, or dropping objects, that occurred during Tic-Tac-Toe games between human participants (n = 17) and the humanoid robot Epi. Our analysis combines multimodal conversation analysis (MCA) and thick description, drawing on our interdisciplinary backgrounds in cognitive science and feminist Science and Technology Studies (STS). We present selected interactional sequences that illustrate a range of participant responses, including physical repair and scaffolding, interpretive support, emotional care, sustained monitoring, and dynamic negotiation of agency. These observations demonstrate how humans co-construct interactional continuity and robot competence through distributed, multimodal, and affective forms of help. They also reveal how agency is dynamically reconfigured, and how roles and responsibilities are distributed across human and robotic actors. We show how the burden of repair often falls to the human participant and conclude by reflecting on the setting and methods used, specifically in regards to the role of the robot as a research tool.

As a young and inherently interdisciplinary field, Human-Robot Interaction (HRI) shows evidence of multiple, competing and complementary epistemologies and methodologies. However, it is clear that HRI user studies are a valued, primary form of knowledge generation. How might this influence, and be influenced by choice of experimental robot platform? Once a clear, common platform of choice, the number of HRI conference papers detailing work utilising the NAO robot has consistently declined since 2015. We take this opportunity to present quantitative and qualitative data regarding the evolving use and role of the NAO robot in establishing what makes “good science” in HRI, and to reflect on what this might mean for, and can tell us about, the field more broadly. We suggest that shared use of a common platform like NAO is emblematic of, and important for, the field's attempts to stabilise. Access to a common platform supports sharing of knowledge and practices amongst researchers in the field, whilst at the same time produces a set of assumptions about what makes for (seemingly) scientific HRI knowledge, practice or “lore” that will continue to shape the future of the field - even beyond the platform's demise.

This paper emphasizes the importance of interdisciplinary collaboration in exploring the concept of robot gender within Human-Robot Interaction (HRI). It draws on a case study of the authors' own collaboration, where interdisciplinary discussions on the nature of gender informed the design of a multimethod study. This approach allowed us to avoid assigning a binary gender to Pepper robot, while still encouraging participants to reflect on their own gendering practices during interactions with robots. Additionally, we invite readers to consider alternative ways of conceptualizing robot gender in HRI—specifically, as fluid and performative rather than binary, which relies on stereotypical cues. After describing how our discussions on gender influenced and reshaped the study design, we offer practical advice on fostering interdisciplinary collaborations. These suggestions focus on communication strategies, mindset, and the practical setup of collaborative studies. We hope that these recommendations will inspire other researchers to continue exploring new and interdisciplinary ways of approaching robot gender in HRI.

Significant amounts of HRI research effort are spent on the design/evaluation of robot bodies. Critical discussion and debates concerning the way bodies are treated and considered within HRI have tended to focus on the implications of designing/interacting with highly anthropomorphic robots, yet drawing attention away from the human body in HRI, particularly in the context of everyday interactions with “unexpectedly” social robots, i.e. those non-humanoid robots that human users interact with in a somewhat “social” way. These kind of robots crystallise particular aspects of (and tensions between) the different ways in which bodies are understood across disciplines. At the same time, a fundamental, and largely neglected tool for HRI research is the researchers' own embodied experience of the intersubjective role. This workshop has invited speakers and audience to engage in cross-disciplinary conversations on embodiment in HRI, highlighting the different ways in which “the body” is or can be variously conceptualised and researched.

Synthetic data is increasingly used throughout the AI development pipeline to address three primary challenges surrounding data use - data scarcity, privacy concerns, and data representativeness or diversity. With the introduction of the AI Act, these three challenges take on new urgency. Creating synthetic data clearly addresses the data scarcity problem and over a decade of research has interrogated the possibilities of differential privacy, yet little attention has been paid to whether and how data diversity is addressed in these systems. When applied to data, the term representation has multiple definitions, including both “representativeness,” which describes quantitative metrics of how many instances of a particular kind or grouping are in a dataset, and “representation,” which concerns the qualities that tend to be assigned to groups and individuals. In this workshop we will explore synthetic data with a view to this plurality of representation as essential to responsible AI development practices.

Smart cities build on visions for using technology to optimise various infrastructural functions and make city management more efficient, sustainable, and reliable. However, scholarship on smart cities has drawn attention to how data-centric planning simplifies the complexity of the urban environment and how a dichotomous approach to smart cities as either top-down or bottom-up may be overly reductive. This paper attempts to remedy this divide by highlighting the horizontal tensions in smart city planning, where tensions around implementing smart technologies appear as multiple actors and discourses converge in creating complex governance structures. We offer a case study of how scalar, temporal and social tensions around implementing smart city technologies are negotiated, based on interviews with employees in a Swedish municipality and several municipal corporations. We elaborate on three themes around time, the role of the municipality and infrastructure to gain a deeper understanding of the governance of and attitudes towards smartification. The interviewees described the complexities of implementing smart technology in reality, spanning various scales and intermingling public and private interests. These issues matter for how the municipality and the municipal corporations work with implementing smart technologies, making it anything but a straightforward process.

智慧城市建立在利用技术优化各种基础设施功能，并使城市管理更加高效、更可持续、更可靠的愿景之上。关于智慧城市的学术研究已经引起了人们对以数据为中心的规划如何简化城市环境复杂性的关注，以及对智慧城市采取自上而下或自下而上的二分法可能会过于简化的关注。本文试图通过强调智慧城市规划中的横向冲突来填补这种鸿沟。在智慧城市规划中，随着多个参与者和话语在创建复杂的治理结构时汇集，就会围绕智能技术的实施出现冲突。基于对瑞典一个市政当局和几家市政公司雇员的采访，我们进行了案例研究，探讨人们如何协商围绕智慧城市技术的实施出现的标量冲突、时间冲突和社会冲突。我们对时间、市政当局的角色和基础设施这三个主题进行了详细阐述，以更深入地了解对城市智慧化的治理和各种态度。受访者描述了在现实中实施智能技术的复杂性，涵盖了各种规模，并融合了公共和私人利益。这些问题关系到市政当局和市政公司如何实施智能技术，这使得这一过程绝不简单。

Domestic robots are already commonplace in many homes, while humanoid companion robots like Pepper are increasingly becoming part of different kinds of care work. Drawing on fieldwork at a robotics lab, as well as our personal encounters with domestic robots, we use here the metaphor of “hard-to-reach corners” to explore the socio-technical limitations of companion robots and our differing abilities to respond to these limitations. This paper presents “hard-to-reach-corners” as a problematic for design interaction, offering them as an opportunity for thinking about context and intersectional aspects of adaptation.