Data has emerged as one of the most powerful resources of the 21st century, yet the processes through which it is collected, transformed, and exploited remain opaque to the general public. While individuals continuously generate data through everyday interactions, they often lack understanding of how data is collected, by whom, and for what purposes. In this poster paper, we present the development process of DataMorph, an artistic provotype inspired by the metaphor of a data factory. It employs data physicalisation to render invisible processes and abstract data flows visible through a physical shape-changing form. Through this design provocation, we aim to foster critical reflection, public dialogue, and engagement with data practices, agency, and power. Lastly, we discuss various contexts in which DataMorph could be deployed.

Current discussion on AI often presents binary for/against stances, making it difficult to foster nuanced discourse. But how can we as designers, developers, researchers, and artists communicate the nuances of our work to non-experts? Art can be a powerful medium for public engagement prompting reflection on complex topics. We examine audience engagement with Cat Royale, an artwork that invited audiences to reflect on AI, robotics, and the trust we place in them. We show that constructing and presenting an art installation as a deliberately ambiguous interface can provoke and encourage critical reflection, and we argue for the importance of making abstract technologies, such as AI, tangible and relatable through concrete examples, including artworks. Finally, we examine forms of ambiguity that arise at the intersection of AI and public engagement, and propose two new kinds relevant to the future of beyond-human interaction in HCI: moral ambiguity and ambiguity of species.

The comparatively recent advent of Large Language Models (LLMs) has resulted in a wide array of new capabilities and components relevant to Human–Robot Interaction (HRI) researchers. LLMs are being applied to vision, manipulation, planning, reasoning, learning, and HRI problems, frequently as “Scarecrows,” in which LLMs serve as black box modules integrated into robot architectures for the purpose of quickly enabling full-pipeline solutions. However, despite this explosion of applications, general questions remain about the best ways to incorporate LLMs into robot architectures, appropriate safety and guardrail considerations, and, critically, how to report properly on HRI research that involves LLMs. In this article, we explore the question of reporting guidelines for HRI researchers who utilize Scarecrows in robot architectures. We identify five key stakeholder groups in the HRI research process, discuss what information each group needs from HRI researchers, and identify appropriate mechanisms for conveying that information from HRI researchers to stakeholders either directly or indirectly. We contribute a set of suggested guidelines regarding what information should be included when researchers disseminate information about HRI research that uses LLMs.

Large Language Models (LLMs) are seemingly infiltrating every domain, and the legal context is no exception. In this paper, we present the results of three experiments (total N=288) that investigated lay people's willingness to act upon, and their ability to discriminate between, LLM- and lawyer-generated legal advice. In Experiment 1, participants judged their willingness to act on legal advice when the source of the advice was either known or unknown. When the advice source was unknown, participants indicated that they were significantly more willing to act on the LLM-generated advice. This result was replicated in Experiment 2. Intriguingly, despite participants indicating higher willingness to act on LLM-generated advice in Experiments 1 and 2, participants discriminated between the LLM- and lawyer-generated texts significantly above chance-level in Experiment 3. Lastly, we discuss potential explanations and risks of our findings, limitations and future work, and the importance of language complexity and real-world comparability.

As robots enter the messy human world so the vital matter of safety takes on a fresh complexion with physical contact becoming inevitable and even desirable. We report on an artistic-exploration of how dancers, working as part of a multidisciplinary team, engaged in contact improvisation exer-cises to explore the opportunities and challenges of dancing with cobots. We reveal how they employed their honed bodily senses and physical skills to engage with the robots aesthetically and yet safely, interleaving improvised physical manipulations with reflections to grow their knowledge of how the robots behaved and felt. We introduce somatic safety, a holistic mind-body approach in which safety is learned, felt and enacted through bodily contact with robots in addition to being reasoned about. We conclude that robots need to be better designed for people to hold them and might recognise tacit safety cues among people. We propose that safety should be learned through iterative bodily experience interleaved with reflection.

Formal Modelling is often used as part of the design and testing process of software development to ensure that components operate within suitable bounds even in unexpected circumstances. We conducted a user study evaluation of predictive formal modelling (PFM) at runtime in a human-swarm mission to determine the benefit of PFM on performance and human-swarm interaction. A total of 180 participants were recruited to perform the role of aerial swarm operators delivering parcels to target locations in a simulation environment. The PFM model was integrated into the simulation software to inform the operator of the estimated mission completion time given the current number of drones deployed. The operator could increase the number of parcels delivered in any timestep by adding drones, which also increased costs, thus requiring the use of the minimum number of drones necessary to complete the task in the given time. We collected user feedback using standard survey questionnaires and measured performance using data obtained from the Human and Robot Interactive Swarm (HARIS) simulator. Our results show that PFM increased the performance of the human swarm team without significantly increasing the operators’ workload or affecting the system’s usability.

We reappraise the idea of colliding with robots, moving from a position that tries to avoid or mitigate collisions to one that considers them an important facet of human interaction. We report on a soma design workshop that explored how our bodies could collide with telepresence robots, mobility aids and a quadruped robot. Based on our findings, we employed soma trajectories to analyse collisions as extended experiences that negotiate key transitions of consent, preparation, launch, contact, ripple, sting, untangle, debris and reflect. We then employed these ideas to analyse two collision experiences, an accidental collision between a person and a drone and the deliberate design of a robot to play with cats, revealing how real-world collisions involve the complex and ongoing entanglement of soma trajectories. We discuss how viewing collisions as entangled trajectories, or ‘tangles’, can be used analytically, as a design approach, and as a lens to broach ethical complexity.

While ethical challenges are widely discussed in HCI, far less is reported about the ethical processes that researchers routinely navigate. We reflect on a multispecies project that negotiated an especially complex ethical approval process. Cat Royale was an artist-led exploration of creating an artwork to engage audiences in exploring trust in autonomous systems. The artwork took the form of a robot that played with three cats. Gaining ethical approval required an extensive dialogue with three Institutional Review Boards (IRBs) covering computer science, veterinary science and animal welfare, raising tensions around the welfare of the cats, perceived benefits and appropriate methods, and reputational risk to the University. To reveal these tensions we introduce beneficiary-epistemology space, that makes explicit who benefits from research (humans or animals) and underlying epistemologies. Positioning projects and IRBs in this space can help clarify tensions and highlight opportunities to recruit additional expertise.

We reflect on the design of a multispecies world centred around a bespoke enclosure in which three cats and a robot arm coexist for six hours a day during a twelve-day installation as part of an artist-led project. In this paper, we present the project’s design process, encompassing various interconnected components, including the cats, the robot and its autonomous systems, the custom end-effectors and robot attachments, the diverse roles of the humans-in-the-loop, and the custom-designed enclosure. Subsequently, we provide a detailed account of key moments during the deployment and discuss the design implications for future multispecies systems. Specifically, we argue that designing the technology and its interactions is not sufficient, but that it is equally important to consider the design of the ‘world’ in which the technology operates. Finally, we highlight the necessity of human involvement in areas such as breakdown recovery, animal welfare, and their role as audience.

Successful entrainment during collaboration positively affects trust, willingness to collaborate, and likeability towards collaborators. In this paper, we present a mixed-method study to investigate characteristics of successful entrainment leading to pair and group-based synchronisation. Drawing inspiration from industrial settings, we designed a fast-paced, short-cycle repetitive task. Using motion tracking, we investigated entrainment in both dyadic and triadic task completion. Furthermore, we utilise audio-video recordings and semi-structured interviews to contextualise participants’ experiences. This paper contributes to the Human-Computer/Robot Interaction (HCI/HRI) literature using a human-centred approach to identify characteristics of entrainment during pair- and group-based collaboration. We present five characteristics related to successful entrainment. These are related to the occurrence of entrainment, leader-follower patterns, interpersonal communication, the importance of the point-of-assembly, and the value of acoustic feedback. Finally, we present three design considerations for future research and design on collaboration with robots.

Evaluating pain in speech represents a critical challenge in high-stakes clinical scenarios, from analgesia delivery to emergency triage. Clinicians have predominantly relied on direct verbal communication of pain which is difficult for patients with communication barriers, such as those affected by stroke, autism, and learning difficulties. Many previous efforts have focused on multimodal data which does not suit all clinical applications. Our work is the first to collect a new English speech dataset wherein we have induced acute pain in adults using a cold pres-sor task protocol and recorded subjects reading sentences out loud. We report pain discrimination performance as F1 scores from binary (pain vs. no pain) and three-class (mild, moderate , severe) prediction tasks, and support our results with ex-plainable feature analysis. Our work is a step towards providing medical decision support for pain evaluation from speech to improve care across diverse and remote healthcare settings.

Robotic appliances are continually being adopted into private homes. However, users have yet to exhibit the same acceptance towards domestic social robots. In this paper, we seek to bridge this issue by augmenting already-existing home appliances with capabilities mimicking social robots. We present a robotic toaster designed with animated movements to enhance and personalize the toast-making experience. Not only does the robotic toaster assist in completing the task itself, it also acts as a conscious agent with whom users may interact in a social and playful manner. Using a series of video vignettes, we identify three key themes of the robotic toaster that influence its relationship with users: these are related to (1) context awareness, (2) increased interactivity through initiative action, and (3) expression of personality despite limited degrees of freedom. Lastly, we discuss how the portrayal of home appliances with social characteristics can potentially serve as an introductory step for social robots in the home.

With the increase in robot complexity and the diversity of domains in which we encounter robots, there is an increased need for research focusing on more varied aspects of human-robot interaction. While most research has focused on the dyadic interaction (one-to-one) between one human and one robot, we are currently observing a paradigm shift towards increased attention to HRI in non-dyadic systems. However, we still have limited knowledge of which interaction techniques work well for non-dyadic HRI combining human participants with multiple digital artefacts, including robots. We investigate what characterises non-dyadic HRI in various contexts, including the home and industry, and how the addition of robots affects how we interact in groups. This paper presents our research questions, preliminary results, and plans for future studies, thereby contributing to a better understanding of the concepts and interaction techniques in non-dyadic interaction in human-robot groups in various contexts.

The current discourse presented by mainstream media towards industrial robots seems to focus on the negative aspects their introduction brings to the workforce. However, it is unclear whether industrial workers share this negative perspective regarding industrial robots. In this paper, we present the results of a survey study (N=94) investigating differences in perception towards industrial robots, depending on the presence or absence of exposure to them in the workplace. Our results show that while workers with robot experience acknowledge that robots can lead to job loss, they also show stronger beliefs in the robots ability to boost new job opportunities. Additionally, we found that first-hand experience with robots in the workplace can positively affect workers perceptions about their advantages. Overall, our findings show that, contrasting the bleak picture drawn by mainstream media, workers exposed to industrial robots developed a more nuanced view of this new technology in the workplace.

Introducing robots in the workplace entails new practices and configurations at the individual, organizational, and social levels. Prior work has focused on how robots may have an immediate effect on individual employees or tasks rather than collectively influencing employees or the organizations they work for gradually over time. By drawing on fourteen in-situ interviews with six collaborative robot (cobot) operators at a Danish manufacturing company, this paper investigates how cobots in the manufacturing context may engage broader interactions beyond the robot-operator interaction. Our focus includes spatial configurations centering around the cobots, social interactions between employees, and information flow through, within, and outside the production cells. Introducing and implementing cobots in the workplace has social dynamics at its core, which we explore in depth. This paper argues that the design of cobots and the environment around them should accommodate the possibility of more complicated social and organizational changes brought about by these robots. Lastly, we discuss research and design implications for the future of workplaces involving robots.

We investigate how collaboration is understood and configured in industrial workplaces with collaborative robots (cobots). Through a qualitative analysis of 115 case studies of companies using cobots and 14 semi-structured interviews with cobot manufacturers and users, we examine the usages of cobots in the manufacturing industry over the entire temporal spectrum from pre-introduction to completed implementation. By synthesizing diverse stakeholders' perspectives, we present a set of main findings; key roles of a few supportive production workers during the adoption of cobots; a fragmentation of work tasks and the resulting loss of job identity among workers; the disunified meaning of "collaboration" which is under constant development; and the collaborative space and the working rhythms between production workers and cobots. By reconsidering what collaboration means in the workplace with cobots, we propose the concept of bounded collaboration, which means that the anticipated collaboration is manifested in a partial and limited manner within a collaborative technology. Finally, we provide practical suggestions for examining and supporting organizations and users in their adoption of cobots.

Going beyond dyadic (one-to-one) interaction has been increasingly explored in HRI. Yet we lack a comprehensive view on non-dyadic interaction research in HRI. To map out 15 years of works investigating non-dyadic interaction, and thereby identifying the trend of the field and future research areas, we performed a literature review containing all 164 publications (2006-2020) from the HRI conference investigating non-dyadic interaction. Our approach is inspired by the 4C framework, an interaction framework focusing on understanding and categorising different types of interaction between humans and digital artefacts. The 4C framework consists of eight interaction principles for multi-user/multi-artefact interaction categorised into four broader themes. We modified the 4C framework to increase applicability and relevance in the context of non-dyadic human-robot interaction. We identify an increasing tendency towards non-dyadic research (36% in 2020), as well as a focus on simultaneous studies (85% from 2006-2020) over sequential. We also articulate seven interaction principles utilised in non-dyadic HRI and provide specific examples. Last, based on our findings, we discuss several salient points of non-dyadic HRI, the applicability of the modified 4C framework to HRI and potential future topics of interest as well as open-questions for non-dyadic research.

Domestic robots such as vacuum cleaners or lawnmowers are becoming popular consumer products in private homes, but while current HCI research on domestic robots has highlighted for example personalisation, long-term effects, or design guidelines, little attention has been paid to automation. To address this, we conducted a qualitative study with 24 participants in private households using interviews, contextual technology tours, and robot deployment. Through thematic analysis we identified three themes related to 1) work routines and automation, 2) domestic robot automation and the physical environment, as well as 3) interaction and breakdown intervention. We present an empirical understanding of how task automation using domestic robots can be implemented in the home. Lastly, we discuss our findings in relation to existing literature and highlight three opportunities for improved task automation using domestic robots for future research.