The increasing deployment of robots in urban spaces calls for design strategies to ensure their adaptation and to mitigate potential disruptions to complex urban contexts. Our research aims to initiate the discussion of contextual adaptability issues of urban robots by exploring everyday scenarios where their presence would appear out of place. We created a design probe for people to carry in their daily lives, facilitating them to envision the robot's presence and capture scenarios where a robot seems to be disruptive. We collected data by distributing the probes among the research team and conducting a city walk activity using the probe at a workshop. This paper presents factors arising from the collected scenarios, encompassing temporal, spatial, cultural, and social dynamics, as well as various stakeholders that robots need to adapt to. These findings provide a blueprint and potential research directions for future research into robot contextual adaptability in urban environments.

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This study investigates error handling intricacies in supervised autonomy orbit-to-ground teleoperation for space exploration robots, emphasizing scenarios with communication delays that render Earth-based ground control assistance unfeasible. In this setting, one major challenge lies in empowering the crew to independently mitigate robot errors that may occur as the robot plans its actions. To address this limitation of current supervised autonomy interfaces, we propose a third-person perspective and game design principles to improve environmental awareness in error situations. 16 experts with similar technical background as the target crew members tested the interface in a physical user study, while 42 people assessed it in an online study. We conclude that a third-person view brings significant improvements to mental workload, overall experience and the ability to identify and rectify planning errors.

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In Industry 5.0, cognitive robots and workers will engage in evolving and reciprocal relations, which we call worker-robot relationships (WRRs). To enable evidence-based work futures with workers, we must co-develop WRRs and understand their impact on work, workers, management, and society. To this end, we posit that the HRI field should work beyond disciplines and include value-driven and plural perspectives through transdisciplinary research done with and for workers. However, WRRs and transdisciplinarity pose unique technical, design, and methodological challenges yet to be explored. We propose a workshop to engage the HRI community working on Industry 5.0, aiming at 1) taking stock of current WRR-related challenges in relevant disciplines, 2) collectively kick-off the exploration of a joint research agenda, 3) preliminary examining if and how transdisciplinarity could help the HRI community, and 4) start discussing how to deal with such complex knowledge integration in practice.

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Speculative design is an emerging form of critical material engagement with possible futures. Designers working speculatively call attention to current and future sociotechnical dilemmas, and aim to provoke debate about the moral, political and ethical implications of sociotechnical innovation. Despite the popularity of speculative design and its presence in a variety of domains, there are very few resources that address it as a pedagogical practice. We attempt to fill this gap by presenting the structure, reasoning and outcomes of a graduate course on speculative design we taught during the academic year 2022-3. The article describes class activities and outcomes, discusses the benefits and challenges of teaching speculative design (especially in a design-engineering program), and concludes by identifying the most considerable obstacles awaiting those who want to integrate speculative design into the curriculum. As such, the article provides a useful resource for those interested in understanding the benefits of speculative design as a critical pedagogical practice, and for those who wish to bring that understanding into the classroom.@en

This paper examines the role that enchantment plays in the design of AI things by constructing a taxonomy of design approaches that increase or decrease the perception of magic and enchantment. We start from the design discourse surrounding recent developments in AI technologies, highlighting specific interaction qualities such as algorithmic uncertainties and errors and articulating relations to the rhetoric of magic and supernatural thinking. Through analyzing and reflecting upon 52 students’ design projects from two editions of a Masters course in design and AI, we identify seven design principles and unpack the effects of each in terms of enchantment and disenchantment. We conclude by articulating ways in which this taxonomy can be approached and appropriated by design/HCI practitioners, especially to support exploration and reflexivity.@en

This work illustrates how artistic robotic systems can provide a reservoir of unfamiliarity and a basis for speculation, to open the field toward new ways of thinking about HRI. We reflect on a collaborative project between design students, a media art studio, and design researchers working with the baggage handling department of the Schiphol airport. Engaging with the industrial context, we developed 'metabehaviours' - abstracted ideas of processes carried out on the worksite-and passed these over to the students who translated them into robotic enactions using a predefined hardware developed by the media art studio. The resulting visit experience challenges the audience to decode the installation in terms of metabehaviours and their possible relations to industrial HRI. We used this to reflect on the value of conducting artistic and speculative work in HRI and to distil actionable recommendations for future research.

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Unprecedented possibilities of quadruped robots have driven much research on the technical aspects of these robots. However, the social perception and acceptability of quadruped robots so far remain poorly understood. This work investigates whether the way we design quadruped robots' behaviours can affect people's perception of safety in interactions with these robots. We designed and tested a dominant and submissive personality for the quadruped robot (Boston Dynamics Spot). These were tested in two different walking scenarios (head-on and crossing interactions) in a 2x2 within-subjects study. We collected both behavioural data and subjective reports on participants' perception of the interaction. The results highlight that participants perceived the submissive robot as safer compared to the dominant one. The behavioural dynamics of interactions did not change depending on the robot's appearance. Participants' previous in-person experience with the robot was associated with lower subjective safety ratings but did not correlate with the interaction dynamics. Our findings have implications for the design of quadruped robots and contribute to the body of knowledge on the social perception of non-humanoid robots. We call for a stronger standing of felt experiences in human-robot interaction research.

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Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into the functioning of physical and digital products, creating unprecedented opportunities for interaction and functionality. However, there is a challenge for designers to ideate within this creative landscape, balancing the possibilities of technology with human interactional concerns. We investigate techniques for exploring and reflecting on the interactional affordances, the unique relational possibilities, and the wider social implications of AI systems. We introduced into an interaction design course (n = 100) nine ‘AI exercises’ that draw on more than human design, responsible AI, and speculative enactment to create experiential engagements around AI interaction design. We find that exercises around metaphors and enactments make questions of training and learning, privacy and consent, autonomy and agency more tangible, and thereby help students be more reflective and responsible on how to design with AI and its complex properties in both their design process and outcomes.

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This paper explores the potential implications of embodied conversational agents (ECAs) in healthcare, focusing on the impact of appearance and conversation style on trustworthiness. We conducted a Research through Design investigation of ECAs for supporting women during the periconception period and in pregnancy. The paper presents the results of a Wizard of Oz study in which two alternative prototypes, a chatbot, and an ECA, were tested in a tertiary hospital by 25 participants. Reflecting on the results we suggest that limited patients' trust in ECAs maybe be beneficial for achieving trustworthy use of these agents in the healthcare context.

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Design fixation, a phenomenon describing designers' adherence to pre-existing ideas or concepts that constrain design outcomes, is particularly prevalent in human-robot interaction (HRI), for example, due to collectively held and stabilised imaginations of what a robot should look like or behave. In this paper, we explore the contribution of creative AI tools to overcome design fixation and enhance creative processes in HRI design. In a four weeks long design exploration, we used generative text-to-image models to ideate and visualise robotic artefacts and robot sociotechnical imaginaries. We exchanged results along with reflections through a digital postcard format. We demonstrate the usefulness of our approach to imagining novel robot concepts, surfacing existing assumptionsand robot stereotypes, and situating robotic artefacts in context.We discuss the contribution to designerly HRI practices and conclude with lessons learnt for using creative AI tools as an emerging design practice in HRI research and beyond.

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In this paper, we problematize popular narratives of driving automation. Whether positive or negative, these propagate simplistic assumptions about human abilities and reinforce technocratic approaches to mobility innovation. We build on narrative approaches to participatory research and adversarial design, to explore how design-led confrontation can create opportunities for reflection on implicit assumptions and narratives that stakeholders may refer to when discussing and making decisions about automated driving technologies. Specifically, we discuss the results of four focus groups where we used contestational artifacts to promote critical discussions and confront taken-for-granted beliefs among stakeholders. We reflect on the results to distill methodological insight and design recommendations for conducting adversarial participatory design research as a way towards confronting dominant narratives. Together with the methodological approach, the main contribution of this work, we also provide a set of narrative tensions that can be used to question common beliefs surrounding automated driving futures.

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Augmented Reality (AR) technology could be utilised to assist pedestrians in navigating safely through traffic. However, whether potential users would understand and use such AR solutions is currently unknown. Nine novel AR interfaces for pedestrian-vehicle communication, previously developed using an experience-based design method, were evaluated through an online questionnaire study completed by 992 respondents in Germany, the Netherlands, Norway, Sweden, and the United Kingdom. The AR indicated whether it was safe to cross the road in front of an approaching automated vehicle. Each interface was rated for its intuitiveness and convincingness, aesthetics, and usefulness. Moreover, comments were collected for qualitative analysis. The results indicated that interfaces that employed traditional design elements from existing traffic, and head-up displays, received the highest ratings overall. Statistical results also showed that there were no significant effects of country, age, and gender on interface acceptance. Thematic analysis of the textual comments offered detail on each interface design's stronger and weaker points, and revealed unintended effects of certain designs. In particular, some of the interfaces were commented on as being dangerous or scary, or were criticised that they could be misinterpreted in that they signal that something is wrong with the vehicle, or that they could occlude the view of the vehicle. The current findings highlight the limitations of experience-based design, and the importance of applying legacy design principles and involving target users in design and evaluation. Future research should be conducted in scenarios in which pedestrians actually interact with approaching vehicles.

Marie Skłodowska-Curie Actions; Innovative Training Networks (ITN); SHAPE-IT; Grant number 860410

Publication date: 21 February 2023

DOI: 10.1016/j.trf.2023.02.005

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The need for critically reflecting on the deceptive nature of advanced technologies, such as social robots, is urging academia and civil society to rethink education and the skills needed by future generations. The promotion of critical thinking, however, remains largely unaddressed within the field of educational robotics. To address this gap and question if and how robots can be used to promote critical thinking in young children's education, we conducted an explorative design study named Bringing Shybo Home. Through this study, in which a robot was used as a springboard for debate with twenty 8- to 9-year-old children at school, we exemplify how the deceptive nature of robots, if embraced and magnified in order for it to become explicitly controversial, can be used to nurture children's critical mindset.

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This article engages with the claimed limitation that critical design fails to address the problems it condemns, such as capitalism, and suggests looking at the different ways critical design practices have related to production in the past. Three examples from different historical moments are discussed through the theoretical lens of tension with progression. The discussion brings to light four areas of reflection which concern the way we understand progression, time, socio-technical contexts, and use. These—all suggesting that critical design is frictional yet can also be progressional—are presented as perspectives relevant to better position critical design in relation to production and to assess its potential contributions.@en

How can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits - but also undesirable situations where moral responsibility for their actions cannot be properly attributed to any particular person or group. The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans; however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging. In this paper, we address the gap between philosophical theory and engineering practice by identifying, through an iterative process of abductive thinking, four actionable properties for AI-based systems under meaningful human control, which we discuss making use of two applications scenarios: automated vehicles and AI-based hiring. First, a system in which humans and AI algorithms interact should have an explicitly defined domain of morally loaded situations within which the system ought to operate. Second, humans and AI agents within the system should have appropriate and mutually compatible representations. Third, responsibility attributed to a human should be commensurate with that human’s ability and authority to control the system. Fourth, there should be explicit links between the actions of the AI agents and actions of humans who are aware of their moral responsibility. We argue that these four properties will support practically minded professionals to take concrete steps toward designing and engineering for AI systems that facilitate meaningful human control.@en

Resonance, a powerful and pervasive phenomenon, appears to play a major role in human interactions. This article investigates the relationship between the physical mechanism of resonance and the human experience of resonance, and considers possibilities for enhancing the experience of resonance within human–robot interactions. We first introduce resonance as a widespread cultural and scientific metaphor. Then, we review the nature of “sympathetic resonance” as a physical mechanism. Following this introduction, the remainder of the article is organized in two parts. In part one, we review the role of resonance (including synchronization and rhythmic entrainment) in human cognition and social interactions. Then, in part two, we review resonance-related phenomena in robotics and artificial intelligence (AI). These two reviews serve as ground for the introduction of a design strategy and combinatorial design space for shaping resonant interactions with robots and AI. We conclude by posing hypotheses and research questions for future empirical studies and discuss a range of ethical and aesthetic issues associated with resonance in human–robot interactions.

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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.

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This work illustrates and reflects on the design process of MLTK01, an open-source toolkit for fast prototyping tangible learning things, built on top of Arduino and ml5js. The toolkit was developed as a response to the current lack of fast and easy to use tools for tangible experiments with machine learning. Learning from insights gained through previous projects, we defined a set of basic building blocks necessary to enable such experiments and engaged in an iterative process of sketching, prototyping and preliminary testing of the toolkit. MLTK01 includes a custom PCB, a software library and accessories. Together with a descriptive account of the design process we also discuss possible applications of the toolkit and its implications for a design process of tangible learning things@en