Artificial intelligence is increasingly diffusing into design and creative education, reshaping how students ideate, iterate, and produce work. While these tools offer clear benefits in terms of speed and experimentation, they also challenge long-standing pedagogical assumptions regarding the importance of process, authorship, and studio-based learning. Educators are therefore faced with a dual task: mitigating the risks AI poses to reflective, process-oriented design while simultaneously exploring ways to meaningfully integrate these technologies into curricula. Through working group activities, this workshop examines these tensions to identify emerging strategies for the critical and transparent use of AI. Ultimately, we aim to address current knowledge gaps, establish a collaborative research agenda, and build a network to support AI collaboration in design and creative education.

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.

AI is increasingly promoted and subsequently embraced across various industries, with promises of unprecedented efficiency, creativity, and productivity. Yet, these technologies often seem not to be fully living up to their promises, feeding critiques about the hype phenomenon in AI innovation and the overclaimed communication surrounding it. However, specific knowledge about how different media strategies contribute to AI hype is still missing. To address this gap, this paper presents an investigation of AI tools advertising to uncover narrative patterns that contribute to hype. Through the analysis of 53 company-released promotional videos about generative AI products retrieved on YouTube, the work presents 6 distinct AI hype patterns with 15 sub-categories and a set of alternative patterns for responsible AI communication. Upon reflecting on these strategies and practices, the authors examine the interplay between patterns across videos and context, and conclude with implications for creative practitioners and in human-computer interaction research.

Robotic technologies are often proposed to relieve dull, dirty, or dangerous work, but may cause work to instead be experienced as boring, or dehumanized. Understanding the impact of robotics on the workfloor is complicated by the entanglement between emerging robotic capabilities, social dynamics, and organizational issues—which we call Worker–Robot Relations. Consequently, the impact of robotics on work is often studied in hindsight. Speculative design methodologies can facilitate alignment of robotic developments with a meaningful future of work, by creating boundary objects for communicating about current and future work practices. Making use of an unfolding artistic collaboration, we propose an experiential approach for speculating about future Worker–Robot Relations. We enabled speculative encounters between participants and robotic creatures that embody seven meta-behaviors. We abstracted these from observed behaviors in a current work context in baggage handling. We present the findings from focus groups responding to these encounters, including implications for HRI and speculative design.

Smart home technologies embed values such as sustainability, comfort, privacy, and security, which can sometimes conflict with one another, considering the complexities of domestic environments. This paper investigates the potential implications of these value conflicts and the corresponding design challenges. Through an enactment session and co-speculations with professional actors, we explored what it means to navigate multiple values simultaneously, live with products that impose their own values, and manage value conflicts both with and among smart products. The findings challenge the seamless and harmonious vision of smart homes conceived by technologists, proposing shifts in the common narrative: from value alignment to value transparency, from service provision to mutual care, and from autonomy to responsiveness. We discuss that acknowledging value conflicts, rather than eliminating them, is an opportunity to gain a deeper understanding of users and home environments and guide the design of smart home technologies.

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.

Work on value alignment aims to ensure that human values are respected by AI systems. However, existing approaches tend to rely on universal framings of human values that obscure the question of which values the systems should capture and align with, given the variety of operational situations. This often results in AI systems that privilege only a selected few while perpetuating problematic norms grounded on biases, ultimately causing equity and justice issues. In this perspective paper, we unpack the limitations of predominant alignment practices of reinforcement learning from human feedback (RLHF) for LLMs through the lens of situated values. We build on feminist epistemology to argue that at the design-time, RLHF has problems with representation in the subjects providing feedback and implicitness in the conceptualization of values and situations of real-world users while lacking system adaptation to real user situations at the use time. To address these shortcomings, we propose three research directions: 1) situated annotation to capture information about the crowdworker’s and user’s values and judgments in relation to specific situations at both the design and use-time, 2) expressive instruction to encode plural values for instructing LLMs systems at design-time, and 3) reflexive adaptation to leverage situational knowledge for system adaption at use-time. We conclude by reflecting on the practical challenges of pursuing these research directions and situated value alignment of AI more broadly.

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.

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.

This paper presents the design of a novel social robot, namely Patbot, to engage people in playful interactions to help reduce their anxiety in waiting environments. We introduce the rationale and design decisions made during the development of the robot. We evaluated the robot’s usability through an experiment within a simulated waiting environment, followed by interviews with the participants. The study indicated a positive effect of interacting with Patbot regarding STAI-6 anxiety measures. Other quantitative and qualitative measures, including Godspeed questionnaires, observation, and post-interviews, revealed positive impressions made by Patbot regarding its likability and animacy and that it could engage individuals in intuitive and playful activities. Our findings suggest the promise of designing social robots for entertainment and relaxation to enhance people’s emotional experiences in waiting environments.

This article presents findings from a Research through Design investigation focusing on a reflexive approach to data curation and the use of generative AI in design and creative practices. Using binary gender categories manifested in children’s toys as a context, we examine three design experiments aimed at probing how designers can cultivate a reflexive human-AI practice to confront and challenge their internalized biases. Our goal is to underscore the intricate interplay between the designer, AI technology, and publicly held imaginaries and to offer an initial set of tactics for how personal biases and societal norms can be illuminated through interactions with AI. We conclude by proposing that designers not only bear the responsibility of grappling critically with the complexities of AI but also possess the opportunity to creatively harness the limitations of technology to craft a reflexive data curation that encourages profound reflections and awareness within design processes.

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.

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.

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.

The word “robot” frequently conjures unrealistic expectations of utilitarian perfection: tireless, efficient and flawless agents. However, real-world robots are far from perfect—they fail and make mistakes. Thus, roboticists should consider altering their current assumptions and cultivating new perspectives that account for a more complete range of robot roles, behaviors, and interactions. To encourage this, we explore the use of metaphors for generating novel ideas and reframing existing problems, eliciting new perspectives of human-robot interaction. Our work makes two contributions. We (1) surface current assumptions that accompany the term “robots,” and (2) present a collection of alternative perspectives of interaction with robots through metaphors. By identifying assumptions, we provide a comprehensible list of aspects to reconsider regarding robots’ physicality, roles, and behaviors. Through metaphors, we propose new ways of examining how we can use, relate to, and co-exist with the robots that will share our future.

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.

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.

The spread of edutainment robotics in everyday life raises new opportunities that can lead to a redefinition of the traditional game scenarios. Robots, indeed, represents a challenge for designer since allows a physical embodiment of a game character/element. These new opportunities have been analyzed in parallel with the world of childhood, its main characteristics, current topics and emerging issues. This analysis is at the basis of the Phygital Play project, a mixed-reality playground in which children can play with or against a robot. The project aims to encourage children to play physically in order to reduce sedentary behaviors, which are recently increasing accordingly to the spread of screen-based activities.