Remote collaboration technologies shape how workers are perceived by colleagues and managers, influencing career progression, trust, and workplace dynamics. This study examines visibility practices—also known as self-presentation or impression management—by exploring interactions through which remote workers establish and maintain visibility. Through 16 semi-structured interviews with remote knowledge workers across various roles and regions, we identify key visibility practices: participating in meetings, leaving traceable links to quality work outputs, and reappropriating miscellaneous features to become visible for others. However, these practices are deeply intertwined with negative psycho-social externalities such as internal pressures, fears, mistrust, and privacy concerns that endanger workers’ overall well-being. Our contributions include (1) empirical insights into workplace visibility and its entangled psycho-social complexities, (2) visibility ecosystem as a socio-material frame, capturing human-technology interactions in when visibility is at stake, and (3) design implications for collaboration technologies that support visibility practices while mitigating associated psycho-social externalities.

In this section, we feature reports from conferences, symposia, workshops, and similar events, focusing on discussions where the boundaries of HCI and UX are being challenged and where debate is lively and ongoing.

As Artificial Intelligence continues to permeate everyday life, concerns over its societal consequences are becoming increasingly pressing. Anticipatory practices have emerged as central to responsible AI development, offering ways to envision and mitigate potential harms. While policymakers engage with anticipation through forecasting and risk assessment, speculative design offers an alternative, more experiential approach to also fosters public engagement and critical reflection. However, most speculative explorations focus on future possibilities, often neglecting the continuum between these and past phenomena. In this pictorial, we argue for integrating historical perspectives into speculative design to enrich anticipatory work on AI. Through a week-long international summer school, we engaged with the legacy of phrenology and the work of Cesare Lombroso. Using this as a springboard for speculation, we illustrate that incorporating historical trajectories into speculative design can deepen understanding of current dilemmas around AI, but dedicated methodological resources are still needed to achieve this value.

Data is central to AI performance, yet its curation remains an invisible and labour-intensive process, often leading to biases and reliability issues. While HCI has explored methods to improve data work, a growing body of research embraces data imperfections in an artistic vein to provoke reflection on human-AI relations. This workshop examines "Data Craft"- practices that creatively manipulate data to challenge conventional AI narratives and lower barriers to public engagement. By framing data craft as a boundary practice, we explore its potential to foster dialogue on AI capabilities, limitations, and societal impact. The workshop will investigate how data craft can be systematically integrated into participatory AI efforts, moving beyond artistic spaces to inform public debate. Through hands-on exploration, we aim to uncover strategies for leveraging data craft to engage diverse communities in shaping AI discourse.

Victims of sexual assault who turn to the criminal justice system for help often end up with negative experiences or even secondary trauma. While previous research has highlighted the challenges victims face, it tends to focus on individual interactions and rarely takes a holistic, victim-centred view of the process. Furthermore, it often highlights the actions of other stakeholders, rather than exploring the victim's ability to act. This means that systemic structures that influence the victim's experience and their ability to shape that experience can go unnoticed.
Using a human-centred design approach, journey mapping, we map the victim's experience, looking at the case of the Dutch criminal justice system. The journey map shows what interactions and non-interactions the victim encounters. We then analyse the map using a feminist theory of power, the Matrix of Domination, to explore how power impacts the victim's experience, both on an interpersonal and structural level.
In our study, we find that victims initially hold power, but that they lose it almost entirely when a case is filed. This lack of power results in the victim not having control of their journey in the criminal justice system, and results in different types of harm. We argue that if we want to improve victims' experiences, mapping power allows us to move beyond individual interactions and focus on systemic, structural changes.

Designing meaningful tangible and embodied interactions remains challenging due to their situated nature, complex user needs, and the limited programming skills of many users as well as designers. We developed an interaction model where users and LLMs co-perform tangible actions through prompt engineering beyond deterministic logic of commercial smart systems. In this model AI systems interpret natural language descriptions of environmental context, internalize technical functionalities and spatial cues, and translate these into tangible actions. We encapsulated the interaction model within a LLM-enabled tangible artifact as a HCI provotype and conducted an initial exploratory study around it. Our preliminary findings point to opportunities in refinement and reappropriation of such systems over the use period as well as challenges in adapting deictic spatial references.

This paper addresses the integration of sound into product design and engineering. Recognizing a gap in design education, the study focuses on introducing product design and engineering students to the principles of product sound design (PSD). By means of interviews with experts and literature research, a three-level framework is developed, addressing product features, object composition, and environmental context. This framework can assist students in understanding how engineering decisions influence sound perception at the product level, how material and structural choices affect sound at the object level, and how environmental factors shape the overall auditory experience. The framework served as the foundation for conceptualizing Les Sons, an educational software tool that mirrors these levels in its architecture. Les Sons supports students in exploring and modifying product acoustics through component and material selection. The paper stresses the role of tools like Les Sons for product sound design education, in order to practice and enhance collaboration and shared understanding in multidisciplinary contexts.

This article aims to develop a semi-formal representation for Human-AI (HAI) interactions, by building a set of interaction primitives which can specify the information exchanges between users and AI systems during their interaction. We show how these primitives can be combined into a set of interaction patterns which can capture common interactions between humans and AI/ML models. The motivation behind this is twofold: firstly, to provide a compact generalization of existing practices for the design and implementation of HAI interactions; and secondly, to support the creation of new interactions by extending the design space of HAI interactions. Taking into consideration frameworks, guidelines, and taxonomies related to human-centered design and implementation of AI systems, we define a vocabulary for describing information exchanges based on the model’s characteristics and interactional capabilities. Based on this vocabulary, a message passing model for interactions between humans and models is presented, which we demonstrate can account for existing HAI interaction systems and approaches. Finally, we build this into design patterns which can describe common interactions between users and models, and we discuss how this approach can be used toward a design space for HAI interactions that creates new possibilities for designs as well as keeping track of implementation issues and concerns.

Experiential artificial intelligence (AI) is an approach to the design, use, and evaluation of AI in cultural or other real-world settings that foregrounds human experience and context. It combines arts and engineering to support rich and intuitive modes of model interpretation and interaction, making AI tangible and explicit. The ambition is to enable significant cultural works and make AI systems more understandable to nonexperts, thereby strengthening the basis for responsible deployment. This paper discusses limitations and promising directions in explainable AI, contributions the arts offer to enhance and go beyond explainability, and methodology to support, deepen, and extend those contributions.

There is a call for more use of future-oriented design methods like speculative de-sign in developing policies. While these methods offer potential benefits in helping future-proof policies, they also run the risk of solidifying existing structures of pow-er if not applied critically. In this paper, we describe a case study examining smart doorbells in Amsterdam, where we created a speculative design exhibition grounded in feminist theory in order to challenge the existing power structures in the public domain. We then discuss the insights from our design process and the reaction the exhibition received in light of how feminist theory can help ensure a critical application of future-oriented design methods in policy design.

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.

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.

This paper presents the design, deployment and qualitative study of a large-scale, public, generative art exhibition, through which passers-by could create artworks, and mint a non-fungible-token (NFT). Following the month-long exhibition, during which 229 anonymous participants produced artworks, 69 non-transferable NFTs were minted, we surveyed (33) and interviewed (14) expert and novice participants about their experiences. We explored contemporary challenges of owning digital things, and the extent to which NFTs, and 'Web3' technologies offer meaningful forms of ownership. Our findings describe how the inability to trade this NFT, and its unique circumstances of acquisition, made it meaningful in ways that extended beyond its immediate (limited) utility and offered participants something through which to construct identity. Reflecting on the aspirations, contradictions, and misconceptions of forms of ownership enabled by NFTs, we conclude with proposals for renewed attention in HCI to the nature of digital possessions, and the potential for 'ownership design'.

In recent years, advances in artificial intelligence (AI) and machine learning have given rise to powerful new tools and methods for creative practitioners. 2022–2023 in particular saw an explosion in generative AI tools, models and use cases. Noting the long history of critical arts engaging with AI, this chapter considers both the application of generative AI in the creative industries, and ways in which artists co-shape the development of these emerging technologies. After reviewing the landscape of generative AI in visual arts, music and games, we propose four areas of critical interest for the future co-shaping of generative AI and creative practice in the areas of communities and open source, deeper engagement with AI, beyond the human and cultural feedbacks.

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.

While the past decade has seen cuts to public funding to the arts, it has also seen the development of online technologies which have the potential to reach increasingly diverse and global audiences. As a result, individuals and organisations across the creative industries and performing arts have experimented and embraced more diverse, innovative, and direct approaches to engage and monetise tangible support from their audiences and communities. Prior work has identified the evolution of crowdfunding in the arts as a form of ‘crowd patronage’ – where platforms such as Patreon and Kickstarter function as new intermediaries that can radically reconfigure how and why creative work is funded. The ‘pivot to digital’ – which brought audiences and creative workers together in new online spaces throughout the pandemic – further reinforced the potential for direct communication and financial support from audiences of creative work. This chapter will reflect on how contemporary data-driven, monetary technologies have begun to decentralise how creative work is valued, supported, and paid for, with a particular focus on the performing arts.

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.

Seen both as a resource and an obstacle to clarity, uncertainty is a concept that permeates many areas of design. As the concept gains prominence in Human-Computer Interaction (HCI), this special issue specifically explores the interplay between uncertainty and prototyping in Research through Design (RtD). We first outline three histories of uncertainty in design, in relation to its philosophical significance, its role in statistical and algorithmic processes, and its importance in prototyping. The convergence of these aspects is crucial as design evolves toward more agentive and entangled systems, introducing challenges such as Design as a Probabilistic Outcome. We then investigate the design spaces for engaging with “being uncertain” that emerge from the papers: from nuancing the relationship between designers and quantitative data to blurring the line between humans, fungi, and algorithms. Finally, we illuminate some preliminary threads for how RtD can navigate and engage with these shifting technological and design landscapes thoughtfully.

Research in the wild can reveal human behaviors, contexts, and needs around products that are difficult to observe in the lab. Telemetry data from the use of physical products can help facilitate in the wild research, in particular by suggesting hypotheses that can be explored through machine learning models. This paper explores ways for designers without strong data skills to engage with multimodal data to develop a contextual understanding of product use. This study is framed around a lightweight version of a data enhanced design research process where multimodal telemetry data was captured by a GoPro camera attached to a bicycle. This was combined with the video data and conversation with the rider to carry out an exploratory sensemaking process and generate design research questions that could potentially be addressed through data capture, annotation, and machine learning. We identify a range of ways that designers could make use of the data for ideation and developing context through annotating and exploring the data. Participants used data and annotation practices to connect the micro and macro, spot interesting moments, and frame questions around an unfamiliar problem. The work follows the designers’ questions, methods, and explorations, both immediate concerns and speculations about working at larger scales with machine learning models. This points to the possibility of tools that help designers to engage with machine learning, not just for optimization and refinement, but for creative ideation in the early stages of design processes.

Ethics should be a practice, not a checkbox. Data scientists want to answer questions about individuals and society using the vast torrent of data that flows around us. Machine learning practitioners want to develop and connect complex
models of the world and use them safely in critical situations. Ethical issues can be seen as getting in the way of the core idea and form pain points around managing, using and learning from data, as well as designing human-centric and ethical systems. This is because there is a design gap around ethics in data
science and machine learning: the tools that we use do not support ethical data use, which means that data scientists and machine learning practitioners, already engaged in technically complex, multidisciplinary work, must add another dimension to their thinking. This work proposes and outlines an infrastructure and framework that can support in-the-moment ethical decision
making and recording, as well as post-hoc audits and ethical model deployment.