Advances in emerging technologies, such as on-body mechanical actuators and electrical muscle stimulation, have allowed computers to take control over our bodies. This presents opportunities as well as challenges, raising fundamental questions about agency and the role of our bodies when interacting with technology. To advance this research field as a whole, we brought together expert perspectives in a week-long seminar to articulate the grand challenges that should be tackled when it comes to the design of computers’ control over our bodies. These grand challenges span technical, design, user, and ethical aspects. By articulating these grand challenges, we aim to begin initiating a research agenda that positions bodily control not only as a technical feature but as a central, experiential, and ethical concern for future human–computer interaction endeavors.

Human autonomy is a core concept that helps explain the acceptance of and interaction with computer systems and AI technology. However, autonomy is often vaguely defined and conflated with related constructs. This paper disentangles autonomy by integrating the dualistic nature of positive and negative liberty from the perspective of political philosophy. Using an online vignette study with N=194 participants, we show that positive and negative liberty act as correlated but distinct dimensions of the autonomy foundation. While negative liberty predicts the sense of agency, positive liberty is a key dimension for people’s willingness to use technology. We argue that this dualistic stand - positive liberty as the freedom to pursue authentic goals, and negative liberty as the freedom from external constraints - offers a valuable and actionable perspective on human autonomy that can inform future system design and better answer the ambivalent question “how much autonomy is enough”?

In high-stakes decision-making, the acceptance of AI recommendations depends not only on system accuracy but also on how decisions are explained. While prior work on explainable AI has largely focused on transparency and interpretability, less attention has been paid to the persuasive dimension of explanations. To address this gap, we investigate how rhetorical strategies drawn from Cialdini’s persuasion theory, when embedded in natural language explanations generated by large language models (LLMs), influence user compliance and their ability to recognize persuasive intent. We conducted a controlled survey study with 129 participants in two application domains—finance and healthcare—where participants evaluated both a baseline and a persuasive explanation for an AI-generated decision across favorable and unfavorable outcomes. In a complementary task, participants rated ten short explanations on perceived persuasiveness and factual strength, enabling us to measure awareness of persuasive intent. Our results show that persuasive explanations significantly increased compliance in the healthcare scenario (p <.001), whereas baseline explanations were more effective in finance (p <.001), regardless of whether the AI decision was positive or negative. A notable proportion of participants rated explanations containing at least one of Cialdini’s persuasion techniques as highly persuasive, yet simultaneously judged them to be factually weaker. Importantly, we found no statistically significant evidence that participants’ ability to recognize persuasive intent influenced compliance. These findings highlight the dual role of persuasive explanations: they can enhance foster compliance in sensitive contexts such as healthcare but risk undermining trust in domains like finance. For HCI and IUI, our study underscores that explanations are not neutral vessels of information: their rhetorical form substantially shapes how users perceive and engage with AI-assisted decision-making. Designers of explainable AI systems should therefore carefully balance transparency and persuasion when developing interfaces for high-stakes applications.

Promoting sustainable mobility requires technological innovation and changes in individual travel behavior. Using the Theory of Planned Behavior, we examined how attitudes, norms, and perceived control shape the willingness to adopt alternatives to car use. We designed 38 future commuting scenarios, each of which isolated a single dimension across three mobility concepts: public transportation, cycling, and shared automated vehicles. In an online survey (N = 168), participants rated their willingness to switch modes and pay more. To deepen our understanding, we conducted follow-up interviews (N = 10), exploring their everyday mobility practices and their likes and dislikes regarding the practicality of the future scenarios. Our findings show that features linked to instrumental attitudes and control beliefs elicit stronger intentions than affective cues, ecological appeals were less persuasive. We argue that effective behavior change depends on linking motivational factors to the realities of everyday mobility contexts.

An immersive single-user virtual reality system possesses the potential to induce a paradigm shift in the realm of professional training, particularly within safety-intensive and complex procedural domains. This innovative system offers a safe, adaptable, engaging, and efficacious training experience, thereby fostering better task performance, reduced errors, and more favorable outcomes. Our goal is to delve into the opportunities and challenges associated with such training programs, while also providing guidelines for their seamless integration into educational curricula. Three case studies were conducted to gauge the efficacy of single-user VR training: the electricians’ scenario (N=30), a spatial orientation scenario (N=20), and a medical trolley scenario (N=21). Employing mixed methodologies, encompassing workshops, semi-structured interviews, and observatory data collection, insights were gathered. The core objective of this investigation was to assess the perceptions of potential users, notably those partaking in apprenticeships or vocational training, toward prototypes of single-user VR training. The study’s findings emphasize the inherent value and constructive attributes of integrating single-user VR training within the realm of professional development. This integration fosters practical experiential learning in procedures and essential competencies for ensuring safety, resulting in enhanced training outcomes. The study showcased augmented individualized learning tempos, expanded opportunities for repetition, heightened concentration, and deeper engagement within the VR-based instructional environment. Moreover, the study underscored the crucial role of personalized design enhancements and continuous content evolution to maximize the effectiveness of VR-based training methodologies. Integral to the comprehensive evaluation was the significance of user experience and the perceived value of the VR system. In parallel with the empirical investigation, foundational design principles were derived from the challenges and prospects unveiled across all three case studies.

Recently, researchers have proposed to develop automated self-balancing functions for bicycles to increase road safety and convenience. However, no study has investigated how self-balancing bicycles are perceived by potential users in a natural urban environment. Therefore, we conducted a field study using a modified “parent-child tandem” in which both the front and back seat passengers could share control of the riding dynamics. An experimenter in the back seat acted as an automated system, and participants in the front seat experienced the ride while responding to text messages on their smartphones. Based on interviews, video observation, and eye-tracking data, the results highlight potential use cases for self-balancing bicycles and uncover that trust and multitasking freedom can lead to similar problems as in automated cars.