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As Artificial Intelligence (AI) and sensing technologies become embedded in daily life, their potential to transform care is undeniable. Yet, while these tools promise real-time insights, personalized interventions, and support for behavior change, their adoption seldom addresses integration of people’s everyday care ecologies and a limited focus on privacy, bias, and other ethical challenges. This means that AI-driven health interventions often fall short in proactive care, as they focus on improving technical efficiency but do not guarantee compatibility with lived experiences or provide meaningful insights into them. This workshop critically examines the role of AI and sensing systems in health and wellbeing, adopting a human-centered perspective for proactive care. By convening researchers, designers, and practitioners from HCI, AI, health, and related fields, we will explore strategies to enhance the effectiveness of sensing and AI in proactive care. Our goal is to shape health technologies that prioritize accessibility, inclusivity, and alignment with users’ lived experiences, ensuring ethical and impactful innovations across diverse care contexts.

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In this one-day workshop we aim to collaboratively step towards developing a framework or vocabulary to critique and reflect on granular attributes and properties of design and interaction of healthcare technology in conjunction with the relational and situated aspects inherent in the larger assemblage it is part of. Many healthcare technologies are designed with efficiency and optimization as their primary focus, paying little attention to the experience, context and relations the artifact enters when deployed. We experience a mismatch between healthcare technologies and the newer vocabularies for engaging critically with the design and interaction of artifacts. It is essential to bring together researchers engaging with fourth wave approaches, healthcare technologies, and healthcare practitioners towards bridging this gap.

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As artificial intelligence (AI) and machine learning (ML) become increasingly embedded in healthcare systems, they are reshaping care workflows and introducing uncertainty and risks associated with value conflicts, including around trust, privacy, and collaboration. While research in Value Sensitive Design has largely focused on individual and professional values, organisational and societal dimensions remain underexplored, leaving a critical gap in addressing broader ethical and socio-technical implications. This half-day, in-person workshop seeks to bring together researchers, designers, developers, healthcare professionals, patients and ethics officers to identify and explore value tensions in AI-enabled healthcare technologies, considering their implications not only for individuals but also for organisations, societal structures, and care environments. Through participatory and cross-disciplinary activities, including speculative design, participants will surface tensions, co-create artifacts envisioning futures, and reflect on human-centred implications to guide responsible design, evaluation and deployment of AI-enabled technologies in health contexts.

Organizers

Description

The Interactive Health (IH) Conference aims to foster a community of researchers and practitioners working at the intersection of Human-Computer Interaction (HCI) and Health. In line with this vision, we propose a workshop that builds on our ongoing initiative, the AIxHealth Research to Impact Collaborative, which seeks to cultivate a global, interdisciplinary community of researchers and practitioners working at the intersection of Artificial Intelligence (AI) and Health Equity, with the goals of enabling critical reflection, collaborations, and resource-sharing. Through this workshop, we aim to join hands with the IH community, which will allow us to expand the AIxHealth community and continue working on key goals, such as co-creating a research agenda that reflects a collective vision of researchers and practitioners across geographies, while amplifying IH’s priorities for global participation. We invite researchers and practitioners working across diverse topics in AI and health, including those engaged in community-driven efforts or adopting critical perspectives, to participate in our discussions, craft a shared research agenda for a responsible integration (or disintegration) of AI in health, and join in our vision of forming and fostering the AIxHealth collaborative.

Organizers

Description

Artificial Intelligence (AI) is increasingly embedded in healthcare, extending from clinical and informal care settings to everyday activities like sports, transportation, and workplace environments. The use of personal data for health monitoring, therapy and care support entails data practices and raises trust, privacy and security challenges, where patients, healthcare professionals, and device providers have different notions of trust. While regulatory cornerstones like the European Health Data Space Regulation (EHDS) aim to empower individuals to share their health data in a trustworthy manner, it is still not clear how HCI research communities should balance between personalization and privacy in health monitoring contexts, implement and evaluate trust, privacy- and security-preserving mechanisms in a transparent and culturally appropriate way, and take the interests of healthy individuals, patients, and care teams on board. At the intersection of trust, privacy, security, and health research, a shared Human-Computer Interaction (HCI) research agenda is needed to map visions and define safeguards for AI-supported healthcare. This workshop will bring together clinicians, patients and the community of academic and industry researchers and practitioners in Human-Computer Interaction at the intersection of HCI, Medical Informatics, Health Informatics, Data Science, Biomedicine, Psychology, Digital Health, Area Studies, Trust, and Privacy and Security research. In this in-person workshop, we will develop a joint understanding of research visions for trust, privacy, and security in AI-supported healthcare. Together, we will define safeguards, which will be followed by a human-AI interaction prototyping session. Through this interdisciplinary and collaborative exchange, our objective is to establish a roadmap and develop safeguards that help the HCI community systematically integrate trust, privacy, and security principles into the health domain, informing academic and industrial research and evaluation practices.

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Designing effective interactive health systems requires rich, realistic data to inform user-centered design activities. However, accessing authentic health data introduces major barriers due to privacy rules (HIPAA, IRBs, data use agreements) governing protected health information. These barriers heavily affect early-stage design and limit opportunities to design for underserved populations and rare health conditions. Generative AI offers a path forward by enabling creation of synthetic health data that preserves realistic context while avoiding actual patient information. AI artifacts—including patient personas, clinical scenarios, and interaction patterns—could enable rapid prototyping that would otherwise require lengthy approvals and data access requests. However, research on synthetic data for interactive health systems design remains limited. This workshop will bring together HCI researchers and experts to explore how AI-generated synthetic data might enable new approaches to user-centered design across four key themes: (1) rapid prototyping and early-stage design exploration, (2) appropriate vs inappropriate use cases for synthetic data in health HCI research, (3) risks, limits, and ethical considerations in using synthetic data, and (4) improving design and educational practices for interactive health systems. We aim to build a community around exploring how synthetic data can support user-centered health design while ensuring appropriate use, validity, and ethical practices.

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Collaborative healthcare is shaped by complex negotiations among patients, caregivers, and clinicians, yet current technologies focus primarily on monitoring and adherence, offering limited support for shared decision-making. Differences in knowledge, power, and goals often generate tension around treatment, lifestyle, and data-sharing decisions. Recent advances in GenAI and LLMs open the possibility for AI to act as a mediator, translating clinical evidence into patient-relevant insights, visualizing trade-offs, and supporting negotiation without overriding human agency. This workshop aims to bring together an interdisciplinary mix of HCI researchers, AI practitioners, clinicians, and designers to explore AI-mediated collaboration. Through hands-on activities, participants will discuss design challenges and opportunities, identify ethical and socio-technical tensions, create speculative design stories, and future research avenues. The goal is to develop a shared research agenda for interactive health systems that foster equitable negotiation, respect stakeholder agency, and place human relationships at the center of collaborative care.

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This three-hour workshop invites the IH community to explore how AI could support and shape ecologies of future palliative care across end-of-life transitions (living, dying, and bereavement). To envision more holistic and sustainable AI-supported palliative care, we frame transitions through three layers of care (individual, community, and professional services) and adopt a relational approach inspired by More-than-Human design practices. This approach foregrounds how AI is entangled with diverse users across these layers. Using speculative and participatory design methods, participants will envision AI-supported care futures and identify emerging research directions at the intersection of palliative care, HCI, and AI. Building on prior ACM workshops combining perspectives on AI, clinical practice, and care in sensitive life transitions, this workshop offers a space to reflect on key challenges and opportunities, and to co-develop design principles as a shared roadmap toward relational, responsible, and sustainable futures of AI in palliative care.