As part of the pre-conference program on July 6 and 7, a series of workshops and a doctoral consortium will take place. A description of each event can be found below. Check the websites of the workshops for the respective Calls for Papers.
All morning sessions take place from 09.00 to 13.00, with a coffee break at 10.30. All afternoon sessions take place from 14.00 to 18.00, with a coffee break at 16.00.
Workshops
Third International Workshop on Reciprocal Knowledge Elicitation for Human-Agent Collaboration
https://eavise.gitlab.io/rkehac/2026/
Traditional knowledge elicitation techniques (e.g., interviews) are a crucial element of modern research but are often accompanied by several shortcomings or biases (e.g., memory misattribution) which makes choosing the right technique imperative. Reciprocal knowledge elicitation describes the beneficial application of mutual knowledge elicitation and knowledge provision between members of a human-agent team. The design of reciprocal knowledge elicitation remains so far unexplored. This workshop aims to identify and scope the relevant context for knowledge elicitation techniques in general and to elevate techniques by applying human-agent collaboration. For the main outcomes, we aim for a domain-specific overview of relevant attributes and a formalized representation of knowledge elicitation techniques.
Hybrid Intelligence for Health Care
https://hi4healthcare.github.io/
This full-day workshop aims to build an interdisciplinary research community for people who are interested in developing hybrid intelligence (HI) systems for health care and well-being. This requires people from various related fields such as computer science, human-computer interaction, psychology, medicine, etc., to exchange their perspectives and collaborate. Therefore, we also want to focus on community building, interdisciplinary exchange, and discussion among participants.
This workshop will contain a combination of a keynote, lightning talks and an interactive session to work out common building blocks for the various health care applications, using design patterns. As with the previous workshop (Hybrid Intelligence for Health Care (2024)), the goal is to jointly write a paper after the workshop.
Third Workshop on Frictional Design in Hybrid Human-AI Systems
https://sites.google.com/view/frictional-ai/home
In its third edition, this workshop builds on and expands its exploration of friction-in-design in AI systems, hosting a full-day event that challenges the pursuit of seamless, rapid interactions. In contrast to the conventional narrative that human over-reliance on AI stems solely from cognitive biases, we emphasize the critical role of designers and developers in fostering user empowerment, skill retention, and ethical responsibility.
This approach advocates for a balanced perspective on Human-AI interaction: one that harmonizes operational efficiency with the demands of meaningful, mindful, and effective human knowledge work.
Central to our discussion is the concept of ‘friction-in-design’ or ‘frictional protocols’ in AI systems, which are deliberate design choices that introduce moments of reflection and cognitive engagement, even at the expense of speed. The main aim of these protocols is reducing risks of over-reliance on AI.
The programme will include paper presentations, a keynote, structured discussions, and a participatory design session. Participants will explore the potential of ‘Frictional AI’ to collaboratively shape future research and practices that ensure AI use remains meaningful and responsible.
Imagining the AI Landscape after the AI Act
The Fifth Workshop on Imagining the AI Landscape after the AI Act (IAIL)
explores the evolving European regulatory framework for Artificial
Intelligence, with particular attention to the AI Act and the proposed Digital
Omnibus. As the European Union advances a comprehensive approach to AI
governance, significant challenges remain in translating regulatory principles
into practical tools for research and technological development.
The workshop brings together scholars, technologists, policymakers, and
stakeholders to discuss the operationalization of AI regulation and its
implications for innovation, transparency, and fundamental rights. Topics
include the implementation of AI Act requirements, the regulation of
generative AI and large language models, AI risk assessment, and the broader
relationship between regulation and innovation.
Through interdisciplinary dialogue, the workshop aims to foster a deeper
understanding of how AI technologies can be developed and deployed responsibly
within the European regulatory landscape.
Reimagining Human Oversight: An Interactive workshop on Experiential Design of Adaptive Oversight in Complex AI System
Contact: Melissa.Wittens@imec.be
The EU AI Act mandates human oversight (HO) for high-risk AI systems, yet it provides limited guidance on how such oversight should be designed and implemented in complex sociotechnical systems. As a result, oversight risks becoming symbolic rather than meaningful, reinforcing the “human-in-the-loop illusion,” where the presence of a human operator does not necessarily guarantee understanding or effective intervention.
This interactive workshop introduces a participatory framework for designing meaningful and adaptive human oversight strategies in AI systems. Participants will analyze an AI system architecture prepared by the organizers, identify key decision points, and use an interactive evidence-based board game to explore appropriate levels of human oversight.
Participants will also examine potential failure scenarios and discuss how responsibilities for monitoring, accountability, and intervention can be realistically distributed across human and technical actors. Through scenario-based exercises and discussion, the workshop highlights tensions between automation and control and supports the development of context-sensitive oversight configurations.
We welcome participants from all backgrounds and disciplines who are interested in AI governance, system design, or responsible AI deployment. No prior experience is required.
If you are encountering challenges with a specific use case, you can fill in this optional questionnaire. Your anonymized input will be incorporated to help identify shared issues and support the plenary discussion at the end of the session.
More-Than-Human Simulated Interactions as Hybrid Intelligene for Contemporary Challenges
We present an interactive workshop as a novel initiative that picks up and combines several ongoing conversations and trajectories that intersect with Hybrid Human-Artificial Intelligence: Socio-technical and socio-ecological entanglement, non-human and more-than-human design, AI-generated synthetic personas, and AI-powered persona simulations. Acknowledging the limitations of generative AI, we invite participants to co-create non-human personas with Large Language Models (LLMs) and include them as interactive simulations (powered by LLMs) to explore how they can support speculations on different contemporary challenges. While additional topics are welcome, we propose three general ones: Technologies in reproductive care relationships, accessible learning experiences, and sustainable technology development.
MULTITTRUST Multidisciplinary Perspectives on Human-AI Team Trust
https://multittrust.github.io/5ed/
This workshop originates from the need to create a multidisciplinary research community of people who study the different perspectives and layers of trust dynamics in teams consisting of both humans and AI agents. Four successful previous editions of this workshop ran in 2023, 2024, and 2025, and in the current edition, we are aiming to continue this momentum to grow this community.
With the increasing prominence of human-agent interaction in hybrid teams in diverse industries, human-agent teamwork is no longer a topic of the future, but of the present. However, several challenges arise that still need to be addressed carefully. One of these challenges is understanding how trust is defined and how it functions in human-agent teams. This challenge requires an inter-disciplinary approach.
Together, we intend to shape the road to address these questions to guarantee a successful and trustworthy human-AI agent teamwork. In this workshop, we aim to share research work through short presentations, build community through encouraging interaction and collaboration, and stimulate discussions with different interdisciplinary perspectives to drive the research on trust in human-AI teams.
Social & Emobied Intelligence for Multimodel Human-AI Interaction
https://cv-ac.github.io/SEI_HHAI2026/
Human communication is inherently social, embodied, and multimodal. People express intentions and emotions through speech, facial expressions, gestures, and body movements. Although recent advances in artificial intelligence have significantly improved machine perception and generation, current AI systems still struggle to understand and participate in socially meaningful human interactions. This workshop explores the emerging research area of Social and Embodied Intelligence for Multimodal Human–AI Interaction, focusing on enabling AI systems to perceive, interpret, and generate socially relevant multimodal behaviors. By integrating multimodal perception, emotion understanding, and generative AI, such systems can better recognize human affective states and respond to social cues. The workshop aims to bring together researchers from AI, computer vision, speech processing, human–computer interaction, and affective computing to discuss recent advances and future directions in socially intelligent multimodal AI systems.
Workshop on Health, Wellbeing and Human-AI Interaction (HAII)
Call for papers here.
The workshop will gather individuals with expertise and interest in challenges and opportunities relating to health, wellbeing and HAII. The schedule will include a leading expert keynote, plenary talks, opportunities for Q&A and a facilitated discussion of key topics. We will close with a discussion of future research directions, opportunities for maintaining a community interest in the theme and the possibilities for future research workshops and events on the theme.
2nd Workshop on Informing ML with Knowledge Engineering for Hybrid Intelligent Systems
Integrating Knowledge Engineering (KE) with Machine Learning (ML) offers a promising approach to building trustworthy AI systems. By combining the strengths of data-driven learning with structured knowledge—such as electronic health records in healthcare, scientific axioms, or legal guidelines—AI systems gain the ability to perform commonsense reasoning, enhancing their reliability and making them more knowledge-aware. Although using knowledge representation and reasoning methods can sometimes limit scalability, their ability to provide verifiable, human-understandable explanations makes them especially valuable in mission-critical applications.
The workshop seeks to bridge the gap between KE and ML by exploring the synergies between these fields. A key focus is on developing hybrid human-AI systems that utilize multimodal approaches, incorporating various forms of data including text, speech, images, and video. This collaborative forum will bring together researchers and practitioners from academia and industry to discuss cutting-edge research and innovative strategies for integrating KE and ML. Ultimately, the goal is to advance the development of AI systems that are not only robust and efficient but also transparent and human-centric, addressing both the challenges and benefits of merging knowledge representation and reasoning with data-driven techniques.
Check out our previous year program and proceedings here HHAI-KEML 2025 Workshop