Hybrid Intelligence for Healthcare

This full-day workshop is an initiative of the HI-TNO collaboration and aims to build an interdisciplinary research community for people who are interested in developing hybrid intelligence (HI) systems for health care and well-being. The workshop will contain a combination of a keynote, lightning talks and an interactive session to work out common building blocks for various health care applications, using a design pattern approach. During the workshop, we will work on different design patterns that we may encounter when working on HI systems in healthcare settings. We aim to provide a space for sufficient communication and discussion, to build further on an interdisciplinary community for HI for health care and define commonly used design patterns that can be used in future research. Additionally, we have as goal to jointly write a paper after the workshop with the participants.

The workshop setup will be based on two different prior workshops, namely Hybrid Intelligence for healthcare (HHAI 2024, workshop website) and Human-Centered Design of Symbiotic Hybrid Intelligence (HHAI 2022, workshop website).

See also the output from those workshops:

[1] Dudzik, B. J., van der Waa, J. S., Chen, P. Y., Dobbe, R., de Troya, Í. M., Bakker, R. M., ... & Kamphorst, B. A. (2024). Hybrid intelligence supports application development for diabetes lifestyle management. Journal of Artificial Intelligence Research, 80, 919-929.

[2] Van Zoelen, E., Mioch, T., Tajaddini, M., Fleiner, C., Tsaneva, S., Camin, P., ... & Neerincx, M. A. (2023). Developing team design patterns for hybrid intelligence systems. In HHAI 2023: Augmenting Human Intellect (pp. 3-16). IOS Press.

Background

As technology, particularly intelligent systems, becomes more integrated into people’s daily life, AI-based systems designed to facilitate lifestyle change or behavior change for health and well-being become more common as well. However, there is still a long process going from research that develops such support systems to deploying such systems in people’s everyday life.

In particular, the challenges associated with the development and deployment of AI-based support systems call for a shift toward a human-centered design approach to design applications in which humans and AI co-evolve over time through mutual adaptation and continuous improvement. This approach can be addressed by HI. Specifically, human capabilities are augmented by their complementary AI capabilities, thus achieving improved results overall. To achieve a better understanding of how HI systems can support health care and well-being and to explore the key challenges for HI systems for health care, this workshop will focus on addressing why we need HI and how HI differs from just AI-based systems for health care. During the interactive session, we will map out design patterns for different healthcare applications following human-centered design principles (see figure below for an example).

Developing HI systems for health and well-being is an interdisciplinary research effort by nature. This requires people from various related fields such as computer science, human-computer interaction, psychology, medicine, etc., to exchange their perspectives and collaborate. Therefore, in this workshop, we also want to focus on community building, interdisciplinary exchange, and discussion among participants.

Tentative Schedule

Time Activity
9:00 - 9:15 Welcome
9:15-10:00 Keynote by Judith Masthoff
10:00-10:15 Break (*depending on the HHAI program)
10:15-12:00 Lightning Talks
12:00 - 13:00 Lunch
13:00-13:15 Introduction of Design Patterns
13:15-15:45 Creation of Design Patterns (in groups)
15:45 – 16:00 Break (*depending on the HHAI program)
16:00 - 16:45 Plenary session to show the design patterns and discuss common patterns
16:45-17:00 Closure

Keynote by Judith Masthoff

Judith Masthoff is a full professor in the Human-Centered Computing group at Utrecht University. She researches intelligent user interfaces, specializing in personalization, persuasive technology, and adaptive systems for domains including e‑health, sustainable transport, and education. Her work on group adaptation and personalized e‑learning covers topics such as adaptive tutoring, feedback, exercise selection, and emotional support. Her projects cover topics such as diabetes walking coaches, study motivation, sustainable mobility, elder social interaction, and cancer self‑monitoring. She is part of the AI4Health consortium, which recently received long-term funding for research on making AI useful for care professionals and patients.

Submissions

We invite people to submit a two-page, single space, single column extended abstract that describes your application or envisioned system on HI in health care. We do not require the submissions to be current work in progress: the goal of the submission is for us to have potential HI systems in health care to create the design patterns with. The papers can be added to the postproceedings (optional). Please follow the Frontiers of AI series by IOS Press format. The submission format is single-blind. The link to the EasyChair submission page is here: HI4healthcare.

Important Dates

Organizing Team

Maaike de Boer

Maaike de Boer (PhD) is a senior Scientist at TNO within the Data Science department. At TNO Maaike focuses on Hybrid AI – specifically combining language models and knowledge graphs / ontologies. She is part of the transfer lab between TNO and the Dutch Hybrid Intelligence program, and (co-)leads the case study on the Health Care domain.



Emma van Zoelen

Emma van Zoelen is a scientist at the TNO Human-Machine Teaming department. She recently finished her PhD on human-machine co-learning, in which she studied collaboration patterns that emerge as a result of human and machine adaptivity. At TNO, she researches human-machine interactions and collaborations as well as topics related to responsible AI. She is part of the transfer lab between TNO and the Dutch Hybrid Intelligence program, and (co-)leads the case study on the Health Care domain.

Mark Neerincx

Mark Neerincx is full professor in Human-Centered Computing at the Delft University of Technology, and principal scientist at TNO Human-Machine Teaming. His research focuses on the socio-cognitive engineering of human–agent/robot collaboration across domains such as healthcare, security, and defense, with the aim of enhancing social, cognitive, affective, and physical processes and enabling meaningful human–agent partnerships. This work emphasizes sustained, memory-based agent support for meaningful activities and moral decision-making, fostering reflective processes, value awareness, and adaptive human–agent collaboration over time.

Annette ten Teije

Annette ten Teije is full professor of Artificial Intelligence in Medicine at the Vrije Universiteit Amsterdam (Learning&Reasoning group), and she specializes in decision systems within the medical field. Her research encompasses various medical domains, including medical guidelines, quality indicators, and clinical studies. Ten Teije’s primary focus lies in the application of knowledge-driven methods and their integration with data-driven approaches. She is particularly interested in formalizing architecture patterns for systems that combine learning and reasoning, as well as developing a theory to determine the appropriate use of these patterns.

Program Committee

For more information: please email us using hi4healthcare@gmail.com.