Frictional Design in Hybrid Human-AI Systems
July 7, 2026, Brussels, Belgium
Full-day Workshop
Previously Workshop on Stimulating Cognitive Engagament in Hybrid Decision-Making
Topics of the Workshop
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 overreliance on AI.
In this third edition, we are also focusing on frictional protocols to foster prosocial goals. Through accepted papers and our keynote address, we will explore nudging in design and other frictional design techniques that are implemented for the purpose of favoring socially beneficial outcomes in AI usage, from recommenders to decision support systems.
The programme includes a keynote, paper presentations, structured collaborative discussions, and a participatory design session. Following the workshops, authors are invited to extend their abstracts into a short paper, and join the fledgling Frictional AI research community.
Together, we will explore the potential of Frictional AI to collaboratively shape future research and practices that ensure AI use remains meaningful and responsible.
Call for Extended Abstracts (500-1,000 words)
Submission Deadline: May 1, 2026 AoE
Author Notification: May 29, 2026 AoE
Workshop (Brussels, Belgium): July 7, 2026
Camera-ready of short paper version (5 pages): September 7, 2026 AoE
We invite extended abstracts from researchers, practitioners, and policymakers on topics including (but not limited to):
Design Principles for Cognitive Engagement: interaction strategies that balance efficiency with reflection and critical engagement.
Methods to Measure Overreliance and Underreliance: frameworks, metrics, or empirical studies assessing how AI affects human judgement, expertise, and decision behaviour.
Trust Calibration and Transparency: investigations of how explanations, uncertainty communication, or interface design influence trust and reliance.
Governance and Policy Approaches: legal, regulatory, or organisational perspectives on incorporating frictional principles into AI deployment and oversight.
Applications and Case Studies: empirical studies, prototypes, or deployments demonstrating seamful or frictional interaction patterns in practice.
A collected volume of HHAI 2026 Workshop and Tutorial proceedings will be compiled under the CEUR-WS umbrella after the conference.
Author Guide
Abstract Length: 500–1,000 words not including references.
IMPORTANT: To be included in the workshop proceedings, authors will be required after the workshop to expand their abstract into a 5-page short paper.
Format: submissions must follow the CEUR-WS single-column format. This format will be required also for the 5-page camera-ready version to be submitted after the workshop.
Ready-to-use templates are available: Overleaf (LaTeX) template; Word template; ODT template.
Review Process: single-blind — authors should include their name(s) and affiliation(s).
Submission Portal: https://cmt3.research.microsoft.com/FrictionalAI2026/
Programme Committee
To Be Announced
Workshop Committee
Chiara Natali (University of Milano-Bicocca, Italy, Human-AI Interaction)
Fabio Michele Russo (IMT School for Advanced Studies Lucca, Italy)
Simon WS Fischer (Radboud University, The Netherlands)
Manni Cheung (University of Cambridge, UK, Computing Education)
Brett M. Frischmann (Villanova University, USA, Law, Business and Economics)