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CALL FOR EXTENDED ABSTRACTS
Third Workshop on Frictional Design in Hybrid Human-AI Systems
Co-located with the 5th International Conference on Hybrid Human-Artificial Intelligence (HHAI26)
July 7, 2026 | Brussels, Belgium (in-person)
Workshop website: https://sites.google.com/view/frictional-ai/home
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Workshop Overview
This full-day workshop explores frictional design strategies in Human–AI interaction: design patterns that deliberately create moments of reflection, critical thinking, and cognitive effort in AI-supported decision-making.
While contemporary AI systems are typically optimised for efficiency and seamless interactions, growing evidence in HCI, cognitive science, and safety-critical domains shows that overly smooth interaction can promote cognitive offloading, automation bias, over-reliance, and skill erosion. Frictional design examines when and how interaction mechanisms can slow down decision-making at appropriate moments in order to support human oversight, judgement, and appropriate reliance.
Example mechanisms include:
– requiring users to reason themselves before accessing AI support and/or scaffold reasoning through staged or reflective interaction
– introducing novel uncertainty visualisations, present explanations or evidence in ways that prompt active scrutiny
– any other approach that balances or favours cognitive engagement over seamless usability and speed
Building on the success of the two previous editions, this workshop aims to advance an interdisciplinary dialogue between scholars across HCI, AI, cognitive science, and AI governance. The programme will include paper presentations, a keynote, structured discussions, and collaborative activities aimed at developing a shared research agenda for stimulating cognitive engagement in human-AI interactions.
Keynote
Bogdana Rakova (DLA Piper, Data & Society Research Institute, ex-Mozilla Fellow)
Talk: “Speculative Friction: Exploring existing, speculative, and instrumental frictions in AI design and governance”
Topics of Interest
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 Over-Reliance and Under-Reliance (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)
Submission Details
– Submission type: Extended Abstracts (500–1,500 words – to be extended to 5 pages for the post-workshop proceedings)
– Format: CEURART-WS template (see workshop website)
– Submission system: https://cmt3.research.microsoft.com/FrictionalAI2026
Accepted papers will be published in the HHAI 2026 Workshop Proceedings (CEUR-WS).
At least one author of each accepted paper must attend the workshop in person and register for the HHAI conference (single-day registration options available).
Important Dates (AoE)
– Submission deadline: 1 May, 2026
– Notification: 29 May, 2026
– Camera-ready: 19 June, 2026
– Workshop: 7 July, 2026
Beyond the Workshop
This workshop series aims to build a research community around frictional and cognitively engaging AI design. Authors and participants will be invited to contribute to follow-up initiatives, including collaborative publications, special issues, and future events.
Interested researchers can join the mailing list: https://www.freelists.org/list/friction
Organisers
Chiara Natali, Vrije Universiteit Amsterdam
Fabio M. Russo, IMT School for Advanced Studies Lucca
Simon W. S. Fischer, Radboud University
Manni Cheung, University of Cambridge
Brett Frischmann, Villanova University
For further information: https://sites.google.com/view/frictional-ai/home
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