BIG::AI is for Interactive AI
Our research in Interactive AI aims to bridge the gap between artificial intelligence systems and human users by making AI more understandable, explainable, and interactive. We study how users interact with AI-driven systems and develop new approaches for AI to support users in tasks like decision-making, learning, and creativity.
BIG::AI Members
Faculty
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Paul Marshall
Associate Professor of Human Computer Interaction -
Aisling O'Kane
Associate Professor of Human-Computer Interaction for Health -
Kenton O'Hara
Professor of Human-Computer Interaction
Researchers
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Ewan Soubutts
Senior Research Associate -
Matthew Guy
Senior Research Associate in AI for Health Ecosystems
Recent Publications
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Integrating Technology into Self-Management Ecosystems: Young Adults with Type 1 Diabetes in the UK using Smartwatches
Sam James, Miranda Armstrong, Zahraa Abdallah, Harry Emerson & Aisling O'Kane
CHI Conference on Human Computer Interaction, 2025. -
Rethinking Lived Experience in Chronic Illness: Navigating Bodily Doubt with Consumer Technology in Atrial Fibrillation Self-Care
Rachel Keys, Paul Marshall, Graham Stuart & Aisling O'Kane
CHI Conference on Human Computer Interaction, 2025. -
The potential and challenges of AI for collective intelligence
Christoph Riedl, David Cremer, Gina Lucarelli, Erika Antoine-Souklaye, Seth Bullock, Nirav Ajmeri, Mike Batty, Michaela Black, John Cartlidge, Robert Challen, Cangxiong Chen, Jing Chen, Joan Condell, Leon Danon, Adam Dennett, Alison Heppenstall, Paul Marshall, Phil Morgan, Aisling O'Kane, Laura Smith, Theresa Smith, Hywel Williams, Niccolo Pescetelli & Georgina Denis
Collective Intelligence, 2025. -
Data Ethics Emergency Drill: A Toolbox for Discussing Responsible AI for Industry Teams
Vanessa Hanschke, Dylan Rees, Merve Alanyali, David Hopkinson & Paul Marshall
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2024. -
Computational Notebooks as Co-Design Tools: Engaging Young Adults Living with Diabetes, Family Carers, and Clinicians with Machine Learning Models
Amid Ayobi, Jacob Hughes, Christopher Duckworth, Jakub Dylag, Sam James, Paul Marshall, Matthew Guy, Anitha Kumaran, Adriane Chapman, Michael Boniface & Aisling O'Kane
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023.