MuM'23 Workshop on Interruptions and Attention Management
Alexander Lingler (University of Applied Sciences Upper Austria, School of Informatics, Communications and Media)
Dinara Talypova (University of Applied Sciences Upper Austria, School of Informatics, Communications and Media)
Fiona Draxler (Ludwig Maximilians University)
Christina Schneegass (TU Delft - Human Technology Relations)
Tilman Dingler (TU Delft - Human-Centred Artificial Intelligence)
Philipp Wintersberger (University of Applied Sciences Upper Austria, School of Informatics, Communications and Media, Technische Universität Wien)
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Abstract
Attention management systems seek to minimize disruption by intelligently timing interruptions and helping users navigate multiple tasks and activities. While there is a solid theoretical basis and rich history in HCI research for attention management, little progress has been made regarding their practical implementation and deployment. Building sophisticated attention management systems requires a great variety of sensors, task- and user models, and multiple devices while considering the complexity of user context and human behavior. Novel AI technologies, such as generative systems, reinforcement learning, and large language models, open new possibilities to create intelligent, practical, and user-centered attention management systems. This proposed workshop aims to bring together researchers and practitioners from diverse backgrounds to discuss and formulate a research agenda to advance attention management systems using novel AI tools to manage and mitigate interruptions from computing systems effectively.