Sandra Ohly

Christoph Anderson, Judith Simone Heinisch, Shohreh Deldari et al.

Pervasive and ubiquitous computing facilitates immediate access to information in the sense of always-on. Information such as news, messages, or reminders can significantly enhance our daily routines but are rendered useless or disturbing when not being aligned with our intrinsic interruptibility preferences. Attention management systems use machine learning to identify short-term opportune moments, so that information delivery leads to fewer interruptions. Humans' intrinsic interruptibility preferences - established for and across social roles and life domains - would complement short-term attention and interruption management approaches. In this article, we present our comprehensive results towards social role-based attention and interruptibility management. Our approach combines on-device sensing and machine learning with theories from social science to form a personalized two-stage classification model. Finally, we discuss the challenges of the current and future AI-driven attention management systems concerning privacy, ethical issues, and future directions.

Christoph Anderson, Clara Heissler, Sandra Ohly et al.

Determining and identifying opportune moments for interruptions is a challenging task in Ubiquitous Computing and Human-Computer-Interaction. The current state-of-the-art approaches do this by identifying breakpoints either in user tasks, activities or by processing social relationships and contents of interruptions. However, from a psychological perspective, not all of these breakpoints represent opportune moments for interruptions. In this paper, we propose a new concept in the field of interruptibility. The concept is based on role theory and psychological interruption research. In particular, we argue that social roles which define sets of norms, expectations, rules and behaviours can provide useful information about the user's current context that can be used to enhance interruption management systems. Based on this concept, we propose a prototype system architecture that uses social roles to detect opportune moments for interruptions.