Big Data for People

Human-Computer Interaction Researcher
Manager, Human Interfaces Group
Mission Operations
NASA Jet Propulsion Lab
Finding-appropriate-roles-for-ai-in-the-home-experiences-learning-dual-income-family-routines

Finding appropriate roles for AI in the home: Experiences learning dual-income family routines

Scott Davidoff. 2011. Finding appropriate roles for AI in the home: Experiences learning dual-income family routines. In Proceedings of the 2011 ACM Conference on Supporting Group Work Workshop on Connecting Families: New Technologies, Family Communication and the Impact on the Domestic Space.
My work looks to comprehend, and (re-)define the appropriate role of intelligent systems in the home. To explore this question, I have focused on routine learners in the context of dual-income family coordination. Families often depend on accurate information about one another’s routines to coordinate. When inaccurate, parents make plans that create conflicts, go to the wrong places, and even leave kids at their activities. Despite this important role, routines, are rarely documented, and so are not available to people for support, or to computational systems as input. My work demonstrates how unsupervised models of family routine can be learned using a single, lightweight sensor. The tacit knowledge of family routine can be captured and exploited by learning systems, providing a new kind of information stream that empowers families and computational systems alike with new capabilities.
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