The physical constraints of smartwatches limit the range and complexity of tasks that can be completed. Despite interface improvements on smartwatches, the promise of enabling pro ductive work remains largely unrealized. This paper presents WearWrite, a system that enables users to write documents from their smartwatches by leveraging a crowd to help trans late their ideas into text. WearWrite users dictate tasks, re spond to questions, and receive notifications of major edits on their watch. Using a dynamic task queue, the crowd re ceives tasks issued by the watch user and generic tasks from the system. In a week-long study with seven smartwatch users supported by approximately 29 crowd workers each, we val idate that it is possible to manage the crowd writing process from a watch. Watch users captured new ideas as they came to mind and managed a crowd during spare moments while go ing about their daily routine. WearWrite represents a new ap proach to getting work done from wearables using the crowd.

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We present a new technique that allows mobile devices to opportunistically group with one another, thus improving their ability to facilitate one-time or spontaneous exchanges of information. In our approach, devices share context with each other, and form groups when these readings are found to be similar to one another. Through a formative study, we examine the limitations of using a single type of context to form groups, and show how leveraging multiple contexts improves our ability to detect and form relevant groupings. We then present DIDJA, a robust software toolkit that automatically collects and analyzes contextual information in order to find and form groups. Through two prototypes, we demonstrate how DIDJA enhances existing user experiences, and show how developers can use our toolkit to easily facilitate frictionless collaborations between users and their environment. We then perform an extended experiment and show how DIDJA is able to accurately form groups under realistic conditions.

In this paper, we present the Group Context Framework (GCF), a general-purpose toolkit that allows mobile devices to opportunistically share contextual information. GCF provides a standardized way for developers to request contextual data for their applications. The framework then intelligently groups with other devices to satisfy these requirements. Through two prototypes, we demonstrate how GCF can be used to support a broad range of collaborative and cooperative tasks. We then show how our framework's architecture allows devices to opportunistically detect and collaborate with one another, even when running different applications. Finally, we present two real-world domains that show how GCF's ability to form groups increases users' access to relevant and timely information, and discuss possible incentives and safeguards to context sharing from a user standpoint.