Location

Grand Wailea, Hawaii

Event Website

https://hicss.hawaii.edu/

Start Date

7-1-2020 12:00 AM

End Date

10-1-2020 12:00 AM

Description

Recent advances in artificial intelligence have demonstrated that the future of work will be defined by collaborative human-machine teams. In order to be effective, human-machine teams will rely on context-aware systems to enable collaboration. In this paper, we present three lessons learned from the past five years of developing context-aware systems that we believe will improve future system design. First, that semantic activity must captured, modeled, and analyzed to enable reasoning across missions, actors, and content. Second, that context-aware systems require multiple, federated data stores to optimize system and team performance. Finally, that real-time inter-actor communications are the essential feature enabling adaptation. We close with a discussion of the influences and implications that these lessons have on human-machine teaming, and outline future research activities that will be necessary before operationalizing these systems.

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Jan 7th, 12:00 AM Jan 10th, 12:00 AM

Practice Makes Perfect: Lesson Learned from Five Years of Trial and Error Building Context-Aware Systems

Grand Wailea, Hawaii

Recent advances in artificial intelligence have demonstrated that the future of work will be defined by collaborative human-machine teams. In order to be effective, human-machine teams will rely on context-aware systems to enable collaboration. In this paper, we present three lessons learned from the past five years of developing context-aware systems that we believe will improve future system design. First, that semantic activity must captured, modeled, and analyzed to enable reasoning across missions, actors, and content. Second, that context-aware systems require multiple, federated data stores to optimize system and team performance. Finally, that real-time inter-actor communications are the essential feature enabling adaptation. We close with a discussion of the influences and implications that these lessons have on human-machine teaming, and outline future research activities that will be necessary before operationalizing these systems.

https://aisel.aisnet.org/hicss-53/cl/machines_as_teammates/4