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Burian, B. K., Kochan, J. A., Mosier, K. L., & Fischer, U. (2017). Autonomous, context-sensitive, task management systems and decision support tools ii Contextual constraints and information sources. NASA Study. 
Resource type: Journal Article
BibTeX citation key: Burian2017
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Categories: Artificial Intelligence, Cognitive Science, Computer Science, Data Sciences, Decision Theory, Education, Engineering, General
Subcategories: Behavioral analytics, Big data, Decision making, Edge AI, Human decisionmaking, Machine learning, Pilot Training, Psychology of human-AI interaction
Creators: Burian, Fischer, Kochan, Mosier
Publisher:
Collection: NASA Study
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Abstract
Recent advances in artificial intelligence, machine learning, data mining and sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the second of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explored fundamental issues associated with the development of such a system. In this report, we extend this work to focus on two critical aspects of these systems: 1) the constraints and conditions that drive the dynamic prioritization and presentation of data and information to the pilots, and 2) specific data and information to be accessed, monitored, integrated, and displayed in such a system.
  
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