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Blaha, L. M. 2018, Interactive ooda processes for operational joint human-machine intelligence. Paper presented at NATO IST-160 Specialist’s Meeting: Big Data and Military Decision Making. 
Added by: SijanLibrarian (2020-07-01 10:06:31)   Last edited by: SijanLibrarian (2020-07-01 10:10:41)
Resource type: Proceedings Article
BibTeX citation key: Blaha2018
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Categories: Artificial Intelligence, Cognitive Science, Complexity Science, Computer Science, Decision Theory, General, Military Science
Subcategories: Augmented cognition, Command and control, Decision making, Deep learning, Human decisionmaking, Human learning, JADC2, Machine intelligence, Machine learning, Psychology of human-AI interaction, Situational cognition, Strategy
Creators: Blaha
Collection: NATO IST-160 Specialist’s Meeting: Big Data and Military Decision Making
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Views index: 18%
Popularity index: 4.5%
Abstract

A key advantage to strategic thinking with the Observe-Orient-Decide-Act (OODA) framework is that it provides a systematic approach to get inside the decision-making process of another agent, either cooperative or adversarial. Indeed, current OODA concepts have supported understanding human decision processes to support agile and competitive decisions about human warfighters and human-centric operations. However, future military decision making based on human-machine teaming relies on technology and interaction concepts that support joint human-machine intelligence, not just human capabilities. This requires new OODA concepts. Herein, I define a machine OODA loop, considering the characteristics that make it similar to and different from the human OODA loop. I consider how advances in artificial intelligence and cognitive modeling can be integrated within the machine-Orient stage, providing the machine a unique advantage over humans in that the machine can integrate a level of understanding and prediction about human operators together with predictions about machine behaviors and data analytics. Additionally, I propose that effective human-machine teaming should be supported by human- machine joint decision-action processes, conceptualized as interacting OODA loops. Consideration of the interacting human-machine OODA processes offers conceptual guidance for design principles and architectures of systems supporting effective operational human-machine decision making.


  
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