Human-Machine Weapons Engagement Decisions: Systems Safety in Complex Decision Environments
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Authors
Johnson, Bonnie W.
Miller, Scot A.
Green, John M.
Kendall, Walter A.
Godin, Arkady A.
Subjects
safety
artificial intelligence
machine learning
human-machine teaming
automated decision aids
weapons engagements
mission planning
metacognition
trust
risk
missile defense
failures
root causes
systems engineering
tactical warfare
artificial intelligence
machine learning
human-machine teaming
automated decision aids
weapons engagements
mission planning
metacognition
trust
risk
missile defense
failures
root causes
systems engineering
tactical warfare
Advisors
Date of Issue
2021
Date
2021
Publisher
Monterey, California: Naval Postgraduate School
Monterey, California. Naval Postgraduate School.
Monterey, California. Naval Postgraduate School.
Language
en_US
Abstract
This project will study system safety requirements regarding the deployment of artificial intelligence (AI) for tactical decision and mission planning aids supporting complex human-machine decisions. Advances in computational technologies and AI methods present new opportunities for developing automated tactical decision aids to support warfighters making weapons engagement decisions. Tactical decisions become increasing complex and can overwhelm human decision-making as threats increase in number, speed, diversity and lethality. It is critical to ensure that the deployment of such AI-enabled decision aids considers system safety. The study will explore the cognitive strengths of humans and machines to identify effective teaming arrangements in a variety of tactical environments of increasing complexity. This study will investigate system safety risks to develop concepts, requirements, and methods that ensure that future automated tactical decision and mission planning aids are safely deployed. Research questions include: What are the safety risks related to the deployment of AI systems that support future automated tactical decision and mission planning aids? Can AI-enabled automated decision aids support system safety analysis in a way that characterizes the cognitive strengths of humans and machines? What concepts, requirements, and methods can ensure that future automated military decision aids are safely deployed? NPS proposes a model-based systems engineering (MBSE) method to develop safety requirements for integrating automated decision aids into weapons engagement and mission planning decisions. The MBSE method will capture and analyze requirements, functional models of weapons engagements, and conceptual architectures for human-machine teaming arrangements. The study will include a multi-disciplinary team of NPS researchers and will offer educational and research opportunities for NPS students. Research deliverables will include a project report and presentation that contain MBSE artifacts, conceptual models, and safety requirements.
Type
Poster
Description
NPS NRP Project Poster
Series/Report No
Department
Systems Engineering
Organization
Naval Research Program (NRP)
Identifiers
NPS Report Number
Sponsors
Naval Air Warfare Center Weapons Division (NAWCWD)
ASN(RDA) - Research, Development, and Acquisition
ASN(RDA) - Research, Development, and Acquisition
Funder
This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrp
Chief of Naval Operations (CNO)
Chief of Naval Operations (CNO)
Format
Citation
Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.