Human-Artificial Intelligence Teaming for the U.S. Navy: Developing a Holistic Research Roadmap

To address the increasing need for efficient data analysis and decision-making in defense, the U.S. Navy is prioritizing AI/ML systems capable of handling multi-source data and suggesting courses of actions. Historically, many such systems failed due to technical issues and lack of usability or mission relevance. Research on human-AI collaboration aims to create AI systems that better integrate with frontline operators. A recent National Academies of Sciences, Engineering, and Medicine Report (NASEM) outlined 57 research goals, but the U.S. Navy requires a more-focused set of priorities. A workshop with 23 experts from various fields was held at the Naval Information Warfare Center Pacific, resulting in five key research priorities spanning different time frames. This panel discusses the workshop’s findings, highlighting critical questions going into this workshop and those coming out of it. Panel participants come from government, academia, and industry, providing unique perspectives on big questions for human-AI teaming.

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Publication Details

Journal
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Published
2024-08-29
DOI
https://doi.org/10.1177/10711813241260352
Citations
1
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.64
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Human-Artificial Intelligence Teaming for the U.S. Navy: Developing a Holistic Research Roadmap

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1 citations
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Human-Automation Interaction and Safety
0.64
article

Human-Artificial Intelligence Teaming for the U.S. Navy: Developing a Holistic Research Roadmap

Erin K. Chiou, Robert S. Gutzwiller, Maia B. Cook, Jason W.H. Wong, Corey K. Fallon
article en
1 citations

Abstract

To address the increasing need for efficient data analysis and decision-making in defense, the U.S. Navy is prioritizing AI/ML systems capable of handling multi-source data and suggesting courses of actions. Historically, many such systems failed due to technical issues and lack of usability or mission relevance. Research on human-AI collaboration aims to create AI systems that better integrate with frontline operators. A recent National Academies of Sciences, Engineering, and Medicine Report (NASEM) outlined 57 research goals, but the U.S. Navy requires a more-focused set of priorities. A workshop with 23 experts from various fields was held at the Naval Information Warfare Center Pacific, resulting in five key research priorities spanning different time frames. This panel discusses the workshop’s findings, highlighting critical questions going into this workshop and those coming out of it. Panel participants come from government, academia, and industry, providing unique perspectives on big questions for human-AI teaming.

Proceedings of the Human Factors and Ergonomics Society Annual MeetingVol. 68(1)
Naval Information Warfare Center Pacific (US), Pacific Northwest National Laboratory (US), Pacific Environment (US), Arizona State University (US)
Partnerships for the goals
Openalex Percentile: Top 28%
Human-Automation Interaction and Safety
0.64
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