TRAINING OF ARTIFICIAL INTELLIGENCE ENHANCED OPERATIONS FOR OPERATIONS WITHIN THE INFORMATION ENVIRONMENT
Authors
Hodge, Travis
Coombs, Austin
Subjects
artificial intelligence
AI
AI-Enhanced Operations
AEO
influence
instruction
AI
AI-Enhanced Operations
AEO
influence
instruction
Advisors
Houck, Shannon C.
Date of Issue
2024-12
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
This thesis addresses a critical gap in the military’s ability to harness artificial intelligence (AI) tools for influence and strategic communications by developing and testing an AI-Enhanced Operations (AEO) Course. This course equips participants with practical skills to integrate AI into influence messaging, data analysis, and strategic planning while navigating ethical and operational considerations. Spanning five iterations, the course was refined through diverse audiences and feedback. The first iteration at Naval Postgraduate School (NPS) tested foundational materials, while subsequent iterations at Fort Liberty and Peru introduced multi-day workshops, regional adaptations, and scenario-specific applications.Survey data revealed that 70% of participants found the course directly applicable to their roles, with an additional 27% noting moderate relevance. Participants highlighted significant gains in understanding AI’s potential for influence messaging and audience profiling, culminating in a 4.7 out of 5 satisfaction rating across all iterations. Key themes from the iterative process included the need for extended hands-on practice, improved access to AI tools, and deeper exploration of ethical considerations. This thesis underscores the value of iterative development and feedback-driven refinement in creating impactful training programs, providing a roadmap for future advancements in AI-driven operations to enhance mission effectiveness and strategic impact.
Type
Thesis
Description
Series/Report No
Department
Defense Analysis (DA)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Distribution Statement A. 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.