Analytics and models in the era of strategic competition

Laurie Fenstermacher; Kathleen Larson; Christine Vitiello; Kirsten Rice; Steve Shellman

doi:10.1117/12.3022732

7 June 2024 Analytics and models in the era of strategic competition

Laurie Fenstermacher, Kathleen Larson, Christine Vitiello, Kirsten Rice, Steve Shellman

Author Affiliations +

Proceedings Volume 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII; 130570E (2024) https://doi.org/10.1117/12.3022732
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

Strategic competition with near peer threats such as Russia and China replaced a focus on non-state extremist threats. Competition “success” is measured by domestic stability, strong alliances, networks and partners; the goal is greater influence in order to shape international norms, institutions. In the current information saturated age, manipulation of truth is common and propaganda can be used to weaponize information in order to compete. Diplomatic and economic strategies (e.g., Belt Road) are also important. Competitive advantage requires national ambition, unified identity, will, effective institutions. Analytics and modeling for strategic competition must characterize competitors across multiple information vectors (culture, cyber, diplomatic, social-cyber, economic, etc.) with “emic” (1st person), “etic” (3rd person) perspectives, leveraging expert-AI to contextualize information for situation awareness, planning, developing tactics for behavior change without war. This paper highlights the state-of-the-knowledge/art re: behaviors and assessment of strategic competition, spotlighting gaps, issues (e.g., inappropriate/outdated assumptions) and identifies future research areas.

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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Laurie Fenstermacher, Kathleen Larson, Christine Vitiello, Kirsten Rice, and Steve Shellman "Analytics and models in the era of strategic competition", Proc. SPIE 13057, Signal Processing, Sensor/Information Fusion, and Target Recognition XXXIII, 130570E (7 June 2024); https://doi.org/10.1117/12.3022732

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