AI Bibliography
AI Bibliography |
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Wellman, A. (2019). Parity avoidance: A proactive analysis of the obsolescence of the third offset strategy NAVAL POSTGRADUATE SCHOOL MONTEREY CA MONTEREY United States. |
| Resource type: Report/Documentation BibTeX citation key: Wellman2019 View all bibliographic details  |
Categories: Artificial Intelligence, Cognitive Science, Complexity Science, Computer Science, Data Sciences, Decision Theory, General, Geopolitical, Military Science Subcategories: Augmented cognition, Autonomous systems, China, Command and control, Decision making, Deep learning, Doctrine, Edge AI, Machine learning, Mosaic warfare, Networked forces, Psychology of human-AI interaction, Russia, Strategy, United States Creators: Wellman Publisher: NAVAL POSTGRADUATE SCHOOL MONTEREY CA MONTEREY United States Collection: |
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Within the Department of Defense, offset strategies are policies of competition that mandate efforts to maintain technological superiority to generate or sustain a strategic advantage over near-peer competitor adversaries. The current strategy, the Third Offset, was implemented in 2014 and directs the development and leveraging of emergent, capabilities-based technologies to defend against the modernized, near-peer competitor nations of Russia and China. This thesis used unclassified resources to summarize the reactiveness of the previous offset strategies, define military supremacy, identify challenges to the Third Offset Strategy, and provide evidence that the current strategy is devalued. It also identified a list of conditions which, if met, render the strategy obsolete, ultimately determining that the Third Offset is, indeed, obsolete in its current form it is unable to provide a strategic advantage to the United States. Finally, the thesis offers recommendations to the Department of Defense to reinforce the Third Offset Strategy with a goal of restoring its efficacy.
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