Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty

Author

Michael David Parrish, Missouri University of Science and Technology

Keywords and Phrases

Artificial Intelligence; Decision Making; Deep Learning; Human-Is-The-Critical-Path (HTCP); Leadership; Uncertainty

Abstract

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize their decision-making under uncertainty. The first significant contribution of this research developed a new program management approach using artificial intelligence genetic algorithm principles combined with the best of traditional acquisition approaches to address the worsening problem that quantitative technology is changing at the speed of innovation as does the qualitative need of the customer and user to change causing accelerated programmatic failures of deploying a solution on time and on budget.

This research further extends results by demonstrating the viability of artificial intelligence tools such as neuro-fuzzy systems to improve military training by adding uncertainty and deep transfer learning to assist in the assessment of military target identification decisions. The research of this dissertation is broadly applicable and can be used by all program managers, engineering practitioners, and leaders to utilize artificial intelligence tools to improve and optimize their decision-making"-- Abstract, p. iv

Advisor(s)

Corns, Steven

Committee Member(s)

Canfield, Casey I.
Schreiner, James
Marley, Robert J.
Raper, Stephen A.
Long, Suzanna, 1961-

Department(s)

Engineering Management and Systems Engineering

Degree Name

Ph. D. in Engineering Management

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2025

Pagination

xvi, 163 pages

Note about bibliography

Includes_bibliographical_references_(pages 71, 111, 144 and 156-162)

Rights

©2024 Michael David Parrish , All Rights Reserved

Document Type

Dissertation - Open Access

File Type

text

Language

English

Thesis Number

T 12468

Recommended Citation

Parrish, Michael David, "Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty" (2025). Doctoral Dissertations. 3361.
https://scholarsmine.mst.edu/doctoral_dissertations/3361