Modernizing the creation of enlisted qualification standards for the United States Air Force

Authors

• Kara O’Neal, Air Force Institute of Technology
• William N. Caballero, Air Force Institute of TechnologyFollow
• Nathan B. Gaw, Air Force Institute of TechnologyFollow
• Nathaniel D. Bastian, Air Force Institute of Technology

Document Type

Article

Publication Date

8-17-2026

Abstract

Excerpt: Explainable / interpretable machine learning is leveraged for USAF personnel actions. A responsible machine learning framework is adapted to ensure ethical governance. Three distinct model classes are evaluated with varied approaches to missing data.

Comments

The full article is available via subscription or purchase, using the DOI link below.

Co-author W. Caballero was co-affiliated with the Department of Mathematical Sciences at the United States Air Force Academy at the time of this article's publication.

The article was published online in August 2026 ahead of inclusion in the November 2026 issue of Computers & Industrial Engineering.

DOI

10.1016/j.cie.2026.112303

Source Publication

Computers & Industrial Engineering (ISSN 0360-8352 | eISSN 1879-0550)

Recommended Citation

O’Neal, K., Caballero, W. N., Gaw, N., & Bastian, N. D. (2026). Modernizing the creation of enlisted qualification standards for the United States Air Force. Computers & Industrial Engineering, 221, 112303. https://doi.org/10.1016/j.cie.2026.112303