Joshua Snoke

Air Force Special Warfare operators conduct physically and mentally challenging missions. For this career field, specialized assessment and selection of future operators is required. The authors examine the programs for assessing and selecting personnel for AFSPECWAR, identify job-relevant attributes, consider how these attributes should be weighted for candidate selection, and improve the accuracy of raters' evaluations of candidates.

The Department of the Air Force cannot confidently apply artificial intelligence (AI) and machine learning (ML) systems to human resource management without an analytic framework to evaluate and augment their safety. The authors developed an analytic framework to measure and augment ML systems' safety. They then developed ML systems and exercised the framework with the examples of officer promotion and developmental education boards.

The U. S. Department of Defense (DoD) is investing heavily in the development of machine learning (ML) algorithms to assist in many decisionmaking processes. This report provides policymakers and developers of ML algorithms with a framework and tools to produce algorithms for personnel management that are consistent with DoD's equity priorities.