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Machine Learning in Air Force Human Resource Management Volume 2, A Framework for Vetting Use Cases with Example Applications : RAND Corporation , February 15, , 2024

February 15, 2024

RAND Corporation

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Background: "The Department of the Air Force (DAF) is working to develop and field artificial intelligence and machine learning (ML) systems for mission areas and support functions, including human resource management (HRM). Recent developments have improved the access that organizations have to data and analytic tools, opening a wide range of possible ML projects that they could pursue.

Given resource limitations, decisionmakers must choose which projects to pursue among many promising options. The DAF needs a framework to evaluate the business value, feasibility, and complexity of proposed projects.

To understand how the DAF can form a balanced portfolio of ML projects for HRM, the authors reviewed how private-sector organizations evaluate and select such projects. From the review, they arrived at a five-step framework. Broadly, the framework involves evaluating the business value, technical feasibility, and implementation complexity of possible ML projects and forming a portfolio from these evaluations. Each of these steps draws on multiple predefined criteria, which may be assessed using qualitative or quantitative methods. The authors demonstrate steps of the framework using 19 use cases for applying ML throughout the DAF HRM life cycle.

Notably, this approach does not purport to find the best approach to a business problem. It finds a potentially useful ML approach to addressing a business problem but does not provide a full analysis of alternative solutions, such as non-ML approaches, to address the problem."

Authors - Walsh, Matthew, Robson, Sean, Robbert, Albert A., Schulker, David



Walsh, Matthew, Robson, Sean, Robbert, Albert A., Schulker, David


RAND Corporation


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