The task of the military historian differs from that of the academic historian because military history has an operational dimension. It is supposed to help inform current military operations with the lessons and the perspectives of the past.
“The historian must always bear in mind that the whole purpose of the history office is to help the warfighter by serving as an advisor and presenting critical documentation when needed,” according to a new US Air Force Handbook on the subject. “The mission drives what is important for the historian, not the historian’s particular interest. ”
The military historian also is responsible for identifying and assembling the raw materials of future scholarship. Contrary to what “many new historians may incorrectly assume, documentation will not automatically arrive in the office. The historian must seek it.” See Aerospace Historian Operations in Peace and War, Air Force Handbook 84-106, April 2, 2020.
But operationally, history can only do so much.
“Military history does not produce solutions for problems and does [not] guarantee success on the battlefield,” an Army manual on the subject explains. “An approach with these goals leads to frustration and biased or inaccurate history.”
“Rather, military history affords an understanding of the dynamics to shape the present and enables Soldiers the perspective of viewing current and future problems with ideas of how similar challenges were confronted in the past. . . If history rarely provides concrete answers, it offers insight and understanding.”
“Historians know that Army history records triumphs, challenges, and failures. Army historians do not judge operations and actions; they seek to tell the full story so that others learn from it.” See Military History Operations, ATP 1-20, US Army, June 2014.
These ideas aim to advance the detailed policy solutions needed to foster public trust and implement fairness in the adoption of AI across diverse domains, from healthcare and government benefits to rural access, education, and worker protections.
The evidence is clear: algorithmic pay-setting is established in app-based work, and payroll/timekeeping failures show how software can produce systemic wage harm at scale
While a few states have taken steps to implement decision-making mechanisms for certain AI systems, too many leaders are simply accepting narratives about AI’s purported public benefit at face value – jumping to the “how” of AI implementation before thoroughly vetting potential systems and deciding whether they are appropriate to use at all.
When properly structured — with specific numeric targets, secured financial obligations, independent monitoring, and meaningful enforcement — CBAs transform data center deals into durable community partnerships.