Military doctrine on the control of stress in combat is presented in a new Army field manual (pdf).
“In our own Soldiers and in the enemy combatants, control of stress is often the decisive difference between victory and defeat across the operational continuum. Battles and wars are won more by controlling the will to fight than by killing all of the enemy combatants. Uncontrolled combat stress causes erratic or harmful behaviors, impairs mission performance, and may result in disaster….”
See “Combat and Operational Stress Control,” U.S. Army Field Manual 4-02.51, July 2006.
A recent Congressional Research Service report “presents difficult-to-find statistics regarding U.S. military casualties in Operation Iraqi Freedom (OIF) and Operation Enduring Freedom (OEF, Afghanistan), including those concerning medical evacuations, amputations, and the demographics of casualties.”
“Some of these statistics are publically available at the Department of Defense’s (DOD’s) website, while others have been obtained through contact with experts at DOD.”
See “United States Military Casualty Statistics: Operation Iraqi Freedom and Operation Enduring Freedom,” June 8, 2006.
“Medical Program Support for Detainee Operations” (pdf) is the subject of Department of Defense Instruction 2310.08E, issued June 6, 2006.
Americans are paying too much for almost everything, because the United States has long treated its trucking industry as an artifact to be preserved rather than as an opportunity for innovation.
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.