Preservation of Iraq War Records, and More DoD Doctrine
The Joint Chiefs of Staff recently reaffirmed the requirement to preserve historically valuable records pertaining to the Iraq War.
“Operations ENDURING FREEDOM and NOBLE EAGLE and current operations pertaining to Iraq are a prominent part of American and world history. It is important that we preserve the historical records of these continuing operations and we obtain information and lessons that can be applied in planning, shaping, and implementing our national defense in the future.”
See Chairman of the Joint Chiefs of Staff Notice 5760, Preservation of Historical Records of Operations Enduring Freedom and Noble Eagle and Pertaining to Iraq (pdf), 7 September 2006, current as of 31 January 2008.
A new Army Regulation defines policies and procedures governing military civilians who are engaged in human intelligence and counterintelligence activities. See Army Regulation 690-950-4, “Military Intelligence Civilian Excepted Career Program” (pdf), 20 February 2008.
A revised new Army Field Manual 3-0 on “Operations” has not yet been released. The Defense Department has released its own revised doctrine on Joint Operations. See Joint Publication 3-0 (pdf), change 1, 13 February 2008.
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.