A new U.S. Air Force directive “provides policies for managing nuclear weapons and weapon systems, and for protecting personnel, property, and the environment from hazardous exposure to radioactive materials.” See Air Force Policy Directive 91-1, “Nuclear Weapons and Systems Surety” (pdf), 13 February 2007.
Another new Air Force document on combating the threat or use of weapons of mass destruction “provides guidance for understanding, planning, and executing counter-chemical, biological, radiological, and nuclear operations to enable US forces to survive and operate effectively in this deadly environment.” See Air Force Doctrine Document 2-1.8, “Counter-Chemical, Biological, Radiological and Nuclear Operations” (pdf), 26 January 2007. (Update: Dick Destiny offers some commentary on AFDD 2-1.8, and provides some corrections.)
Army doctrine on the use of attack helicopters to locate and destroy enemy forces and to gather or confirm intelligence is presented in a new field manual. See “Attack Reconnaissance Helicopter Operations” (large pdf), Field Manual FM 3-04.126, February 16, 2007. The new manual notes that it has been reviewed for operations security considerations and approved for public release.
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.