Changes in the cyber threat environment require the Army to be able to rapidly reprogram its own military software, a newly updated Army Regulation directs.
“Warfare is rapidly moving into a new domain: cyberspace. This will affect warfighting in all domains, and the Army will take measures to adapt to the cyberspace environment.”
“This increased responsiveness demands shortened timelines to combat enemy threats as they adapt to new technology and to new methods of employment.”
“RSR [Rapid Software Reprogramming] will be required to become even more adaptive, automated, and integrated with weapons systems operating in the EMS [electromagnetic spectrum].”
“This policy gives the Army a process which enables soldiers a reach-back RSR capability that will assist commanders to attain tactical superiority, achieve surprise, gain and retain the initiative, maintain awareness of new and emerging threats, and obtain decisive results…,” the unclassified Regulation said.
The Assistant Secretary of the Army (ALT) will “Ensure that sensor-based weapons and CEMA [Cyber Electromagnetic Activities] systems are developed using software reprogrammable signature detection, classification, and response capabilities that can be responsive and enabling to EW [Electronic Warfare], spectrum management and cyber operations.”
See Software Reprogramming for Cyber Electromagnetic Activities, Army Regulation 525-15, 19 February 2016.
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.