Army Program Seeks to Heighten Soldiers’ Cognition
A properly trained soldier can distinguish a vegetarian from a meat-eater based on their smell, a new Army publication says, since “different diets produce different human odors.”
He or she can to determine the age, gender and even the mental state of a target by studying their footprints.
Not simply a warrior, the ideal soldier is also an intelligence analyst, a cultural anthropologist, and a student of human nature with the ability to confront and overcome adversity — Sherlock Holmes and Leatherstocking and a bit of Tarzan, all in one.
That, at any rate, seems to be the goal of the US Army’s Advanced Situational Awareness program, which trains soldiers to discern even subtle anomalies in the combat environment, to swiftly assess their implications, and to act decisively in response.
Advanced Situational Awareness “optimizes human performance through building the skills necessary to develop agile, resilient, adaptive, and innovative Soldiers who thrive in conditions of uncertainty and chaos.”
The program was described in Advanced Situational Awareness, US Army Training Circular TC 3-22.69, 316 pages, April 2021.
After months of delay, the council tasked by President Trump to review the FEMA released its final report. Our disaster policy nerds have thoughts.
FAS and FLI partnered to build a series of convenings and reports across the intersections of artificial intelligence (AI) with biosecurity, cybersecurity, nuclear command and control, military integration, and frontier AI governance. This project brought together leaders across these areas and created a space that was rigorous, transpartisan, and solutions-oriented to approach how we should think about how AI is rapidly changing global risks.
Investment should instead be directed at sectors where American technology and innovation exist but the infrastructure to commercialize them domestically does not—and where the national security case is clear.
AI is already consequential, but its future trajectory remains contested. Policymakers should make their assumptions explicit, focus on what can be shaped rather than what can be perfectly predicted, and build institutions that can learn and respond as evidence changes.