Download

Download Full Text (63 KB)

Description

This commentary explores how neuromorphic artificial intelligence, AI designed to mimic the causal and adaptive processing of the human brain, differs from traditional mechanistic systems and what this means for military applications. Traditional AI follows straightforward stimulus-response patterns that work well in predictable scenarios, but they struggle in complex, dynamic environments. Neuromorphic AI uses more human-like causal processing, integrating multiple streams of data and contextual cues to make decisions that better adapt to ambiguity and uncertainty. While this offers potential advantages in autonomy and operational flexibility, it also raises challenges for predictability, command and control, verification, and accountability. The article argues that successful military integration will require careful oversight, phased implementation, and new training models to ensure ethical, effective, and controllable use of these emerging AI capabilities.

Document Type

Article

Topic(s)

Emerging Science and Technologies, National Security, Defense Policy

Region(s)

United States

Publication Date

9-24-2025

Keywords

neuromorphic AI, causal decision processing, military artificial intelligence, adaptive autonomous systems, human-like AI, command and control, AI governance, contextual decision-making, strategic AI integration, defense technology, neural-inspired architecture, accountability, oversight

Beyond Mechanistic Control: Causal Decision Processing in Neuromorphic Military Artificial Intelligence

Share

COinS