Feedback Loops: The Quiet Force Shaping AI System Behavior

Modern AI systems operate within feedback environments where human responses and operational incentives continuously reshape system behavior through behavioral accumulation. Over time, these feedback loops can lead to decision substitution, override erosion, and governance drift, as users increasingly treat AI outputs as default decision references while formal oversight erodes. The article argues that robust AI systems require execution-time governance mechanisms that operate continuously, as feedback loops ultimately transform behavioral patterns into governance infrastructure.