Invisible Friction: Friction Displacement in Low-Friction AI Systems

This paper proposes the concept of Friction Displacement: the structural relocation of friction from user-facing interfaces to infrastructure, labor, and environmental systems in low-friction AI environments. Drawing on Maura Theory, the paper argues that seamless AI systems may not eliminate friction, but redistribute it across invisible layers including energy consumption, water use, data center infrastructure, labor systems, and ecological load. The paper introduces a multi-layer friction framework (F_total) spanning cognitive, infrastructure, labor, and environmental dimensions, and proposes that sustainable AI design requires minimizing total systemic friction across cognitive, infrastructure, labor, and environmental layers rather than merely reducing user-side friction.