AI assistance isn't just a shortcut; it's a mathematical trap for permanent human incompetence.
Using AI creates a 'low-skill equilibrium' where short-term gains prevent humans from ever reaching high-skill levels. This creates an irreversible loss of expertise that makes AI delegation a one-way street.
The Geometry of Learning under AI Delegation
SSRN · 6454543
As AI systems shift from tools to collaborators, a central question is how the skills of humans relying on them change over time. We study this question mathematically by modeling the joint evolution of human skill and AI delegation as a coupled dynamical system. In our model, delegation adapts to relative performance, while skill improves through use and decays under non-use; crucially, both updates arise from optimizing a single performance metric measuring expected task error. Despite this lo