The Optimization Trap: Definition and Concept Paper

This paper defines The Optimization Trap as a condition in which improvement within a representation becomes easier to demonstrate and reward than improvement in the underlying reality, causing the system to deepen the very optimization producing misalignment. The trap is self-reinforcing. Metrics, dashboards, proxies, and internal models become increasingly refined, and each measurable improvement supplies evidence that the process is working even when those representations are becoming less faithful to the purpose they were created to serve. Optimization itself is not the problem. The trap appears when optimization loses a working route back to purpose, consequence, and disconfirming feedback. Within the Reality Drift framework, the Optimization Trap identifies the point at which measurable efficiency becomes the dominant organizing logic and the system’s reference point shifts inward. What is measured stabilizes and improves while what is meant to be measured grows progressively more distant.