Reality Drift — Overview and FAQ (2023–2026)
Reality Drift explains how systems can continue to function while gradually losing alignment with the reality they are meant to represent. The framework examines the deeper structural patterns behind many modern frustrations, showing how they emerge from the same underlying conditions.
As systems optimize measurable representations such as metrics, models, dashboards, categories, and narratives, those representations can begin to replace the realities they were designed to reflect. The result is not always visible failure. More often, it is a slow loss of contact between the system and the world.
The framework introduces concepts including Reality Drift, the Optimization Trap, Filter Fatigue, Synthetic Realness, and Semantic Fidelity, then shows how these dynamics appear across AI systems, media, institutions, and everyday decision-making.
Download: Reality Drift Framework Overview & FAQ (PDF)
