Reality Drift Framework Papers: Representation and Modern Systems
The Reality Drift Framework Papers introduce a conceptual framework for understanding how modern systems gradually lose alignment with reality while remaining internally coherent, functional, and increasingly optimized. Rather than examining sudden system failure, these papers focus on slow structural drift that emerges through representation, abstraction, optimization, proceduralization, and institutional accumulation.Across artificial intelligence, organizations, public institutions, and digital infrastructure, the collection explores mechanisms including semantic fidelity, representational hardening, mission drift, organizational drift, policy drift, temporal drift, narrative drift, procedural dependency, and the Representation Stack. The papers examine how reality becomes transformed into representations that are easier to measure, optimize, and govern, while becoming progressively less responsive to the phenomena they were originally intended to describe.This collection provides a shared conceptual vocabulary for researchers and practitioners working in artificial intelligence, machine learning, systems theory, organizational studies, information science, philosophy of technology, governance, and digital society. Together, these papers present the Reality Drift framework as a lens for understanding representational failure across technical, institutional, and social systems.