2026/01/01 by A. Jacobs · 1 voice
Neuroscience · Social Sciences · #Embodied and Extended Cognition #Ethics and Social Impacts of AI #Innovation, Sustainability, Human-Machine Systems
paper · doi:10.2139/ssrn.6150706
crossref issued 2026/01/01 · crossref published 2026/01/01 · openalex publication_date 2026/01/01 · crossref created 2026/03/05 · crossref deposited 2026/03/05 · crossref indexed 2026/03/05 · openalex created_date 2026/03/06 · openalex updated_date 2026/08/01
Across institutions, technologies, and knowledge environments, systems increasingly remain operational while producing outcomes that feel hollow, performative, or disconnected from reality. Metrics improve even as results degrade, language remains fluent as meaning erodes, and individuals experience cognitive exhaustion and disorientation without obvious error, deception, or collapse. Existing explanations such as corruption, misinformation, misaligned incentives, or information overload capture surface symptoms. However, they fail to identify a unifying structural mechanism. This paper proposes Reality Drift , a theory of representational failure in scaled symbolic systems. The core claim is that, as symbolic systems expand and optimize, their representations drift away from reality faster than corrective constraints can bind them. This drift is gradual, non-intentional, and self-reinforcing. Systems continue to function, but meaning detaches. Optimization replaces reference and symbols circulate autonomously. As a result, human cognition adapts at increasing cost. The paper introduces a five-operator explanatory grammar consisting of drift, constraint, compression, representation, and filtering. Together these describe how the condition emerges and persists across domains. The theory generates testable predictions for institutions, artificial intelligence, and human cognition while providing a structural diagnosis of how meaning degrades under scale.