realitydriftproject/reality-drift-mechanics-taxonomy-ai-systems-alignment

该数据集包含来自Reality Drift框架的基础性论文，形式化了技术、制度和认知系统中漂移的机制、生命周期和分类法。Reality Drift描述了一种结构性条件，即系统在保持功能和内部一致性的同时，逐渐与它们本应代表的现实脱钩。论文详细阐述了漂移的因果链、生命周期阶段（包括对齐阶段、优化阶段、脱钩阶段、合成真实阶段和崩溃或纠正阶段）以及跨领域的漂移分类法（如语言和意义、认知、制度、经济和AI及技术系统）。此外，还提出了纠正机制，如语义保真度、递归纠正循环和现实锚定机制，以恢复系统与现实的对齐。

This dataset contains a foundational paper from the Reality Drift framework, formalizing the mechanics, lifecycle, and taxonomy of drift across technological, institutional, and cognitive systems. Reality Drift describes a structural condition where systems remain functional and internally coherent while gradually decoupling from the realities they are meant to represent. The paper details the causal chain of drift, lifecycle stages (including Alignment Phase, Optimization Phase, Decoupling Phase, Synthetic Realness Phase, and Collapse or Correction Phase), and a taxonomy of drift across domains (such as Language and Meaning, Cognitive, Institutional, Economic, and AI and Technical Systems). It also proposes correction mechanisms like Semantic Fidelity, Recursive Correction Loops, and Reality Anchoring Mechanisms to restore alignment between systems and reality.