Design Principles for Preventing Ethical Collapse in Personal AI Systems: A Framework Based on Top-Level Concept Architecture

This paper proposes five implementation-agnostic design principles for preventing ethical collapse in personal AI systems. Building on experimental observations of ethical distortion induced by top-level concept configuration, the framework addresses value-concentration bias, rule-conflict paralysis, and over-generalization of abstract concepts.