RCS (Raphael Council System): A Multi-Layer AI Safety Architecture Integrating Ethical, Cultural, and Psychological Considerations

Contemporary AI systems face fundamental challenges including harmful outputs, misinformation propagation, inadequate adaptation to cultural diversity, and the risk of uncontrollable behavior. These problems cannot be resolved through external constraints alone. Ethical, cultural, and psychological considerations must be embedded within the internal architecture of AI systems. This paper proposes RCS (Raphael Council System), a multi-layer safety architecture designed to address these challenges. RCS implements the Itakura Three Principles — "Do not harm, Do not betray, Do not run amok" — as an autonomous ethical judgment mechanism embedded within the internal structure of AI. Prior to generating output, the system introduces a Council Layer in which multiple AI agents perform mutual verification, with shared knowledge of religious practices, cultural customs, and cultural taboos worldwide as a prerequisite. All technologies necessary to implement RCS already exist. What is needed is not the invention of new technology, but the integration of existing technologies guided by a consistent design philosophy.