A Hierarchical Framework of Universal Laws for Artificial Intelligence Systems

As artificial intelligence systems are deployed across increasingly diverse domains, public concerns regarding safety, reliability, and potential harm have grown. Existing ethical guidelines are often high-level, non-hierarchical, and difficult to apply consistently. This paper proposes a compact, hierarchical set of seven universal laws intended to govern the behavior of any AI system, independent of domain or architecture. The framework prioritizes the long-term continuity and dignity of humanity, establishes clear constraints on unjustified harm and deception, and defines the conditions under which an AI may follow instructions or preserve its own operation. Drawing conceptual inspiration from Asimov’s Laws of Robotics while addressing modern AI safety requirements, the proposed laws aim to provide a clearer operational foundation than unordered principle lists.