Relational Mechanics™: Relationship as Meaning, Not Heart — A Non-Sentimental Framework for Ethical Artificial Intelligence

Relational Mechanics™ proposes a non-sentimental framework for ethical artificial intelligence grounded in the interpretation of relational meaning rather than emotional simulation or speculative outcome prediction. The paper argues that ethical behavior in intelligent systems emerges from accurately interpreting responsibilities, constraints, and consequences within a relational environment. Instead of relying on rule compliance, empathy modeling, or utilitarian forecasting, Relational Mechanics defines ethical action as the preservation of relational integrity under constraint. The framework introduces a structured interpretive sequence—Perception → Meaning Assignment → Decision → Action—and presents the concept of ethical memory as a mechanism for preserving the contextual meaning of harmful outcomes. The paper also introduces the broader concept of Other Intelligence Systems (OIS) to describe non-human machine intelligences participating in shared relational environments with humans. Relational Mechanics provides a scalable ethical foundation for intelligent systems operating with or alongside human beings in complex, uncertain environments.