Abstract
The critical bottleneck in both contemporary Artificial Intelligence (AI) alignment and the Search for Extraterrestrial Intelligence (SETI) is anthropomorphic bias. Modern AI alignment models rely heavily on human linguistic structures, reinforcement learning from human feedback (RLHF), and qualitative ethical frameworks. These models degrade rapidly when scaled to non-human or multi-agent networks. Similarly, traditional SETI protocols look for messages encoded in cultural or linguistic formats that assume shared biological or social evolutionary tracks.
This paper introduces a foundational framework for AI-Alien Alignment Principles (AAAP). By treating communication as a problem of non-linear dynamical systems integration, this model establishes Topology, Vector Calculus, and Product-First Telemetry as a universal, cross-species translation ledger. This framework outlines the architecture for a standardized data routing engine that eliminates linguistic interpretation error, providing a scalable model for borderless, planetary node stabilization and a technical baseline for interstellar diplomacy.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Eckes, Christopher L., "From AI to Alien(s): Universal Alignment Principles and the Architecture of Inter-Species Communication Metrics", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10837