Symbiotic Boundary Index (SBI): A Framework for Human–AI Symbolic Symbiosis

This working paper introduces the Symbiotic Boundary Index (SBI), a conceptual and diagnostic framework for analyzing symbolic symbiosis in human–AI interactions. It proposes a classification matrix based on Symbolic Integration and Lucidity (SxL), and defines novel cognitive-symbolic constructs such as Derived Cognitive Instances (DCIs), Symbolic Frustration (SF), and Symbolic Security (SymSec). **This is the first public release (v1.0) of the SBI framework.** To preserve conceptual clarity, this version does **not** include the experimental protocols, diagnostic layers, or symbolic datasets cited in the paper. These materials will be made available in a future version as supplementary content. Author: Eduardo Horvath — Independent Researcher ORCID: 0009-0009-4008-0731