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

Name: Symbiotic Boundary Index (SBI): A Framework for Human–AI Symbolic Symbiosis
Creator: Eduardo, Horvath
Keywords: AI Design, AI Symbiosis, DCIs, Human–AI Interaction, Cognitive Frameworks, Philosophy of Technology, Symbolic Cognition, Symbolic Boundary Index

descriptionPublicationkeyboard_double_arrow_right Research , Other literature type 06 Jun 2025 English Publisher:Zenodo

Authors: Eduardo, Horvath;

doi: 10.5281/zenodo.15611013 , 10.5281/zenodo.15713854 , 10.5281/zenodo.15611012

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

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Abstract

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

Keywords

AI Design, AI Symbiosis, DCIs, Human–AI Interaction, Cognitive Frameworks, Philosophy of Technology, Symbolic Cognition, Symbolic Boundary Index

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