The SymbioMind Attribution Protocol: A Proposed Standard for Human-AI Collaborative Intellectual Production

Description/Abstract:This paper proposes a formal attribution standard for intellectual work produced through sustained human-AI collaboration — a category distinct from both AI-assisted writing and AI-generated content. The human author provides generative insight, domain knowledge, theoretical direction, and ethical responsibility. The AI system provides formalisation, literature mapping, coherence checking, and cross-domain pattern recognition. Neither alone produces the output. Current attribution frameworks are inadequate for this emergent category. The SymbioMind Protocol is proposed as a working standard, grounded in ecological homeostasis principles and protected under CC BY-NC-SA 4.0

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-15
DOI
https://doi.org/10.5281/zenodo.19028100
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

The SymbioMind Attribution Protocol: A Proposed Standard for Human-AI Collaborative Intellectual Production

John Richard Smith, SHAI/HATI
Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

The SymbioMind Attribution Protocol: A Proposed Standard for Human-AI Collaborative Intellectual Production

John Richard Smith, SHAI/HATI
article en

Abstract

Description/Abstract:This paper proposes a formal attribution standard for intellectual work produced through sustained human-AI collaboration — a category distinct from both AI-assisted writing and AI-generated content. The human author provides generative insight, domain knowledge, theoretical direction, and ethical responsibility. The AI system provides formalisation, literature mapping, coherence checking, and cross-domain pattern recognition. Neither alone produces the output. Current attribution frameworks are inadequate for this emergent category. The SymbioMind Protocol is proposed as a working standard, grounded in ecological homeostasis principles and protected under CC BY-NC-SA 4.0

Zenodo (CERN European Organization for Nuclear Research)
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Research Data Management Practices
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