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Bibliographic Details
Main Author: Chu, Melinda
Format: Recurso digital
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Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.19198704
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Table of Contents:
  • <p><span>As artificial intelligence systems increasingly participate in ideation, drafting, and development workflows, distinguishing human-originated contributions from AI-generated outputs has become a critical challenge for intellectual property, scientific attribution, and legal compliance.</span></p> <p><span> </span><span>This work introduces the Human Conception Ledger (HCL), a structured framework for capturing, verifying, and preserving human-origin inventive acts in AI-augmented environments. </span></p> <p><span> </span><span>The system defines explicit human contribution taxonomies, incorporates AI systems as digital witnesses, and establishes multi-layered provenance bundles supported by cryptographic hashing and cross-model corroboration.</span></p> <p><span> </span><span>HCL enables individuals and organizations to document human conception, support inventorship claims, and generate structured evidentiary records for legal, academic, and corporate contexts.</span></p>