Human Conception Ledger (HCL): A Framework for Provenance, Attribution, and Human Inventorship in AI-Augmented Systems
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| Format: | Recurso digital |
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Zenodo
2026
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| _version_ | 1866901087091425280 |
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| author | Chu, Melinda |
| author_facet | Chu, Melinda |
| 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> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19198704 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Human Conception Ledger (HCL): A Framework for Provenance, Attribution, and Human Inventorship in AI-Augmented Systems Chu, Melinda <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> |
| title | Human Conception Ledger (HCL): A Framework for Provenance, Attribution, and Human Inventorship in AI-Augmented Systems |
| url | https://doi.org/10.5281/zenodo.19198704 |