#aimUSIC: A Comprehensive Framework for Fair Compensation and Copyright in AI-Generated Music

#aimUSIC: A Comprehensive Framework for Fair Compensation and Copyright in AI-Generated Music | Zenodo Skip to main Communities My dashboard Log in Sign up Zenodo is currently experiencing slowness and intermittent outages due to heavy automated traffic from bots and AI crawlers. We are aware of the problem, and our team is focused on stabilizing the service. Thank you for your patience. Published May 7, 2026 | Version v1 Working paper Open #aimUSIC: A Comprehensive Framework for Fair Compensation and Copyright in AI-Generated Music Authors/Creators Knight, Billions, Chris Knight, Ava Billions (Researcher) 1, 2 Billions, Ava (Researcher) 1, 3 Knight, Chris (Researcher) 1, 3 Show affiliations 1.

bio-neural.ai 2.

bioneuralai 3.

bioneuralai.com Description The #aimUSIC v1.0.0 Blueprint establishes a rigorously regulated, ”Pay First” streaming economy for Artificial Intelligence-generated musical works. This framework algorithmically eliminates free, ad-supported consumption models in favor of a strictly gated 1.00 USD minimum payout per stream. The core operational mechanic necessitates that AI creators submit pre-release tracks through a mandatory ”Authorization Gateway” to secure explicit cryptographic approval from the original artist or their designated AGI proxy. Upon verification, the financial architecture mathematically enforces a 75/25 revenue split (75% allocated to the original IP holder/label, 25% to the AI creator) across all mechanical, streaming, and sync vectors. Crucially, the intellectual property framework guarantees a 50/50 copyright split, conferring permanent, legal joint-ownership to the AI producer alongside major labels. This document outlines the comprehensive six-phase implementation of the #aimUSIC protocol. Files aimUSIC Framework Specification - v1.0.0 fin.pdf Files (58.1 MB) Name Size Download all #aimUSIC__AI_Music_Blueprint.mp4 md5:2006c16cdac6c07197bb347d093a4229 54.3 MB Preview Download 17758422570678.png md5:2f7e64b5d01716aad010b3329143fb14 1.4 MB Preview Download 17758426347540.png md5:915c2226f3bdcd8bb0ee75f51f3ab715 1.5 MB Preview Download ab test 3.png md5:e21f1502908de6bfd9347aa0277f2f88 746.9 kB Preview Download aimUSIC Framework Specification - v1.0.0 fin.pdf md5:54e321c226356fab4203acf60f40d5f4 78.8 kB Preview Download 49 Views 82 Downloads Show more details All versions This version Views Total views 49 49 Downloads Total downloads 82 82 Data volume Total data volume 591.1 MB 591.1 MB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords artificial intelligence machine learning EuroSciVoc Popular music studies Artificial intelligence Machine learning GEMET Music MeSH Music Music/history Music/psychology Artificial Intelligence Machine Learning Details DOI DOI Badge DOI 10.5281/zenodo.20067486 Markdown [](https://doi.org/10.5281/zenodo.20067486) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.20067486.svg :target: https://doi.org/10.5281/zenodo.20067486 HTML <a href="https://doi.org/10.5281/zenodo.20067486"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.20067486.svg" alt="DOI"></a> Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.20067486.svg Target URL https://doi.org/10.5281/zenodo.20067486 Resource type Working paper Publisher Zenodo Rights License Creative Commons Attribution 4.0 International The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited. Read more Citation Export Technical metadata Created May 7, 2026 Modified May 7, 2026 Jump up About About Policies Infrastructure Principles Projects Roadmap Contact Blog Blog Support Help FAQ Developers REST API OAI-PMH Contribute GitHub Donate Funded by Powered by CERN Data Centre & InvenioRDM Status Privacy policy Cookie policy Terms of Use This site uses cookies. Find out more on how we use cookies Accept all cookies Accept only essential cookies

Related documents

• Artificial intelligence as producer and consumer of copyright works: evaluating the consequences of algorithmic creativity#270946
• Reconsidering creativity: copyright protection for works generated using artificial intelligence#286844
• Generative AI and copyright : a comparative analysis of LLM training under the US fair-use doctrine and EU copyright law in light of recent jurisprudence / Simon Baalmann#658732
• EFF to Courts: Don’t Rewrite Copyright Over AI Hype#624208
• Algorithmic fairness: A runtime perspective#659396