Authorship Transparency Statement (ATS) Framework: A Technical Standard for the Multi-Tiered Disclosure of Generative AI in Creative Works

The Authorship Transparency Statement (ATS) is a comprehensive technical protocol designed to replace the primitive binary disclosure of AI—centered on the question "Did you use AI?"—with a nuanced, multi-tiered lexicon for creative synthesis. This framework provides an objective, methodology-based audit for creators, publishers, and legal institutions to accurately describe the degree of human-AI collaboration in any creative project. Framework deep dive on Youtube: [LINK] Abstract The rapid proliferation of generative artificial intelligence (GenAI) has fundamentally disrupted the traditional concept of singular authorship, creating a critical nomenclature gap in the creative industries. Existing disclosure requirements frequently rely on low-resolution binaries that facilitate a "transparency paradox," wherein creators are incentivized toward obfuscation rather than honest methodology. This paper proposes the Authorship Transparency Statement (ATS) Framework, a multi-tiered technical protocol anchored by the Bright Line of Prose Origin. This mechanical distinction shifts the focus from subjective "creative control" to the objective origin of first-pass drafting. By defining a six-tier hierarchy (ATS-0 through ATS-5), the protocol categorizes the human role across a gradient of increasing AI autonomy: from the Traditional Artisan (ATS-0) and Architect (ATS-1) to the Director (ATS-3) and Systems Architect (ATS-4). Furthermore, the ATS framework provides the foundational schema for institutional implementation, offering standardized intake templates and machine-readable metadata structures designed to interoperate with emerging provenance standards such as C2PA. By replacing primitive binaries with a rigorous, methodology-based audit, the ATS protocol seeks to preserve the integrity of authorship and establish a verifiable "paperwork of becoming" for the new creative age. Key Features The Bright Line Principle: A mechanical threshold determining the boundary between reactive augmentation and generative synthesis. The 6-Tier Scale (0–5): A memorable, citable hierarchy of AI integration and human roles. The Extent Axis (E-Scale): A quantitative modifier (E0–E4) indicating the volume of AI involvement in a work. Multi-modal Support: Domain-specific interpretations for Research, Visual Arts, Music, Video, Code, and Data Assets. Technical Implementation: Machine-readable JSON and JSON-LD schemas for automated parsing and library indexing. Institutional Triage Logic: Ready-to-use policy bands for publishers and submission portals to automate legal and editorial reviews. Metadata & Implementation The official machine-readable schemas, validation tools, and community-driven edge-case rulings are maintained at the public repository:https://github.com/MeaningfulnessMediaGroup/ATS-Framework Protocol ID: ATS-FRAMEWORK-1.0License: Creative Commons Attribution 4.0 International (CC BY 4.0) Authorship & IdentityWriting as Djeff Bee, Dominic Branchaud (ORCID: 0009-0008-2046-4378) applies 25 years of systems engineering methods to philosophical modeling.