Reproducibility is the New Copyleft: Defining AGI-oriented Reproducible Builds
Copyleft, as implemented in licenses such as the GNU General Public License, was a legal hack that used copyright to guarantee user freedom by tying the availability of source code to every act of distribution. Its normative force rested on an implicit technical premise: that source code and object code stand in a well-defined, humanly auditable, and reproducible relationship. Large language models and, prospectively, Artificial General Intelligence (AGI) systems systematically violate this prem
Record details
Published: 2 June 2026
Source: arXiv
Category: Research
Topics: Copyright & IP · Transparency
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
A Framework for Graph-Conditioned Hierarchical Shapley Attribution in Patent Valuation
arXiv · 1 June 2026
Auditing Training Data in Domain-adapted LLMs: LoRA-MINT
arXiv · 5 June 2026
Vietnam clarifies AI authorship, training data and copyright liability: A comparative lens
Baker McKenzie Connect On Tech · 9 July 2026
WTF is SPUR’s publisher-run Content Telemetry Framework?
Digiday (AI/media) · 13 July 2026
Japan’s “Principle Code” for Generative AI (Part 2): What the Public Consultations Reveal
Baker McKenzie Connect On Tech · 29 July 2026
A Practice Auditing Framework for Large Language Model Use: Collective Empiricism, Pseudo-Rational Cognition, and Governance of AI-Generated Content
arXiv · 2 June 2026
How to cite this record
ethics.ai (2 June 2026), “Reproducibility is the New Copyleft: Defining AGI-oriented Reproducible Builds,” evidence record 3252, https://ethics.ai/record/3252 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.