This issue reminded me of the following:
These conditions are ripe for "copyright laundering"-the use of multi-generational synthetic pipelines, an "AI Ouroboros," to render traditional proof of infringement impracticable.
This Article adapts the "fruit of the poisonous tree" (FOPT) principle to propose a novel AI FOPT standard: if a foundational AI model's training is adjudged infringing (either for unlawful sourcing or for non-transformative ingestion that fails fair-use), then subsequent AI models principally derived from the foundational model's outputs or distilled weights carry a rebuttable presumption of taint.
The burden then shifts to the downstream developers-those who control the evidence of provenance-to restore the evidentiary bargain by affirmatively demonstrating a verifiably independent and lawfully sourced lineage or a curative rebuild, without displacing fair-use analysis at the initial ingestion stage. Absent such proof, commercial deployment of tainted models and their outputs is actionable.
Source: https://arxiv.org/pdf/2601.02631 (Copyright Laundering Through the AI Ouroboros...)