SOURCE-LINKED INTELLIGENCE
Beyond "Made with AI": Visualizing Provenance Density to Mitigate the Transparency Penalty
As generative AI makes polished prose cheap to produce, users can no longer rely on fluency as a proxy for truth. We call this failure mode the Fluency Trap: users trust fluent hallucinations while also discounting accurate content once it is disclosed as AI-generated. Binary ``Made with AI'' labels respond with authorship disclosure, but they do not show what supports a claim. We propose Provenance Density, an evidence-visualization interface that shows the density of verified claims in a text. In a user study with 81 participants, an idealized Provenance Density interface produced a large di
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-03T07:18:42.000Z
First collected: 2026-09-21T05:11:56.580Z. This is not the publication date.