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A Massachusetts school district published AI rules before Big Tech did
Publication date: 18.09.2026
In short
- Greg Jarboe advises brands to publish an AI accountability document, pointing to a Massachusetts school district that did it before Big Tech.
- Such a document should be dated, name its reviewer, and state plainly whether customer data goes into model training.
- The author argues that a published primary document is exactly what AI cites when asked about a company's accountability.
Big Tech spent years running on "launch first, ask permission later". Greg Jarboe writes in Search Engine Journal that with AI the approach has stopped working.
He cites surveys: 61% of Americans oppose new data centres near their homes, and 68% consider AI regulation too weak.
The gap between usage and trust is plain: people open assistants every day and at the same time do not believe the companies behind them.
79%of the district's students understand when using generative AI would harm their learning; another 72% know exactly what is allowed.
What the school district in Arlington did
The Arlington regional school district in Massachusetts (ABRSD) published its "AI Guidelines & Guardrails" several months before the large technology companies produced anything substantive.
The document rests on five principles: people first, adaptive literacy, responsible resource stewardship, strict governance and deliberate use.
The student survey figures are telling too: 79% understand when AI would harm their learning, and 72% know what exactly is permitted. The text is read, and it works.
What interests me most is something else: an organisation without corporate budgets managed what platforms with billions in revenue did not. Trust here is built on a document you can point at.
Three elements a brand can move onto its own site
Jarboe singles out three components, and each has its own logic for search.
- An indexed policy document: dated, signed, with names in it, rather than a vague "we care about ethics". Such a text becomes a primary source that AI can quote.
- An AI disclosure with a named reviewer. The author calls it a potential trust signal for readers and for the models already citing your content, and warns that it is not a legal disclaimer for the footer.
- A direct answer to the data question: whether customer data is used to train third-party models. After the Annenberg study, he says, people no longer take this on faith.
The practical part, which the original does not have, concerns our market. Ukrainian companies are only starting to write such pages, so there is almost no competition for queries like "does the company use your data to train AI".
If the page lives at its own URL, carries an update date and an author, it is easy to find and to quote. We wrote about who on the team should own such decisions in our piece on the owner of AI marketing accountability, and about making a page machine-friendly in the text on a single source of truth for AI.
Where the argument is weaker
It is worth remembering that this is an opinion column, not a study.
That AI really does cite accountability documents more often than anything else the author does not prove. It is an assumption that sounds logical, but nobody has measured it.
A school district is also not a brand: it has no competitors, no sales and none of the pressure that softens wording. Jarboe himself sums it up sharply: Big Tech "keeps trying to win it with a pitch instead of a document".
I'd build the page anyway. Not for the sake of being cited by AI, but because the question "what do you do with our data" will have to be answered sooner or later, and it is better to have a dated answer ready.
I am curious how many companies will follow the advice on paper only: publish the page and never name the reviewer.
