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Google’s Policy on AI-Generated Content
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GUIDE Sosiete
A content farm publishes large volumes of low-value pages, sometimes using generative AI, scraping, or rewriting to attract traffic.
High output, templated pages, and weak sourcing justify closer review but do not prove AI authorship; evaluate reporting, sourcing, corrections, ownership, and value to readers.
A content farm is generally understood as a publishing operation that produces many pages to capture attention or search traffic while contributing little original reporting or value for readers. Generative AI can be one production method, but high volume does not establish that a page was written by AI. People can mass-produce thin material, while a newsroom may use AI responsibly and still publish well-researched reporting. The important questions concern evidence, accountability, and usefulness. Review several pages rather than judging one article. Do claims link to primary documents, named experts, or direct reporting? Does the site add reporting or mostly paraphrase other pages? Can readers identify its owner, editors, author expertise, contact information, and correction process? Are there many near-duplicate pages targeting small keyword variations, irrelevant links, or citations that do not support the cited sentence? These clues guide investigation but do not prove authorship, coordination, or deception. Trace citations to their underlying material. Google Search’s spam policy defines scaled content abuse around generating many pages primarily to manipulate search rankings rather than help users. It says this may happen regardless of how content is created, including generative AI, scraping, or other methods. This is a search policy, not a general judgment that all AI-assisted publishing is abusive or proof that a particular site used AI. Search enforcement decisions also do not independently verify each factual claim on a page. Readers should corroborate consequential claims with original reporting, public records, and independent outlets with their own sourcing. Record exact URLs and dates when documenting a suspected network because pages can change. Avoid treating AI-detector results or repetitive prose as verdicts. If the evidence establishes only that a site publishes repetitive, weakly sourced pages, say that. If a claim cannot be verified, leave it unverified rather than repeating it as news.
Gaañ-gaañu IA yu mag yi ak yu bës bu nekk yépp a ngi aju ci ki xam risk yi ak ki mëna def dara.
Liggéeyukaay ak xam-xam bu ñépp bokk mooy wane ndax politiku kaaraange bu dëgër mën na am ci wàllu politik.
Faram-fàcce yu leer dañuy wàññi li ñuy jàpp ci hype, PR lab, ak tiyaatar bu leerul.
Search systems and publishers will continue changing quality signals and disclosure practices as AI-assisted production spreads. Provenance and editorial records may help readers assess accountability, but no label replaces checking the reporting itself. A publisher may mix human reporting, automation, and syndication across pages. A durable habit is to evaluate each claim’s evidence, inspect the publisher’s accountability, and corroborate consequential facts through independent sources. Assess quality and sourcing without guessing at unseen production methods. Readers can also retain page captures and note correction dates when a claim matters.
A reader checks whether a headline links to original records or merely repeats another site.
An editor compares author information and sourcing across a group of pages.
A journalist checks ownership, contact details, and the site’s correction process.
A researcher applies Google’s scaled-content policy without treating it as an AI detector.
Jàppale risku nekk gi ni siyaas fiksioŋ fekk kàttan gi dafay yokk.
Jaxasoo kaaraange produit surface ak jubluwaay ci suufu autonomie bu kawe.
Bàyyi nit ñi xamul làkku Àngle ak ñi xamul làkku Angale, ñu am balluwaay yu baaxul.
Tàqale loraange yi ci produit bi, jëfandikoo bu baaxul, ak risku ñàkka mëna yor / ñàkka méngoo.
Laajteel ban firnde mooy soppi sa xalaat ci kalendriye yi ak tar gi.
Danga taamu balluwaay yu njëkk yi ak jàngat yu fëgër yi moo gën waxtaanu njaay mi.
Xaarandil benn yoonu jëf: liggéey, politik, xaalis, wala xam-xam — du xam-xam kese.
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A content farm publishes large volumes of low-value pages, sometimes using generative AI, scraping, or rewriting to attract traffic. High output, templated pages, and weak sourcing justify closer review but do not prove AI authorship; evaluate reporting, sourcing, corrections, ownership, and value to readers.
High output can merit scrutiny but does not show the production method.
Google defines abuse by purpose and user value, regardless of method.
Missing bylines are a transparency signal, not proof of method or truth.
These details help identify responsibility and correction practices.
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Up nextGis bi ci topp
Google’s Policy on AI-Generated Content
Askan wi