Google's people-first content page, dated October 1, now warns site owners that fabricating creator profiles counts as deception and "a signal of a low-quality page."

The update adds a new paragraph to the "Who (created the content)" section of Google's guidance for creating helpful, reliable, people-first content. The page now reads:

"However, avoid using deceptive authorship information. Fabricating creator profiles (such as by using AI-generated headshots, made-up names, or false credentials to make content appear as if it was written by human experts) is a form of deception. Any form of deception makes a page untrustworthy to both users and our automated quality systems, and is a signal of a low-quality page."

What changed in the guidance?

A copy of the page saved June 8 moves from the bylines advice directly to the "How" section, with no paragraph on deceptive authorship. The October 1 version inserts the new warning right after Google's existing advice to add accurate authorship information such as bylines.

The October 1 edit also adds a section defining main content. The Google Search Central documentation updates page logged the AI content guidance change the same day, but as of publication, it does not list the people-first content edit.

How does this compare to the rater guidelines?

Google's quality raters have worked from similar instructions for months. Section 4.5.3 of the Search Quality Rater Guidelines lists AI-generated content paired with made-up author profiles — built from AI images or deceptive bios — as an example of deception. The same section covers author profiles that falsely claim credentials, such as posing as a medical professional. Raters give such pages the Lowest rating.

Roger Montti covered that rater-side guidance in May 2025.

The people-first content page reminds publishers that search raters "have no control over how pages rank." The new paragraph instead points to Google's "automated quality systems." It does not explain how those systems would spot a fabricated profile, so the practical enforcement signal remains inference rather than confirmation.

What does this mean for publishers?

Sites that publish content under invented experts now see that practice labeled as deception in both the rater guidelines and the guidance written for site owners. Author pages and bylines are the most direct places to check that a name, photo, or credential isn't creating a false impression of human expertise.

Google's Search Liaison account said in January 2024 that bylines do not help pages rank better. The new warning shifts the focus from whether to use a byline to whether the person behind it is real.

For YMYL sites — health, finance, legal — the exposure is highest. The rater guidelines already single out fake medical credentials as an example. A medical review or financial guide attributed to a non-existent doctor now sits in the crosshairs of two Google documents at once.

Where does Google draw the line on deception?

The rater guidelines' deception section runs wider than the new Search Central paragraph. It also covers fake business details, impersonation, and deceptive page design. Google has not added those categories to the people-first content page.

The guidance targets the appearance of human expertise, not the use of AI to write content. It treats the fake profile as the deceptive act, separate from the question of how the text itself was produced. That distinction matters: a real author who uses AI to draft a post does not fall under this rule. An AI-built persona paired with AI-written text does.

What should publishers watch next?

The documentation updates page did not flag this particular edit, so check the people-first content page directly for further changes. Watch the rater guidelines for any shift that would expand the automated systems' detection of fabricated authorship. Monitor whether Google follows the rater-side list with broader site-owner rules covering fake business details and impersonation.

If Google adds detection signals to its automated systems, expect image-forensic checks, credential cross-referencing, and profile-pattern matching to surface as ranking factors in future core updates.