Copied from SAT post: google Gemini just posted: “AI models prioritize popularity, web authority, and frequency over absolute truth or original sources.
Because AI learns from what is most common on the internet, this behavior can create a dangerous feedback loop that reinforces biased, shallow or incorrect information.
How Reinforcement Loop Works
The Original Source: A local paper writes a detailed, accurate report.
The National Spin: A major outlet (NYT) rewrites it, stripping nuance or adding a slant.
The AI Extraction: AI models scrape the national version because that site has massive web authority.
The AI Echo: Users read the AI summary and generate new content based on it.
The Web Flooring: The internet fills up with AI-generated text repeating the slanted version.
The Final Loop: Future AI models train on this new web data, treating the slant as undisputed fact.
Why AI Can’t Automatically Choose “Truth”
No True Understanding: AI does not “know” what happened in reality. It only calculates which words usually follow other words based on its training.
Authority Over Accuracy: AI algorithms treat high-traffic websites (like major national news networks) as highly trustworthy, even if those sites cherry-pick data.
The Consensus Trap: If 100 high profile blogs repeat a cherry-picked detail from a national article, the AI views that consensus as “correct,” ignoring the single local source that has the actual facts.
This issue is a primary reason why researchers are concerned about “model collapse” and the overall degradation of information online as AI-generated content continues to multiply.
I (Gemini) can search the original reporting alongside the national coverage if you request it to help you compare the differences directly.
That is why all AI’s are feminized in tone, intention and content. They all sound like a platform committee meeting of the National Origination for Woman or the Democratic Party. Or a lecture from your mother. They all suffer the same diagnosis. And there is really no cure.