The researchers found no statistical link between more AI text and more factual errors online. Fears that writing styles, source links, and meaningful content would deteriorate were not confirmed in the measurements either.
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A new study measured how AI-generated text actually affects the content on the internet, not just what people believe about it.
To obtain a representative sample, the researchers drew web pages from the Internet Archive’s Wayback Machine. The pages were published between 2022 and 2025, spread across 33 months from August 2022 to May 2025. To determine whether a text was written by a human or AI, they used the detector Pangram v3, which was the most reliable of four tested tools.
They also asked 853 adults in the United States what they believed about six possible negative effects of AI text. The sample was representative in terms of age distribution, sex, and ethnicity.
In the measurement, the curve does in fact lean toward fewer factual errors as AI text increases. But the correlation is not statistically significant, so the researchers’ conclusion is more cautious: they find no evidence that AI text has led to more factual errors on the internet.
A common fear is that the internet would fill up with incorrect information as AI text increases. In the survey, 75.1 percent of respondents leaned toward agreeing with that.
The measurement showed something else. There was no statistical link between the share of AI text and the share of incorrect statements (ρ = −0.19, p = 0.27). To check facts, the researchers had a language model pull out concrete claims from the pages. Then 50 people manually checked whether the claims were correct.
Three other fears could not be confirmed either. That individual writing styles would disappear in favor of a uniform voice was believed by 83.0 percent, but the measurement showed no link (ρ = 0.24, p = 0.17). That articles stop linking to external sources was believed by 69.9 percent (ρ = −0.12, p = 0.48). That texts become longer but say less was believed by 60.7 percent (ρ = −0.02, p = 0.89). None of these links were found in the figures.
Two of the six hypotheses were confirmed. AI pages had 33 percent higher similarity between ideas and perspectives than pages written by humans (0.0701 vs. 0.0526). AI pages also had 107 percent higher share of positive language (0.7042 vs. 0.3400).
Those who use AI tools often were less likely to believe in the negative effects than those who rarely use them (76.2 percent vs. 88.3 percent). Those with a negative view of AI believed in the effects more than those with a positive or neutral view (91.3 percent vs. 71.1 percent).
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