The uneven rise of AI-generated web content
Read the original on Hugging Face Trending Papers →The Flow has not summarised this story yet — read it at Hugging Face Trending Papers.
The Flow has not summarised this story yet — read it at Hugging Face Trending Papers.
The study examines how generative AI has reshaped the public web in under five years, using over 5 million crawlable pages. It finds that AI-generated text has risen sharply but unevenly, with higher prevalence on English-language and .com sites, lower on .gov and .edu, and varying by a page’s centrality in the web graph. The authors employ multiple detection tools and a Bayesian hierarchical model to estimate prevalence while accounting for detector errors.
DeGenTWeb is a system that identifies websites whose informational prose is largely machine‑generated text (MGT) with minimal human input. By adapting MGT detectors for web pages and aggregating results across sites, the study reports that 20.9% of Common Crawl‑archived sites (Jan–Jul 2026) and 13.6% of Bing‑linked sites (2025) are MGT‑dominant, with a 0.12% mislabeling rate for human‑authored sites. The prevalence of MGT‑dominant sites is increasing over time and many share the same owner.
The study measures Google AI Overviews (AIOs), noting they activate for 13.7% of queries overall and 64.7% of question-form queries, with lower rates for politically sensitive topics. AIOs cite more credible domains than typical search results, yet 30% of cited pages are not shown in the first-page results, indicating a distinct source selection process. Among 98,020 atomic claims, 11.0% lack support from cited pages, mainly due to omissions, and over half of cited pages contain display ads, reducing publisher revenue while Google’s ads remain.
arXiv:2609.15369v1 Announce Type: new Abstract: Word-level detectors identify unedited AI-generated text almost perfectly, but the literature documents their brittleness under rewording, and a word-l...
arXiv:2605.16428v4 Announce Type: replace-cross Abstract: Search engines traditionally complement online content platforms by directing users seeking information to external websites. The emergence o...
arXiv:2603.16138v2 Announce Type: replace-cross Abstract: Generative search systems are increasingly replacing link-based retrieval with AI-generated summaries, yet little is known about how these sy...