[2511.12920] Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy

Computer Science > Computation and Language arXiv:2511.12920 (cs) [Submitted on 17 Nov 2025 (v1), last revised 20 Mar 2026 (this version, v3)] Title:Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy Authors:Desheng Hu, Joachim Baumann, Aleksandra Urman, Elsa Lichtenegger, Robin Forsberg, Aniko Hannak, Christo Wilson View a PDF of the paper titled Auditing Google's AI Overviews and Featured Snippets: A Case Study on Baby Care and Pregnancy, by Desheng Hu and 6 other authors View PDF HTML (experimental) Abstract:Google Search increasingly surfaces AI-generated content through features like AI Overviews (AIO) and Featured Snippets (FS), which users frequently rely on despite having no control over their presentation. Through a systematic algorithm audit of 1,508 real baby care and pregnancy-related queries, we evaluate the quality and consistency of these information displays. Our robust evaluation framework assesses multiple quality dimensions, including answer consistency, relevance, presence of medical safeguards, source categories, and sentiment alignment. Our results reveal concerning gaps in information consistency, with information in AIO and FS displayed on the same search result page being inconsistent with each other in 33% of cases. Despite high relevance scores, both features critically lack medical safeguards (present in just 11% of AIO and 7% of FS responses). While health and wellness websites dominate source categori...