This study investigates the information diversity and authority shifts of Google’s AI Overviews for health queries in the United States.
RAT was used to collect the results of 900 health related search queries in Google in the United States to analyse the AI prevelance and the source overlap between organic results and AI citations.
Abstract
Commercial search engines are shifting from being intermediaries to generative answer engines, significantly altering Health Information-Seeking Behavior (HISB). Auditing these “black-box” systems is challenging due to dynamic client-side rendering and restricted data access. To address this, we use a custom-built browser extension to collect search engine results data. In a study of 900 health-related queries in Google US, we found an AI prevalence of 87.7% and a substantially low source overlap of 46.2% between organic results and AI citations. We observe a distinct platform shift: while organic rankings favor clinical authorities, generative AI elevates user-generated multimedia, making YouTube the second-most-cited source. Given high user trust in AI responses, this shift poses risks to public health, highlighting the need for independent auditing toolkits.
RAT functionality used
Scrapers: Google (US)
Publication
Paper
Sünkler, S., Lewandowski, D., Schultheiß, S., & Koop, O. (2026). Information Diversity and Authority Shifts in Google’s AI Overviews: An Audit of Health Queries. Companion Publication of the 2026 18th ACM Web Science Conference (WebSci Companion ’26), 24–28. https://doi.org/10.1145/3795513.3807429