In this episode, Alba Ribera Martínez interviews Todd Davies, a former Google engineer and competition law scholar, about the implications of AI Overviews in Google Search. They explore how AI features are transforming search dynamics, competition concerns, and potential regulatory responses.
Find Todd's and Spencer Cohen's paper, Opt-out Remedies Will Not Fix AI Overviews here: https://doi.org/10.1093/jeclap/lpag025.
Throughout the conversation, we touched upon a few topics relating to the deployment of AI Overviews on Search. Click on them below to access them directly:
- Google's introduction of AI Overviews: https://blog.google/products-and-platforms/products/search/generative-ai-google-search-may-2024/.
- Google's experience researchers, often known as User Experience (UX) Researchers, are professionals dedicated to understanding how people interact with technology to build better, more inclusive products for everyone. They conduct in-depth studies, including interviews, surveys, and usability tests, to inform the design and functionality of Google products.
- The European Commission's sanctioning of Google for its conduct in the Google Shopping vertical: https://ec.europa.eu/competition/antitrust/cases/dec_docs/39740/39740_14996_3.pdf.
- AI Overviews Impact on Traffic: https://www.theguardian.com/technology/2025/jul/24/ai-summaries-causing-devastating-drop-in-online-news-audiences-study-finds.
- Click-through rates decrease as a consequence of the introduction of AI Overviews: https://searchengineland.com/google-ai-overviews-hurt-click-through-rates-454428.
- European Commission's cases against Google's AI Overviews: https://ec.europa.eu/commission/presscorner/detail/da/ip_25_2964.
- The General Court's ruling in the EC's Google Android case, para 1028: https://infocuria.curia.europa.eu/tabs/document?source=document&text=&docid=265421&pageIndex=0&doclang=EN&mode=lst&dir=&occ=first&part=1&cid=100147.
- The relevance of secondary reporting, as illustrated by TV series: https://www.imdb.com/title/tt35615598/.
- Grounding in AI is the process of connecting an AI model's abstract, probabilistic language outputs to verified, real-world data and context. It acts as a "reality check" to prevent hallucinations (invented content), ensuring answers are accurate, relevant, and backed by specific information.
- Madhavi Singh and Fiona Scott Morton's paper, A Roadmap for a Monopolization Case against Google: Monopsony Power and AI Overviews: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6303280.
To learn more about Dr. Alba Ribera Martínez and her research, we invite you to visit her website: https://www.albariberamartinez.com.
She also writes, from time to time, in her newsletter, the DMA Agora, about the latest developments surrounding the European regulation: https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7344021393451184128.