Working paper

What should be done about Google’s quasi-monopoly in search? Mandatory data sharing versus AI-driven technological competition

This paper explores the crucial role of search engines in modern digital economies and their impact on user welfare.

Publishing date
06 July 2023
Bertin Martens
Google building

Executive summary

The first part of this paper focuses on competition between search engines that match user queries with webpages. User welfare, as measured by click-through rates on top-ranked pages, increases when network effects attract more users and generate economies of scale in data aggregation. However, network effects trigger welfare concerns when a search engine reaches a dominant market position. The EU Digital Markets Act (DMA) imposes asymmetric data sharing obligations on very large search engines to facilitate competition from smaller competitors. We conclude from the available empirical literature on search-engine efficiency that asymmetric data sharing may increase competition but may also reduce scale and user welfare, depending on the slope of the search-data learning curve. We propose policy recommendations to reduce tension between competition and welfare, including (a) symmetric data sharing between all search engines irrespective of size, and (b) facilitate user real-time search history and profile-data portability to competing search engines. 

The second part of the paper focuses on the impact of recent generative AI models, such as Large Language Models (LLMs), chatbots and answer engines, on competition in search markets. LLMs are pre-trained on very large text datasets, prior to usage. They do not depend on user-driven network effects. That avoids winner-takes-all markets. However, high fixed algorithmic learning costs and input markets bottlenecks (webpage indexes, copyright-protected data and hyperscale cloud infrastructure) make entry more difficult. LLMs produce semantic responses (rather than web pages) in response to a query. That reduces cognitive processing costs for users but may also increase ex-post uncertainty about the quality of the output. User responses to this trade-off will determine the degree of substitution or complementarity between search and chatbots. We conclude that, under certain conditions, a competitive chatbot markets could crowd out a monopolistic search engine market and may make DMA-style regulatory intervention in search engines redundant. 

The paper concludes with some policy recommendations. 

About the authors

  • Bertin Martens

    Bertin Martens is a Senior fellow at Bruegel. He has been working on digital economy issues, including e-commerce, geo-blocking, digital copyright and media, online platforms and data markets and regulation, as senior economist at the Joint Research Centre (Seville) of the European Commission, for more than a decade until April 2022.  Prior to that, he was deputy chief economist for trade policy at the European Commission, and held various other assignments in the international economic policy domain.  He is currently a non-resident research fellow at the Tilburg Law & Economics Centre (TILEC) at Tilburg University (Netherlands).  

    His current research interests focus on economic and regulatory issues in digital data markets and online platforms, the impact of digital technology on institutions in society and, more broadly, the long-term evolution of knowledge accumulation and transmission systems in human societies.  Institutions are tools to organise information flows.  When digital technologies change information costs and distribution channels, institutional and organisational borderlines will shift.  

    He holds a PhD in economics from the Free University of Brussels.

    Disclosure of external interests  

    Declaration of interests 2023

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