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Begin New Search Topic Artificial Intelligence Author Christophe Carugati

1. Antitrust issues raised by answer engines

Author:
Christophe Carugati
Publication Date:
06-2023
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Rapid development of generative artificial intelligence chatbots like ChatGPT is leading search engine providers to move from search to answer engines. Unlike search engines, which provide search results in the form of blue links to content creators, answer engines generate personalised answers through a conversation with end users. This revolution impacts the internet ecosystem of content creators and the digital advertising market. This paper outlines some early antitrust issues related to answer engines, from the transition from search to answer engines (sections 2 and 3) and the response competition authorities should adopt (section 4). It finds that search and answer engines complement and compete with each other. While the answer-engine market is still at an early stage of development, it already raises some competition issues in relation to data scraping, vertical integration and unfair terms and conditions. Intervention by competition authorities is more likely than not to prevent market power in this new market. In this regard, competition authorities should act to preserve dynamic competition and minimise adverse effects on content creators. Finally, the paper concludes with several research questions for future research (section 5).
Topic:
Science and Technology, Governance, European Union, Digital Economy, Innovation, Artificial Intelligence, and Competition
Political Geography:
Europe

2. The competitive relationship between cloud computing and generative AI

Author:
Christophe Carugati
Publication Date:
12-2023
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Cloud computing providers and generative artificial intelligence (GenAI) providers nurture a close, interdependent relationship: GenAI providers need cloud providers to train, run and deploy their GenAI solutions, while cloud providers see GenAI providers as a business driver to grow their market shares in cloud and related markets, such as productivity software or search engines. The cloud/GenAI relationship takes various forms, including exclusive and strategic partnerships, especially between large cloud providers and GenAI providers across all parts of the cloud market, including infrastructure, platforms and software. Competition benefits and risks are likely to result from the relationships. Competition benefits arise from increased competition and innovation in the cloud and GenAI sectors. Risks relate to potential concentrations arising from the partnerships between cloud and GenAI providers, and from anticompetitive practices, including discrimination in the supply of IT equipment by dominant IT providers, interoperability obstacles to switching, use of business-user data, self-preferencing of cloud services over third parties, tying and pure bundling. Merger control and antitrust laws can address some of the competition risks, while laws, including the European Union’s Digital Markets Act and Data Act, can deal with competition issues in digital markets and the cloud sector. Nevertheless there are gaps. The European Commission should amend existing EU instruments, including by changing the definition of a concentration under merger control, and should specify interoperability requirements for cloud providers under the Data Act. The Commission should also closely monitor developments in and outside Europe through market investigations, including with international counterparts, and should intervene to tackle imminent competition risks using fast procedural tools, such as interim measures.
Topic:
European Union, Antitrust Law, Artificial Intelligence, Cloud Computing, and Competition
Political Geography:
Europe and Global Focus

3. Competition in generative artificial intelligence foundation models

Author:
Christophe Carugati
Publication Date:
07-2023
Content Type:
Working Paper
Institution:
Bruegel
Abstract:
Foundation models (FMs) are the origin of breakthrough innovations in generative artificial intelligence (AI) applications, such as ChatGPT. Only responsible developments in competitive markets can help ensure that FMs deliver their full benefits at minimum risk. FM developers require language models (LMs), data and computing power to generate natural language output, such as texts, from language input. Thus, the FM value chain is composed of three main elements: LMs, data and computing resources. These markets are currently competitive, with multiple providers and degrees of openness thanks to several closed- and open-source models, open-source and proprietary data, and vigorous competition between firms at the computing-resources level, despite high degrees of concentration in some of these markets. These market characteristics ensure that FM developers face low or surmountable entry barriers. Still, potential competition issues are likely to arise in the future. Dominant firms could leverage their dominant positions, refuse to give access to their LMs, scrape data, refuse to grant access to data, impose undue barriers to switching and lock their users into their ecosystems. Firms could also use LMs to achieve an anticompetitive agreement through algorithmic collusion. Competition authorities should focus their efforts on short-term risks. They should also remain vigilant in terms of ensuring the competitive process between open- and closed-source models works and that open-source developers and public authorities do not impose undue restrictions to mitigate the risks of open-source models, which would deter their development in a way that would favour closed-source models. Finally, at this development stage, studies are lacking. Researchers and competition authorities should investigate the impact of fms on content providers and the digital advertising industry, the role of FMs in digital ecosystems, and cooperation mechanisms between competent authorities across regulatory fields and countries.
Topic:
Digital Economy, Artificial Intelligence, Competition, and ChatGPT
Political Geography:
Global Focus