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Publish in core platform
No
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URL
https://www.oecd.org/publications/artificial-intelligence-data-and-competition-e7e88884-en.htm
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Link text
Artificial intelligence, data and competition
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Link Type
Skills Intelligence publication url
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Target audience
Digital skills for allDigital technology / specialisation
Artificial IntelligenceDigital skill level
BasicGeographic Scope - Country
European UnionIndustry - Field of Education and Training
Business and administration not further definedTarget language
Type of initiative
International initiative
Event setting
Publication type
General information
The impact of artificial intelligence (AI), particularly generative AI, on markets needs a close examination of its implications for competition. This paper, part of the OECD Artificial Intelligence Papers series, focuses on the potential effects of generative AI on market competition, considering the three key stages of AI development: training foundation models, fine-tuning, and deployment. It highlights the importance of maintaining competitive markets to ensure the broad benefits of AI while identifying risks to competition, such as linkages across the AI value chain and barriers to accessing critical inputs like quality data and computing power.
The life-cycle of generative AI is still developing, making it too early to predict how competition will evolve definitively. However, there are notable risks that merit attention. These include the potential concentration of market power due to interdependencies within the AI value chain and challenges in accessing necessary resources.
The paper emphasises the role of competition authorities and policy-makers in monitoring these developments and utilising various advocacy and enforcement tools to address potential issues. Furthermore, cooperation among authorities is crucial to maintaining expertise and effectively responding to the fast-changing AI landscape.
The paper is structured as follows:
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The first chapter provides an overview of the report and the context of AI in market competition.
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The second chapter explains critical concepts and the AI value chain, including essential inputs and their implications.
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The third chapter discusses potential competition issues within the AI sector and the rationale for considering these issues.
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The fourth chapter reviews the tools and strategies that competition authorities can use to address AI-related competition risks.
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The fifth chapter identifies potential future issues and areas for further exploration in AI competition policy.
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The sixth chapter summarises the findings and emphasises the importance of ongoing monitoring and cooperation among competition authorities.