AI regulation: Competition, arbitrage and regulatory capture
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Filippo Lancieri
Abstract
The commercial launch of ChatGPT in November 2022 and the fast development of large language models have catapulted the regulation of artificial intelligence to the forefront of policy debates. A vast body of scholarship, white papers, and other policy analyses followed, outlining ideal regulatory regimes for AI. The European Union and other jurisdictions have moved forward by regulating AI and LLMs. One overlooked area is the political economy of these regulatory initiatives—or how countries and companies can behave strategically and use different regulatory levers to protect their interests in the international competition on how to regulate AI.
This Article helps fill this gap by shedding light on the tradeoffs involved in the design of AI regulatory regimes in a world where (i) governments compete with other governments in using AI regulation, privacy, and intellectual property regimes to promote their national interests; and (ii) companies behave strategically in this competition, sometimes trying to capture the regulatory framework. We argue that this multilevel competition to lead AI technology will force governments and companies to trade off risks of regulatory arbitrage versus those of regulatory fragmentation. This may lead to pushes for international harmonization around clubs of countries that share similar interests. Still, international harmonization initiatives will face headwinds given the different interests and the high-stakes decisions at play, thereby pushing towards isolationism. To exemplify these dynamics, we build on historical examples from competition policy, privacy law, intellectual property, and cloud computing.
© 2025 by Theoretical Inquiries in Law
Articles in the same Issue
- Frontmatter
- AI, Competition & Markets
- Introduction
- Brave new world? Human welfare and paternalistic AI
- Regulatory insights from governmental uses of AI
- Data is infrastructure
- Synthetic futures and competition law
- The challenges of third-party pricing algorithms for competition law
- Antitrust & AI supply chains
- A general framework for analyzing the effects of algorithms on optimal competition laws
- Paywalling humans
- AI regulation: Competition, arbitrage and regulatory capture
- Tying in the age of algorithms
- User-based algorithmic auditing
Articles in the same Issue
- Frontmatter
- AI, Competition & Markets
- Introduction
- Brave new world? Human welfare and paternalistic AI
- Regulatory insights from governmental uses of AI
- Data is infrastructure
- Synthetic futures and competition law
- The challenges of third-party pricing algorithms for competition law
- Antitrust & AI supply chains
- A general framework for analyzing the effects of algorithms on optimal competition laws
- Paywalling humans
- AI regulation: Competition, arbitrage and regulatory capture
- Tying in the age of algorithms
- User-based algorithmic auditing