From Theory to Tech: Computational Antitrust

Eugenio Ruiz-Tagle W. Abogado, Pontificia Universidad Católica de Chile. Master of Laws (University College London) y Master of Science in Computer Science (Birkbeck College, University of London). El autor se desempeñó como Sub Jefe de la División Anti-Carteles de la Fiscalía Nacional Económica entre 2017 y 2022. Actualmente es colaborador del proyecto Computational Antitrust del centro Codex de la Universidad de Stanford.

Building upon the characterization of “Political Antitrust” and “Economic Antitrust” as successive ‘waves’ in the evolution of Antitrust law, this paper explores the hypothesis—originally introduced by Dr. Thibault Schrepel—that we are now entering a phase termed “Computational Antitrust” or “Antitrust 3.0.” This emerging era arises from exponential advances in computing power, the expansion of network infrastructure, and digital transformation of nearly all aspects of economic life. These and other technological achievements have driven the emergence of “Algorithmic Competition,” a phenomenon that has garnered attention from both international organizations and competition authorities, as it may pose significant challenges to the institutions tasked with preserving competitive markets. These developments might also call into question established paradigms in competition policy.

In response, authorities face the task of implementing a strategy aimed at integrating analytical tools and computational methods throughout multiple dimensions of their workflow. This paper underscores the importance of investing in both technological infrastructure and specialized human resources, fostering a collaborative environment among data scientists, computer science experts, economists, and legal professionals. Additionally, it examines the Stanford University Computational Antitrust Project and its contributions to advancing interdisciplinary research networks to connect experts, academics, and competition agencies globally.

Finally, this work proposes a roadmap to Computational Antitrust is envisioned as a bottom-up structured progression, with Latin America and other developing jurisdictions in mind. It is structured around three key milestones: Adopting Big Data management methods for optimizing and organizing internal ‘experience-base’ resources, establishing Data Units following best international experiences, and deploying advanced predictive tools to support judicial decision-making and legal reasoning. The paper concludes offering reflections on the challenges ahead.

«This incremental strategy acknowledges the realities faced by Latin America and other developing regions, where competition agencies often contend with resource constraints, limited staffing and infrastructure to meet the demands of the digital economy. However, precisely because of these limitations, a well-planned action plan, optimized use of existing resources, and a focus on building local technical capacity could enable these jurisdictions to achieve a comparatively greater productivity boost than their counterparts in more developed countries».

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