The book "Artificial Intelligence and Competition Policy" is edited by Alden Abbott (Mercatus Center at George Mason University) and Thibault Schrepel (Vrije Universiteit Amsterdam (VU Amsterdam) & Stanford University) and published by Concurrences. The book contains 20 essays by leading academics and practitioners that explore a wide range of issues related to the impact of AI on the competitive process. Divided into three sections, the collection of essays provides a solid foundation for exploring the emerging issues: "Market Dynamics, Mergers and Partnerships in AI", "AI Challenges for Competition Law" and "Policy Responses to the AI Boom".
The publication by Dr Noskova and Prof Budzinski (pp. 231-243) takes a closer look at the use of algorithms in merger review. Each subsection deals with one of the standard steps in merger review: (1) selection of merger and acquisition cases for notification, (2) investigation phase, (3) judicial proceedings, (4) final decision (with or without remedies), and (5) ex post control (if applicable), and discusses the applicability and existence of computational tools within the respective step. It also addresses two research questions: (1) does the use of computational tools allow for a better selection of merger cases, and (2) are predictions of merger effects based on computational tools better than those based on typical types of evidence? The chapter draws on insights from computational research in merger review, modern economics, institutional economics and political economics. Among other findings, the authors conclude that each step of the merger review process offers opportunities to improve the quality of merger analysis.
The published chapter can be accessed: www.researchgate.net/publication/385015295_Computational_Methods_in_the_Evaluation_of_Mergers_and_Acquisitions
The book: https://www.concurrences.com/en/all-books/artificial-intelligence-and-competition-policy