Abstract

The AI Act is poised to become a pillar of modern competition law. The present article seeks to provide competition practitioners with a practical yet critical guide to its key provisions. It concludes with suggestions for making the AI Act more competition friendly.

Read at SSRN.

Abstract

The Federal Trade Commission and the U.S. Department of Justice published a draft update of their merger guidelines in July 2023. This paper reviews the Draft Merger Guidelines from a dynamic competition perspective. We base our findings and recommendations on recent economic literature dealing with innovation.

Abstract

W. Brian Arthur is the father of complexity economics. He is also known for his work on the nature of technology, his experiments with agent-based modeling, and his entrepreneurial approach to science. This article seeks to explore the reasons why a scholar might identify as an “Arthurian,” with the aspiration of encouraging others to embrace Arthur’s research interests and emulate his approach to science.

Abstract

Generative AI is set to become a critical technology for our modern economies. If we are currently experiencing a strong, dynamic competition between the underlying foundation models, legal institutions have an important role to play in ensuring that the spring of foundation models does not turn into a winter with an ecosystem frozen by a handful of players.

Abstract

In the first quarter of 2023, the Stanford Computational Antitrust project team invited the partnering antitrust agencies to share their advances in implementing computational tools. Here are the 26 contributions we received.

Abstract

Innovation plays a crucial role in defining competitive dynamics. Given this fact, one might expect ‘innovation’ to play a consistent role in antitrust law. The present article conducts a systematic content analysis of the case law of the Court of Justice of the European Union to test this hypothesis. The results suggest that EU courts assign a fragmented role to innovation in competition law cases. We end with proposals to remedy this situation.

Video from the International Center for Law & Economics’ (ICLE) March 24, 2023 event “Exploring the Outer Boundaries of Antitrust: Democracy, Sustainability, & Industrial Policy” in Madrid, Spain. This session features a debate, moderated by ICLE Academic Affiliate Thibault Schrepel of Vrije Universiteit, between Giorgio Monti, professor of competition law at Tilburg Law School, and Nicolas Petit, joint chair in competition law at the European University Institute’s Department of Law and at the Robert Schuman Centre for Advanced Studies, on the topic “Should Antitrust Pursue Broader Social Goals?” The full video is embedded below.

Abstract

Complexity science permeates the policy spectrum but not antitrust. This is unfortunate. Complexity science provides a high-resolution screen on the empirical realities of markets. And it enables a rich understanding of competition, beyond the reductionist descriptions of markets and firms proposed by neoclassical models and their contemporary neo-Brandeisian critique. New insights arise from the key teachings of complexity science, like feedback loops and the role of uncertainty. The present article lays down the building blocks of a complexity-minded antitrust method.

Counter-positioning is a business strategy in which a company positions itself in a way that its competitors are unwilling to replicate to avoid cannibalization. A well-known example of counter-positioning is Netflix’s policy not to charge late fees. In 2000, Blockbuster was earning a large portion of its revenue ($800 million) from late fees. When Netflix entered the market, the company began shipping DVDs to customers’ homes. Customers could pay for up to three DVDs at a time, and if they didn’t return them, Netflix simply wouldn’t send the next one on the list. This strategy caused Blockbuster to eliminate late fees in 2004, i.e., Netflix essentially forced Blockbuster to cannibalize its business model in order to survive.

By integrating ChatGPT, Bing is poised to put Google in a similarly difficult situation. In 2021, Google earned $148.95 billion (out of $256.74 billion) from search ads. The more users click on different results and reformulate requests, the more advertisers are willing to pay to appear at the top… the more Google generates revenue.

Read the full piece here.