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.

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Abstract

Web2 giants and Web3 projects entertain a complex relationship. They cooperate to maximize their chances of survival, yet they also compete through a combination of dynamic factors and anti-competitive strategies. The present contribution untangles Web2 and Web3’s relationship, explores their distinct value propositions, and outlines what may be one of tomorrow’s enforcement priorities for antitrust agencies.

Abstract

Computational antitrust promises not only to help antitrust agencies preside over increasingly complex and dynamic markets, but also to provide companies with the tools to assess and enforce compliance with antitrust laws. If research in the space has been primarily dedicated to supporting antitrust agencies, this article fills the gap by offering an innovative solution for companies. Specifically, this article serves as a proof of concept whose aim is to guide antitrust agencies in creating a decision-trees-based antitrust compliance API intended for market players. It includes an open access prototype that automates compliance with Article 102 TFEU, discusses its limitations and lessons to be learned.

Abstract

In the first quarter of 2022, the Stanford Computational Antitrust project team invited the partnering antitrust agencies to share their advances in implementing computational tools. Here are the results of the survey.

Abstract

The classical “law & technology” approach focuses on harms created by technology. This approach seems to be common sense; after all, why be interested—from a legal standpoint—in situations where technology does not cause damage? On close inspection, another approach dubbed “law + technology” can better increase the common good.

The “+” approach builds on complexity science to consider both the issues and positive contributions technology brings to society. The goal is to address the negative ramifications of technology while leveraging its positive regulatory power. Achieving this double objective requires policymakers and regulators to consider a range of intervention methods and choose the ones that are most suitable.

Law and technology overlap in many ways, but scholars and regulators tend to focus on incompatibilities between the two. I propose that they also explore synergies between law and tech, and address frictions in a way that preserves them. This exploration should begin with blockchain and antitrust.

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ICLE President Geoffrey Manne moderated a Nov. 17 chat with Thibault Schrepel, author of Blockchain + Antitrust: The Decentralization Formula, and Neil Chilson, author of Getting out of Control: Emergent Leadership in a Complex World. The full clip is embedded below.

The Digital Markets Act (“DMA”) is a complex piece of regulation. It includes some great ideas (as tackling predatory innovation) while being surprisingly conservative (defined as “?the wish to resist great or sudden change” by the Oxford Dictionary).

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