Monopolizing Water in a Tsunami: Finding Sensible Antitrust Rules for Big Data

Posted by Social Science Research Network

Monopolizing Water in a Tsunami: Finding Sensible Antitrust Rules for Big Data

David A. Balto & Matthew Cameron Lane (Law Offices of David A. Balto)

Abstract:     Competition concerns related to the collection, use, and sale of data have gained currency recently, and there are claims that this is a fundamentally different and new challenge for antitrust. These concerns range from companies not being able to achieve minimum efficient scale of data, data being a barrier to entry, and abuse of privacy as both a signal of and abuse in its own right of market dominance. The focus of these concerns has centered on personal data, not business data. Personal data is generally defined as describing aspects of the person generating that data.

However, these concerns are poorly explained and confusing because they often don’t define what “data” is relevant or the competitive mechanism by which the data is collected and used or allegedly misused. It is lazy to talk about “data competition” generally because the analysis of data with respect to competition varies fundamentally based on whether the data is an input versus an output; or is common and non-rivalrous (e.g., browsing behavior) versus unusual and difficult to collect (e.g., health records).

This paper addresses three questions: 1) does competition law have the tools to address anticompetitive uses of data; 2) would jurisprudence support expanding the scope of competition law to account for data concerns; and 3) would expanding the scope of competition law be beneficial, i.e., does it add value to pursue matters through competition laws rather than other laws such as consumer protection laws. The paper focuses on common personal data, such as that sold by data brokers, and does not comment on niche data sets, like health records, that can involve unique characteristics that lead to different issues and concerns.