Algorithmic Personalized Pricing in the United States: A Legal Void

Abstract

The United States is the Wild West of algorithmic personalized pricing. It is practiced (and researched) extensively, possibly more than anywhere else in the world, and at the same time, it is less regulated than in many of the jurisdictions surveyed in this Handbook, most notably the EU and China. This is not necessarily puzzling. American corporations have been the driving force behind many of the technological innovations associated with the rise and development of algorithmic personalized pricing. However, there is a long tradition in the US of opposition to regulating markets, and algorithmic personalized pricing exemplifies this approach. On this background, the goal of this Chapter is twofold.
First, the Chapter considers legal rules from various fields that can be used to regulate algorithmic personalized pricing. In mapping out and analyzing these rules, a primary aim of this Chapter is to demonstrate that many legal rules designed for seemingly unrelated purposes are, in fact, often well-suited to regulating algorithmic price personalization, with specific focus on antitrust law, consumer contracts law, and data protection law. While these legal fields have evolved, respectively, to protect competition, regulate consumers’ access to information, and protect consumers’ privacy (“data subjects,” in European terminology), each arguably has the potential to improve how the US legal system contends with algorithmic personalized pricing.
Second, using economic analysis, the Chapter seeks to develop analytical approaches to understanding how the legal rules it considers can be expected to affect algorithmic personalized pricing in ways that may not be immediately apparent. The analysis demonstrates the importance of understanding the economic (and technological) foundations of the phenomenon as well as the rules that regulate it. It is important to note that economic analysis here is not aimed at a normative evaluation of the extent to which the law should regulate algorithmic personalized pricing, which is a stance this Chapter refrains from taking given the theoretical and empirical ambiguity surrounding the welfare implications of algorithmic personalized pricing. Instead, focus is set on the potential effectiveness of certain legal rules for regulating algorithmic personalized pricing to any desired extent, without making any assertions about what that extent should be. Specifically, the Chapter demonstrates how economic analysis can inform two main lines of inquiry: first, whether a legal rule applies to algorithmic personalized pricing given the conditions stipulated by the former and the characteristics of the latter; and, second, how the legal rule, if applied, can be expected to affect sellers’ ability to engage in algorithmic personalized pricing. As such, the analysis attempts to develop the strongest claims for both sides of the debate over whether algorithmic personalized pricing should be limited or expanded.

Keywords: Algorithmic Pricing; Price Discrimination; Antitrust Law; Consumer Contracts Law; Consumer Protection Law

JEL Classification: K12; K21; D42