Machine Learning Archives - Columbia Law Review

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Introduction The leading online platforms—Google in search, Facebook in social network services, and Amazon in e-commerce—benefit from economies of scale and access to user data that are difficult for rivals to replicate. These barriers are reinforced by advances in machine learning, a set of artificial intelligence (AI) techniques[footnote]As used here, artificial intelligence refers to technologies that mimic or resemble some aspect of human intelligence. In some contexts, the AI label can be misleading, given that the task at issue—for example, online search—was automated to begin with, and the deployment of improved software does not entail any direct replacement of labor. See Timothy Bresnahan, Artificial Intelligence Technologies and Aggregate Growth Prospects 2 (May 2019) (unpublished manuscript) (on file with the Columbia Law Review ) (discussing this issue).[/footnote] that use models to “learn” desired behavior from “examples rather than instructions.”[footnote]Machine Learning, IBM Design for AI, https://ai-design.eu-de.mybluemix.net/ design/ai/basics/ml [https://perma.cc/T5NK-TCU7] (last visited Sept. 30, 2019). See generally A.L. Samuel, Some Studies in Machine Learning Using the Game of Checkers, 3 IBM J. Res. & Dev. 211 (1959) (coining the term “machine learning”). For further discussion, see infra section I.A.[/footnote] This Essay considers how competition might be enhanced, notwithstanding these advantages, under existing antitrust law.[footnote]Machine learning also challenges antitrust policy by facilitating collusion and price discrimination. For a discussion, see generally Ariel Ezrachi & Maurice Stucke, Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy (2016). These developments are beyond the scope of this Essay.[/footnote] Two sources of platform competition are particularly important. A nascent competitor is a threatening new entrant that, in time, might become a full-fledged platform rival. For example, Instagram posed an important threat to Facebook shortly after Instagram’s launch in 2010. A disruptive incumbent is an established firm, often another platform, that introduces fresh competition in an adjacent platform market. For example, Microsoft’s Bing search platform competes with Google’s. In turn, Google vies with Amazon for so-called shopping starts—that is, to be the starting place for online shoppers. Antitrust law protects nascent competitors as a source of platform entry.[footnote]See infra Part II.[/footnote] This Essay argues that the Sherman Act prohibits the acquisition of a nascent competitor as a form of unlawful monopolization.[footnote]See 15 U.S.C. § 2 (2012).[/footnote] Monopolization, a branch of antitrust law typically concerned with exclusionary conduct, also reaches acquisitions and other cooperative behavior. The law extends to both newly announced mergers and other transactions, such as Facebook’s acquisition of Instagram in 2012, that have been consummated. Some transactions also violate Section 7 of the Clayton Act, the statute ordinarily relied upon to prohibit unlawful mergers.[footnote]See id. § 18.[/footnote] The Sherman Act approach, however, is a better fit for the evaluation of some acquisitions, due in part to judicial recognition that the target need not operate in the same antitrust market as the acquirer.[footnote]See infra section II.B.[/footnote] Disruptive incumbents are a second, and underappreciated, source of platform competition.[footnote]See infra Part III.[/footnote] A disruptive incumbent is well positioned to compete with a dominant platform in an adjacent market. Such firms can deploy a variety of large-firm advantages without fear of cannibalizing their home market. Thus, disruptive incumbents sidestep a longstanding debate, associated with economists Joseph Schumpeter and Kenneth Arrow, about whether monopoly or competition best promotes innovation.[footnote]See infra section III.A.[/footnote] This Essay suggests that antitrust enforcers should consider a lighter touch toward enforcement, on the margin, if such a firm is “punching up” to compete with a platform—think of Google presenting shopping search results in a particular (by assumption, legally contestable) manner to better compete with Amazon. As challengers, neither nascent competitors nor disruptive incumbents are sure things. Instagram, absent the acquisition, might have failed to compete with Facebook. Google might ultimately lose its battle with Amazon for shopping starts, even if antitrust enforcers leave this aspect of its conduct alone. Given the potentially large benefits of successful competition from a disruptive incumbent, a modest probability of success may sometimes justify a lighter touch, provided that the negative collateral consequences—and, to be clear, there may be some—are not too large. This Essay proceeds in three parts. Part I spells out several barriers to platform entry, emphasizing the role of machine learning, and the benefits of increased competition. Part II makes the case that a platform’s acquisition of a nascent competitor may constitute unlawful monopolization. Part III explains the role of disruptive incumbents and their relevance to the Arrow–Schumpeter debate, suggesting conditions under which their conduct might merit a lighter touch from antitrust enforcers.