Addressing the Competitive Harms of Opaque Online Surveillance and Recommendation Algorithms

Abstract

Facebook and Alphabet operate free internet services that are widely used. They provide these services for free because users are online ad targets. Together Facebook and Alphabet have a large share of the market for online advertising in the U.S. Their dominance delivers monopolistic returns, reflected in the persistently high valuations financial markets place on each company. Online ad sales depend on the ability of these platforms to individually target ads and messages to huge numbers of people. Targeting is made possible by surveillance which is large in scale, scope, and effectiveness. User engagement, which helps determine target numbers, is stimulated and directed by “recommendation” algorithms on Facebook and Alphabet’s YouTube platform. These algorithms can affect what users read and view, and can influence their attitudes, emotions, and behavior. While surveillance has negative effects on user privacy, and algorithms have had powerful effects on user attitudes and behavior, platform users have limited knowledge about how these practices operate or their impacts. These information asymmetries between platforms and users have important competitive effects. They divert users from competing platforms that do not engage in these business practices, and inhibit entry and the innovation it would stimulate, thereby helping sustain the monopoly power of dominant incumbents. Section 5 of the Federal Trade Commission Act, which prohibits “unfair methods of competition” and includes rulemaking authority, may be the most effective way to address anticompetitive practices that are technically complex, can evolve rapidly, and are difficult for industry outsiders to observe.