On December 3, 2015, the DOJ unsealed an indictment against Daniel William Aston and his company, Trod Ltd. (doing business as Buy 4 Less, Buy For Less, and Buy-For-Less-Online), for conspiring with third-party sellers to fix the prices of posters sold online via Amazon Marketplace. According to the indictment, Aston and his co-conspirators agreed to adopt specific pricing algorithms to coordinate changes in their respective prices. The DOJ claimed that because of this conduct, shoppers faced the same prices for the same products, regardless of what seller they chose.
This indictment came after a recent plea agreement announced in April between the DOJ and executive David Topkins. Similar to the Aston case, the DOJ alleged that Topkins and his co-conspirators agreed to use computer software to fix the prices of posters sold online. In accordance with the terms of their pricing agreement, the co-conspirators allegedly developed and implemented pricing algorithms that coordinated changes in their respective prices. The agency lauded the Topkins case as its “first online marketplace prosecution.” Assistant Attorney General Bill Baer emphasized that the DOJ “will not tolerate anticompetitive conduct, whether it occurs in a smoke-filled room or over the Internet using complex pricing algorithms.”
While the DOJ’s pursuit of E-Commerce executives for criminal prosecutions is certainly noteworthy, the targeting of algorithms as pricing mechanisms raises some interesting issues. At its core, these cases propound the theory that price-fixing schemes are potentially being implemented by computer algorithms that can efficiently and simultaneously adjust prices in a matter of seconds.
Accordingly, algorithms may soon be at the center of future investigations because their efficiency has led to widespread use in the online marketplace and modern commerce (e.g., online hotel reservations, Uber’s surge-pricing, etc.). Already, the FTC’s newly created Office of Technology, Research, and Investigation has started researching how algorithms affect consumers. Some scholars have even theorized that algorithms could be designed to detect breaches in a cartel and punish actors for deviations from a pricing agreement.
It is not yet clear, however, to what extent algorithms really represent a brand new species of antitrust conspiracy. Common use of algorithms by competitors may amount to nothing more than a new form of parallel conduct. In such cases, antitrust enforcers will face familiar problems of proving an overt agreement to coordinate pricing. After all, even though the Aston and Topkins cases centered around nascent technology, the DOJ still alleged that there was a traditional “meeting of the minds” where co-conspirators agreed to collude with one another. Future cases, however, may be less straightforward, especially as algorithms and their implementation grow more sophisticated.
Additionally, pricing algorithms may benefit consumers in the marketplace. For example, consumers may benefit from enhanced price discovery (i.e., the market can more quickly and accurately determine the competitive price of a good or service because of the efficiency of pricing algorithms). Some scholars have also cautioned that requiring algorithms to ignore market conditions may ultimately end up undermining overall competition.
Nevertheless, as algorithms get more sophisticated, defining collusion and outlining the limits of liability may become more difficult. With the development of “smart machines” that possess something resembling artificial intelligence, sophisticated computers may end up reaching predictable pricing outcomes that resemble an agreement with little or no direct human involvement. In such cases, antitrust liability may turn not on overt human conduct, but on the failure of humans to monitor their “smart machines.” Needless to say, this is a brave new world that antitrust enforcers are only just beginning to grapple with.