This blog post is the first in a three-part series exploring the intersection between AI and antitrust.
The first blog post in this series discusses the U.S. Department of Justice, Antitrust Division’s (Division) first criminal antitrust case involving the use of AI. The second part, which will be published next week, summarizes the FTC’s and Division’s positions on AI collusion and unlawful agreements among competitors, and offers proactive measures that companies can take to avoid government inquiries and/or liability.
Part I: Antitrust and Algorithms
In economic terms, the Topkins case is relatively small. The affected volume of commerce was a mere $175,000, and that limited the range penalties under the U.S. Sentencing Guidelines. In 2015, Topkins paid a fine of $20,000 and received no jail time. In 2016, Trod Limited, one of the companies participating in the conspiracy, paid a $50,000 fine and agreed to retain KPMG to serve as a compliance monitor. In 2019, defendant Daniel William Aston, part owner of Trod when it was doing business as “Buy For Less,” was given a prison sentence of six months but received five months credit for time served in custody in Spain as he awaited extradition to the U.S.
Despite the relatively low penalties, Topkins case is considered a watershed case because it was the first time that the Division prosecuted defendants where AI was a tool to further antitrust misconduct. In the years that have passed since Topkins, the Division and the FTC have closely scrutinized the intersection between AI and Antitrust as we will see in next week’s Part II.