Antitrust threats to companies lurk in some AI pricing algorithms

The surge in popularity of AI-based pricing algorithms is generating increased antitrust scrutiny from agencies, state and federal legislators, and private litigants.

Last month, Federal Trade Commission Chair Lina Khan encouraged law enforcement and regulators to remain vigilant because AI-based pricing algorithms “may facilitate collusion that unfairly inflates prices.” Earlier this year, Congress proposed legislation aimed at “preventing anticompetitive behavior through the use of pricing algorithms.”

This growing analysis highlights the importance of understanding the antitrust regulations and policies that could potentially result from the use of AI-based pricing algorithms.

Sherman Act

Section 1 of the Sherman Antitrust Act prohibits agreements or conspiracies that unreasonably restrain trade. The use of AI algorithms may violate the provisions of section 1 in two ways.

The first is the traditional handshake conspiracy, in which competitors agree, expressly or tacitly, to follow the algorithm’s pricing decisions. Agreements with horizontal competitors to use pricing algorithms to fix prices, rig bids or divide markets are themselves illegal and potentially subject to criminal liability.

The second potential Section 1 violation occurs when competitors (the spokes) enter into an agreement with an AI provider (the hub) to allow competitors to coordinate pricing decisions.

Section 1 claims related to AI pricing algorithms have already begun making their way through courts across the country, impacting industries from real estate to hotels. However, these claims pose a challenge to those who have the burden of proof.

For example, earlier this year, a federal court in Las Vegas dismissed a case against a hotel group in which defendants were not required to accept the recommendations of an artificial intelligence algorithm and in which plaintiffs were unable to “persuasively allege the exchange of confidential information from a single spoke with each other via hub algorithms “

Unilateral or mere parallel behavior is not enough to prove theorem in section 1, which means that a single company’s decision to rely on algorithmic pricing is not in itself sufficient evidence of a conspiracy. Similarly, regulators or plaintiffs must demonstrate conduct on behalf of companies or entities, and AI offering higher prices may also not be sufficient to establish a Section 1 claim.

Despite these challenges, antitrust agencies have been steadfast in their belief that conspiracies involving AI pricing algorithms can result in Section 1 liability.

Section 2 of the Sherman Act prohibits entities from illegally monopolizing or attempting to monopolize a relevant market. While antitrust researchers are paying attention to Section 1 issues arising from AI pricing algorithms, Section 2 concerns are still on the radar of antitrust agencies.

The Federal Trade Commission warns that “companies operating in generative artificial intelligence markets may leverage network effects to maintain dominant positions or concentrate market power,” which could lead to unfair competition tactics by dominant companies.

Additionally, concerns about predatory pricing, as discussed in Section 2, may arise where a dominant firm’s algorithms set prices below cost for an extended period of time, driving competitors out of the market and then raising prices to recoup losses.

Antitrust criminal liability

Serious violations of Sections 1 and 2 can expose companies to criminal liability. Although criminal antitrust charges have been rare over the past few decades, the agencies have signaled an increased willingness to bring such charges, including in the context of AI pricing algorithms.

For example, in May, the FBI executed a search warrant at the office of the owner of Cortland Management as part of the Justice Department’s investigation into RealPage alleged AI pricing conspiracy. Over the past few months, the Department of Justice has issued statements regarding its interest in RealPage, another real estate price-fixing action, and the Atlantic City hotel price-fixing case.

The reported RealPage raid demonstrates the Justice Department’s willingness to follow up on its October 2021 announcement to strengthen its response to corporate crime. Potential criminal liability for the coordinated use of algorithmic pricing raises the possibility of imprisonment for individuals, as well as significant financial penalties in the event of conviction.

FTC Act

Section 5 of the FTC Act protects unfair or deceptive conduct affecting commerce. The FTC has actively exercised its Section 5 powers and has stated that Section 5 is broader in scope than antitrust laws.

Section 5 also forms the basis of the FTC’s 2023 lawsuit against Amazon.com, Inc. Given the FTC’s current interest in AI, the FTC may use Section 5 as a mechanism to combat AI-based price discrimination.

Permission to merge

Antitrust agencies are now widely reviewing contracts for a wide range of potentially anti-competitive conduct, examining factors such as interconnected directorates, non-competition agreements and potential concerns related to artificial intelligence during the settlement process.

The FTC and Department of Justice Merger Guidance issued in December 2023 specifically warns that the use of pricing algorithms may signal an increased risk of coordination among competitors, indicating that the use of algorithms may be subject to review in the antitrust settlement process.

Conductivity

Given increased antitrust scrutiny, companies using AI-based pricing algorithms should take several high-level steps to ensure compliance with U.S. federal antitrust law.

Avoid illegal agreements. Avoid entering into agreements with competitors that seek to use AI-based pricing algorithms to set prices, set bids or allocate markets.

Know your algorithm. Learn how the AI ​​pricing algorithm collects information, including whether it uses information from competitors.

Document pro-competitive benefits. By implementing AI pricing algorithms, it helps document the pro-competitive benefits of the process. This may include increasing transparency of consumer prices and increasing efficiency and reducing costs in setting competitive prices.

Include AI in your merger due diligence process. Find out if and how the parties involved in the transaction are using AI pricing algorithms and whether such use could increase control in the transaction approval process.

Consult an advisor. General counsel can explain the legal risks and frameworks associated with algorithmic pricing and help update compliance and training policies to reflect best practices.

While AI algorithms promise new ways of efficiency for a range of industries, the AI ​​boom is also fair game for antitrust enforcers. Their recent activity shows that they are watching and are willing to employ a range of enforcement strategies. Companies looking to implement AI in their business should be aware of recent developments and take steps to ensure they are complying with antitrust laws.

This article does not necessarily reflect the opinions of Bloomberg Industry Group, Inc., publisher of Bloomberg Law and Bloomberg Tax, or its owners.

Information about the author

Emily Renzelli is an attorney at Rule Garza Howley, specializing in antitrust litigation and government investigations for clients in the healthcare and technology industries.

Whitney Williams is an associate at Rule Garza Howley, focusing on antitrust clearances and government investigations.

Erica Baum is an associate at Rule Garza Howley, specializing in antitrust litigation and government investigations.

Write to us: Author’s guidelines