Antitrust is the Engine of Free Enterprise: It shapes countless lines of trade, from tech to baths, beer to baseball, and healthcare to hardware. Antitrust drives price, quality, variety, innovation, and opportunity.

Today, artificial intelligence is rapidly changing the way Companies perceive, reason and adapt to the market. In every industry, companies are leveraging machine learning to gain valuable insights without extensive employee involvement. But these innovative capabilities are creating a sea change in the way companies interact with competitors and consumers.

Experienced competition and consumer protection attorneys can help companies capitalize on the opportunities presented by AI as they navigate the terranova regulatory and litigation risk. Although it is wrong to approach AI as a black box, the complexity of AI systems can make reasoning opaque. This means that the links between AI results and rational business justifications risk being obscured or even lost entirely.

However, regulators are unlikely to justify consumer and competitive concerns simply because an organization cannot explain why certain actions were taken and others were not. Legal exposure exists under the Sherman Antitrust Act, the Federal Trade Commission (FTC) Act, the Robinson-Patman Act, as well as state antitrust and consumer protection laws. By implementing policies and processes that preserve human control and accountability, organizations can minimize legal exposure and avoid unintended consequences.

A proactive and personalized approach is essential. AI affects competition and consumers in countless ways, even when used for basic business functions.

Prices

AI helps companies make pricing decisions by quickly responding to instant changes in demand, inventory, and input costs. By synthesizing and summarizing large amounts of complex data, it can be an important aid in the construction and adaptation of pricing policies. But the results that AI-assisted pricing generates can also be seen as facilitating illegal collusion per se, such as price fixing or bid rigging. According to the chair of the FTC, Lina KhanAI “may facilitate collusive behavior that unfairly inflates prices.”

These concerns may arise directly or indirectly from the use of AI to perform a wide range of activities, such as benchmarking, information disaggregation, signaling, information sharing, or price trend analysis. Pricing algorithms, for example, can raise antitrust issues when competitors use them to enforce an anticipated deal, algorithm providers initiate or orchestrate a deal, companies apply algorithms to dramatically increase prices, or even when competitors independently employ algorithms that subsequently engage in collusive conduct.

The Antitrust Division of the US Department of Justice. highlights that “increased data aggregation, machine learning and pricing algorithms…can increase the competitive value of historical data” and justifies “revising how we think about sharing competitively sensitive information” .

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