Competitive concerns in the age of AI

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By Webdesk


Antitrust is the engine of free enterprise: it shapes countless lines of business, from technology to toilets, from beer to baseball, and from health care 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 using machine learning to gain valuable insights without extensive employee involvement. But these groundbreaking capabilities are shaking up the way companies interact with competitors and consumers.

Experienced competition and consumer protection lawyers can help companies capitalize on the opportunities that AI presents as they navigate the new earth of regulatory and litigation risks. While it is incorrect to approach AI as a black box, the complexity of AI systems can obscure the reasoning. This means that links between AI outputs and rational business justifications risk being obscured or even lost altogether.

Still, regulators are unlikely to excuse consumer and competitor concerns just because an organization can’t explain why certain actions have been taken and others have not. Legal exposure exists under the Sherman Antitrust Act, Federal Trade Commission Act (FTC), Robinson-Patman Act, as well as state antitrust and consumer protection laws. By implementing policies and processes that maintain human control and accountability, organizations can minimize legal exposure and prevent unintended consequences.

A proactive, tailor-made approach is crucial. AI impacts competition and consumers in countless ways, including when used for core business functions.

Prices

AI helps companies make pricing decisions by quickly responding to instantaneous changes in demand, inventory and input costs. By synthesizing and summarizing vast amounts of complex data, it can be an important tool in formulating and adjusting 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 FTC Chair Lina Khan, AI “could facilitate colluding behavior that unfairly inflates prices.”

These concerns can arise directly or indirectly from using AI to perform a wide variety of activities such as benchmarking, breaking down information, signaling, exchanging information or analyzing price trends. For example, pricing algorithms can raise antitrust issues when competitors use them to enforce a prior agreement, algorithm providers initiate or organize an agreement, companies apply algorithms to dramatically increase prices, or even when competitors independently use algorithms that then engage in stealthy behavior.

The U.S. Department of Justice’s antitrust division emphasizes that “the rise of data aggregation, machine learning, and pricing algorithms … can increase the competitive value of historical data” and justifies “rethinking how we think about the exchange of competitively sensitive information.”

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