AI Offers Class Action Firms An Edge — At A Price

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Generative artificial intelligence is helping smaller class action firms gain an edge over well-monied BigLaw competitors, but litigation attorneys say the advantages come with several catches.

Boies Schiller Flexner LLP is one of several trial law firms pursuing class action lawsuits against artificial intelligence developers, including Meta and OpenAI, over copyright infringement claims, while simultaneously using AI tools to compete against BigLaw firms.

"The irony is not lost on us," said David Simons, partner at Boies Schiller. "If we want to punch above our weight and handle the incoming fire that we're getting from some of these big tech companies, we want to use every resource that we have, and that includes using these generative AI products. … You don't want to litigate any case with a hand tied behind your back."

He believes that AI will help his firm when going up against AI companies that are represented by "armies of lawyers" from large law firms like Cooley LLP and Paul Weiss Rifkind Wharton & Garrison LLP.

While smaller litigation law firms are leveraging generative AI tools in e-discovery and trial preparation to take on bigger firms, the technology also presents both practical use challenges and complications concerning fraud and costs for these firms.

Some of the challenges are the same as those in other practice areas, including issues with accuracy and confidentiality. Typically, law firms say attorneys need to check AI outputs and not put confidential client information into public generative AI tools.

Jake Bissell-Linsk, partner at Labaton Keller Sucharow LLP and a member of the firm's AI committee, said he is concerned about attorneys using AI tools to find answers quickly without reading a full deposition transcript or case opinion.

"It's not just a matter of 'use the system and then make sure the citations are real.' That's not the way I want us doing our work. I want us really thinking through these issues, and if we're citing cases, reading those cases and thinking about what they mean in the context of this opinion, not just finding a quote that works in the case," he said.

In class action litigation, however, AI can raise particular concerns.

Dena Sharp, managing partner at San Francisco-based boutique litigation firm Girard Sharp LLP, said another challenge with AI tools is that they are being used to file fraudulent claims in class action settlements.

Attorneys want to make it easy for class members to file settlement claims online, but that also makes it easy for criminals to file multiple false claims, she said.

In 2024, Sharp told a California federal judge that the claims administrator for a $45.5 million settlement with e-cigarette Juul investor Altria received roughly 14 million claims, which was five times the number they had expected to receive. But many of the claims were fraudulent and likely submitted by AI bots.

"This is the give-and-take of us using all the capabilities of the internet and digital technology to drive claims and to really try to make sure that we get money into class members' hands, and at the same time we're dealing with a flood of fraudulent claims that are driven to some degree by all of these technological capabilities that are out there," Sharp said.

Geoffrey Kozen, partner at Robins Kaplan LLP and chair of the firm's pro bono committee, said that he hopes AI tools bring down discovery costs, but believes the technology's impact on costs might be similar to that of e-discovery.

He said that attorneys anticipated a decrease in costs from the added efficiency of e-discovery; instead the amount of documents produced in discovery increased and costs didn't decline as much as expected.

"I suspect as time goes on, the AI tools become more advanced, we'll see more use of it," Kozen said. "Whether that leads to cost savings or just increased scope, we'll find out, but I can see a scenario where there are significant cost savings, especially in discovery."

--Editing by Robert Rudinger.


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