It’s been quite a couple weeks for stories about AI in the courtroom. You might have heard about the deceased victim of a road rage incident whose family created an AI avatar of him to show as an impact statement (possibly the first time this has been done in the US). But there’s a bigger, far more consequential controversy brewing, legal experts say. AI hallucinations are cropping up more and more in legal filings. And it’s starting to infuriate judges. Just consider these three cases, each of which gives a glimpse into what we can expect to see more of as lawyers embrace AI.

A few weeks ago, a California judge, Michael Wilner, became intrigued by a set of arguments some lawyers made in a filing. He went to learn more about those arguments by following the articles they cited. But the articles didn’t exist. He asked the lawyers’ firm for more details, and they responded with a new brief that contained even more mistakes than the first. Wilner ordered the attorneys to give sworn testimonies explaining the mistakes, in which he learned that one of them, from the elite firm Ellis George, used Google Gemini as well as law-specific AI models to help write the document, which generated false information. As detailed in a filing on May 6, the judge fined the firm $31,000. 

Last week, another California-based judge caught another hallucination in a court filing, this time submitted by the AI company Anthropic in the lawsuit that record labels have brought against it over copyright issues. One of Anthropic’s lawyers had asked the company’s AI model Claude to create a citation for a legal article, but Claude included the wrong title and author. Anthropic’s attorney admitted that the mistake was not caught by anyone reviewing the document. 

Lastly, and perhaps most concerning, is a case unfolding in Israel. After police arrested an individual on charges of money laundering, Israeli prosecutors submitted a request asking a judge for permission to keep the individual’s phone as evidence. But they cited laws that don’t exist, prompting the defendant’s attorney to accuse them of including AI hallucinations in their request. The prosecutors, according to Israeli news outlets, admitted that this was the case, receiving a scolding from the judge. 

Taken together, these cases point to a serious problem. Courts rely on documents that are accurate and backed up with citations—two traits that AI models, despite being adopted by lawyers eager to save time, often fail miserably to deliver. 

Those mistakes are getting caught (for now), but it’s not a stretch to imagine that at some point soon, a judge’s decision will be influenced by something that’s totally made up by AI, and no one will catch it. 

I spoke with Maura Grossman, who teaches at the School of Computer Science at the University of Waterloo as well as Osgoode Hall Law School, and has been a vocal early critic of the problems that generative AI poses for courts. She wrote about the problem back in 2023, when the first cases of hallucinations started appearing. She said she thought courts’ existing rules requiring lawyers to vet what they submit to the courts, combined with the bad publicity those cases attracted, would put a stop to the problem. That hasn’t panned out.

Hallucinations “don’t seem to have slowed down,” she says. “If anything, they’ve sped up.” And these aren’t one-off cases with obscure local firms, she says. These are big-time lawyers making significant, embarrassing mistakes with AI. She worries that such mistakes are also cropping up more in documents not written by lawyers themselves, like expert reports (in December, a Stanford professor and expert on AI admitted to including AI-generated mistakes in his testimony).  

I told Grossman that I find all this a little surprising. Attorneys, more than most, are obsessed with diction. They choose their words with precision. Why are so many getting caught making these mistakes?

“Lawyers fall in two camps,” she says. “The first are scared to death and don’t want to use it at all.” But then there are the early adopters. These are lawyers tight on time or without a cadre of other lawyers to help with a brief. They’re eager for technology that can help them write documents under tight deadlines. And their checks on the AI’s work aren’t always thorough. 

The fact that high-powered lawyers, whose very profession it is to scrutinize language, keep getting caught making mistakes introduced by AI says something about how most of us treat the technology right now. We’re told repeatedly that AI makes mistakes, but language models also feel a bit like magic. We put in a complicated question and receive what sounds like a thoughtful, intelligent reply. Over time, AI models develop a veneer of authority. We trust them.

“We assume that because these large language models are so fluent, it also means that they’re accurate,” Grossman says. “We all sort of slip into that trusting mode because it sounds authoritative.” Attorneys are used to checking the work of junior attorneys and interns but for some reason, Grossman says, don’t apply this skepticism to AI.

We’ve known about this problem ever since ChatGPT launched nearly three years ago, but the recommended solution has not evolved much since then: Don’t trust everything you read, and vet what an AI model tells you. As AI models get thrust into so many different tools we use, I increasingly find this to be an unsatisfying counter to one of AI’s most foundational flaws.

Hallucinations are inherent to the way that large language models work. Despite that, companies are selling generative AI tools made for lawyers that claim to be reliably accurate. “Feel confident your research is accurate and complete,” reads the website for Westlaw Precision, and the website for CoCounsel promises its AI is “backed by authoritative content.” That didn’t stop their client, Ellis George, from being fined $31,000.

Increasingly, I have sympathy for people who trust AI more than they should. We are, after all, living in a time when the people building this technology are telling us that AI is so powerful it should be treated like nuclear weapons. Models have learned from nearly every word humanity has ever written down and are infiltrating our online life. If people shouldn’t trust everything AI models say, they probably deserve to be reminded of that a little more often by the companies building them. 

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.