On this, Goddard appears to be caught in the identical predicament the AI boom has created for a lot of us. Three years in, corporations have built tools that sound so fluent and humanlike they obscure the intractable problems lurking underneath—answers that read well but are flawed, models which might be trained to be decent at every little thing but perfect for nothing, and the chance that your conversations with them will likely be leaked to the web. Every time we use them, we bet that the time saved will outweigh the risks, and trust ourselves to catch the mistakes before they matter. For judges, the stakes are sky-high: In the event that they lose that bet, they face very public consequences, and the impact of such mistakes on the people they serve might be lasting.
“I’m not going to be the judge that cites hallucinated cases and orders,” Goddard says. “It’s really embarrassing, very professionally embarrassing.”
Still, some judges don’t need to get left behind within the AI age. With some within the AI sector suggesting that the supposed objectivity and rationality of AI models could make them higher judges than fallible humans, it’d lead some on the bench to think that falling behind poses an even bigger risk than getting too far out ahead.
A ‘crisis waiting to occur’
The risks of early adoption have raised alarm bells with Judge Scott Schlegel, who serves on the Fifth Circuit Court of Appeal in Louisiana. Schlegel has long blogged in regards to the helpful role technology can play in modernizing the court system, but he has warned that AI-generated mistakes in judges’ rulings signal a “crisis waiting to occur,” one that will dwarf the issue of lawyers’ submitting filings with made-up cases.
Attorneys who make mistakes can get sanctioned, have their motions dismissed, or lose cases when the opposing party finds out and flags the errors. “When the judge makes a mistake, that’s the law,” he says. “I can’t go a month or two later and go ‘Oops, so sorry,’ and reverse myself. It doesn’t work that way.”
Consider child custody cases or bail proceedings, Schlegel says: “There are pretty significant consequences when a judge relies upon artificial intelligence to make the choice,” especially if the citations that call relies on are made-up or incorrect.
This just isn’t theoretical. In June, a Georgia appellate court judge issued an order that relied partially on made-up cases submitted by considered one of the parties, a mistake that went uncaught. In July, a federal judge in Recent Jersey withdrew an opinion after lawyers complained it too contained hallucinations.
Unlike lawyers, who might be ordered by the court to clarify why there are mistakes of their filings, judges should not have to point out much transparency, and there may be little reason to think they’ll achieve this voluntarily. On August 4, a federal judge in Mississippi needed to issue a brand new decision in a civil rights case after the unique was found to contain incorrect names and serious errors. The judge didn’t fully explain what led to the errors even after the state asked him to achieve this. “No further explanation is warranted,” the judge wrote.
These mistakes could erode the general public’s faith within the legitimacy of courts, Schlegel says. Certain narrow and monitored applications of AI—summarizing testimonies, getting quick writing feedback—can save time, they usually can produce good results if judges treat the work like that of a first-year associate, checking it thoroughly for accuracy. But a lot of the job of being a judge is coping with what he calls the white-page problem: You’re presiding over a posh case with a blank page in front of you, forced to make difficult decisions. Pondering through those decisions, he says, is indeed the work of being a judge. Getting help with a primary draft from an AI undermines that purpose.
“If you happen to’re making a call on who gets the youngsters this weekend and any person finds out you utilize Grok and you need to have used Gemini or ChatGPT—you recognize, that’s not the justice system.”
