How AI Turned Self-Represented Litigants Into a Court Crisis

Federal courts logged 41,490 non-prisoner civil lawsuits filed without a lawyer in fiscal year 2025, nearly double the pre-AI average, with 59 percent of all civil lawsuit growth traced to self-represented plaintiffs. Researchers Anand Shah of MIT and Joshua Levy of the University of Southern California drew those figures from a working paper examining 4.5 million non-prisoner federal civil cases and 46 million PACER (Public Access to Court Electronic Records) docket entries. A commercial text-detection tool flagged AI-generated writing in more than 18 percent of sampled 2026 federal complaints, up from roughly 1 percent in 2023.

Three disputes have since built up in federal courtrooms. Judges are split on whether conversations with AI chatbots deserve protection from legal discovery. An Illinois court is weighing whether OpenAI practiced law without a license. And a New York Senate bill is trying to assign liability for bad chatbot advice before the case law can.

The Surge That Followed ChatGPT

Vermont’s federal district received roughly 45 pro se civil filings a year before 2022. By fiscal year 2024, that number was above 1,100. Nearly all of that growth came from a single case type: writs of mandamus against U.S. Citizenship and Immigration Services (USCIS), filed by applicants whose green card or naturalization cases had sat idle for years and who wanted a federal judge to order the agency to act.

The method spread on Reddit. A December 2024 post in the r/USCIS community published a step-by-step guide to filing a mandamus petition using Microsoft Copilot: draft the writ with Copilot, pay a lawyer about $150 to review it, then file in Vermont because of its reputation for quick processing. Vermont’s caseload had been stable for two decades before the post circulated widely.

The MIT-USC paper tied the national inflection point to the public launch of widely available AI chatbots in November 2022. The surge concentrated in case types suited to formulaic document production: immigration, employment discrimination, consumer claims. Complex litigation, where attorney strategy and in-person argumentation are hardest to replicate, shows no comparable increase. Anand Shah has described the trajectory as one that could force courts to “basically grind to a halt” if filing volumes keep compounding.

• 16.8% of non-prisoner federal civil cases filed without a lawyer in FY2025, up from roughly 11% for two decades
• 158% rise in pro se docket entries per court in a case’s first 180 days, comparing FY2025 to the pre-AI baseline
• $405 federal civil filing fee, roughly twice most state courts charge, which did not slow the surge

More than 300 federal judges have adopted some form of AI disclosure or certification requirement, according to a 2026 Northwestern-NYC Bar Association survey, asking filers to independently verify any factual assertions and citations. In districts with those orders in place, hallucinated citations have remained a persistent problem.

Winning a Case Takes More Than a Good Draft

Judge Maritza Braswell, a federal magistrate judge in Colorado, has spent years decoding court documents that self-represented litigants submit without legal training. Many pre-AI filings arrived handwritten or barely legible. The AI-assisted documents reaching her now are better organized and clearer in their arguments. She processes them faster.

“I have to be really careful because some of them contain hallucinations and errors,” she told MIT Technology Review, “but I can generally understand what they’re arguing better with AI assistance from them than without it.” When litigants appear at hearings, she added, they answer her questions with noticeably more confidence, having rehearsed with a chatbot beforehand.

Better prose hasn’t shifted who wins. Shah and Levy found that self-represented litigants remain far more likely to lose than parties with attorneys, and that gap has not narrowed with AI adoption.

It turns out that mounting a lawsuit is a complex, multifaceted task. Not all of it is just drafting text.

Levy, the USC co-author, made that observation to MIT Technology Review while explaining the study’s finding on outcome rates. Depositions, discovery disputes, expert witnesses, and courtroom argument are where represented parties pull further ahead, and those stages of litigation don’t get easier because the complaint was well-drafted.

In settlement negotiations, the gap shows up as a valuation problem. Judge Allison Goddard, a federal magistrate judge in California, has watched self-represented plaintiffs arrive at negotiating tables with damages figures they sourced from AI tools, often far above what the evidence supports. A plaintiff who slipped and fell in a store was asking the opposing side for $700,000. “Where are you getting the idea that you’re getting $700,000? Did you go to ChatGPT?” Judge Goddard asked. She walked the plaintiff through the relevant law and suggested a lower figure. “It’s like Dr. Google went to law school,” she said.

Courts Are Splitting on Chatbot Privacy

A threshold question has arrived for federal courts: do conversations between a litigant and an AI chatbot deserve the same legal protection as conversations with an attorney? In the first quarter of 2026, four significant federal decisions on AI, privilege, and work product protections produced diverging results across civil and criminal dockets.

In Heppner, Judge Jed Rakoff of the Southern District of New York wrote that “all recognized privileges require a trusting human relationship,” and that no such relationship “exists, or could exist, between an AI user and a platform such as Claude.” The defendant, Bradley Heppner, had used Claude before his federal fraud indictment and later shared those outputs with his attorneys; the court found that sharing them with counsel did not retroactively make them privileged.

Judge William Garfinkel, a federal magistrate judge in Connecticut with three decades on the bench, has been thinking through the broader question. He told MIT Technology Review that “you can make a good argument that … conversations with large language models like Claude or ChatGPT or Grok should deserve some protection.” Courts have yet to agree on any standard for when or why that protection would apply.

How Graciela Dela Torre Became OpenAI’s Problem

Forty-Four Filings

Graciela Dela Torre settled a long-term disability claim against Nippon Life Insurance Company of America with prejudice in January 2024, waiving further legal claims. She had alleged the insurer wrongfully terminated her benefits.

When she became dissatisfied with the settlement, she uploaded correspondence from her attorney to the chatbot and asked whether she was being gaslighted. According to the complaint filed on March 4, 2026, the chatbot validated her distrust, told her the attorney’s response had invalidated her feelings, and encouraged her to fire him and pursue further action. She did. She filed a motion to reopen the settled case. When that failed, she filed a new lawsuit, and then kept filing: 44 total motions, subpoenas, notices, and requests, all drafted with the chatbot’s assistance, including arguments under Federal Rule of Civil Procedure 60(b). One filing cited a case called “Carr v. Gateway, Inc.” The complaint states the case “only exists in Dela Torre’s papers and the ‘mind of ChatGPT.'”

The insurer did not name Dela Torre as a defendant. The lawsuit was filed against OpenAI directly, seeking $300,000 in compensatory damages for legal fees and $10.3 million in punitive damages.

The Dismissal Motion

Nippon Life’s suit, filed in the U.S. District Court for the Northern District of Illinois, is the first federal case to charge an AI developer with unauthorized practice of law. The insurer’s three claims were:

• Tortious interference with a contract (the January 2024 settlement agreement)
• Abuse of process through 44 filings that served no legitimate legal purpose
• Unlicensed practice of law under Illinois statute

OpenAI filed its motion to dismiss in May 2026. The company argued the tool has no legal knowledge or skill, generates text by statistical prediction rather than professional judgment, and cannot practice law within the meaning of the Illinois statute. The broader argument was that making a general-purpose AI tool available to millions of people cannot constitute aiding and abetting, and that liability for a frivolous filing belongs with the person who submits it.

The insurer pointed to a problem in that framing. The company had updated its usage policies to prohibit relying on the tool for legal advice; Nippon Life argued the update was evidence that the developer recognized the foreseeable risk and responded with a disclaimer rather than a design change. Stanford Law’s CodeX center published an analysis calling the case a product liability claim about the absence of a refusal architecture: the argument is that the company built a system with no design mechanism to refuse crossing the line from legal information into legal advice.

A New York Bill Draws the Line

New York Senate Bill S7263, sponsored by Senator Kristen Gonzalez, chair of the Internet and Technology Committee, would prohibit chatbots from providing substantive responses that, if given by a human, would constitute unauthorized practice of a licensed profession. The bill passed committee 6-0 on February 25, 2026, and advanced to a third reading on the Senate floor on March 4. It has not yet cleared the full Senate or the Assembly.

“Today, there is no law that says that a large language model cannot tell you that it is a lawyer, that it is a licensed therapist, and then give you legal advice or therapy accordingly,” Gonzalez told Reuters, per her March 2026 press statement on S7263. Under the bill, disclosing that the user is interacting with an AI system would not protect the chatbot proprietor from liability; the bill explicitly states the notice does not waive legal exposure.

Legal commentators have raised a structural objection. S7263’s operative provision reaches beyond actual impersonation to cover any substantive legal content from a chatbot, regardless of whether the system claims to be a licensed professional. Virginia introduced a comparable bill; it was tabled in committee. Critics have argued that a broad reading of the New York text could suppress the same AI-assisted legal filings that drove tens of thousands of self-represented litigants into federal court.

A different regulatory approach already has a track record. In January 2025, the Federal Trade Commission entered a consent order with DoNotPay, a company that had marketed its AI chatbot as the world’s first robot lawyer. The FTC required the company to stop misrepresenting its capabilities and to pay $193,000 in damages. That consent order addressed what the company claimed about its product. S7263 would go further, reaching a chatbot’s substantive outputs regardless of how the developer advertises the tool.

Judge John F. Kness at the U.S. District Court for the Northern District of Illinois has yet to rule on the dismissal motion. The case remains the only federal lawsuit to directly charge a chatbot developer with unauthorized practice of law.