By Amanda Robert
September 29, 2026

As artificial intelligence systems grow more powerful and users become increasingly adept at digital investigation, the legal landscape is facing a profound reckoning regarding privacy, data security, and court transparency. Legal experts warn that the digital sleuthing seen in recent high-profile incidents is merely the tip of the iceberg, forcing courts, prosecutors, defense attorneys, and litigators to rethink how they protect sensitive information in an era where redactions and traditional secrecy measures may no longer suffice.

The catalyst for these mounting concerns played out earlier this spring, when news broke of an unnamed federal judge engaging in a sexual relationship in their chambers with a high-ranking police officer. The sensational revelation immediately sparked widespread curiosity, prompting journalists at Above the Law to launch an investigation to uncover the judge’s identity.

In May, the Judicial Conference of the United States’ Committee on Judicial Conduct and Disability issued an order affirming a private reprimand of the judge by the Judicial Council of the 11th U.S. Circuit Court of Appeals in Atlanta. Although both the initial disciplinary order and the subsequent review concealed the judge’s name and court location, the reporters bypassed these anonymization efforts by using generative artificial intelligence. By feeding the text into an AI tool and zeroing in on subtle contextual details scattered throughout the documents—such as the fact that the judge hired law clerks for two-year staggered terms, possessed prior prosecutor experience, and attended a district attorney’s primary election victory party—the reporters successfully identified U.S. District Judge Eleanor Ross of the Northern District of Georgia. The entire identification process took a mere 45 minutes.

This rapid digital unmasking has reignited urgent conversations across the legal community. As AI tools become more sophisticated, legal experts say this sort of advanced sleuthing will inevitably become more frequent. However, they emphasize that the underlying phenomenon is not entirely new; rather, technology is dramatically accelerating tactics that legal professionals have used for decades.

Jonah Perlin, a professor at the Georgetown University Law Center whose scholarship focuses on legal ethics and the technology of law, recalls utilizing the internet and a combination of paid and unpaid search tools earlier in his career while working as a litigator at Williams & Connolly in Washington, D.C. Back then, junior lawyers and investigators routinely pulled together fragmented pieces of information that were never explicitly provided within a single court document.

"AI is providing us, for better or for worse—and most of the time, I think it’s for the better—with opportunities to do things that were always possible but maybe not scalable," Perlin says.

Perlin does not anticipate that generative AI will execute sophisticated cryptographic hacks to breach properly redacted or sealed information. Instead, as the Above the Law case study vividly illustrates, he expects that details "hiding in plain sight" will continue to be rapidly uncovered. It is the kind of information that surfaces when a user possesses the capacity to read between the lines, connecting dots across documents. What once required a human researcher extensive domain knowledge and upwards of 20 hours of painstaking manual searching can now be accomplished in mere seconds.

Andrew Guthrie Ferguson, a professor at the George Washington University Law School and author of the book Your Data Will Be Used Against You: Policing in the Age of Self-Surveillance, shares this assessment. He notes that AI possesses a unique capacity to connect disparate information that previously flew under the radar or remained too fragmented to interpret. For example, he points out that if a sophisticated user or developer deploys an AI tool within a court management system—databases that are not typically open to the general public—the technology could potentially reveal underlying patterns and connections that would ordinarily go completely unnoticed.

That said, Ferguson notes practical limitations. Most ordinary individuals do not have access to restricted, closed court management systems, meaning internal court data remains somewhat more protected than open-source digital footprints.

Nevertheless, Ferguson warns of a parallel danger involving public-facing court data. Information concerning criminal dockets and civil proceedings hosted on public court websites can easily be scraped by automated bots and transferred into separate, private datasets. Once housed in these independent environments, generative AI can cross-reference and analyze the material to forge entirely new connections that public administrators never anticipated.

How could this affect the courts?

The widespread integration of artificial intelligence into everyday research is poised to fundamentally alter public and institutional expectations of privacy, according to Perlin. He compares this technological shift to previous eras of digital disruption, noting how the introduction of GPS tracking devices into police investigations similarly forced courts to redraw constitutional boundaries around surveillance and privacy rights.

"I think it will be much harder to say that information is truly private, and that will have an effect on parties and inevitably have an effect on courts," Perlin says.

David Lizmi, a partner at Mayer Brown in New York City who focuses on cybersecurity, data privacy, and artificial intelligence, brings a distinct perspective shaped by his prior service as an assistant U.S. attorney in the Eastern District of New York, where he acted as the computer hacking and intellectual property coordinator. In Lizmi’s experience, criminal defense attorneys have historically sought to identify confidential informants and unnamed co-conspirators. Today, by leveraging generative AI, defense counsel can pair government-produced discovery with their own responses to an indictment to spot patterns and cross-reference identities at unprecedented speeds.

"There are concerns for the court and the government that stem from that," Lizmi says, emphasizing that judicial authorities and prosecutors are only just beginning to contemplate the full scope of potential risks.

Defense lawyers may utilize these capabilities to develop impeachment material for trial, but Lizmi cautions that significant hazards accompany the practice. For one, AI systems can hallucinate or incorrectly identify the wrong individual, leading to false accusations or severe reputational damage. Furthermore, in high-stakes criminal proceedings, prematurely or erroneously publicizing the names of confidential informants or unindicted co-conspirators can trigger immediate, dangerous security concerns.

On the civil litigation side, Lizmi notes that attorneys could easily process thousands or tens of thousands of pages of corporate documents and discovery through AI models in systematic attempts to reverse-engineer or pierce redacted material.

Jeremy Fogel, executive director of the Berkeley Judicial Institute and a former federal judge for the Northern District of California, recently participated in a specialized conference for federal judges where jurists debated their own internal use of artificial intelligence alongside the challenges posed by AI-driven litigation tactics. Fogel observes that the widespread availability and growing acceptance of these technologies will inevitably pressure courts to reevaluate how they safeguard confidential information, such as the identities of endangered informants in criminal cases.

"If the court is trying to protect documents, and sometimes there are very good reasons why they should be protected, you want to make sure you are accounting for the fact that AI is out there so you don’t leave a trail unwittingly," Fogel explains.

Fogel adds that judges have raised broader security and privacy concerns, including whether advanced AI could eventually be deployed to analyze the web browsing histories or digital research patterns of judges during the adjudication of complex cases. Such granular insight into a judge’s research habits could theoretically provide litigators in fiercely contested proceedings with predictive advantages regarding judicial decision-making.

"It’s just a matter of being able to use these tools in an appropriate and secure way, and I think that is very much on people’s minds right now," Fogel says.

To address these mounting institutional challenges, the federal judiciary is actively drafting comprehensive recommendations regarding the courts’ internal and external use of artificial intelligence. Judge Sidney Thomas of the 9th U.S. Circuit Court of Appeals in San Francisco announced that the judiciary’s dedicated AI task force aims to release its finalized guidance by the end of the year. Judge Thomas, who chairs the task force, previously noted that the group released interim guidance in July 2025 specifically addressing how judges should govern their own utilization of AI tools.

What can lawyers do to protect clients?

As judicial bodies draft formal guidelines, practicing lawyers are similarly forced to reevaluate how they handle private, sensitive, and confidential information on behalf of their clients.

Ferguson suggests that legal practitioners must fundamentally rethink their approach to redactions. Because generative AI models are exceptionally proficient at predicting contextual gaps in text—and legal redactions are, at their core, gaps in documents—traditional black-box redaction methods may no longer offer foolproof protection.

"Unless the court system and lawyers are very conscious of all the ways data can be reconnected, redactions may not be as effective as they used to be," Ferguson says. "This does not mean that courts cannot keep secrets, just that some of the old ways of doing things will need an update for the AI age."

Focusing specifically on criminal litigation, Lizmi notes that government prosecutors may respond to these technological capabilities by altering their disclosure timelines. Specifically, prosecutors might choose to delay the formal disclosure of Giglio material—information used to impeach the credibility of government witnesses—and Brady material, which encompasses evidence favorable to the defense. Delaying these disclosures would narrow the window of opportunity for defense counsel to systematically comb through discovery via AI to unmask confidential sources or co-conspirators.

To further mitigate emerging security vulnerabilities, Lizmi anticipates an increase in legal motions aimed at sealing sensitive judicial records entirely.

Meanwhile, in civil practice, Lizmi stresses that attorneys must proactively draft protective orders and electronically stored information protocols designed explicitly to counter AI-driven de-anonymization. This could entail negotiating protective agreements that require opposing counsel to provide advance formal notice before running specific court filings or proprietary documents through third-party artificial intelligence platforms.

"This is a new circumstance to apply those protections, and so I think we’ll have to aggressively do that to protect clients," Lizmi concludes.