Arizona Judge Samuel Thumma Backs Generative AI for Access to Justice, With Humans in the Loop

A judge at the center of legal AI policy

According to Everlaw, Thumma sits on the Arizona Supreme Court's AI Steering Committee and is a leader within the ABA Task Force on Law and Artificial Intelligence. He has served on the Arizona Court of Appeals, Division One, in Phoenix since 2012, including terms as Chief Judge and Vice Chief Judge. Earlier, he worked as an attorney at firms including Arnold & Porter and Perkins Coie.

Everlaw describes him as a consistent advocate of a human-in-the-loop approach to innovation. The company says he sees the arrival of generative AI as a once-in-a-generation chance to modernize a profession that has historically been slow to change.

In the interview, Thumma said: "I'm optimistic about generative AI generally in the sense that it can help enhance access to justice and help the courts figure out how we can do things better."

Why active case management matters

Asked about judges managing discovery rather than watching from the sidelines, Thumma described a shift in civil courts over the last generation or two. In his telling, courts moved from letting parties take all the time they needed to a more active style in which deadlines have meaning.

He tied this to access to justice. Civil litigants are likely paying someone by the hour, he said, so every extra day a case stays pending adds cost. In criminal matters, he noted, a delayed trial can mean a person not yet found guilty stays in custody. He also said judges must listen carefully when a case has unique needs that justify extended deadlines or accommodations. He pointed to the standard that "justice delayed is justice denied" as one his appellate court tries to keep in mind.

Thumma said his own trial experience was in juvenile and criminal rotations, not civil litigation. He presided over about 35 felony jury trials in two years, which he said involved different discovery from the large-scale management he was asked about.

Cheaper review, more motions?

Ediscovery has long been one of the most expensive parts of litigation. Everlaw's question was whether generative AI, by lowering the cost of reviewing large datasets, would send more cases to trial or start a new arms race in pretrial motions.

Thumma, who practiced as a civil defense litigator, said the technology has the potential to result in a lot more pretrial motion practice. He explained that his own approach was to pursue motions in the hope that clients could avoid trial, because trial meant large costs and possible appeals. The source text breaks off before he finishes his answer.

What it means for the profession

The interview shows a sitting appellate judge involved in state and national AI work framing the technology as a way to improve access to justice, while expecting new procedural pressures. For practitioners, his comments point to courts that expect deadlines to be kept and to a possible rise in pretrial motion work as review costs fall. Everlaw says the wider conversation also covers the shifting responsibilities of practitioners in an automated world.