Arizona judge dismisses DUI case because the trooper's report was written with AI

Nov 14, 2026
A Maricopa County judge said he could not weigh a probable cause statement that ended with the line 'This report was generated with assistance from Truleo AI.'

A Maricopa County judge has dismissed a DUI case against Anthony Quidera because the state trooper involved used AI to write the probable cause statement, AZFamily reports. Quidera was released.

The statement's last paragraph read: "This report was generated with assistance from Truleo AI." Judge Fenzel said: "The court is unable to meaningfully weigh whether the facts and allegations made in the narrative were authored whether in whole or in part by a generative AI." According to the report, the trooper had clocked Quidera at 30 mph over the speed limit and found several open alcohol containers in his car. The Arizona Department of Public Safety has used Truleo since 2024, AZFamily found.

Sean Harrington, director of the AI and Legal Technology Lab at Arizona State University's law school, said the reasoning "didn't really seem to hold water" to him. "There's nothing in the rules that says an officer can't use AI when they're drafting something like a probable cause statement. They're still responsible for all the facts they put in there," he said, adding that guidance in Arizona has been to evaluate the reliability of the facts rather than impose a blanket ban.

Court records show Quidera was scheduled to be arraigned after his release but did not show up for court.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Legal AI Weekly, AI Policy Brief or Daily AI Brief.

Also, consider following us on social media:

Free newsletter

Legal AI Weekly

The source for the Legal AI software news, analysis, emerging applications: contract review, e-discovery, research.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.