Important Appellate Decision: Defense Entitled to Face Recognition Information
Case Background
NACDL joined forces with the Electronic Frontier Foundation (EFF) and the Electronic Privacy Information Center (EPIC) to file an amicus brief in support of the defense in New Jersey v. Arteaga.
The question before the Appellate Division was whether the defense is entitled to information about how a face recognition search identifying the defendant as the suspect in the case was conducted. The trial court rejected the defense's argument.
Appellate Division's Ruling
On June 6, citing and adopting many of the arguments set forth in NACDL’s co-authored amicus brief, the Appellate Division reversed the lower court’s ruling, holding that the defendant is entitled to the requested discovery in accordance with Brady v. Maryland.
The court found that “defendant through his expert, and the secondary sources cited by defense counsel and amici, provide us convincing evidence of FRT’s [face recognition technology’s] novelty, the human agency involved in generating images, and the fact FRT’s veracity has not been tested or found reliable on an evidential basis by any New Jersey court.”
The case is now remanded to the lower court for an order directing the state to fulfill the discovery request.
You can read the full opinion above.
Significance and Impact
This is the first time an appellate court has found that this information is subject to Brady disclosure — an issue that we expect many courts will have to grapple with given the widespread use of face recognition technology in criminal cases.
The decision recognizes, at the appellate level, a position that defense attorneys around the country have been arguing for years.
It contains powerful language on the state’s burden to disclose information about face recognition as an unproven technology to uphold the due process rights of a defendant.
Broadly speaking, this decision will be helpful to defense attorneys filing discovery motions and otherwise seeking to challenge the state’s use of face recognition technology to identify their clients.