To advance the development and adoption of artificial intelligence (AI) technologies within crime laboratories, this project seeks to help forensic service providers and developers better understand…

The National Institute of Standards and Technology awarded the New Zealand Institute For Public Health And Forensic Science LIMITED (doing business as ESR) $246,365 on June 1, 2026, under the Measurement and Engineering Research and Standards program (CFDA 11.609).

ESR will develop use-case profiles of artificial intelligence applications in forensic science, aligned with NIST forensic science process maps, and build an open-access library of forensic AI use cases. The organization will analyze AI development and procurement strategies through stakeholder interviews and document reviews, then create a procurement framework outlining key considerations for acquiring AI systems in forensic contexts. ESR will design, validate, and publish a conceptual taxonomy and metadata structure for standardizing how forensic AI systems are described. Additionally, ESR will conduct a case study of Lumi Drug Scan, an AI-powered field drug detection system, as a real-world example of responsible AI deployment in forensic science. All activities include engagement with forensic practitioners to ensure alignment with casework and lab operations.

The award runs through May 31, 2027, with performance taking place in New Zealand. Deliverables include a validated and accessible library of forensic AI use cases, a procurement framework, a taxonomy for describing AI systems, and an open-access platform for sharing these resources. The project benefits forensic laboratories, AI developers, legal professionals, courts, and law enforcement agencies.

Activities

The researchers will develop use-case profiles of AI in forensic science, aligned with NIST forensic science process maps, and build an open-access library of forensic AI use cases. Further, they will analyze strategies for AI development and procurement through stakeholder interviews and document reviews, and create a procurement framework outlining key considerations acquiring AI systems in forensic contexts. ESR will also design, validate, and publish a conceptual taxonomy for forensic AI application types. And lastly, they will conduct a case study of lumi drug scan, an AI-powered field drug detection system, which will serve as a practical example of responsible AI deployment in forensic science. These activities will all included working with forensic practitioners to ensure relevance to casework and real-world lab operations.

Expected outcomes

The expected outcomes include a validated and accessible library of forensic AI use cases, a procurement framework, a taxonomy and metadata structure to describe AI systems, and an open-access platform to share these resources.

Intended beneficiaries

The project is intended to benefit forensic laboratories, AI developers, legal professionals, courts, and law enforcement agencies. Ultimately, IT will also serve the general public by supporting more reliable and transparent use of AI in the justice system.

Subrecipient activities

The recipient does not intend to subaward funds.