60NANB26D149↗
New Zealand Institute for Public Health and Forensic Science Limited received this grant or assistance award from National Institute of Standards and Technology: $246.4K obligated so far for measurement and engineering research and standards. Its latest action was on 2026-06-03.
Key facts · data as of Oct 26, 2026
- Recipient
- New Zealand Institute for Public Health and Forensic Science Limited
- Awarding agency
- National Institute of Standards and Technology (Department of Commerce)
- Obligated to date
- $246.4K
Source: USAspending.gov prime award records (obligations: money committed, not outlays), data as of Oct 26, 2026.
Cite this page: SpendQuery, Award 60NANB26D149, data as of Oct 26, 2026, https://spendquery.com/award?id=ASST_NON_60NANB26D149_013
New Zealand Institute for Public Health and Forensic Science Limited: all federal awards · Department of Commerce: spending
PURPOSE: 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 HOW AI CAN BE TRANSFORMATIVE IN FORENSIC WORKFLOWS. THE APPLICANT PROPOSES TO DEVELOP USE-CASE PROFILES, ALIGNED WITH NIST FORENSIC SCIENCE PROCESS MAPS; CREATE A PROCUREMENT FRAMEWORK OUTLINING KEY CONSIDERATIONS FOR ACQUIRING AI SYSTEMS IN FORENSIC CONTEXTS; AND CREATE A TAXONOMY THAT CAN BE USED TO STANDARDIZE HOW AI SYSTEMS ARE DESCRIBED. LASTLY, THE APPLICANT WILL CONDUCT A CASE STUDY OF LUMI DRUG SCAN, A FIELD DRUG DETECTION TOOL, AS A REAL-WORLD AI APPLICATION IN FORENSICS.ACTIVITIES TO BE PERFORMED: 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.
What it is
- Program
- Measurement and Engineering Research and Standards (Assistance Listing 11.609)
- Where the work is
- NZL
- Topics
- artificial_intelligence
Obligations by fiscal year
SpendQuery holds FY2023 on; earlier years are on USAspending.gov.
Subrecipients: where the money went next
No subawards reported for this award. Primes report subawards of $30,000 or more; many awards have none.
Every action
1 action since 2026-06-03. Each is a modification or amendment with the money it added or took back.
| Date | Amendment | Kind | Amount | What the agency wrote |
|---|---|---|---|---|
| 2026-06-03 | 0 | New award | $246.4K | PURPOSE: 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 HOW AI CAN BE TRANSFORMATIVE IN FORENSIC… |
Source: USAspending.gov prime award transactions and FSRS subaward reports, as loaded by SpendQuery (data as of 2026-10-26). Amounts are obligations (money committed), not outlays. The official record on USAspending.gov ↗