DOJ · DOJ-0038 · record R1508

Thomson Reuters Vigilant Vehicle Manager

Department of Justice · Department of Justice / ATF

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: High-impactSource: a) High-impact
Impact justification: Not reported
Start date: 2020-09 (month precision)Source: 09/2020
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Law Enforcement
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The purpose of the AI use case in Thomson Reuters Vigilant Vehicle Manager is to intelligently organize, correlate, and analyze large volumes of license plate and vehicle sightings data. By automating the identification of recurring patterns and providing data-driven insights, it streamlines the workflow for identifying vehicles that may warrant attention. The AI capabilities reduce time-consuming manual reviews, improve accuracy in spotting significant trends, and help allocate investigative resources more effectively for timely and well-informed actions.

Expected benefits

License plate reader systems are used by law enforcement to assist with identification of vehicles associated with criminal investigations. ATF has no role in training or managing AI capabilities which are incidental to providing the service.

System outputs

The AI features produce overviews of vehicle activity, highlight recurring patterns, and point to areas for further review.

Technology

AI classification: Computer visionSource: Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
System name(s): Redacted for cybersecurity purposes.
Custom-developed code: No
Public source code: Not reported

Sourcing

How it was built: Purchased from vendorSource: a) Purchased from a vendor
Vendor (as reported): Motorola
Vendors (standardized): Motorola Solutions

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: Yes
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: This AI use case utilizes one or more of the demographic variables listed in compliance with all federal laws and agency regulations.
Training and evaluation data: The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.
Federal Data Catalog: Not reported

Governance

8 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingReported in progressSource: b) In-progress

AI impact assessmentReported in progressSource: b) In-progress

Independent reviewReported in progressSource: d) In-progress

Ongoing monitoringReported in progressSource: b) Development of monitoring protocols is in-progress

Operator trainingReported in progressSource: b) Establishment of sufficient and periodic training is in-progress

Fail-safeReported in progressSource: c) In-progress

Appeal processReported in progressSource: c) Establishment of an appropriate appeal process is in-progress

User and public consultationReported in progressSource: e) In-progress

Potential impacts and how they were identified

Consistent with Executive Orders and OMB guidance, the case owner relied on DOJ AI governance practices to evaluate impacts and risks.