CargoNet
Description
The purpose of the AI use case in CargoNet is to detect and interpret patterns within logistics and theft incident data automating the process of identifying unusual activities or recurring risks.
Detailed example
The AI features produce alerts, reveal clusters, and connect events to show underlying trends.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
The expected benefit is focusing efforts on deviating areas/goods/patterns to improve effectiveness of subsequent steps.
Audit / financial statement impact
Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
Controls / human review
ATO: No; PIA: Not published
Data needed
The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.