Global Maritime Intelligence
Description
The AI is intended to solve the problem of investigators having to manually piece together fragmented maritime activity data from many sources, which makes it difficult to see relationships among vessels, shipments, and ports and identify potential leads on illicit maritime activity.
Detailed example
The platform uses several machine learning (ML) models and other AI techniques to process and analyze large volumes of maritime data from multiple sources, such as satellite imagery, Automatic Identification System (AIS) signals, and transactional maritime data. The platform’s AI models detect patterns and anomalies that may indicate potential threats or behaviors consistent with illicit activities like smuggling or trafficking. These AI-generated insights are incorporated into detailed intelligence reports and risk assessments for platform users. These outputs support HSI analysts’ decision-making and are reviewed in conjunction with other HSI data holdings to determine whether analysts should take follow-up actions, such as investigations, into flagged entities.
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
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The use of AI in this process helps Homeland Security Investigations quickly identify potential threats, improves the efficiency of intelligence operations, and enables faster responses to maritime risks that would be difficult to detect through manual analysis alone.
Audit / financial statement impact
This use case does not meet the definition of "high-impact" as outlined in Section 5 of M-25-21 because its outputs do not serve as a "principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety." Instead, the AI system generates intelligence reports and risk assessments that are used to support human decision-making. Analysts review the outputs and initiate follow-on actions after validating the source data, such as inspections or investigations, ensuring that the AI's outputs are not the sole or principal basis for these decisions. While the use case aligns with a presumed high-impact category due to its critical role in maritime safety and law enforcement, it does not meet the stricter definition of high-impact because its outputs are advisory and produce leads that must be validated as part of the investigative process prior to action being taken.
Controls / human review
ATO: Not reported; PIA: Not published