Passenger Security Assessment Model

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

2013-04-01 (day precision)Source: 2013-04-01T00:00:00

Withheld from public reporting

Not reported

Mission

Topic area

Law Enforcement

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

This model aids CBP to efficiently identify security risks, especially related to narcotics interdiction, by providing real-time risk assessments that overcome limitations of traditional, time-intensive methods. The model solves the problem by providing CBP personnel with real-time risk assessments and actionable recommendations integrated into existing systems. By analyzing data not typically accessible during initial processing, the model enhances the ability to detect smuggling indicators and prioritize high-risk individuals or vehicles for further inspection. This improves the efficiency and effectiveness of border security operations, enabling CBP to better safeguard the nation while maintaining the flow of legitimate travel and trade.

Expected benefits

This model is designed to support CBP personnel in quickly recognizing crossings that may warrant additional scrutiny, thereby enhancing border security and safety.

System outputs

The outputs include risk assessments and recommendations, which are integrated into existing passenger processing and threat targeting systems, such as the Automated Targeting System (ATS). These notifications equip CBP personnel with actionable insights to address potential security concerns in real-time.

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Automated Targeting System (ATS)

Custom-developed code

Yes

Public source code

Not reported

Sourcing

How it was built

Developed in-houseSource: b) Developed in-house

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

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

www.dhs.gov ↗

Authorization to Operate

Yes

Demographic features

b) Sex; c) Age

Training and evaluation data

This model leverages data housed within the Automated Targeting System (ATS) Unified Passenger (UPAX).

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.

Potential impacts and how they were identified

Risks include false positives and negatives, which could result in delays for travelers, failure to detect narcotics smuggling, or missed detections; algorithmic bias may disproportionately target certain types of travelers and crossing behaviors (related to model training using historical seizures); and ongoing challenge of traffickers adapting their methods to evade detection. These risks have been identified through research, real-world applications, and expert analyses.