Automated Targeting System

Automated Targeting System
Name	Automated Targeting System
Type	risk assessment system
Owner	U.S. Customs and Border Protection, U.S. Department of Homeland Security
Introduced	2000s

Automated Targeting System

The Automated Targeting System is a risk-analysis platform used by U.S. Customs and Border Protection, U.S. Department of Homeland Security, U.S. Congress oversight committees and external auditors to screen passengers, cargo, and conveyances bound for or entering the United States. It integrates data from transportation networks such as Federal Aviation Administration manifests, maritime registries like the International Maritime Organization, and financial records tied to institutions including the Federal Reserve System and private firms to generate risk scores for investigative units such as Immigration and Customs Enforcement and Transportation Security Administration. The system has been the subject of oversight by bodies including the Government Accountability Office, litigation in courts such as the United States District Court for the District of Columbia, and scrutiny from civil liberties organizations like the American Civil Liberties Union.

Overview

The system functions as a predictive screening tool employed at ports of entry overseen by agencies like U.S. Customs and Border Protection and coordinated with partner agencies including Federal Bureau of Investigation and Drug Enforcement Administration. It aggregates identifiers that appear in databases maintained by Social Security Administration, Department of State, and private carriers such as Delta Air Lines and Maersk Line to produce alerts for analysts in units comparable to National Targeting Center. Developers consulted standards from bodies like the National Institute of Standards and Technology and interoperability protocols referenced by the International Organization for Standardization.

History and Development

Origins trace to post-9/11 homeland security initiatives driven by policy makers such as officials from the 9/11 Commission and legislative acts like the Homeland Security Act of 2002. Initial prototypes were piloted in collaboration with vendors who had contracts involving firms similar to Boeing and IBM and were evaluated by auditors from the Government Accountability Office and the Privacy and Civil Liberties Oversight Board. Subsequent iterations responded to rulings and inquiries involving entities such as the United States Court of Appeals for the District of Columbia Circuit and reporting by media outlets like The New York Times, The Washington Post, and ProPublica.

Architecture and Components

The platform is comprised of modular components analogous to architectures used by major technology projects at Amazon Web Services and Microsoft Azure. Core modules include ingestion pipelines that interface with cargo systems used by carriers like Maersk Line and airline reservation systems operated by Amadeus IT Group, analytic engines employing techniques similar to those reported in research labs at Massachusetts Institute of Technology and Stanford University, and user interfaces accessed by officers at John F. Kennedy International Airport and Port of Los Angeles. Logging and audit trails are designed to comply with guidance from the National Institute of Standards and Technology and oversight logs reviewed by committees in the United States Senate.

Data Sources and Processing

Data inputs come from manifests and passenger name records supplied by airlines such as American Airlines and cruise operators like Carnival Corporation, shipping manifests registered through the International Maritime Organization systems, visa and passport data from the Department of State, and watchlists maintained by Interpol and Terrorist Screening Center. The system performs cross-referencing and entity resolution techniques similar to methods described in publications from Carnegie Mellon University and University of California, Berkeley research groups, applying rules and machine-learned models influenced by work at institutions like Google and OpenAI. Data sharing agreements often invoke statutes and guidance from the Privacy Act of 1974 and oversight by the Department of Justice.

Applications and Use Cases

Operational use includes screening inbound passengers at hubs like Los Angeles International Airport, vetting maritime cargo entering Port of New York and New Jersey, and supporting investigations by Immigration and Customs Enforcement and Customs and Border Protection targeting teams. Analysts use risk scores to trigger secondary inspections at facilities such as San Francisco International Airport and to prioritize referrals to investigative bodies like the Federal Bureau of Investigation or Department of Commerce for trade enforcement. The system has been integrated into broader initiatives such as preclearance operations with partners in countries represented by organizations like the International Civil Aviation Organization.

Privacy, Ethics, and Legal Issues

Civil liberties groups such as the American Civil Liberties Union and Human Rights Watch have raised concerns paralleling debates involving the Electronic Frontier Foundation about accuracy, redress, and potential bias. Legal challenges have invoked courts including the United States District Court for the Southern District of New York and prompted reviews by the Privacy and Civil Liberties Oversight Board and the Government Accountability Office. Issues intersect with international instruments and practices associated with the European Court of Human Rights and data-protection regimes influenced by the European Union directives, prompting comparisons with systems used by agencies like the Canada Border Services Agency.

Effectiveness and Criticisms

Evaluations by entities such as the Government Accountability Office and independent researchers at institutions like Harvard University and Columbia University have produced mixed findings regarding predictive validity, false positives, and operational impacts on travel and trade. Critics cite examples reported by investigative outlets including The Guardian and Reuters to argue that reliance on automated scoring can produce disparate outcomes similar to controversies involving algorithms in sectors monitored by the Federal Trade Commission and academia. Supporters point to interdictions and enforcement actions credited to analysts using the platform and to interagency coordination efforts modeled after task forces such as those convened by the National Security Council.

Category:Risk assessment systems