Person-Centric Identity Services Information Compilation Check

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

Presumed high-impact, determined notSource: b) Presumed high-impact, but determined not high impact

Impact justification

This use case verifies the ongoing accuracy of information compiled from within the Person-Centric Identity Services (PCIS). It identifies which records from within PCIS best match search criteria to support case processing. ------ The AI outputs do not serve as a principal basis for a decision or action concerning a specific individual or entity that has a legal, material, binding, or similarly significant effect on that individual’s or entity’s civil rights, civil liberties or privacy, equal opportunities, or access to or the ability to apply for critical government resources or services. The use case compiles records from across a variety of USCIS systems to provide a comprehensive history of a person’s interaction with USCIS. The output of this can be visualized through a report or dashboard to assist with case review ensuring access to helpful and accurate records. Adjudicators review the outputs of this use case, alongside other information and insights, to process a case and make a final determination. The adjudication process can be conducted without this tool, however, doing so would significantly increase the time and effort required to process immigration requests.

Start date

2022-07-01 (day precision)Source: 2022-07-01T00:00:00

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

The output of the use case is the numerical confidence score which is used to determine the validity of the A-number presented in search results. The confidence score identifies which records from within PCIS best match search criteria for an A-number.

Expected benefits

The aim of this use case is to leverage machine learning to test the accuracy of PCIS to identify and manage associations between individuals and their assigned A-numbers, which is a unique 7, 8, or 9 digit number assigned to a noncitizen by DHS. The A-Number plays a critical role in surfacing of a person and all their associated records from across PCIS.

System outputs

Numerical likelihood score which is used to determine the validity of the A# presented. Likelihood scores are subjected to a high threshold (.98, maximum 1) to assess whether the A# presented belongs to the individual.

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)

Person Centric Identity Services

Custom-developed code

Yes

Public source code

Not reported

Sourcing

How it was built

Contract and in-houseSource: c) Developed with both contracting and in-house resources

Vendor (as reported)

MetroIBR

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

Not reported

Training and evaluation data

USCIS-only data derived from 7 form-processing source systems including C3, ELIS, CPMS, GLOBAL, CIS2, AR-11, CAMINO.

Federal Data Catalog

Not reported

Governance

0 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

Not reported