DOJ · DOJ-0324 · record R1749

Background Searches

Department of Justice · Department of Justice / EOIR

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: 2025-01 (month precision)Source: 01/2025
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Administrative Functions
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

To perform background searches to inform an EOIR character and fitness determination for individuals applying to be an EOIR accredited representative.

Expected benefits

Timely, comprehensive, and efficient background check. Character and fitness determinations made based on accurate background information. EOIR approves accreditation applicants with the requisite character and fitness. Individuals in EOIR immigration proceedings are assisted by accredited representatives with the requisite character and fitness.

System outputs

Background check findings.

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): Redacted for cybersecurity purposes.
Custom-developed code: No
Public source code: Not reported

Sourcing

How it was built: Purchased from vendorSource: a) Purchased from a vendor
Vendor (as reported): TransUnion Risk and Alternative Data Solutions, Inc.
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: Not reported
Authorization to Operate: Yes
Demographic features: This AI use case utilizes one or more of the demographic variables listed in compliance with all federal laws and agency regulations.
Training and evaluation data: The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.
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.

Pre-deployment testingReported in progressSource: b) In-progress

AI impact assessmentReported in progressSource: b) In-progress

Independent reviewReported in progressSource: d) In-progress

Ongoing monitoringReported in progressSource: b) Development of monitoring protocols is in-progress

Operator trainingReported in progressSource: b) Establishment of sufficient and periodic training is in-progress

Fail-safeReported in progressSource: c) In-progress

Appeal processReported in progressSource: c) Establishment of an appropriate appeal process is in-progress

User and public consultationReported in progressSource: e) In-progress

Potential impacts and how they were identified

Consistent with Executive Orders and OMB guidance, the case owner relied on DOJ AI governance practices to evaluate impacts and risks.