HHS · no agency ID · record R0614

Unaccompanied Child Sponsor Identity Verification

Department of Health and Human Services · HHS/ACF

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: High-impactSource: a) High-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Government Benefits Processing
Operational functions: Fraud, waste and improper payments, Biometrics and identity Derived by keyword rules; see methodology

Problem the AI is intended to solve

How can ACF strengthen sponsor identity verification to reduce fraudulent sponsor applications? Throughout the process of sponsor vetting, there are various touchpoints where the identity of the sponsor is critical to ensuring a child will be placed with a safe guardian. Knowing that the person (sponsor, household adult) is who they claim to be and that the person presenting at different points of the sponsor application process is consistently the person who was vetted is essential to ensure the welfare of a child.

Expected benefits

Increased certainty that the adults applying to sponsor/care for a child release from ORR care are who they claim to be, so that they may be properly vetted in providing a safe environment for children post-release.

System outputs

Confirmation that person A is person A at all touchpoints of the sponsor vetting process.

Technology

AI classification: Computer visionSource: Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
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: Not reported
Privacy Impact Assessment: Not reported
Authorization to Operate: Not reported
Demographic features: Not reported
Training and evaluation data: Not reported
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.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported