ELIS Card Photo Validation Service

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 supports beneficiaries submitting an e-filed I-765 via myUSCIS to apply for employment authorization. These applications include a digital ID photo of the applicant, which will be printed on their Employment Authorization Document (EAD) card if the application is accepted. The use case determines whether a user-uploaded ID photo is suitable for use on an EAD card, and notifies the submitter if it detects a potential quality issue with the photo. (SEE DHS CAIO SUPER MEMO FY24) --- 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 AI outputs are a real-time advisory message to the submitter of the photo that it is of insufficient quality for card production at which point the submitter may choose to resubmit or not. While adjudication of EADs is not dependent on this use case, this tool enhances efficiency and customer service by minimizing the number of cards failing in production and delays related to subsequent requests for information. (SEE USCIS REQUEST FOR DHS CAIO DETERMINATION FY24)

Start date

2022-03-15 (day precision)Source: 2022-03-15T00:00:00

Withheld from public reporting

Not reported

Mission

Topic area

Service Delivery

Operational functions

No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The card photo validation solution was developed to validate each submitted photo against a set of business-defined requirements in near-real-time in order to eliminate rejections/RFEs for the user uploaded photos.

Expected benefits

Ensuring beneficiary uploaded photos meet USCIS requirements. This helps ensure photos are correct before making ID cards, saving adjudicator time and avoiding delays.

System outputs

Response back to user based on the pre-defined quality checks if the uploaded photo meets USCIS requirements. Users still have the option to ignore the warnings and upload the photo.

Technology

AI classification

Computer visionSource: Computer Vision: AI that processes and interprets visual data (e.g., images and videos).

System name(s)

ELIS

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)

SAIC and DV United

Vendors (standardized)

SAIC

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

Initial face detection is performed by pretrained dlib embeddings as implemented in opencv. Validation tests requiring object detection (headwear and eyeglasses) is performed using custom fine-tuning from Detectron2, an open-source object detection model. Training and testing data for these object detection problems was sourced from a combination of public domain face detection datasets and USCIS production data passport photos.

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