DOE · DOE-477 · record R3343

OPQ-AI

Department of Energy · ANL - Argonne National Laboratory (SC43 OIM)

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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: Not high-impactSource: c) Not high-impact
Impact justification: Impact of system failure or erroneous results is negligible.
Start date: 2021-03-01 (day precision)Source: 2021-03-01T00:00:00
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

Semi-automated person ID matching with existing database before new accounts are created.

Expected benefits

Significantly reduces person-hours for manual review of incoming people registrations to match with existing database records by recommending most likely matches, if an existing record is identified that matches with the registration details.

System outputs

Recommendation of matched person record that already exists or that a new person record should be created.

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): Argonne National Laboratory Information Technology Infrastructure
Custom-developed code: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
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: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: Not reported
Training and evaluation data: Data includes read-only access internal person/HR records existing in current database systems.
Federal Data Catalog: No

Governance

5 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 placeSource: a) Yes

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringReported in placeSource: a) Yes, sufficient monitoring protocols have been established

Operator trainingReported in placeSource: a) Yes, sufficient and periodic training has been established

Fail-safeReported in placeSource: a) Yes

Appeal processNo answer reported

User and public consultationReported in placeSource: a) Direct usability testing

Potential impacts and how they were identified

Not reported