DOE · DOE-658 · record R3514

pComply-AI-High Risk

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: 2024-01-01 (day precision)Source: 2024-01-01T00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Procurement and Financial Management
Operational functions: Procurement and acquisition Derived by keyword rules; see methodology

Problem the AI is intended to solve

Preemptive procurement compliance: daily scans of recent PARIS requisition records.

Expected benefits

Developed as a rapid response for a corrective action to eliminate incidents when high-risk materials are procured inadvertently without the required review processes and handling.

System outputs

Solution features an interactive report dashboard and automatic email notifications to persons involved with the requisition when a high-risk scenario is identified.

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): pComply-AI-High Risk
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: ANL Operational data.
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