USDA · USDA-135 · record R1433

Yearly Incident Procurement Classification Report

Department of Agriculture · Natural Resources and Environment

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2024-12-11 (day precision)Source: 12/11/2024
Withheld from public reporting: Not reported

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

As part of planning for the upcoming fire season, all previous year incident-related procurements are categorized manually. This is a time-consuming process and humans may not be able to identify more nuanced, purchasing patterns.

Expected benefits

The goal is to identify patterns and cost savings opportunities for purchases in the upcoming fire season, which in turn could lead to quicker resource allocation to incident locations.

System outputs

The outputs are classification numbers representing common purchase categories identified by procurement staff.

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): Not reported
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: No
Demographic features: k) None of the above
Training and evaluation data: Training data inputs were item descriptions (i.e. protective work gloves) of purchases from 2023. Validation data was human-labeled item categories from the same year.
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