Categorization and Labelling Administrative Requests

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

Not reported

Withheld from public reporting

Not reported

Mission

Topic area

Administrative Functions

Operational functions

Risk scoring and triage Derived by keyword rules; see methodology

Problem the AI is intended to solve

The categorization and labeling functionality is intended to support functions such as administrative intake requests. This is intended to support use cases such as rapid triage of Information Technology intake requests. This solves the problem of manual data entry.

Expected benefits

Increased efficiency.

System outputs

1. The system selects a category based on a list of categories defined by a person. 2. The system labels long text fields in under 50 characters.

Technology

AI classification

Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).

System name(s)

Not reported

Custom-developed code

Yes

Public source code

github.com ↗

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

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.

Potential impacts and how they were identified

Not reported