TREAS · TREAS-IRS-63 · record R2847

F1023 Hybrid NLP and ML Pipeline

Department of the Treasury · Internal Revenue Service (IRS)

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: The output is not presumed to be high-impact and is not used as the principal basis for significant decisions/actions
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Information Technology
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The model attempts to predict non-compliance among tax-exempt entities by leveraging embedding-based feature extraction feeding a downstream classifier.

Expected benefits

F1023 and F990 contain natural text fields around activity descriptions, mission or purpose statements making it difficult for Tax Exempt Government Entities (TEGE) to detect non-compliance among the population of Exempt Organizations (EOs). This use case provides improved ability to predict non-compliance.

System outputs

This solution will address multiple F1023 strategies in TEGE and the output will be tailored to improve operational efficiency for each strategy.

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): Not reported
Custom-developed code: Not reported
Public source code: Not reported

Sourcing

How it was built: Not reported
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.

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