TREAS · REQ-2024-01872 · record R2778

Large Language Model (LLM) Chatbot for Proof of Concept

Department of the Treasury · Bureau of the Fiscal Service (BFS)

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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: The tool, once deployed, is only for productivity and does not impact any of the defined high-impact areas
Start date: 2024-06-10 (day precision)Source: 6/10/2024
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Information Technology
Operational functions: Chatbot or virtual assistant Derived by keyword rules; see methodology

Problem the AI is intended to solve

Code Assistance - Generating, debugging, and documenting code

Expected benefits

Test PaaS to assist developers. The LLM will generate comments and documentation alongside code snippets, promoting better code understanding and maintainability. The LLM works with COBOL, JAVA, Angular, and other programming languages, making it versatile for multi-language projects. The LLM has the ability to catch common mistakes, improving code quality and reducing debugging time, thereby accelerating the overall coding process.

System outputs

Code comments, documentation, improvement suggestions

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: No
Public source code: Not reported

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
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: N/A. Evaluating tools only at this stage
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