USDA · USDA-001 · record R1314
Repair Spend
Department of Agriculture · Research, Education and Economics
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
- Not reported
- Start date
- 2020-06-09 (day precision)Source: 6/9/2020
- Withheld from public reporting
- Not reported
Mission
- Topic area
- Procurement and Financial Management
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
The AI is to review financial documents and then classify each expense as money spent on "facility repairs" or "not facility repairs".
Expected benefits
The expected benefits include reduction of manual hours identifying the types of transactions.
System outputs
The output of the model is a recommendation of which financial transactions should be identified as "repair" expenses.
Technology
- AI classification
- Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
- System name(s)
- Enterprise Data Analytics Platform & Toolset (EDAPT, Impala, Tableau)
- Custom-developed code
- Yes
- 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)
- Accenture
- Vendors (standardized)
- Accenture
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
- k) None of the above
- Training and evaluation data
- Approximately 14,000 financial transactions were used to train the model and finetune its parameters. Approximately 3,500 financial transactions were used to test the performance of the final model.
- 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