DOI · DOI-0004 · record R2740

Automate Project Execution of FI&R (Facilities Improvement and Repair) Projects

Department of the Interior · ASIA

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: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

Mission

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

Problem the AI is intended to solve

Strategically prioritize Facilities Improvement and Repair (FI&R) projects based on a set of criteria developed in concert with policy, customer need, and capacity. Project funding based on compliance with policy and funding parameters. Process based on an objective and holistic review of IA-wide priorities. Aggregate data across systems and apply analysis to develop a schedule, reporting, identify dependencies, and develop notifications.

Expected benefits

Strategic use of funds, allocation of multiple needs (projects), transparency of status, identification of dependency on external factors.

System outputs

Data based decision making, streamlined project execution, reduce risk, cost optimization, improved stakeholder relationship, better tracking and reporting Structured decision making (policy/data), risk management, improved compliance

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: No
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: No
Privacy Impact Assessment: Not reported
Authorization to Operate: No
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