STATE · no agency ID · record R3237

Natural Language Processing (NLP) for Foreign Assistance Appropriations Analysis

Department of State · F/FAO

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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: 2021-08-05 (day precision)Source: 08/05/2021 00:00:00
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Service Delivery
Operational functions: Summarization Derived by keyword rules; see methodology

Problem the AI is intended to solve

Summarizing the key points of a lengthy report using AI.

Expected benefits

The NLP application reduces the time needed to extract congressional directives from the annual appropriations bill which ultimately shortens the cycle time for generating the report detailing the annual allocation of U.S. foreign assistance funds to foreign countries and international organizations (i.e. the 653(a) report).

System outputs

Consolidated congressional directives from the annual appropriations bill to be included in the report detailing the allocation of U.S. foreign assistance funds to foreign countries and international organizations (i.e. the 653(a) report).

Technology

AI classification: Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.
System name(s): FACTS Info
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): Guidehouse
Vendors (standardized): Guidehouse

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: Annual appropriations bills
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