NARA · NARA - 0007 · record R3203

Auto-fill of Descriptive Metadata for Archival Descriptions

National Archives and Records Administration · National Archives & Records Administration (NARA)

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: 2024-09-01 (day precision)Source: 2024-09-01T00:00:00
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

The AI is intended to solve the problem of the "descriptive gap" created by labor-intensive manual cataloging by automatically generating metadata and summaries from document content, allowing NARA to process massive backlogs and make millions of records instantly searchable for the public.

Expected benefits

NARA is using AI to automatically create descriptions (metadata) for its digital archives. This will save archivists time, make records easier to find, and help the public better understand the information in the National Archives Catalog.

System outputs

This AI use case will create more complete and informative descriptions for records, making them easier to find in the National Archives Catalog.

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: Yes
Public source code: Not reported

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
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: www.archives.gov ↗
Authorization to Operate: No
Demographic features: k) None of the above
Training and evaluation data: The data is publicly available at catalog.archives.gov
Federal Data Catalog: catalog.data.gov ↗

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