2_use_case_name: AI Pilot Project to Screen and Flag for Personally Identifiable Information (PII) in Digitized Archival Records
3_agency: National Archives and Records Administration
3_abr: NARA
8_topic_area: Mission-Enabling
10_commercial_ai: Digitizing text from scanned documents or smart forms for archival purposes using AI.
11_purpose_benefits: NARA is using AI to automatically find and remove sensitive personal information from its digitized historical records. This will make the process faster, more accurate, and better protect privacy while allowing for greater public access to these records. The AI will also help NARA manage its vast collection and adapt to future privacy needs.
12_outputs: This AI use case will produce redacted records, a prioritized list for redaction, and a tool for staff to redact unpublished records.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 7/15/1905
19_date_acq_dev_began: 7/15/1905
20_date_implemented: TBD
22_dev_method: Developed in-house.
24_hisp_support: No
27_public_info: Yes
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: Agency is strictly using its data to test the pre-trained model for the purpose of prototype work. The data is publicly available at catalog.archives.gov.
34_data_docs: Documentation has been partially completed: Some documentation exists (detailing the composition and any statistical bias or measurement skew for training and evaluation purposes), but documentation took place within this use case’s development.
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
40_has_ato: No
41_system_name: National Archive Catalog (NAC) 
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Use of existing data platforms: This use case is being developed on existing enterprise data and analytics platforms within the agency rather than procuring additional platforms or SaaS to operate.
50_internal_review: Limited documentation for review: Some information regarding the model’s performance on specific benchmarks are available or have been shared with specific stakeholders within the agency.
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: Planned or in-progress.
53_real_world_testing: Benchmark evaluation: Testing of the AI model has involved the use of benchmarks (either publicly available or internally created) to estimate performance in real-world settings, but has not been tested in an operational environment. 
55_independent_eval: Yes – by another appropriate agency office that was not directly involved in the system’s development
56_monitor_postdeploy: Intermittent and Manually Updated: A plan for monitoring the AI use case is in place, and requires data science teams to work with DevOps engineers to manually update models at scheduled intervals, and create metrics to detect data distribution shifts between the operational environment and the training data for the model. 
57_autonomous_impact: No - Some individual decisions or actions require direct human oversight.
59_ai_notice: Online - in the terms or instructions for the service.
59_question_type: Not in production yet
61_adverse_impact: No
63_stakeholder_consult: Direct user testing