GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: Using AI to Help with Coding-Related Tasks/Questions
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Enforcement (ENF); Division of Economic and Risk Analysis (DERA)
8_topic_area: Education & Workforce
10_commercial_ai: None of the above.
11_purpose_benefits: Helps staff with coding-related tasks, for a subset of supported languages. Staff can also use this as an educational tool to learn how to code more efficiently.
12_outputs: It outputs code responsive to the user’s request. It is textual, non-self-executing, and typically has non-code text explaining the logic behind the code and how to use the code.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 24-Jan
19_date_acq_dev_began: 24-Jan
20_date_implemented: 24-Jun
22_dev_method: Developed in-house.
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: Not Applicable
34_data_docs: Documentation is widely available: Documentation is not only complete, but is widely accessible within the agency, and has an owner and a regular update cadence.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: Yes
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: SEARCH
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Re-use production level code from a different use-case: This use case re-uses production level code and/or internally developed code libraries for model development from existing AI systems or repositories inside the agency.
50_internal_review: Documentation has been published: Complete documentation has been published to a repository or data catalog within the agency and is made accessible to other data science teams for review and feedback.
2_use_case_name: Optical Character Recognition (OCR) for Records Analysis
3_agency: Securities and Exchange Commission
3_abr: SEC
4_bureau: Division of Enforcement (ENF)
8_topic_area: Other
8_question_type: Securities & Financial Markets
10_commercial_ai: Digitizing text from scanned documents or smart forms for archival purposes using AI.
11_purpose_benefits: Assists ENF staff in extracting relevant information from digital image files. This will accelerate associated ENF investigations.
12_outputs: A text string of all text recognized from the associated image. 
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 24-Mar
19_date_acq_dev_began: 24-Mar
20_date_implemented: 24-Oct
22_dev_method: Developed with both contracting and in-house resources.
23_contract_piids: 50310220D0012_50310221F0160 
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: Yes
31_data_catalog: Yes
33_agency_data: Image data
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
35_demo_features: Other
35_question_type: Not Applicable
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: SEARCH
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Yes
45_compute_request: Yes
47_timely_resources: Yes
49_existing_reuse: Re-use production level code and/or data products: This use case re-uses production level code as well as data products that have been published or made widely available for data science teams for within the agency.
50_internal_review: No documentation is available: No documentation detailing model performance metrics, model architecture, features and intended use of the models have been created or are currently accessible to other data science teams within the agency.
2_use_case_name: Microsoft Copilot for Internal Employees 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: Improving the quality of written communications using AI tools.
11_purpose_benefits: USAGM is exploring the potential of Microsoft Copilot to enhance workplace productivity and collaboration across its internal teams. The tool leverages generative AI capabilities integrated within the Microsoft 365 suite, enabling employees to streamline workflows and focus on high-value tasks. Key features include drafting documents and presentations, summarizing content, automating reminders, managing editorial calendars, scheduling meetings, recording and transcribing conversations, and conducting natural language search for quick access to files and records. This initiative supports operational efficiency by integrating AI capabilities across collaboration, task management, and content creation workflows. 
16_dev_stage: Initiated
17_impact_type: Neither
2_use_case_name: Automated Transcription Generation 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: Transcribing and summarizing a recorded meeting or interview using AI.
11_purpose_benefits: Generative AI is being leveraged in USAGM’s media workflows to enhance efficiency and accessibility. This use case integrates Latakoo, which utilizes OpenAI's Whisper technology for transcription. With high accuracy, the system transcribes content as it is processed and passes it into USAGM’s media asset management (MAM) system, ensuring that the content is easily searchable and accessible for future use. 
16_dev_stage: Initiated
17_impact_type: Neither
2_use_case_name: Content Enhancement for Articles 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: This project uses AI integrated with our content management system (CMS) and digital platforms to assist journalists in optimizing article quality. AI generates multiple versions of titles, automates the creation of SEO-friendly tags and text, and provides concise summaries for articles. These summaries enhance user engagement by increasing the time spent on pages, particularly when readers arrive via search engines or social media. Journalists can review and adjust AI suggestions to ensure alignment with their goals. 
16_dev_stage: Initiated
17_impact_type: Neither
2_use_case_name: Automated Translations 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: This initiative uses AI integrated with our content management system (CMS) to streamline multilingual content production across USAGM’s networks. Unlike typical translation tasks, USAGM faces the unique challenge of efficiently translating content into 50-plus languages, spanning diverse linguistic and cultural contexts. The AI translation tool provides draft translations for cloned articles, enabling seamless content reuse between language teams while maintaining accuracy and cultural sensitivity. This solution is critical for ensuring high-quality, localized content delivery to audiences worldwide. 
16_dev_stage: Initiated
17_impact_type: Neither
2_use_case_name: AI-Powered CMS Guide Agent 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: An AI-driven agent is being developed to enhance user support within the CMS. The agent will respond to natural language questions, offering tailored guidance and solutions from the CMS’s internal help documentation. 
16_dev_stage: Planned
17_impact_type: Neither
2_use_case_name: Content Summarization and Audience Engagement 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: AI tools integrated with our content management system (CMS) are being piloted to create multi-article summaries, "smart search" responses, and interactive highlights tailored for mobile-first users. These tools enhance content discoverability within the CMS and enable the creation of widgets like "all you need to know" summaries, improving user engagement and accessibility. Additionally, AI-generated interactive formats provide better comprehension for long-form articles, ensuring a seamless user experience across digital platforms. 
16_dev_stage: Planned
17_impact_type: Neither
2_use_case_name: Automated Text Narration 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: AI-generated audio narrations are being explored as a tool to enhance accessibility and engagement for long-form articles. An integrated audio player would allow users to consume content in a more convenient and flexible manner. 
16_dev_stage: Planned
17_impact_type: Neither
2_use_case_name: Automated Metadata Generation 
3_agency: United States Agency for Global Media
3_abr: USAGM
4_bureau: OCIO
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: AI is being tested to automate the generation of descriptive metadata, such as content summaries and SEO tags. This capability aims to simplify cataloging processes, improve content discoverability, and reduce the manual effort required for metadata creation
16_dev_stage: Planned
17_impact_type: Neither
2_use_case_name: Microsoft Copilot Integration
3_agency: United States Commission on Civil Rights
3_abr: USCCR
4_bureau: ASCD/IT
8_topic_area: Mission-Enabling
10_commercial_ai: Summarizing the key points of a lengthy report using AI.
11_purpose_benefits: Efficiency and improved administrative tasks.
12_outputs: Text-based summaries and AI generated text. 
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
51_extension_request: No – Agency did not request an extension for this use case.
52_impact_assessment: No
53_real_world_testing: Performance evaluation in operational environment: The AI use case has been tested in an operational environment before being fully implemented as a solution, or has been tested in simulated or controlled environment using operational or synthetic data.
54_key_risks: AI is not safety or rights-impacting.
55_independent_eval: AI is not safety or rights-impacting.
56_monitor_postdeploy: AI is not safety or rights-impacting.
57_autonomous_impact: AI is not safety or rights-impacting.
59_ai_notice: AI is not safety or rights-impacting.
61_adverse_impact: No
62_disparity_mitigation: AI is not safety or rights-impacting.
63_stakeholder_consult: None of the above
65_appeal_process: No – it is not operationally practical to offer this.
66_no_appeal_reason: AI is not safety or rights-impacting.
67_opt_out: Other
67_question_type: AI is not safety or rights-impacting, is not required for the completion of any tasks, and is optional for individual employees to use.
2_use_case_name: Relativity One 
3_agency: United States Commission on Civil Rights
3_abr: USCCR
4_bureau: OGC
8_topic_area: Other
8_question_type: FOIA
10_commercial_ai: Summarizing the key points of a lengthy report using AI.
11_purpose_benefits: Efficiency and improved administrative tasks.
12_outputs: Text-based summaries and AI generated text. 
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
53_real_world_testing: Performance evaluation in operational environment: The AI use case has been tested in an operational environment before being fully implemented as a solution, or has been tested in simulated or controlled environment using operational or synthetic data.
2_use_case_name: Lookout for mobile security
3_agency: United States Trade and Development Agency
3_abr: USTDA
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Lookout uses AI and machine learning to detect and respond to cyberattacks in real time. Lookout's threat intelligence services include data forensics, incident response, and research.
12_outputs: A Dashboard used for monitoring activity and reports
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 12/1/2022
19_date_acq_dev_began: 5/1/2023
20_date_implemented: 7/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: Shared Service through DHS CISA's CDM Program
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
33_agency_data: Not applicable. The Lookout software is a commercial-off-the-shelf platform, which is provided to USTDA by the Continuous Diagnostic and Mitigation Program under the Department of Homeland Security, Cybersecurity and Infrastructure Security Agency. The platform is one of several DHS/CISA services contracted by USTDA for security.
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: Lookout (FEDRAMP) PK ID F1603297883
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Other
43_question_type: Shared Service DD Form 1149
45_compute_request: No
47_timely_resources: Yes
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
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.
2_use_case_name: Qualys Cloud Detection and Response
3_agency: United States Trade and Development Agency
3_abr: USTDA
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Qualys uses AI to detect threats in real time, such as malware, ransomware, and unauthorized access.
12_outputs: A Dashboard used for monitoring activity and reports; real-time alerts when issues are discovered.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 7/1/2021
19_date_acq_dev_began: 11/1/2021
20_date_implemented: 12/1/2021
22_dev_method: Developed with contracting resources.
23_contract_piids: Shared Service through DHS CISA's CDM Program
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
33_agency_data: Not applicable. The Qualys tool is a commercial-off-the-shelf platform, which is provided to USTDA by the Continuous Diagnostic and Mitigation Program under the Department of Homeland Security, Cybersecurity and Infrastructure Security Agency. The platform is one of several DHS/CISA services contracted by USTDA for security.
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: Qualys (FEDRAMP) PK ID F1508207205
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Other
43_question_type: Shared Service DD Form 1149
45_compute_request: No
47_timely_resources: Yes
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
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.
2_use_case_name: Crowdstrike Falcon Threat Detection and Response
3_agency: United States Trade and Development Agency
3_abr: USTDA
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Crowdstrike uses AI to detect and respond to threats in real-time, such as malware, ransomware, and unauthorized access.
12_outputs: A Dashboard used for monitoring activity and reports; real-time alerts when issues are discovered.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 7/1/2021
19_date_acq_dev_began: 11/1/2021
20_date_implemented: 12/1/2021
22_dev_method: Developed with contracting resources.
23_contract_piids: Shared Service through DHS CISA's CDM Program
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
33_agency_data: Not applicable. The Crowdstrike tool is a commercial-off-the-shelf platform, which is provided to USTDA by the Continuous Diagnostic and Mitigation Program under the Department of Homeland Security, Cybersecurity and Infrastructure Security Agency. The platform is one of several DHS/CISA services contracted by USTDA for security.
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: Crowdstrike (FEDRAMP) PK ID FR1807853629
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Other
43_question_type: Shared Service DD Form 1149
45_compute_request: No
47_timely_resources: Yes
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
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.
2_use_case_name: Exiger Due Diligence IQ (“DDIQ”) Research Software
3_agency: United States Trade and Development Agency
3_abr: USTDA
8_topic_area: Mission-Enabling
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: The AI utilized by Exiger’s team of analysts improves the efficiency of their research efforts into individuals and companies under consideration for partnership with USTDA by reviewing and consolidating relevant publicly available information, such as news reports.
12_outputs: Exiger’s DDIQ platform produces consolidated publicly available data on searched subjects for review, refinement, and analysis by Exiger’s due diligence and research professionals.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 2/24/2024
19_date_acq_dev_began: 3/1/2024
20_date_implemented: 5/1/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 1131PL24CCP91094 
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
33_agency_data: Not applicable. The DDIQ software is a proprietary product developed by Exiger as a commercial-off-the-shelf platform, which is available to purchase by anyone in the general public and has not been modified for government use. The DDIQ platform is one of several Exiger services contracted by USTDA for due diligence.
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: Yes
41_system_name: Exiger Insight 3PM (FEDRAMP) PK ID FR2122140784
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Yes
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
50_internal_review: No documentation is available: No documentation detailing model performance metrics, model architecture, features and intended use of the models have been created or are currently accessible to other data science teams within the agency.
2_use_case_name: Evolv WDS - OSSO
3_agency: Department of Veterans Affairs
3_abr: VA
4_bureau: VHA: Veterans Health Administration
8_topic_area: Law & Justice
10_commercial_ai: Creating visual representations of data sets for reports and presentations using AI.
11_purpose_benefits: Using heat map technology to identify heat signature of known weapons.
12_outputs: Areas of interest for a heat map that include objects that would produce heat indicators aligned with heat signatures of known types of different weapons.
16_dev_stage: Operation and Maintenance
17_impact_type: Both
18_date_initiated: 10/1/2022
19_date_acq_dev_began: 11/1/2022
20_date_implemented: 2/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 36C25023P0332 
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: No
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Other
45_compute_request: Other
47_timely_resources: Other
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
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: Yes – Agency requested an extension for this use case.
2_use_case_name: VA Chat Copilot Meta Pilot
3_agency: Department of Veterans Affairs
3_abr: VA
4_bureau: OIT: Office of Information & Technology
8_topic_area: Mission-Enabling (internal agency support)
10_commercial_ai: Improving the quality of written communications using AI tools.
11_purpose_benefits: Administrative efficiency for VA employees 
12_outputs: Chat Copilot is a generative AI interface that allows users to upload documents and query the tool about those documents. Outputs can include draft emails, draft communications, document summaries, draft project templates, responses to questions about content of documents, etc.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 12/1/2023
19_date_acq_dev_began: 1/31/2024
2_use_case_name: Avigilon Camera/Search Function - OSSO
3_agency: Department of Veterans Affairs
3_abr: VA
4_bureau: VHA: Veterans Health Administration
8_topic_area: Law & Justice
10_commercial_ai: Searching for information using AI.
11_purpose_benefits: A search function in a security video surveillance system that search's for points of interest in the video.
12_outputs: Video or picture of requested searches from the video surveillance systems.
16_dev_stage: Operation and Maintenance
17_impact_type: Both
18_date_initiated: 3/1/2022
19_date_acq_dev_began: 8/1/2022
20_date_implemented: 10/1/2022
22_dev_method: Developed with contracting resources.
24_hisp_support: No
27_public_info: No
29_contains_pii: Yes
30_saop_review: No
31_data_catalog: Yes
34_data_docs: Documentation is missing or not available: No documentation exists regarding maintenance, composition, quality, or intended use of the training and evaluation data.
37_custom_code: No
38_code_access: No – agency does not have access to source code.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: Other
45_compute_request: Other
47_timely_resources: Other
49_existing_reuse: None: This use case does not re-use any internally developed tooling or managed infrastructure from any other AI development efforts within the agency.
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: Yes – Agency requested an extension for this use case.