GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: Intelligent forecasting for COVID-19 vaccines (Mali)
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Global Health
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Optimizing health supply chains to reduce costs and improve quality of care by avoiding stock-outs.
12_outputs: Supply chain predictions
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 9/1/2022
19_date_acq_dev_began: 10/1/2022
20_date_implemented: 5/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA20CA00009
24_hisp_support: No
27_public_info: No
29_contains_pii: No
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: Yes
38_code_access: No – agency does not have access to source code.
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No relevant resources
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: Intelligent forecasting for TB products (Indonesia)
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Global Health
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Optimizing health supply chains to reduce costs and improve quality of care by avoiding stock-outs.
12_outputs: Supply chain predictions
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 8/1/2022
19_date_acq_dev_began: 8/1/2022
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA20CA00009
24_hisp_support: No
27_public_info: No
29_contains_pii: No
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: Yes
38_code_access: No – agency does not have access to source code.
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No relevant resources
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: Drip irrigation system with AI control
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for the Middle East
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: GEAR Center's  smart irrigation system uses artificial intelligence to predict local weather, enabling the system to optimize water and energy use. This caters specifically to the unique challenges faced by smallholder farmers in water-stressed regions. By predicting solar exposure and tailoring irrigation needs for individual locations, this technology improves agricultural efficiency, addressing critical issues of soil degradation and water scarcity in regions that can most benefit from these gains.
12_outputs: The AI system outputs a hyper-local weather prediction for the next 24 hours based on historical data and inputs from local weather sensors.
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 7/1/2019
19_date_acq_dev_began: 9/1/2019
20_date_implemented: 9/1/2022
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA21C00056
24_hisp_support: No
27_public_info: No
29_contains_pii: No
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: Yes
38_code_access: No – agency does not have access to source code.
40_has_ato: No
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No relevant resources
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: Streamlining recruitment with AI-powered online testing
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Democratic Republic of the Congo
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: TestGorilla is a pre-employment testing platform that enables companies to assess candidates' skills and aptitudes through a variety of tests, including cognitive ability, programming, software proficiency, personality, and culture fit assessments. By focusing on objective skills evaluations, TestGorilla aims to reduce reliance on traditional resumes, thereby minimizing biases and enhancing the efficiency of the hiring process.
12_outputs: Candidate scores and rankings
16_dev_stage: Initiated
17_impact_type: Rights-Impacting

18_date_initiated: 10/1/2024
2_use_case_name: Qualitative Analysis of Countering Violent Extremism (CVE) Community Perception Data
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Kenya and East Africa
8_topic_area: Diplomacy & Trade
10_commercial_ai: Creating visually appealing presentations using AI-driven design suggestions.
11_purpose_benefits: AI-assisted coding of long-form survey responses
12_outputs: Text classification
16_dev_stage: Retired
17_impact_type: Neither
21_date_retired: 11/1/2024
24_hisp_support: No
2_use_case_name: AI-based translation for key Global Health documents
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Global Health
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: USAID has missions in over 80 countries and programs in more than 100. THis means that there are likely hundreds if not thousands of languages spoken in the countries USAID supports. Translating key health documents and information into all the languages spoken where USAID has programming can be time consuming and expensive. The purpose of this use case is to see if we can make translation cheaper, faster, and eaiser so that more key USAID global health documents are available to partners and populations where we work. Note: no sensitive information is used in this use case.
12_outputs: Two word documents are produced for each translation, one containing just the translated material and one containing a translation report, highlighting any word choice differences or potential inconsistencies.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 7/1/2024
19_date_acq_dev_began: 7/1/2024
22_dev_method: Developed in-house.
24_hisp_support: 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.
40_has_ato: No
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No relevant resources
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: Retrieval-augmented generation for government-to-government due diligence
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Inclusive Growth, Partnerships, and Innovation
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Government-to-government (G2G) agreements provide a more efficient way for USAID to program funds, but require careful assessment of a partner country's fiscal management and budgetary systems. This application is using AI tools to expedite the initial desk review phase of the G2G Country Context Report by querying a set of authoritative documents with a standardized list of due-diligence questions.
12_outputs: Excel spreadsheet containing columns for questions, answers, and source citations.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 2/27/2024
19_date_acq_dev_began: 7/11/2024
22_dev_method: Developed in-house.
24_hisp_support: No
31_data_catalog: Yes
33_agency_data: Completed country context report workbooks from previous G2G assessments were used to benchmark the reliability of the vector search.
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.
40_has_ato: No
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No relevant resources
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: ESDB/IDEA Series Classification
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Reduce labor hours involved in classifying new economic and social data indicators to categories in the ESDB/IDEA system by providing automatically suggested categories to data curation staff.
12_outputs: Suggested category assigments for social and economic indicator series.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 5/2/2024
40_has_ato: No
2_use_case_name: CDR Document Data Improvement with AI
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Enable improvement of data quality and coverage not acheivable without AI automation given current staffing resources: (1) Filling gaps in summary data, (2) Adding audio/video transcripts (with summaries) (3) Adding descriptions to images. These data improvements will benefit overall user experience, quality of search results, and accessibility.
12_outputs: (1) Text transcripts for video and audio files (2) Text summaries of documents, video files, and audio files (3) Text descriptions of images
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 5/24/2024
2_use_case_name: Evaluation Registry Abstracts Generator
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Automate the generation of USAID evaluation report abstracts for the Evaluation Registry Dashboard based on existing fields in survey data. This automation will streamline the process, reducing recurring labor hours for manually creating the abstract content.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 3/21/2024
2_use_case_name: FADB QA Support Automation
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Reduce data QA and curation level of effort by automating "first-pass" of following: 
 
(1) Classification of activities by DAC purpose code
(2) Identification of countries and regions present in activity descriptions
12_outputs: (1) Suggested DAC purpose codes for a list for activities (2) Suggested countries and regions for activities
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 6/11/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 72MC1024M00002
2_use_case_name: TOSSD Data Curation Automation
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Reduce data curation level of effort by automating "first-pass" of:

(1) Classifcation of activities as "R&D" 
(2) Classifcation of activities as "Aligned with International Public Good Definitions"
(3) Scoring of activity benefit to TOSSD recipients
(4) Scoring of activity compliance with TOSSD guidance
(5) Classification of activity to applicable Sustainable Development Goals (SDGs)
12_outputs: (1) Suggested activity category classifications (2) Suggested scoring of activity for assessed benefit and compliance
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 6/7/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 72MC1024M00002
2_use_case_name: BHA/DMEAL: Application Review Processes Automation
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Use AI/ML algorithms to perform automated "first-pass" reviews and trends analysis of partner-submitted RFSA applications for reduction of burden on BHA staff.
12_outputs: (1) M&E Plan Review Support: flag missing components of the M&E Plan Narrative (e.g. section headers, required detail, etc.) and create summaries of the M&E Plan Narrative sections.
(2) RFSA Application Review Support:  flag missing components, providing initial scoring of requirements compliance, identifying issues for inclusion in issues letters, summarizing application sections for reviewers, utilizing predictive analytics for objective feasibility and impact assessments, and incorporating data visualization tools to facilitate transparent decision-making.
(3) RFSA Solicitation Issues Letters Analysis: use data from Issues Letters and other data sources to identify trends and issues in the solicitation and application review process for past and future Resilience and Food Security Activities (RFSAs). 
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 9/6/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 72MC1024M00002
2_use_case_name: BHA/DDAIM: Decision Support via CHOPP
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: (1)  Implement "Ask CHOPP" Feature: Introduce on-demand Gen AI insights with narrative and graphic outputs.
(2) Enhance Emergency Application Processing: Improve processes per PLRP requirements to ensure applications meet USAID/BHA guidelines, include all required annexes, and propose activities aligned with humanitarian needs and standards.
(3) Improve BHA Situational Awareness: Analyze needs and programming trends over time through enhanced proposal processing.
(4) Enrich Contextual Awareness: Blend BHA application needs data with other data sources for a richer understanding of humanitarian contexts.
(5) Generate Comprehensive Reports: Produce situation reports and narrative summaries from structured and unstructured data for internal and external reporting, briefings, and historical analyses.
12_outputs: (1) Responses to user inquiries in "Ask CHOPP" chat agent
(2) Required component inventories and guidance compliance scores.
(3) Historical trend analyses for programming trends
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 9/13/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 72MC1024M00002
2_use_case_name: GenDev Key Issue Narrative Generation
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: A series of AI use cases focused on processing, validating, and summarizing PPR narratives from Facts Info, particularly related to USAID's Gender Development (GenDev) sector. The use cases include:

(1) Parsing Narratives by Implementing Mechanism (IM): Extract IM names and corresponding numbers from PPR narratives, and cross-reference them with data reported on operational plan attributions for each IM and Key Issue pulled from the Key Issue Attributions Report on Facts Info.

(2) Reviewing and Validating Narratives: Review the PPR narratives against predefined criteria to ensure they meet reporting requirements. This involves flagging whether certain criteria are present, such as correct reporting of IM numbers, description of interventions, and key results.

(3) Synthesizing Narrative Review Notes: Synthesize review notes generated by Data Services after the previous use case into concise summaries that are under 500 characters for easy integration into official reports.

(4) Keyword-Based Summarization: Combine narratives flagged with similar keywords into harmonized summaries, creating comprehensive narratives on specific themes or issues.
12_outputs: (1) List of extracted IM names and numbers
(2) List of binary values for criteria compliance fields
(3) Summary of narrative review notes. 
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 4/17/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 72MC1024M00002
2_use_case_name: USAID CDM-XDR (Extended Detection and Response)
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Management
8_topic_area: Mission-Enabling
10_commercial_ai: Identifying unusual patterns in system logs from a single incident report using AI.
11_purpose_benefits: Cybersecurity threat detection, threat hunting, and threat response tools to pinpoint vulnerabilities and bolster the security of the Agency's information technology (IT) infrastructure.
12_outputs: Software agents forward security telemetry data to the USAID proxy which directs it to the cloud-based management console, which provides a centralized view and control plane for USAID security analysts.
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 5/1/2024
22_dev_method: Developed with contracting resources.
2_use_case_name: Boomitra: Accelerating soil carbon removal on a planetary scale.
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Boomitra: Accelerating soil carbon removal on a planetary scale. Utilizes satellites and AI to measure soil moisture, nutrients and carbon. Boomitra aids farmers in reducing water and nutrient use by 30 percent while enhancing soil fertility. Funded through WFP Innovation Accelerator
12_outputs: Reports, visualizations
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 4/30/2024
19_date_acq_dev_began: 4/30/2024
20_date_implemented: 4/30/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA24IO00037
24_hisp_support: No
27_public_info: No
29_contains_pii: No
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: Yes
38_code_access: No – agency does not have access to source code.
40_has_ato: No
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No resources provisioned by USAID
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: DARTS: Accurate, accountable cash transfer data and reconciliation
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: DARTS: A web app that uses advanced machine learning to enable WFP country offices to ensure accurate, accountable cash transfer data and reconciliation. DARTS (Data Assurance and Reconciliation Tool Simplified) is a user-friendly web app. It enables WFP to implement controls on large cash transfer data and generate reconciliation reports, which is vital in cash assistance programs. This ensures accountability, evaluating efficiency, building trust and ensuring accurate fund distribution. Funded through WFP Innovation Accelerator
12_outputs: Web app interface
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 4/30/2024
19_date_acq_dev_began: 4/30/2024
20_date_implemented: 4/30/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA24IO00037
24_hisp_support: No
27_public_info: No
29_contains_pii: No
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: Yes
38_code_access: No – agency does not have access to source code.
40_has_ato: No
43_infra_provisioned: No
45_compute_request: No
47_timely_resources: Other
47_question_type: No resources provisioned by USAID
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.