GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: Media synthesis for food security
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: The FEWS NET Data, Learning and Communications Hub is implementing a dashboard application developed by the International Center for Tropical Agriculture (CIAT) that uses natural language processing (NLP) and machine learning to identify to report on relevant topics is both social media (currently Telegram) and formal media (using MedlaCloud) in relevant countries. The media content is evaluated for relvance using a comprehensive taxonomy covering drivers of food insecurity.
12_outputs: Reports, visualizations
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 10/1/2024
19_date_acq_dev_began: 10/1/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA24F00008
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: AI translation of water, sanitation, and hygiene learning materials
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: BHA WASH-funded partner CAWST uses AI for translation of online WASH learning materials.
12_outputs: Reports 
16_dev_stage: Initiated
18_date_initiated: 10/1/2024
2_use_case_name: Labeling and classifying food security activities
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Through a buy-in to IPI's Technical Assistance Project for Economic Growth (TAP-EG) award, ALT funded a third Food Assistance and Food Security Assessment (FAFSA-3), which included AI and machine learning models to discover and label each occurence of three project-specific approaches within 3,000 BHA files from resilience food security activities (since 2015) against a taxonomy developed within this project. 
12_outputs: Project classifications
16_dev_stage: Retired
17_impact_type: Neither
18_date_initiated: 5/1/2023
19_date_acq_dev_began: 6/25/2023
20_date_implemented: 4/1/2024
21_date_retired: 6/24/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 47QRAD20DD1072 (TO - 7200AAN00006)
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: SOPHIA: Solutions Platform for Humanitarian analysis
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: Searching for information using AI.
11_purpose_benefits: ACAPS, part of the Norwegian Refugee Council (NRC), is a humanitarian information provider that has developed a tool called the Solutions Platform for Humanitarian Analysis (SOPHIA), which uses NLP to filter through hundreds of humanitarian data sources in more than 70 languages, highlighting where to find specific indicators upon request by a user.
12_outputs: Report excerpts
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 1/18/2023
19_date_acq_dev_began: 9/26/2023
20_date_implemented: 5/30/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23CA00034
24_hisp_support: No
2_use_case_name: DEEP: Data Entry and Exploration Platform
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Mission-Enabling
10_commercial_ai: Summarizing the key points of a lengthy report using AI.
11_purpose_benefits: The Data Entry and Exploration Platform (DEEP), an online platform for storing, sharing, and analyzing humanitarian data, especially unstructured and qualitative data. This includes an AI component of the platform that uses NLP to filter, annotate, and categorize content much faster than a human can. This “tagging” feature is offered to the humanitarian community at large, decreasing the time and effort required to summarize data for decision-makers.
12_outputs: Reports, visualizations
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/8/2020
19_date_acq_dev_began: 10/1/2021
20_date_implemented: 4/1/2022
22_dev_method: Developed with contracting resources.
23_contract_piids: 720FDA20CA00076
24_hisp_support: No
2_use_case_name: AI for humanitarian logistics
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Emergency Management
10_commercial_ai: None of the above.
11_purpose_benefits: Handicap International: Uses AI to create an operational decision support tool based on the automatic analysis of field data. This tool will enable aid providers to develop optimized strategies in the Cabo Delgado and Nampula regions. Models a logistical environment (warehouses, airports, hospitals, schools, etc.) through their interactions, thus forming a complex network. Enables a better understanding of the complex interactions between all the network's constituents. Funded through Humanitarian Grand Challenge
12_outputs: Reports, visualizations
16_dev_stage: Retired
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 9/24/2024
21_date_retired: 12/4/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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: SMARTplus: digital system for fast, reliable malnutrition data tackling the health-crisis in Somalia
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Health & Medical
10_commercial_ai: None of the above.
11_purpose_benefits: SMARTplus: digital system for fast, reliable malnutrition data tackling the health-crisis in Somalia, Action Against Hunger ACF (Canada): SMARTplus uses 3D scans to streamline nutrition and mortality data collection. It analyzes and verifies data, aggregating it for visualization on a public dashboard. This prevents delays and reliance on potentially false information. Funded through Humanitarian Grand Challenge
12_outputs: Reports, visualizations
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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.
35_demo_features: age, gender
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: HOPE and HELP: Modeling for complex humanitarian engagement
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Emergency Management
10_commercial_ai: None of the above.
11_purpose_benefits: HOPE and HELP: Modeling for complex humanitarian engagement, Humanity Data Systems: HOPE and HELP, created by Lensinsight and AllSource Analytics, use advanced technology like Machine Learning and Complex Event Processing to simplify gathering community feedback in humanitarian efforts. They also aid in project and stakeholder management. Funded through Humanitarian Grand Challenge
12_outputs: Reports, visualizations
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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: Advanced language technology in marginalized languages for efficient information gathering
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Mission-Enabling
10_commercial_ai: None of the above.
11_purpose_benefits: Language technology to improve data quality and engagement, Translators without Borders US Inc. aims to create advanced language technology in marginalized languages for efficient information gathering.This pioneering effort could revolutionize understanding of humanitarian needs and priorities in remote regions. Funded through Humanitarian Grand Challenge
12_outputs: App interface
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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: Camp forecast: AI-driven supply chain forecasting to reach 7% more refugees without spending more
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: Camp forecast: AI-driven supply chain forecasting to reach 7% more refugees without spending more. The "Camp Forecast" (CF) tool employs AI for camp managers to make precise demand forecasts, potentially saving 7% of operational costs. It predicts resident numbers and required supplies in humanitarian camps, pioneering AI-driven forecasting in this context. Funded through Humanitarian Grand Challenge
12_outputs: Reports, visualizations
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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: Humanitarian language toolkit: AI-enabled qualitative engagement with conflict populations
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: Humanitarian language toolkit: AI-enabled qualitative engagement with conflict populations, Kobo, Inc.: This project aims to create a toolkit using NLP to record, transcribe, and translate qualitative interviews in humanitarian settings. Field workers can use standard data collection platforms for automatic recording and correction of transcriptions and translations. Funded through Humanitarian Grand Challenge
12_outputs: Text 
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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: Chatbot photo diagnosis for malnutrition
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Health & Medical
10_commercial_ai: None of the above.
11_purpose_benefits: Smart and effective communication in nutrition; "Chatbot photo diagnosis platform", Fundación Acción Contra el Hambre (Spain): This project establishes a smart communication channel for effective malnutrition diagnosis and monitoring, a joint effort between the World Food Programme (WFP) and Action Against Hunger (ACF). Funded through Humanitarian Grand Challenge
12_outputs: Chatbot interface
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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.
35_demo_features: age, gender
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: PathVis: A water monitoring device for Vibrio cholerae detection
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: PathVis: A water monitoring device for Vibrio cholerae detection, OmniVis Inc: A groundbreaking smartphone diagnostic tool for rapid V. cholerae detection, providing results in under 30 minutes. Data is instantly sent to a cloud-based server for automated logging. In remote areas, a wifi hotspot enables data upload.This is the first water-based V. cholerae detection device, offering automated, time-stamped, and location-specific data logging. Funded through Humanitarian Grand Challenge
12_outputs: Prediction of V. Cholerae contamination
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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: NeedsBot - Aggregating real-time needs from anywhere via chatbot
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Humanitarian Assistance
8_topic_area: Emergency Management
10_commercial_ai: None of the above.
11_purpose_benefits: NeedsBot - Aggregating real-time needs from anywhere via chatbot, Needslist: NeedsBot enables vetted frontline responders to text urgent information, supply, and resource needs into the NeedsList platform.This data is then securely aggregated and accessible to multiple stakeholders, facilitating real-time response from individuals, corporations, and governments in the humanitarian aid sector. Funded through Humanitarian Grand Challenge
12_outputs: Reports, visualizations
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 6/26/2023
19_date_acq_dev_began: 3/14/2024
20_date_implemented: 3/14/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 720BHA23GR00104
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.