GreatNorthCollective/greatnorth-us-federal-ai-inventory-2024 huggingface dataset:
2_use_case_name: FarmerChart
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Nigeria
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: FarmerChart is an AI-powered application that provides agricultural advisory services inclduing weather prediction to smallholder farmers.  This platform is accessible via android phones in two major Nigerian languages (Hausa and Yoruba). The system integrates real-time weather data and climate predictions to build farmers resilience against cimate change impacts.
12_outputs: The telephone-based technology allows small holder farmrs access to extension services and information about market trends to impact them mitigate the impact of climate change.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 4/18/2023
19_date_acq_dev_began: 4/18/2023
20_date_implemented: 5/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 72062020C00001
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: Automated due diligence for corruption risks
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Democracy, Human Rights, and Governance
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: This platform will process and standardize data from published reports and make it publicly available on a screening platform. Compliance teams at financial institutions and corporations around the world will be able to screen their customers, transactions, and supply chains against the NGO data in the same way that they already screen sanctions and other watchlists.
12_outputs: Reports, visualizations
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 11/1/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200-AA-21D-00024
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: AI-powered portal for the Development Experience Clearinghouse
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Conflict Prevention and Stabilization
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Making information in the Development Experience Clearinghouse easier to access and use
12_outputs: Excel tables that feed into a Tableau dashboard with tables and other visualizations.
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 8/1/2023
19_date_acq_dev_began: 9/1/2023
20_date_implemented: 1/1/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA20D00013
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: Yes
33_agency_data: Documents from the Development Experience Clearinghouse
34_data_docs: Documentation is complete: Documentation exists regarding the maintenance, composition, quality, and intended use of the training and evaluation data, as well as any statistical bias across model features and protected groups. 
37_custom_code: Yes
38_code_access: Yes – agency has access to source code, but it is not public.
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: 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: Documentation has been developed: Complete documentation detailing model performance across a range of benchmarks, architecture, relevant features and information regarding the appropriate use of the model for predictive tasks has been created.
2_use_case_name: ARTS - Automated Indirect Cost and Tracking System
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. Increased Efficiency and Productivity
24/7 Availability: Chatbots can operate continuously, providing support to IPs outside traditional business hours with troubleshooting, FAQs, and routine requests.
Rapid Responses: Chatbots can process and respond to IP inquiries immediately providing improved support to IPs around the globe
Automation of Repetitive Tasks: AI can handle routine questions, document creation, and workflows, freeing up valuable time for CAS and IP personnel.
2. Enhanced User Experience/Time Savings. Generative AI can tailor trend analysis for indirect rates improving engagement with IPs and reduce the time needed to issue negotiated indirect cost rate agreements.
3. Improved Decision-Making. The CAS Division will use AI to receive data-driven Insights. AI can summarize large datasets of indirect cost rate information to extract insights. Generative AI will synthesize information from the IPs helping negotiators to make informed decisions regarding indirect rate negotiations. AI models for indirect cost rates can predict outcomes and forecast rates based on data provided by USAID IPs. 
12_outputs: Chatbot, Generative AI for trend analysis reports, Indirect Cost Rate Predictions 
16_dev_stage: Initiated
17_impact_type: Neither
18_date_initiated: 10/1/2023
23_contract_piids: 47QTCA20D005E / Order # 72MC1023M00003), USAID CIO Enterprise Customer Relationship Management (ECRM) contract
2_use_case_name: Crop pest identification and advisory
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Resilience, Environment, and Food Security
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: To more efficiently and precisely identify crop diseases and provide tailored recommendations on how to control the pest or disease
12_outputs: The AI system generates tailored plant health advisory in the form of text in local languages
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 7/12/1905
19_date_acq_dev_began: 7/12/1905
20_date_implemented: 7/15/1905
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA21LE00005
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: AI-enabled agricultural logistics in Mozambique
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Resilience, Environment, and Food Security
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Appload is improving accessibility to logistics services for small agricultural aggregators and small transporters in Nampula and Zambezi provinces and the Beira Corridor via Appload's digital marketplace. Through the partnership, Appload will reach 1,588 shippers and 740 small transporters, facilitating the movement of over $675,000 in cargo through 860 unique trips on the platform. Additionally, in partnership with Hollard Insurance, the company is subsidizing goods in transit insurance for all shippers using the app.
12_outputs: App interface, supply chain predictions
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 10/15/2023
19_date_acq_dev_began: 10/14/2025
20_date_implemented: 10/30/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA20C00054
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: Using AI to detect information manipulation
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Democracy, Human Rights, and Governance
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: To detect narratives and trends in social media alterations of images and video in order to identify information manipulation.
12_outputs: Reports, visualizations
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 12/1/2020
19_date_acq_dev_began: 12/1/2020
20_date_implemented: 7/1/2023
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA18CA00059
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: HelloTask: multichannel job platform for blue-collar workers
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Bureau for Asia
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Under the Market Systems & Partnerships mechanism, USAID/Asia is supporting a partnership with HelloTask, a multichannel job platform for blue-collar workers that connects clients to care service providers (e.g., cooking, cleaning, laundry) via a smartphone application. As part of this activity, USAID is providing funding to support the development of an AI-based interactive voice response (IVR) technology that allows users to speak into their phones to interact with the job placement functions of the app.
12_outputs: The telephone-based IVR technology will allow lower-income users to better interface with the online technology platform to accept jobs and provide feedback. Users often do not have smartphones, but instead feature phones that have limited capability to support more sophisticated mobile apps often used by gig workers in other countries. The IVR system currently allows domestic workers to speak directly into their featurephones with the message being transcribed into the online tracking system. The next phase is to allow domestic workers to verbally accept and decline jobs, file feedback, and otherwise interact with the company in a way that is similar to other apps with gig employment.
16_dev_stage: Acquisition and/or Development
17_impact_type: Neither
18_date_initiated: 8/1/2023
19_date_acq_dev_began: 3/1/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 7200AA20C00054
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: Georgian speech-to-text transcription
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Georgia
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: The purpose of the tool is to transcribe spoken speech via automatic speech recognition (ASR). The expected benefit, based on use-cases, is to help users transcribe large amounts of audio data into text with enterprise accuracy and in a short amount of time.
12_outputs: Text (spoken audio content)
16_dev_stage: Operation and Maintenance
17_impact_type: Neither
18_date_initiated: 9/22/2020
19_date_acq_dev_began: 10/1/2021
20_date_implemented: 12/30/2022
22_dev_method: Developed with contracting resources.
23_contract_piids: 72011420CA00002
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: No
31_data_catalog: Other
31_question_type: Program collected and labeled the dataset for purpose of training the system to learn to transcribe the speech in Georgian language; repository not currently maintained
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
42_dev_tools_wait: Less than 6 months
43_infra_provisioned: No
45_compute_request: Other
45_question_type: Our partner organization has in-house computing resources for model training and development
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: 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: Skhivi: AI tools for Georgian journalists
3_agency: United States Agency for International Development
3_abr: USAID
4_bureau: USAID/Georgia
8_topic_area: Diplomacy & Trade
10_commercial_ai: None of the above.
11_purpose_benefits: Skhivi is designed for journalists, news editors, and media researchers and offers a news aggregator, trend analysis, a news distribution timeline across various media outlets, polarization metrics, and a temperature index. The team is now accepting subscription requests for more advanced features, and the tool is already being used by local Georgian media outlets like Tabula and Aprili.
12_outputs: Online dashboard with visualizations and reports
16_dev_stage: Implementation and Assessment
17_impact_type: Neither
18_date_initiated: 8/1/2022
19_date_acq_dev_began: 4/1/2024
20_date_implemented: 6/9/2024
22_dev_method: Developed with contracting resources.
23_contract_piids: 72011422CA00004
24_hisp_support: No
27_public_info: No
29_contains_pii: No
30_saop_review: 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: 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 Family Planning products (Cote d'Ivoire)
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: 7/12/1905
19_date_acq_dev_began: 7/13/1905
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 Malaria products (Cote d'Ivoire)
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: 7/12/1905
19_date_acq_dev_began: 7/14/1905
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 Routine Vaccines (Serbia)
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: 7/15/1905
19_date_acq_dev_began: 4/1/2024
20_date_implemented: 8/1/2024
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.