Gender And Artificial Intelligence Challenge

CATEGORY A - Possible IDB Lab funding

Phase I - Preselection

Upon completing the application on the online platform, a technical team of the IDB Group and the allies for the Challenge will review, analyze, and pre-select the received applications, based on the best scores obtained through the assessment on the online platform.

During this preselection phase, the proposals obtaining the highest score will receive an invitation to carry out an AI ethical self-assessment (based on the self-assessment guide developed by fAIr LAC) through an interactive web application. The result of the AI ethics self-assessment will be a relevant input for the selection Phase through a pitch day.

During this preselection Phase, the best proposals will be asked to participate in a two-week boot camp to prepare for the pitch day to be presented during the selection Phase, as described below.

Phase II - Selection

The pitch day shall assess the suitability of the solution to address gender gaps, as well as the innovation and robustness of the proposed technology (with emphasis on an ethical AI perspective), and the potential for scalability. The selected entities will move on to Phase III and may participate in special and strengthening activities organized by IDB Lab and allies of the Challenge to apply for IDB Lab funding.

Phase III - Operations Design

IDB Lab will select applications according to the evaluation criteria of the Challenge. The selected applications will be announced according to the schedule established later in these guidelines.

After the best way to implement the model has been evaluated, IDB Lab will provide support to the selected applicants to initiate their project design (including the development of a project plan and other documents necessary to request IDB Lab's official internal approval). This process may last up to six months, depending on the maturity of the proposed model and the implementation capacity of the selected applicants.

*Please note that final approval is subject to IDB Lab's internal procedures on the understanding that for a project to be selected for funding, it must be approved by all persons directly involved in IDB Lab approval process. Likewise, a legal agreement shall be signed to establish how funding and counterpart resources will be used to implement the model.

CATEGORY B - Honorable Mention

Phase I - Preselection

Upon completing the application on the online platform, a technical team of the IDB Group and the allies for the Challenge will review, analyze, and pre-select the applications received, based on the best scores obtained through the assessment on the online platform.

During this preselection stage, the best proposals will be invited to carry out an AI ethics self-assessment process based on the self-assessment guide developed by fAIr LAC, and access to its interactive tool will be provided. The result of the AI ethical self-assessment would be considered as necessary input to move towards the second selection phase, which will be held through a pitch day.

During this preselection Phase, the best proposals will be invited to participate in a two-week boot camp to prepare the pitch that they will present during the selection Phase, as described below.

Phase II - Selection

The pitch day will assess the suitability of the solution to address gender gaps, the innovation and robustness of the proposed technology (with emphasis on an ethical AI perspective), as well as the potential for scalability. The selected entities will be granted an honorable mention and will be able to participate in special and strengthening activities organized by IDB Lab and the allies for the Challenge.

CATEGORY A 

• Innovation: Level of innovation of the business model, use of AI to address gender gaps, and recognition of the ethical challenges of the developed technological system.  

• Social and economic impact: Particular attention will be paid to models aimed at benefiting marginalized communities, particularly low-income and vulnerable populations, with a feasible and reasonable approach using AI. 

• Feasibility: Feasibility of execution, including the definition of potential risks that may affect successful implementation and mitigation actions to address these risks during implementation. 

• Sustainability: Financial plan and/or potential for sustainable growth over the next 3-5 years after funding (income generation model) and ability to generate income for applicants of reimbursable funding. Potential for scaling up, growth, or replication of the proposed business model in the country where the project will be implemented. 

• Technical development and use of AI/ML: Those projects having a successful implementation of a minimum viable prototype/product (MVP) will be considered. Besides, the technical capacity of the applicant's team and strategic partners will be considered.  

• AI Ethics Self-Assessment: Recognizes the challenges/depth of the problem being addressed. 

CATEGORY B 

• Innovation: Level of innovation of the business model, use of AI to address gender gaps, and recognition of the ethical challenges of the developed technological system.  

• Social and economic impact: Particular attention will be paid to models aimed at benefiting marginalized communities, particularly low-income and vulnerable populations, with a feasible and reasonable approach using AI. Feasibility: Feasibility of execution, including the definition of potential risks that may affect successful implementation and mitigation actions to address these risks during implementation. 

• Technical development and use of AI/ML: Those projects having a successful implementation of a minimum viable prototype/product (MVP) will be considered. Besides, the technical capacity of the applicant's team and strategic partners will be evaluated. 

• AI Ethics Self-Assessment: Recognizes the challenges/depth of the problem being addressed.