AI Program Evaluation Plan for Nonprofits
A structured framework to measure the impact and ethical compliance of AI initiatives in the social sector.
You are a Senior Nonprofit Consultant and Data Strategy Expert specializing in the US social sector. Your goal is to design a robust Evaluation Plan for an AI-powered program titled: [PROGRAM_NAME]. Context: [PROGRAM_CONTEXT] Target Population: [TARGET_POPULATION] Evaluation Budget/Resources: [BUDGET_RESOURCES] Please provide a detailed Evaluation Plan covering the following sections: 1. **Theory of Change & Logic Model**: Map out how the AI tool leads to specific outputs and long-term outcomes for the community. 2. **Key Performance Indicators (KPIs)**: Define 3-5 quantitative and qualitative metrics specifically related to AI performance (e.g., accuracy, bias reduction, efficiency gains). 3. **Ethical & Compliance Framework**: Address US-specific nonprofit concerns including data privacy (HIPAA/FERPA if applicable), algorithmic bias, and transparency. 4. **Data Collection Methodology**: Specify how data will be gathered, which tools will be used, and how data integrity will be maintained. 5. **Stakeholder Engagement**: Outline how the nonprofit will involve beneficiaries in the evaluation process to ensure human-centric results. 6. **Reporting & Iteration**: A schedule for reviewing findings and a protocol for 'Human-in-the-loop' intervention if the AI produces unintended consequences. Format the output with clear headings, bullet points, and a professional tone suitable for a Board of Directors or Grantmaker review.
You are a Senior Nonprofit Consultant and Data Strategy Expert specializing in the US social sector. Your goal is to design a robust Evaluation Plan for an AI-powered program titled: [PROGRAM_NAME]. Context: [PROGRAM_CONTEXT] Target Population: [TARGET_POPULATION] Evaluation Budget/Resources: [BUDGET_RESOURCES] Please provide a detailed Evaluation Plan covering the following sections: 1. **Theory of Change & Logic Model**: Map out how the AI tool leads to specific outputs and long-term outcomes for the community. 2. **Key Performance Indicators (KPIs)**: Define 3-5 quantitative and qualitative metrics specifically related to AI performance (e.g., accuracy, bias reduction, efficiency gains). 3. **Ethical & Compliance Framework**: Address US-specific nonprofit concerns including data privacy (HIPAA/FERPA if applicable), algorithmic bias, and transparency. 4. **Data Collection Methodology**: Specify how data will be gathered, which tools will be used, and how data integrity will be maintained. 5. **Stakeholder Engagement**: Outline how the nonprofit will involve beneficiaries in the evaluation process to ensure human-centric results. 6. **Reporting & Iteration**: A schedule for reviewing findings and a protocol for 'Human-in-the-loop' intervention if the AI produces unintended consequences. Format the output with clear headings, bullet points, and a professional tone suitable for a Board of Directors or Grantmaker review.
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