AI Evaluation Framework for Development
Comprehensive framework for evaluating AI systems across the entire lifecycle—from design to scale-up. Ensure your AI solutions are ethical, effective, safe, and context-appropriate for development programs, humanitarian work, and social impact initiatives.
Evaluation Progress
Your AI Evaluation Results
Complete the Evaluation
Please complete all dimensions of the evaluation to view your comprehensive AI system assessment results and recommendations.
AI Evaluation Resources
Explore comprehensive resources to enhance your AI evaluation capabilities and stay updated with best practices in responsible AI for development contexts.
🎓 EvalCommunity Academy
Access comprehensive courses on AI evaluation, monitoring, and responsible implementation in development and humanitarian contexts.
Visit Courses Archive →📚 AI Ethics Guidelines
Explore international frameworks and standards for ethical AI development and deployment in development programs.
AI Governance Frameworks →🔧 M&E Tools & Frameworks
Discover comprehensive monitoring and evaluation tools for assessing AI system performance and impact.
Visit M&E Center →🌍 Responsible AI Practice
Learn from case studies and real-world examples of responsible AI implementation in global development.
Partnership on AI →📊 Technical Performance Metrics
Access frameworks for measuring AI system accuracy, fairness, and technical robustness across populations.
The Engine Room →💬 Community Forum
Join discussions with evaluators worldwide on AI assessment challenges, solutions, and emerging practices.
Join EvalCommunity →📖 Recommended Reading
- AI Evaluation Best Practices - Comprehensive guide for evaluating AI systems in development contexts
- Technical Performance Assessment - Methods for measuring accuracy, robustness, and fairness
- Do-No-Harm in AI Systems - Frameworks for identifying and mitigating potential harms
About the AI Evaluation Framework for Development
The AI Evaluation Framework for Development provides evaluators, donors, and implementing partners with a structured approach for assessing AI solutions across the entire lifecycle—from initial design through to scale-up. This framework ensures AI systems are ethical, effective, safe, and context-appropriate for development programs, humanitarian work, and social impact initiatives.
Why Rigorous AI Evaluation Matters
As AI systems become more prevalent in development work, rigorous evaluation is essential to ensure these technologies enhance rather than undermine our mission to create positive social impact. This framework provides a systematic approach to assess whether AI solutions truly serve communities, respect human dignity, promote equity, and deliver sustainable value—while identifying and mitigating potential harms before they occur.
Eight Core Evaluation Dimensions
The framework evaluates AI systems across eight interconnected dimensions, each addressing critical questions that must be answered throughout the AI lifecycle:
1. Relevance & Problem Definition
- Real development challenge
- AI appropriateness vs alternatives
- Clear user demand
- Context suitability
2. Data Quality, Governance & Ethics
- Representative datasets
- Ethical data handling
- Privacy protection
- Bias audits
3. Technical Performance
- Accuracy and reliability
- Cross-population robustness
- Model explainability
- Performance benchmarking
4. Equity, Fairness & Do-No-Harm
- Discrimination prevention
- Vulnerable group protection
- Intersectional analysis
- Harm mitigation strategies
5. Human-Centered Design & Usability
- User needs alignment
- Accessibility features
- Trust and understanding
- Feedback mechanisms
6. Governance, Accountability & Compliance
- Clear accountability structures
- Decision-making workflows
- Audit capabilities
- Regulatory compliance
7. Monitoring & Evaluation Over Time
- Continuous performance monitoring
- Drift detection systems
- Regular evaluation intervals
- Incident reporting
8. Cost-Effectiveness & Sustainability
- Financial viability
- Local capacity building
- Long-term maintenance
- Vendor dependency risks
Application Throughout the AI Lifecycle
This framework should be applied continuously across four critical phases:
During Design
- Validate problem definition
- Assess AI appropriateness
- Conduct needs assessments
During Development
- Audit data quality and bias
- Test technical performance
- Establish governance structures
During Deployment
- Validate with end users
- Assess equity impacts
- Implement monitoring systems
During Scale-Up
- Monitor ongoing performance
- Track sustainability metrics
- Evaluate long-term impact
Who This Framework Serves
The AI Evaluation Framework for Development is designed for:
- M&E Professionals: Evaluate AI systems within development projects with structured assessment criteria
- Evaluators & Consultants: Conduct independent evaluations of AI initiatives with comprehensive frameworks
- Donors & Funders: Assess AI proposals and monitor implementation quality with evidence-based criteria
- Program Managers: Make informed decisions about AI adoption and deployment
- Technical Teams: Ensure AI systems meet ethical, performance, and quality standards
- Organizational Leaders: Develop responsible AI strategies aligned with mission and values
🎯 Our Commitment
EvalCommunity Academy is dedicated to building capacity among development professionals to evaluate AI systems rigorously and responsibly. This framework represents our commitment to ensuring that AI serves humanity, respects dignity, promotes equity, and enhances the impact of development work worldwide through systematic, evidence-based evaluation.
By using this framework, you join a global community of evaluators committed to ensuring AI systems truly serve the communities they're intended to help, while safeguarding against potential harms.