AI-Powered Tools for Refugee Mental Health & Education [Proposal]
1. Executive Summary
- Objective: Deploy culturally adapted, AI-driven tools to address dual crises of mental health and education among refugees in Northern Uganda, leveraging Learning through Play (LtP) methodologies.
- Innovation: Combines trauma-informed AI design with play-based learning for scalable, low-tech solutions.
- Target Beneficiaries: 10,000+ refugee children and caregivers in Bidibidi, Rhino Camp, and Imvepi settlements.
2. Problem Statement
- Mental Health:
- 67% of refugees report PTSD/depression/anxiety symptoms (UNHCR 2023)
- 1 counselor per 10,000 refugees (WHO 2022)
- Education:
- 72% lack formal schooling access (Uganda Education Response Plan 2023)
- 15+ languages spoken with limited multilingual resources
3. Project Objectives
- Mental Health: 40% reduction in PTSD/depression symptoms in 2 years
- Education: 50% literacy rate improvement for children 6-12
- Community Capacity: Train 200+ educators/caregivers
4. Methodology
A. AI + Learning through Play Framework
- Trauma-Informed AI Design:
- Voice-Based Play Therapy Chatbot: NLP-driven CBT in Acholi/Lugbara/English
- Emotion Recognition: Vocal tone analysis for distress signals
- Multilingual Literacy Tools:
- AI Storytelling Companion: Personalized folktales with phonics
- AR Sandbox: Adaptive projection-based learning
B. Implementation Science Approach
- RE-AIM Framework:
- Reach: RLO partnerships
- Effectiveness: RCT pilots
- Adoption: AI-powered training modules
- Implementation: Low-cost tablets/solar audio
- Maintenance: Government integration
5. AI Tools & Technologies
| Tool | Function | Tech Stack |
|---|---|---|
| Tarian Chatbot | Voice-based CBT + literacy games | Sunbird AI NLP, Hugging Face, NVIDIA Ai*[will be locally hosted by ASAT Labs] |
| AR Sandbox | Projection-based LtP | TensorFlow Lite, Raspberry Pi 4 |
| Emotion Analytics | Vocal tone analysis | OpenSMILE, PyTorch |
6. Partnerships
- Local:
- UHURU Refugee-Led Network
- Gulu University
- Global:
- UNHCR Innovation
- AI for Good Foundation
7. Monitoring & Evaluation (M&E)
- Metrics:
- WHO-5 Well-Being Index
- Ugandan curriculum assessments
- Tools:
- CommCare mobile tracking
- Tableau dashboards
- N8N Automations
8. Ethical Safeguards
- Data Privacy:
- GDPR-compliant anonymization
- Local servers at ASAT Labs/ AWS
- Bias Mitigation:
- Quarterly participatory audits
- Fairness algorithms for marginalized groups
9. Sustainability & Scalability
- 50+ refugee “AI Ambassadors”
- Uganda’s National AI Policy integration
- AR Sandbox licensing model
10. Budget & Funding Needs [3 Years]
| Component | Cost (USD) | Donate/ Pledge |
|---|---|---|
| AI Tool Development | $150,000 | Donate Here | Pledge Here |
| Caregiver Training | $50,000 | Donate Here | Pledge Here |
| M&E Systems | $30,000 | Donate Here | Pledge Here |
11. Expected Outcomes
- Year 1: 1,000 children pilot: 30% PTSD reduction, 25% literacy gain
- Year 3: 10,000 beneficiaries, Ministry of Education adoption
12. Call to Action
Visit asatlabs.org/ai-refugee-resilience to:
- Download technical proposal
- Partner via tech support/funding
- Explore co-design opportunities
13. Academic Endorsements
“A groundbreaking fusion of AI and play therapy that centers refugee voices.”
— Dr. Amina J. Mohammed, MIT D-Lab
“Exemplifies ethical AI for low-resource settings.”
— Prof. John Bosco Komakech, Gulu University
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