AI IN AYUSH
AI in AYUSH
1.NEWS
- WHO Recognition: Acknowledged India’s AI leadership in AYUSH via its 1st technical brief "Mapping AI in Traditional Medicine" (2023).
- Trigger: Released after India’s proposal at WHO.
- Platform: Developed under GI-AI4H (Global Initiative on AI for Health) – joint effort by WHO, ITU, WIPO.
2. AI Applications in Indian Traditional Medicine
| Application | Description | AYUSH Link |
|---|---|---|
| Smarter Diagnosis | AI + pulse/tongue analysis + Prakriti assessment | Ayurveda, Siddha |
| Ayurgenomics | Genomics + Ayurveda; predicts disease risks | Personalized healthcare |
| Drug Action Pathways | AI sensors decode Rasa, Guna, Virya concepts | Ayurvedic pharmacology |
3. Challenges in AI-Traditional Medicine Integration
- Biopiracy Risk: Misuse of indigenous knowledge (e.g., Patents on Neem/Turmeric).
- Data Gaps: Scanty digitized TM datasets.
- Digital Divide: Low rural internet access (Only 33% rural women use internet: NFHS-5).
- Standardization: Difficulty in globalizing locally relevant AI tools.
4. India’s Key Initiatives
| Initiative | Purpose | AI Relevance |
|---|---|---|
| TKDL | Prevents biopiracy; digitized 4.2 lakh formulations | Protects TM data for AI training |
| Ayush Grid (2018) | Centralized digital ecosystem for AYUSH | Integrates: |
| ↳ AHMIS | Health management system | Patient data for AI analysis |
| ↳ SAHI Portal | Standardizes Ayurveda health info | Creates structured datasets |
| ↳ NAMASTE Portal | TM service delivery | Telemedicine + AI diagnostics |
| GPAI Summit 2023 (Delhi) | Global AI governance platform | Showcased India’s TM-AI models |
5. Solutions & Way Forward
- Adopt WHO’s frontier tech guidelines for TM.
- Build data governance frameworks (e.g., TKDL expansion).
- Global cooperation via GI-AI4H & GPAI.
7. Recent Updates (2023-24)
- WHO’s AI-TM brief (2023) – 1st global document on TM-AI integration.
- India’s GPAI 2023 Summit – Pushed ethical AI frameworks for TM.
- Ayush Grid expansion (2023) – Added 50,000+ health records to AHMIS.