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RAIGH Curriculum — Responsible AI in Global Health

Status: Incubating License: Apache-2.0 Part of: Evidence Commons

"Workforce development for clinical AI cannot be an afterthought — LMIC researchers need structured pathways from awareness to methodology leadership."

Attribute Value
Status Incubating
Maturity Design Phase
License Apache-2.0
Part of Evidence Commons
Mission Pillar Pillar 7 (Education & Workforce Development)

Overview

RAIGH (Responsible AI in Global Health) Curriculum is a collection of open educational resources for AI workforce development, targeting researchers and clinicians in low- and middle-income countries. The curriculum is organized into tiered certification tracks that map directly to platform access levels, creating a structured pathway from foundational AI literacy through independent methodology leadership. The program is aligned with SDG 4 (Quality Education, Target 4.4).

This repository is intended to contain original curriculum content — course modules, competency frameworks, assessment rubrics, and practical exercises. Unlike other EvidenceOSS repositories, this is not an extraction from existing code; it is new content developed specifically for open distribution. The curriculum is currently in concept and Cohort 1 planning phase. No course materials have been published yet.

Certification Tiers

Tier Name Capabilities Platform Integration
Tier 0 Awareness AI literacy foundations, ethical considerations Free Lab-in-a-Box tools (SAP template, EPV calculator, TRIPOD checklist)
Tier 1 Foundation Data stewardship, basic clinical AI evaluation Basic Lab-in-a-Box access ($200/paper for LMIC researchers)
Tier 2 Evaluator Independent evaluation methodology, 1 LSR slot/yr Standard Lab-in-a-Box access
Tier 3 Senior Evaluator Advanced methodology, 2 LSR slots/yr + mentoring Premium Lab-in-a-Box access
Fellowship Methodology Lead Research leadership, 1 LSR as lead/yr Elite Lab-in-a-Box access

RAIGH certification is designed to serve as the pricing gate for Lab-in-a-Box LMIC access (INT-02). This integration is not yet built.

Current State

What exists:

  • Tier structure and competency mapping (documented)
  • Integration design with Lab-in-a-Box pricing tiers (INT-02, not built)
  • Open Badges 3.0 credential issuance specification (planned)

What does not exist yet:

  • Course content for any tier
  • Assessment instruments or rubrics
  • Learning management system deployment (OpenEdX and MinnaLearn under evaluation)
  • INT-02 authentication middleware linking credentials to Lab-in-a-Box pricing
  • Cohort 1 pilot materials

Development Plan

  1. Finalize Tier 0 and Tier 1 learning objectives and module outlines
  2. Develop Tier 0 course content as Markdown-based open educational resources
  3. Design assessment rubrics aligned with competency framework
  4. Select and configure LMS platform (OpenEdX or MinnaLearn)
  5. Define Open Badges 3.0 credential schema for each tier
  6. Pilot Tier 0 with Cohort 1 participants
  7. Iterate on Tier 1-3 content based on pilot feedback

Ecosystem Context

graph LR
    A[RAIGH Academy<br/>certification tiers] --> B[RAIGH-Curriculum]
    B -->|INT-02| C[Lab-in-a-Box<br/>pricing gate]
    D[Clinical Arena<br/>failures] -->|INT-06| B
    style B fill:#2A9D8F,stroke:#1E3A8A,color:#fff
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RAIGH Curriculum is part of the University-in-a-Box product family under PAATHI (Partnership on AI, Technology and Health Innovation). Graduates feed into Lab-in-a-Box as credentialed researchers (INT-02) and receive training cases generated from Clinical Arena evaluation failures (INT-06). The long-term target is 10M MOOC participants leading to 1M certified researchers.

Canonical source: Standalone (original curriculum content)

Contributing

This project is not yet accepting contributions. Curriculum design and pedagogical review are ongoing. See CONTRIBUTING.md for future plans.

License

Apache-2.0 — see LICENSE for details.

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Research AI for Global Health curriculum — MOOC content, certification framework, clinical AI workforce development

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