Governance of AI Ethics in Digital Health for Indigenous Communities: A Narrative Review and Conceptual Framework
Clinical Scorecard: Governance of AI Ethics in Digital Health for Indigenous Communities: A Narrative Review and Conceptual Framework
At a Glance
Category Detail
Condition AI Ethics in Digital Health Key Mechanisms Incorporation of AI to enhance health outcomes and address systemic inequities. Target Population Indigenous populations Care Setting Digital health delivery
Key Highlights
AI has potential to improve health outcomes and bridge healthcare gaps. Ethical issues in AI integration include accountability, privacy, and governance. Indigenous perspectives are crucial in AI development to avoid perpetuating inequities. A unified ethical governance framework for AI in Indigenous health is lacking. The review synthesizes literature to inform ethical considerations in AI integration. Guideline-Based Recommendations
Diagnosis
Management
Monitoring & Follow-up
Risks
Exclusion from governance procedures and risks from misuse of health-related data. Patient & Prescribing Data
Indigenous communities
Incorporation of Indigenous governance and knowledge systems in AI development.
Clinical Best Practices
Ensure equitable involvement of Indigenous communities in AI system design. Utilize culturally grounded implementation strategies for AI technologies. Incorporate representative training datasets to avoid bias. Related Resources & Content
