Human-Centered AI in Healthcare: Ethical Design Principles for Diverse and Resource-Limited Settings

Abstract

The deployment of artificial intelligence in healthcare settings necessitates a fundamental shift toward human-centered design principles that prioritize the needs, values, and circumstances of end-users and affected communities. This article examines the ethical dimensions of AI design and implementation in healthcare, with particular attention to resource-limited regions and diverse population groups. Through systematic analysis of contemporary scholarship, the study identifies critical ethical considerations including bias mitigation, local contextual adaptation, stakeholder engagement, and the prevention of technological monopolization. Findings reveal that AI systems developed without adequate attention to human-centered principles risk amplifying existing healthcare inequities, particularly in underserved regions of the Global South. The article proposes a comprehensive framework for human-centered AI in healthcare, encompassing participatory design methodologies, culturally sensitive implementation strategies, and governance structures that ensure equitable access and benefit distribution. The European GDPR framework provides foundational data protection standards, yet its principles must be extended to address the specific ethical challenges of AI deployment in diverse healthcare contexts.