Governance and Ethical Regulation of Artificial Intelligence in Healthcare: Towards a Global Policy Framework

Background and Aims: The integration of artificial intelligence (AI) into healthcare has unlocked innovative opportunities, yet persistent ethical and governance challenges—including data protection, transparency, accountability, and equitable access—demand a comprehensive policy framework. The absence of unified standards underscores the urgent need for a global governance model. This study proposes an evidence-based framework for ethical AI governance in healthcare through a mixed-methods empirical approach. Methods: The research adopted a sequential mixed-methodology design. A quantitative phase surveyed ۵۰۰ policymakers, healthcare professionals, AI developers, and ethicists from diverse global regions to capture perceptions of regulatory challenges and governance priorities. A qualitative phase followed, involving ۵۰ semi-structured interviews with key experts, analyzed via thematic analysis. A Delphi method was then employed to establish consensus on core elements of a global policy framework. Results: Findings revealed regional disparities in governance priorities: European stakeholders emphasized privacy and algorithmic fairness, while North American respondents prioritized innovation and legal accountability. The qualitative analysis identified five foundational principles for AI governance: (۱) algorithmic transparency and explainability, (۲) bias mitigation and ethical risk assessment, (۳) international data-sharing protocols, (۴) dynamic regulatory adaptation to AI advancements, and (۵) participatory oversight mechanisms. Conclusion: This study underscores the necessity of a global, multi-stakeholder governance framework for AI in healthcare, engaging policymakers, healthcare experts, and industry leaders to foster transparent, accountable, and equitable AI systems. Future research should evaluate proposed governance models and their impact on healthcare quality.

کلیدواژه ها:

AI Governance ، Healthcare Ethics ، Mixed-Methods Research