This study explores the governance challenges and opportunities associated with the implementation and use of AI in healthcare, offering practical insights informed by extensive stakeholder interviews. By analyzing perspectives from academia, government, clinicians, healthcare associations, and consumer groups, the research highlights critical themes, including data governance, ethical considerations, accountability, risk management, and equity. Findings highlight the need for robust frameworks to address fragmented data systems, privacy concerns, and systemic biases while recommending tiered risk management approaches to AI implementation. Enhanced AI literacy, improved infrastructure, and centralized governance structures are proposed to streamline decision-making and ensure safe, equitable, and sustainable AI adoption in healthcare organizations.
Freeman et al. (Thu,) studied this question.
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