An AI-assisted framework for the ethical use of machine learning in healthcare

This paper presents the development and validation of the ETHICS framework, an artificial intelligence (AI)-assisted protocol for the ethical integration of machine learning (ML) in clinical practice. While existing frameworks from internationally recognized entities provide foundational ethical guidance, the ETHICS framework offers distinct contributions tailored specifically to clinical contexts. It contextualizes general AI ethics within the daily realities of healthcare, emphasizing actionable principles related to clinical workflows, patient engagement, and health data governance. The framework was developed using a novel human-AI collaborative methodology: ChatGPT generated initial drafts, which were then refined through linguistic simplification, expert evaluation, and scenario-based stress testing. ETHICS also employs a mnemonic structure to enhance recall and communication among clinicians, increasing its practical utility. It encompasses six core principles: equity and fairness, transparency and patient-centered care, human oversight and clinical integrity, information privacy and data governance, continuous improvement and sustainability, and support and education for professionals. This study also stresses the potential of large language models to support ethical innovation when guided by expert oversight.