The Triple Ethical Tensions of Intelligent Healthcare

While artificial intelligence (AI) significantly enhances medical efficiency, it also raises a series of ethical concerns, including blurred clinical responsibility, imbalanced data governance, and algorithmic bias. This paper examines three major ethical tensions in intelligent healthcare: first, the integration of AI reshapes clinical decision-making structures, leading to ambiguous responsibility allocation and a weakening of physicians' subjectivity; second, algorithm-driven data governance may result in the failure of informed consent and the marginalization of patients' lived experiences; third, regional disparities embedded in technical standards exacerbate health inequalities, with algorithmic discrimination potentially entrenching imbalances in resource distribution. In response, this study proposes ethical reconstruction strategies, including the establishment of shared responsibility frameworks, enhancement of algorithmic transparency, reinforcement of data protection, and optimization of fairness mechanisms, aiming to promote the responsible development of medical AI.