The article discusses the integration of machine learning (ML) into healthcare, highlighting its potential to enhance medical decision-making and improve healthcare delivery. However, it emphasizes the need to address ethical challenges that arise from this integration. These challenges include the risk of algorithms mirroring human biases, particularly in areas like racial discrimination, and the potential for algorithms to become the repository of the collective medical mind, which could lead to unintended consequences. The authors also caution against the ethical strain that may arise from the tension between improving health and generating profit, and the potential for ML systems to be used in ways that do not align with the best interests of patients. They argue that ethical guidelines and education are crucial to ensure that ML systems are developed and used responsibly, and that the nature of the relationship between physicians and patients must be reimagined in the context of a learning health care system.The article discusses the integration of machine learning (ML) into healthcare, highlighting its potential to enhance medical decision-making and improve healthcare delivery. However, it emphasizes the need to address ethical challenges that arise from this integration. These challenges include the risk of algorithms mirroring human biases, particularly in areas like racial discrimination, and the potential for algorithms to become the repository of the collective medical mind, which could lead to unintended consequences. The authors also caution against the ethical strain that may arise from the tension between improving health and generating profit, and the potential for ML systems to be used in ways that do not align with the best interests of patients. They argue that ethical guidelines and education are crucial to ensure that ML systems are developed and used responsibly, and that the nature of the relationship between physicians and patients must be reimagined in the context of a learning health care system.