Spurred on by recent health care reforms and the Triple Aim's goals of improving population health outcomes, reducing health care costs, and improving the patient experience of care, emphasis on population health is increasing throughout medicine. Population health has the potential to improve patient care and health outcomes for individual patients. However, specific population health activities may not be in every patient's best interest in every circumstance, which can create ethical tensions for individual physicians and other health care professionals. Because individual medical professionals remain committed primarily to the best interests of individual patients, physicians have a unique role to play in ensuring population health supports this ethical obligation. Using widely recognized principles of medical ethics-nonmaleficence/beneficence, respect for persons, and justice-this article describes the ethical issues that may arise in contemporary population health programs and how to manage them. Attending to these principles will improve the design and implementation of population health programs and help maintain trust in the medical profession.

Internal medicine physicians are increasingly interacting with systems that implement artificial intelligence (AI) and machine learning (ML) technologies. Some physicians and health care systems are even developing their own AI models, both within and outside of electronic health record (EHR) systems. These technologies have various applications throughout the provision of health care, such as clinical documentation, diagnostic image processing, and clinical decision support. With the growing availability of vast amounts of patient data and unprecedented levels of clinician burnout, the proliferation of these technologies is cautiously welcomed by some physicians. Others think it presents challenges to the patient-physician relationship and the professional integrity of physicians. These dispositions are understandable, given the "black box" nature of some AI models, for which specifications and development methods can be closely guarded or proprietary, along with the relative lagging or absence of appropriate regulatory scrutiny and validation. This American College of Physicians (ACP) position paper describes the College's foundational positions and recommendations regarding the use of AI- and ML-enabled tools and systems in the provision of health care. Many of the College's positions and recommendations, such as those related to patient-centeredness, privacy, and transparency, are founded on principles in the ACP Ethics Manual. They are also derived from considerations for the clinical safety and effectiveness of the tools as well as their potential consequences regarding health disparities. The College calls for more research on the clinical and ethical implications of these technologies and their effects on patient health and well-being.