The application of artificial intelligence (AI) in clinical practice presents numerous ethical concerns. However, the attitudes of stakeholders toward its ethical impact have yet to be reviewed. We aimed to review the attitudes of stakeholders toward the ethical impact of applying AI in clinical practice. We undertook a literature search of Ovid Medline and Scopus. We included empirical studies of clinicians, patients, and caregivers that investigated their attitudes toward applying AI in clinical practice. We developed a methodology based on the four principles of bioethics—beneficence, non-maleficence, autonomy, and justice—plus explainability to determine if a study investigated ethical impact. 103 studies were included. Themes related to beneficence included improved efficiency, improved decision-making and health outcomes, and more patient-centered care. Themes related to non-maleficence included inefficiency, diminished decision-making and worse health outcomes, less patient-centered care, de-skilling, and data insecurity. Themes related to autonomy included patient consent, sharing AI-generated information, and respecting patient preferences. Themes related to justice included bias, healthcare access, and responsibility. Themes related to explainability included improved decision-making and better health outcomes as well as de-skilling. While all of the included studies queried at least one theme related to ethics, very few had the explicit objective of studying ethical attitudes. Moreover, few studies queried attitudes toward explainability. Further research is needed to address these gaps. Studies often reported conflicting attitudes, with stakeholders reporting that AI could harbor both ethical advantages and disadvantages for clinical practice. Further research is needed to address these ethical trade-offs.
Daus et al. (2026) studied this question.