This qualitative study explores the ethical considerations in clinical trials of artificial intelligence (AI) for diabetic retinopathy (DR) screening, focusing on the generalizability of the 7 ethical principles endorsed by the National Institutes of Health (NIH) and unique ethical challenges. The study involved 11 investigators engaged in AI clinical trials, using a combination of deductive and inductive approaches to analyze their perspectives. Key themes identified include difficulties in measuring social value, establishing scientific validity, ensuring fair participant selection, evaluating risk-benefit ratios across patient subgroups, and addressing complex informed consent processes. Participants highlighted the need for nuanced understanding and application of ethical principles in AI trials, emphasizing the importance of transparency, equitable access, and informed consent. The study underscores the need for further guidance to support the ethical conduct of AI clinical trials and minimize unintended harm to participants.This qualitative study explores the ethical considerations in clinical trials of artificial intelligence (AI) for diabetic retinopathy (DR) screening, focusing on the generalizability of the 7 ethical principles endorsed by the National Institutes of Health (NIH) and unique ethical challenges. The study involved 11 investigators engaged in AI clinical trials, using a combination of deductive and inductive approaches to analyze their perspectives. Key themes identified include difficulties in measuring social value, establishing scientific validity, ensuring fair participant selection, evaluating risk-benefit ratios across patient subgroups, and addressing complex informed consent processes. Participants highlighted the need for nuanced understanding and application of ethical principles in AI trials, emphasizing the importance of transparency, equitable access, and informed consent. The study underscores the need for further guidance to support the ethical conduct of AI clinical trials and minimize unintended harm to participants.