Artificial intelligence (AI) in medicine presents significant ethical challenges, including trust, responsibility, discrimination, privacy, autonomy, and potential benefits and harms. AI has the potential to revolutionize healthcare but requires ethical oversight to ensure it is used for the good. Ethical relativism is challenged by the idea that universal human rights should be upheld, while context-specificity means ethical judgments depend on particular facts. Case examples, such as the breast cancer algorithm and DermAssist, highlight risks like bias, discrimination, and unequal performance across different groups. AI systems may perpetuate injustice and undermine autonomy, and there are concerns about the reliability of AI in diverse populations. The use of AI in medicine raises questions about responsibility, as harm may occur due to algorithmic errors or biases. Trust in AI is complex, as it requires accountability and transparency. AI also raises issues of privacy, as it relies on large datasets that may be re-identified. There is a need for interpretable AI to ensure transparency and informed decision-making. AI can also be used to promote justice and fairness, but it must be designed with explicit values and ethical considerations. The ethical use of AI in medicine requires a balance between benefits and risks, with a focus on ensuring that AI is used to enhance patient care and uphold ethical principles. The article emphasizes the importance of ethical frameworks, transparency, and accountability in the development and use of AI in medicine.Artificial intelligence (AI) in medicine presents significant ethical challenges, including trust, responsibility, discrimination, privacy, autonomy, and potential benefits and harms. AI has the potential to revolutionize healthcare but requires ethical oversight to ensure it is used for the good. Ethical relativism is challenged by the idea that universal human rights should be upheld, while context-specificity means ethical judgments depend on particular facts. Case examples, such as the breast cancer algorithm and DermAssist, highlight risks like bias, discrimination, and unequal performance across different groups. AI systems may perpetuate injustice and undermine autonomy, and there are concerns about the reliability of AI in diverse populations. The use of AI in medicine raises questions about responsibility, as harm may occur due to algorithmic errors or biases. Trust in AI is complex, as it requires accountability and transparency. AI also raises issues of privacy, as it relies on large datasets that may be re-identified. There is a need for interpretable AI to ensure transparency and informed decision-making. AI can also be used to promote justice and fairness, but it must be designed with explicit values and ethical considerations. The ethical use of AI in medicine requires a balance between benefits and risks, with a focus on ensuring that AI is used to enhance patient care and uphold ethical principles. The article emphasizes the importance of ethical frameworks, transparency, and accountability in the development and use of AI in medicine.