Ethical Challenges in Integrating Artificial Intelligence into Nursing Care: A Narrative Review abstract
Background: The integration of
Artificial Intelligence (AI) into nursing practice is revolutionizing healthcare delivery by enhancing diagnostic accuracy, patient monitoring, and personalized care. However, ethical challenges such as privacy, transparency, equity, accountability, and the preservation of humanistic care complicate its implementation, especially in culturally specific contexts like Iran. This narrative review aims to explore the ethical challenges of AI integration in nursing care within the Iranian context, aligning global principles with cultural and religious values.Materials and methods: A narrative review approach was adopted. International (PubMed, Scopus, DOAJ) and Iranian (Magiran, SID) databases were searched for relevant articles published between 2018 and 2023 using keywords like Artificial Intelligence, Nursing Ethics, and Islamic Bioethics. Of 60 initial articles, 20 met the inclusion criteria and were analyzed using thematic synthesis.Findings: The review identified five key ethical challenges associated with integrating AI into nursing care. Privacy and data security emerged as critical concerns, with breaches undermining trust and conflicting with the Islamic principle of Satr (privacy). Transparency and informed consent are jeopardized by the complexity of AI systems, which compromise Ekhtiyar (autonomy). Equity and bias were highlighted as algorithmic biases exacerbate healthcare disparities, contradicting the ethical principle of Adl (justice). Accountability remains ambiguous, particularly regarding responsibility for AI-driven errors, raising significant ethical concerns. Lastly, humanistic care is threatened by overreliance on AI, which risks dehumanizing patient interactions and undermining Rahmat (compassion), a cornerstone of Iranian nursing ethics.Conclusion: AI integration into nursing requires frameworks that reconcile ethical principles with Iranian cultural and religious values. Recommendations include culturally sensitive AI governance, bias mitigation strategies, and educational initiatives to empower nurses.
