ETHICAL CHALLENGES OF AI DECISION-MAKING IN HEALTHCARE

Abstract

Artificial intelligence (AI) increasingly supports clinical decision-making in healthcare systems, offering opportunities to improve diagnostic accuracy, treatment planning, and operational efficiency. However, integrating AI technologies introduces significant ethical issues related to algorithmic prejudice, transparency, accountability, patient autonomy, and data governance. This narrative literature review examines ethical issues associated with AI-based decision-making in healthcare by synthesizing contemporary scientific literature. A structured search strategy was applied across major scientific databases, including PubMed, Scopus, Web of Science, and Google Scholar, focusing on publications from 2015 to 2025 that address ethical aspects of AI in clinical contexts. The analysis identified recurring ethical themes, including fairness, explainability, responsibility distribution, and trust in human–AI collaboration. Evidence indicates that although AI enhances evidence-based practice, unresolved ethical risks may affect clinical accountability and patient trust. The study points out the need for evidence-based administrative frameworks and multidisciplinary collaboration to ensure ethical integration of AI technologies into healthcare decision-making procedures.

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