Analyzing Ethical Dilemmas in AI-Assisted Diagnostics and Treatment Decisions for Patient Safety

Artificial intelligence (AI) raises challenging ethical questions concerning patient safety, liberty, and trust as it is used increasingly in healthcare systems, particularly in regard to diagnostic and treatment choices. Big improvements in the quality of care would follow from considerably more accurate and efficient medical assessments and treatment plans made possible by AI-assisted systems. These developments, meantime, also bring challenges about transparency, accountability, and the danger of depending too much on automated systems. Especially when crucial judgements have to be taken, one should carefully consider the moral questions raised by artificial intelligence use in medical care. This is to guarantee that without violating ethical standards, these technologies enhance patient well-being. The moral issues raised by utilising artificial intelligence to support diagnostic and treatment decisions are investigated in this paper. It mostly addresses the discrepancy between human expertise and machine recommendations. Among the issues are the possibility of artificial bias, the clarity of AI decision-making procedures, and how AI will change the rapport between a doctor and a patient. The research also examines the need of patients continuing to trust automated medical systems as well as the possibility of dehumanising treatment when artificial intelligence systems take over decision-making duties. The paper also addresses the difficulty of ensuring that artificial intelligence systems abide by moral standards like promoting good, avoiding damage, and honouring patient liberty. With an eye on striking a balance between new technology and patient safety, the research also proposes guidelines and criteria for the appropriate use of artificial intelligence in healthcare. The interactions between ethical norms and artificial intelligence technology are examined in this paper. The aim is to provide a whole picture of how artificial intelligence might be employed in healthcare settings to raise patient outcomes while reducing risks and maintaining confidence by means of effective application.