Abstract

The increasing integration of Artificial Intelligence (AI) into healthcare presents significant ethical considerations, particularly as systems approach Artificial General Intelligence (AGI) capabilities. Core issues include safeguarding patient autonomy, ensuring data privacy, and mitigating algorithmic bias. It’s crucial to establish accountability for AI decisions and errors. Explainable AI (XAI) and transparency are vital for building trust in these advanced systems. Moreover, responsible AI development, grounded in human-centered principles like fairness, beneficence, and non-maleficence, is paramount. This demands transitioning from abstract ethical guidelines to practical, actionable frameworks to ensure safe and equitable deployment of AI in clinical settings and biomedical research, preventing unintended harm and fostering societal well-being