With the rapid advancement of Artificial Intelligence (AI) technologies in healthcare, unprecedented achievements have become possible in early diagnosis, disease prediction, and the improvement of treatment quality. However, this technological progress is accompanied by numerous ethical challenges and privacy concerns that raise fundamental questions about how these tools can be used responsibly and safely within healthcare systems. One of the most prominent ethical issues is transparency. AI systems often rely on highly complex algorithms that are difficult to interpret, even by their developers—a phenomenon commonly referred to as the “black box.” This lack of transparency creates challenges in making sensitive medical decisions, particularly when physicians and patients cannot understand how a system arrived at a specific diagnosis or recommendation. Consequently, trust in these technologies may be diminished. Another significant ethical concern is algorithmic bias. AI algorithms can produce unfair outcomes if they are trained on unbalanced datasets or data that disproportionately represent certain patient groups. Such biases may lead to unintended discrimination against specific populations or exacerbate existing healthcare disparities. From a privacy perspective, AI systems require vast amounts of sensitive medical data for training and performance improvement. While such data are essential for building accurate models, their collection, storage, and analysis can create risks of privacy violations, especially if data are not adequately protected or are shared without the explicit consent of patients. Accountability is another important issue. As healthcare increasingly relies on AI-driven recommendations, questions arise regarding responsibility when medical errors occur. Should accountability fall on the physician who followed the recommendation, the software developer, or the AI system itself? This legal ambiguity highlights the need for clear regulatory frameworks to protect patients and define the relationship between human professionals and intelligent systems. In light of these challenges, it is essential to develop policies and governance frameworks that balance innovation with protection. This can be achieved by enforcing transparent development standards, ensuring diversity in the datasets used to train AI models, adopting the principle of “Privacy by Design,” and involving ethicists, healthcare professionals, and patients in the design and implementation of these systems. In conclusion, there is no doubt that artificial intelligence holds enormous potential for improving healthcare. However, its effectiveness depends on its ethical application, respect for patient privacy, and commitment to keeping human well-being at the center of the medical process. The future belongs not only to smarter technologies but also to healthcare systems that are more humane, fair, and trustworthy. Al-Mustaqbal University is the first one university in Iraq.