Artificial intelligence (AI) applications in healthcare promise significant advances in patient care and outcomes. However, this development raises ethical concerns, requiring careful consideration of the AI tool utilization. AI models must align with clinical knowledge and ethical standards to gain trust among healthcare providers and patients. The ethical landscape of AI in healthcare is complex, involving various challenges such as bias, fairness, transparency, privacy, and security issues. One of the primary concerns regarding AI and ethics is the potential for bias. AI algorithms are only as unbiased as the data they are trained on, and if that data is biased in any way, it can lead to biased results. For example, if an AI system is trained on biased data against a specific group of people, it can lead to discriminatory outcomes. Another ethical consideration when it comes to AI is transparency. Transparency in AI algorithms is crucial for ensuring fairness and trust. As such, interpretability and explainability are vital to making AI algorithms understandable and safe for use in healthcare. To address these ethical considerations, several initiatives are underway to develop ethical guidelines and principles for the development and use of AI. While organizations like the IEEE and the EU have developed ethical AI design and deployment frameworks, a global consensus is still needed. In conclusion, the successful and ethical implementation of AI in healthcare relies on a unified effort that encompasses interdisciplinary education, comprehensive policy-making, and a commitment to transparent algorithm design, ensuring that the advancements in AI are employed responsibly and fairly within healthcare.