Key points from article :
Artificial intelligence (AI) is increasingly embedded in modern healthcare, from diagnostics and robotic surgery to wearable technologies and drug development. As its use expands, AI raises complex ethical challenges related to the core principles of medical ethics: autonomy, beneficence, non-maleficence, and justice. These principles guide not only how care is delivered but also how patients and healthcare providers engage with rapidly evolving technologies.
Patient autonomy may be compromised when AI systems operate without sufficient transparency. It is essential that patients understand how AI is involved in their care and have control over their personal health data. On the other hand, AI offers opportunities to improve beneficence by enhancing diagnostic accuracy and personalising treatment. However, these benefits must be balanced with the need for transparency and human oversight to ensure patients and clinicians are not blindly relying on opaque systems.
Non-maleficence, the obligation to avoid harm, underscores the importance of testing AI systems rigorously and maintaining human control to catch potential errors or biases. A "human-in-the-loop" approach is key to ensuring safety. Justice remains a critical concern: AI tools often reflect the biases present in their training data, potentially exacerbating health disparities, particularly in underrepresented or resource-limited populations.
To address these challenges, there is a pressing need for robust, flexible regulatory frameworks, global ethical standards, and interdisciplinary oversight. AI must support—not replace—the human connection in healthcare, ensuring that innovations promote safety, equity, and compassion across all levels of medical practice.
