AI Ethics in Smart Healthcare

AI in healthcare introduces new ethical challenges beyond traditional medical ethics, particularly around transparency and bias. Unlike conventional medical devices with predictable behavior, AI systems can make decisions in ways that are difficult to explain to patients and doctors, raising concerns about whether healthcare providers truly understand how treatment recommendations are being made.

Bias in AI healthcare systems can perpetuate or worsen existing health disparities. The paper identifies bias as a key ethical concern, meaning AI trained on data from certain populations may perform poorly for others, potentially denying equitable care to underrepresented groups.

Privacy and safety require continuous monitoring throughout an AI system's entire lifecycle, not just during initial development. The paper emphasizes that ethical oversight must extend from design through deployment, monitoring, repair, and eventual retirement of AI healthcare products—a more comprehensive approach than traditional medical device regulation.

Clear responsibility and accountability structures are essential but currently unclear. When an AI system makes a harmful medical decision, it's often ambiguous whether responsibility lies with the developers, the healthcare facility, the doctors, or the AI itself, creating a gap in accountability that the paper identifies as a critical challenge.

Patient autonomy must be preserved in AI-driven healthcare. The paper highlights that integrating AI into medical decisions requires ensuring patients remain informed participants in their own care, rather than passive recipients of AI-determined treatments.