Defining Responsibility: A Framework Analysis of Error Attribution and Accountability in AI Telemedicine Services

Abstract

This study examines the regulatory landscape governing liability and accountability in AI telemedicine in Ghana. Using the CREAC (Context, Rules, Explanation, Application, Conclusion) legal analytical approach, it analyzes existing Ghanaian healthcare laws and regulations in the context of AI telemedicine. The study finds that while Ghana has a comprehensive set of healthcare regulations, they are inadequately equipped to address the unique challenges posed by AI in telemedicine, particularly regarding liability determination, accountability mechanisms, and error management. Significant gaps exist in current legislation, leaving Ghana vulnerable to the risks associated with AI in healthcare. The study recommends developing AI-specific healthcare legislation, updating existing laws, establishing a national AI in healthcare ethics committee, implementing a certification system for AI in healthcare, and creating a specialized AI healthcare liability framework. These measures aim to balance innovation in AI telemedicine with patient safety and ethical healthcare delivery.