Research on Ethical Issues and Countermeasures in Artificial Intelligence-Assisted Healthcare
Abstract
Since emerging in the 1950s, medical artificial intelligence (AI) has been deeply integrated into all segments of healthcare systems. It delivers prominent advantages in medical image diagnosis, pathological analysis, intelligent surgery, drug research and development and other fields, effectively lifting the efficiency, accuracy and overall quality of medical services, and becoming a core driving force for the digital and intelligent transformation of the healthcare industry. Nevertheless, the extensive application and technological iteration of AI have also brought new governance challenges. Focusing on ethical risks arising from AI-assisted medical services, this paper analyzes the relevant ethical dilemmas, root causes and corresponding solutions. When diagnostic and therapeutic errors occur in AI-aided medical activities, liabilities involve three stakeholders: technology developers, medical institutions and patients. The complicated liability structure renders the traditional single-subject liability model inapplicable, creating obstacles to liability identification. In addition, medical AI features complex technical frameworks and the "black box" algorithm effect: its internal processing logic cannot be fully interpreted by humans, leading to untraceable decision-making processes. Meanwhile, safety and ethical problems including medical data leakage, algorithmic bias and clinicians’ over-reliance on technology have become increasingly prominent in China. To address the above ethical risks, this paper compares and draws on mature regulatory practices of the United States, the European Union and Japan for medical AI. It puts forward targeted suggestions to improve the liability system and regulatory mechanism of medical AI, clarify the rights and obligations of all stakeholders, standardize the clinical application of artificial intelligence, and strike a balance between technological innovation and medical safety. This research provides references for the standardized development of AI-assisted healthcare in China.