全国政协委员、汇珩资本梁颖宇：建议明确AI医疗事故责任认定机制，建立多方共担模式

Core Viewpoint - The rapid development of AI in healthcare brings new challenges such as data privacy, algorithm bias, and legal regulation, necessitating a clear responsibility framework for AI-related medical errors [1][5]. Group 1: AI in Healthcare Challenges - AI has penetrated various healthcare sectors including clinical health management, hospital operations, drug development, and insurance payments, but it faces issues like data incompleteness and bias, especially when training data is limited to specific populations [5]. - The lack of interoperability between institutions creates data silos, hindering the transferability of AI models [5]. - Ethical concerns arise from the sensitivity of medical data, complicating cross-institutional data flow and necessitating improvements in patient consent and risk communication regarding AI diagnostics [5]. Group 2: Recommendations for AI Implementation - Establish a cross-institutional data sharing mechanism to enhance data flow and interoperability, and implement privacy-preserving technologies to ensure data is usable yet not visible [7]. - Create a clear framework for AI medical error responsibility, including a multi-party accountability model and a tiered regulatory system based on risk levels [7]. - Develop a national AI medical data infrastructure to support AI applications and reduce urban-rural disparities in healthcare access [8]. Group 3: Biopharmaceutical Industry Trends - China's biopharmaceutical companies are increasingly expanding overseas, with the country being the largest exporter of active pharmaceutical ingredients, accounting for 30% of global capacity [10]. - The trend of "selling seedlings" (early-stage licensing) poses risks of losing core assets and long-term value, which could hinder the establishment of independent commercialization systems [11]. - To strengthen the domestic market, it is essential to enhance the value of innovative drugs and improve the payment system involving government, insurance, and charitable funds [11]. Group 4: Investment Sentiment in Biopharmaceuticals - Investment confidence in the biopharmaceutical sector is gradually recovering, with several innovative drug companies successfully listing on the Hong Kong stock market [14]. - The focus remains on late-stage investments, but early-stage capital is crucial for the industry's growth, emphasizing the need for patience from investors [14]. - The AI healthcare sector is viewed as one of the most promising applications of AI, with potential for significant growth, although caution is advised regarding market saturation and resource allocation [14].