摘要
生成式人工智能以数据密集型范式高效整合跨地域患者和基因数据,重塑了药物研发流程,但也带来了数据控制削弱、权利主体弱化与数据公平缺位等数据权利困境。在此基础上,提出“可解释-可协商-可追责”三维数据权利治理框架,强调通过分层解释与公共平台降低信息壁垒;用事件驱动再授权和多方协商保障数据主体持续参与;以责任节点标注、问责委员会和风险预警闭合责任链来实现人-机-数据共治并重新确认数据主体的道德地位,在加速药物创新的同时维护个体尊严与社会公正。
Generative artificial intelligence reshapes drug development with a data-intensive paradigm,efficiently integrates cross-regional patient and genetic data,but also brings data rights dilemmas such as weakened data control,weakened rights subjects,and a lack of data equity.On this basis,a three-dimensional data rights governance framework of"explainable-negotiable-accountable"is proposed,emphasizing the reduction of information barriers through layered interpretation and public platforms.The study promotes sustained data subject engagement via event-driven reauthorization and multi-stakeholder negotiation,and ensures human–machine–data co-governance through mechanisms such as responsibility node labelling,accountability committees,and risk-warning systems that close the responsibility loop.This approach seeks to reaffirm the moral status of data subjects,thereby accelerating pharmaceutical innovation while safeguarding individual dignity and social justice.
作者
庞钰
PANG Yu(School of Government,Peking University,Beijing 100871,China)
出处
《医学与哲学》
北大核心
2025年第13期12-16,32,共6页
Medicine and Philosophy
关键词
生成式人工智能
药物研发
数据权利
伦理困境
算法治理
generative artificial intelligence
drug development
data rights
ethical dilemmas
algorithmic governance
