With the rapid advancement of medical artificial intelligence(AI)technology,particularly the widespread adoption of AI diagnostic systems,ethical challenges in medical decision-making have garnered increasing attentio...With the rapid advancement of medical artificial intelligence(AI)technology,particularly the widespread adoption of AI diagnostic systems,ethical challenges in medical decision-making have garnered increasing attention.This paper analyzes the limitations of algorithmic ethics in medical decision-making and explores accountability mechanisms,aiming to provide theoretical support for ethically informed medical practices.The study highlights how the opacity of AI algorithms complicates the definition of decision-making responsibility,undermines doctor-patient trust,and affects informed consent.By thoroughly investigating issues such as the algorithmic“black box”problem and data privacy protection,we develop accountability assessment models to address ethical concerns related to medical resource allocation.Furthermore,this research examines the effective implementation of AI diagnostic systems through case studies of both successful and unsuccessful applications,extracting lessons on accountability mechanisms and response strategies.Finally,we emphasize that establishing a transparent accountability framework is crucial for enhancing the ethical standards of medical AI systems and protecting patients’rights and interests.展开更多
With the increasing complexity of social public affairs,cross-departmental collaborative governance has become an important model of modern administrative management.However,conflicts of interest frequently occur duri...With the increasing complexity of social public affairs,cross-departmental collaborative governance has become an important model of modern administrative management.However,conflicts of interest frequently occur during the collaboration process,which are mainly reflected in resource allocation,goal differences,and power games.These conflicts are caused by factors such as cultural differences within departments,inconsistent performance evaluation systems,and personal interests of department members.To address these issues,it is necessary to design multi-level integration mechanisms,including establishing stable communication channels and unified goals and evaluation systems.Successful integration cases in various fields,such as food safety supervision,environmental protection,and urban transportation governance,show that effective integration mechanisms need to establish institutionalized communication carriers,form a consensus target system,and design guarantee measures with both incentives and constraints.Although current research has achieved certain results,there are still limitations,such as insufficient attention to underdeveloped regions,a lack of consideration of cultural factors,and a narrow focus on internal government collaboration.Future research can explore differentiated integration models,introduce third-party assessment institutions,and strengthen research on the participation mechanism of enterprises and social organizations.展开更多
文摘With the rapid advancement of medical artificial intelligence(AI)technology,particularly the widespread adoption of AI diagnostic systems,ethical challenges in medical decision-making have garnered increasing attention.This paper analyzes the limitations of algorithmic ethics in medical decision-making and explores accountability mechanisms,aiming to provide theoretical support for ethically informed medical practices.The study highlights how the opacity of AI algorithms complicates the definition of decision-making responsibility,undermines doctor-patient trust,and affects informed consent.By thoroughly investigating issues such as the algorithmic“black box”problem and data privacy protection,we develop accountability assessment models to address ethical concerns related to medical resource allocation.Furthermore,this research examines the effective implementation of AI diagnostic systems through case studies of both successful and unsuccessful applications,extracting lessons on accountability mechanisms and response strategies.Finally,we emphasize that establishing a transparent accountability framework is crucial for enhancing the ethical standards of medical AI systems and protecting patients’rights and interests.
文摘With the increasing complexity of social public affairs,cross-departmental collaborative governance has become an important model of modern administrative management.However,conflicts of interest frequently occur during the collaboration process,which are mainly reflected in resource allocation,goal differences,and power games.These conflicts are caused by factors such as cultural differences within departments,inconsistent performance evaluation systems,and personal interests of department members.To address these issues,it is necessary to design multi-level integration mechanisms,including establishing stable communication channels and unified goals and evaluation systems.Successful integration cases in various fields,such as food safety supervision,environmental protection,and urban transportation governance,show that effective integration mechanisms need to establish institutionalized communication carriers,form a consensus target system,and design guarantee measures with both incentives and constraints.Although current research has achieved certain results,there are still limitations,such as insufficient attention to underdeveloped regions,a lack of consideration of cultural factors,and a narrow focus on internal government collaboration.Future research can explore differentiated integration models,introduce third-party assessment institutions,and strengthen research on the participation mechanism of enterprises and social organizations.
