Application,Challenges,and Prospects of Artificial Intelligence Generated Content in Medical Education
With the emergence of generative artificial intelligence technologies represented by ChatGPT,Artificial Intelligence Generated Content(AIGC)has significantly propelled theoretical instruction,practical training,and assessment in medical education.As a pivotal component of innovative medical education development,the application,challenges,and future prospects of AIGC warrant meticulous attention.To advance the construction of new medical disciplines and effectively integrate AIGC into China's medical education framework,it is essential to synthesize innovative applications of AIGC in both domestic and international medical education contexts,thereby furnishing instructive lessons for enhancing our educational practices.Furthermore,delving into the ethical challenges and application risks associated with AIGC,this paper presents three avant-garde case studies illustrating how AIGC technologies are being employed across various stages of medical education,thereby empowering the educational process.Looking ahead,the potential utilization of AIGC-related technologies such as retrieval-augmented generation,multi-agent systems,and Sora in future medical education underscores the need for anticipation.These considerations give rise to the following insights:As a representative of novel productive forces,AIGC holds immense promise for application within medical education,yet its development and implementation necessitate a comprehensive evaluation of multiple dimensions,including technical feasibility,ethical norms,societal receptiveness,legal frameworks,and pedagogical outcomes.The medical education community must not only seize the opportunities presented by AIGC technologies,but also prepare diligently to address the attendant challenges,thereby optimizing the value and efficacy of AIGC in enhancing medical education.
AIGCMedical educationGPTLarge language modelDigitalizationHealthcare
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