거대언어모델의 발전과 기초의학교육에 미치는 영향에 대한 고찰
Reflections on the Development of Large Language Models and Their Impact on Basic Medical Education
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인공지능, 특히 자연어 처리 분야의 급속한 발전으로 인해 의학교육도 변화하고 있다. 거대언어모델은 방대한 양의 텍스트를 처리하고 일관된 문맥을 가진 텍스트를 생성할 수 있는 기능을 통해 의학 분야의 교육과 학습을 향상시킬 수 있는 유례 없는 기회를 제공한다. 이 논문에서는 거대언어모델의 교육적 잠재력을 검토하고, 통합과 사용에 관련된 잠재적 문제점을 살펴본다. 거대언어모델은 개인화된 학습 경험을 제공하고, 광범위한 의학 지식에 대한 접근성을 넓히며, 문헌 검토를 간소화하여 연구를 지원할 수 있다. 또한 임상 환경을 모사할 수 있는 대화형 학습 환경을 통해 역동적이고 몰입감 있는 교육 경험을 제공할 수 있다. 그럼에도 불구하고 의학교육에 거대언어모델을 통합하는 데 우려되는 점이 없는 것은 아니다. 제공되는 정보의 정확성과 신뢰성, 윤리적 영향, 비판적 사고력을 저해할 수 있는 기술에 대한 과도한 의존성에 대한 신중한 고려가 필요하다. 따라서 의학교육 과정에 거대언어모델을 통합할 때 신중하게 접근할 필요가 있으며, 기술과 전통적인 학습 방법론 간의 균형이 필요하다. 이를 위해 본 논문은 근거 기반 거대언어모델 도입, 다학제 협업, 투명성, 인지 부하 개념 등을 강조하는 지침을 제시한다. 본 논문이 거대언어모델을 의학교육에 효과적으로 통합하기 위한 논의를 촉발하여 디지털 시대의 의료 전문가를 양성하는 데 도움이 될 것으로 기대한다.
Abstract
Rapid advances in artificial intelligence, particularly in natural language processing, are transforming medical education. Large language models (LLMs), which are capable of processing vast amounts of text and generating coherent, contextualized text, offer an unprecedented opportunity to enhance teaching and learning in medicine. This paper reviews the educational potential of LLMs and explores the potential challenges associated with their integration and use. LLMs can facilitate personalized learning experiences and support research by broadening access to a wide range of medical knowledge and streamlining literature reviews. They can also provide a dynamic and immersive educational experience through interactive learning environments that can mimic clinical settings. However, the integration of LLMs in medical education is not without its concerns. It is important to consider the accuracy and reliability of the information provided, the ethical implications, and the over-reliance on technology, which may affect the development of critical thinking skills. Therefore, the integration of LLMs into medical curricula must be approached with careful consideration, ensuring a harmonious balance between cutting-edge technology and traditional learning methodologies. To achieve this, this paper presents guidelines that emphasize the importance of adopting LLMs based on evidence-based reviews, fostering multidisciplinary collaboration, ensuring transparency, and effectively managing cognitive load. These recommendations aim to facilitate a discourse on the effective integration of LLMs into medical education, ultimately helping to prepare healthcare professionals for the challenges and opportunities of the digital age.
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