随着人工智能的快速发展，以人工智能为驱动的科学范式应运而生，并在多个领域的科研创新过程中得到了有效应用，推动科学研究的高质量发展。与此同时，由于人工智能模型存在科学知识体系受限、可解释性缺乏，以及结果失真等问题，导致人工智能驱动下的科学范式面临着相应的挑战。在这种情况下，应通过深化人智协同的科研工作模式、加快发展可解释的人工智能模型、建立健全面向人工智能模型的工作机制，从而应对人工智能驱动下科学范式遇到的挑战，推动人工智能驱动下科学范式的发展。

The rapid development of artificial intelligence (AI) technology has precipitated the emergence of AI driven scientific paradigms, which have been efficaciously employed in the domains of scientific research and innovation across numerous fields. This has promoted the high-quality development of scientific research. Concurrently, the scientific paradigm driven by artificial intelligence faces corresponding challenges due to the problems of limited scientific knowledge system, lack of interpretability, and distortion of results in artificial intelligence models. In this situation, it is necessary to deepen the research work model of human-intelligence collaboration, accelerate the development of interpretable artificial intelligence models, and establish and improve the working mechanisms specifically for these artificial intelligence models. These measures will address the challenges faced by the scientific paradigm driven by artificial intelligence and promote the development of the scientific paradigm under the influence of artificial intelligence.