AI 赋能社会科学研究过程的变革

A Study on the AI-empowered Transformation of Social Science Research Process

随着人工智能技术的快速发展,社会科学研究正经历着前所未有的变革。文章探讨了AI如何赋能社会科学研究过程的各环节,基于研究过程新技术、新关联、新模式,进一步论述其带来的作用与转向。具体而言,首先分析了AI在学术资源获取、成果梳理、研究对象关联、研究主题产生和学术论文投稿等环节的渗透,揭示了AI技术如何提升研究效率、拓宽研究视野,并促进研究主体的多元化和创新能力的提升。然后,辩证分析了AI赋能下社会科学研究过程面临的新挑战,包括价值观偏差和研究界限的模糊化等问题,并提出了对应的建议。最后,展望了AI驱动的社会科学研究转向,包括从解释导向到解决导向、从理论驱动到数据驱动、从方法细节到方法原理的转变,并探讨了实现这些转变的机制和路径。文章认为,AI技术将在尊重社会科学研究本质的基础上,进一步推动理论的创新、方法的革新以及实践的应用,为解决社会问题提供更加科学有效的方案。

With the rapid progression of artificial intelligence,social science research is experiencing an unparalleled transformation.This paper delves into how AI is invigorating various facets of the social science research through the incorporation of innovative technologies,newly-built correlations,and novel models,thereby elucidating the consequent effects and shifts.Specifically,this paper first evaluates how AI permeates key stages like the acquisition of academic resources,the organization of research findings,the linking of research subjects,the evolvement of research themes,and the submission of academic papers.It highlights that AI technologies amplify research efficiency,expand scholarly viewpoints,and foster the diversification and innovation capabilities of research subjects.Following this,the discussion takes a critical perspective on the challenges presented in the AI-empowered social science research process.Issues such as ethical discrepancies and the dilution of research boundaries are thoroughly examined.In response to these challenges,this paper proposes tailored recommendations to mitigate such concerns effectively.Lastly,this paper anticipates future trans-formations in social science research prompted by AI, including a shift from explanatory to solution-oriented approaches, from theory-heavy to data-driven frameworks, and from focusing on methodological specifics to embracing overarching methodological principles. The discussion elaborates on the potential mechanisms and pathways to facilitate these transitions, maintaining a strong emphasis on the core principles of social science research. This paper presents a robust argument that AI, while respecting the fundamental essence of social sciences, will catalyze theoretical innovation, methodological refreshment, and enhanced practical applications, thereby offering more scientifically robust solutions to societal challenges.