图书馆杂志

图书馆杂志 ›› 2025, Vol. 44 ›› Issue (410): 17-26.

• 信息素养论坛 • 上一篇    下一篇

中外人工智能素养框架研究

余维杰 郑梦婷 张颖(中山大学信息管理学院)   

  • 出版日期:2025-06-15 发布日期:2025-07-02
  • 作者简介:

    余维杰 中山大学信息管理学院,副教授。研究方向:数字素养、智能信息处理等。作者贡献:选题策划、论文撰写与修改。E-mail: yuweijie6@mail.sysu.edu.cn 广东广州 510006

    郑梦婷 中山大学信息管理学院,硕士研究生。研究方向:人工智能素养。作者贡献:资料收集与分析、论文撰写。 广东广州 510006

    张 颖 中山大学信息管理学院,硕士研究生。研究方向:人工智能素养。作者贡献:资料收集与分析、论文撰写。 广东广州 510006

Research on Artificial Intelligence Literacy Frameworks in China and Abroad

Yu Weijie, Zheng Mengting, Zhang Ying (School of Information Management, Sun Yat-sen University)   

  • Online:2025-06-15 Published:2025-07-02
  • About author:Yu Weijie, Zheng Mengting, Zhang Ying(School of Information Management, Sun Yat-sen University)

摘要:

当下人工智能技术深度融合社会发展,人工智能素养已成为数智时代公民必备的核心素养。本研究基于国内外权威机构及学术期刊的数据源,综合运用网络调研法与内容分析法,系统解构40 种代表性人工智能素养框架,揭示其共性要素及差异化特征。研究发现:框架核心内容可归纳为“认知—技能—应用—创新—伦理”五大维度,整体呈现出技术导向、工具驱动、创新拓展与伦理关切的共性特点;国内框架更强调系统性知识构建,注重思维培养、技术应用和风险规避;而国外框架更关注价值判断与社会影响,突出技能发展、内容创造和主动治理。研究提出搭建均衡内容体系、强化动态更新机制、注重全球视野与本土适配的框架完善建议,为我国人工智能素养框架的更新拓展提供参考依据。

Abstract:

As artificial intelligence (AI) technologies become deeply integrated into societal development, AI literacy has become a core competency essential for citizens in the digital and intelligent era. This study systematically deconstructs 40 representative AI literacy frameworks using data sources from domestic and international institutions and academic journals, employing web-based research and content analysis to identify the common elements and distinctive characteristics. The findings indicate that the core components of these frameworks can be categorized into five key dimensions: cognition, skills, application, innovation, and ethics, collectively characterized by technology orientation, tooldriven approaches, innovation expansion, and ethical awareness. Domestic frameworks prioritize systematic knowledge development, cognitive training, technology application, and risk avoidance, while international frameworks focus more on value judgment and social impact, skill cultivation, content creation, and proactive governance. The study concludes with recommen dations for improving AI literacy frameworks, including establishing a balanced content system, strengthening mechanisms for dynamic update, and integrating global perspectives with local relevance. It aims to provide reference for the evolution of China’s AI literacy frameworks.