中国科技期刊研究 ›› 2024, Vol. 35 ›› Issue (7): 890-898. doi: 10.11946/cjstp.202403150235

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生成式人工智能重塑科技期刊产业的影响、挑战及应对策略研究

陈晓峰1,2)()(), 沈锡宾3,4),*()()   

  1. 1) 湖北省科技信息研究院《科技进步与对策》编辑部,湖北省武汉市武昌区洪山路2号 430071
    2) 武汉理工大学计算机与人工智能学院,湖北省武汉市洪山区珞狮路122号 430070
    3) 中华医学会杂志社新媒体部,北京市西城区东河沿街69号 100052
    4) 国家新闻出版署医学期刊知识挖掘与服务重点实验室,北京市西城区东河沿街69号 100052
  • 收稿日期:2024-03-15 修回日期:2024-05-10 出版日期:2024-07-15 发布日期:2024-08-02
  • 通讯作者: 沈锡宾
  • 作者简介:

    陈晓峰(ORCID:0000-0003-3598-695X),硕士,副研究员,E-mail:

    作者贡献声明: 陈晓峰:设计论文框架,收集资料,撰写论文; 沈锡宾:审定论文框架,修改论文。
  • 基金资助:
    2023年度中国科协科技期刊有关项目“大模型技术对中国科技期刊发展的影响分析及对策”(2023KJQK012); 中国科学技术期刊编辑学会2023—2024年度基金项目“生成式人工智能冲击下科技期刊的应对策略研究”(CESSP-2023-A02)

Impact, challenges, and coping strategies of generative artificial intelligence in reshaping scientific journal industry

CHEN Xiaofeng1,2)()(), SHEN Xibin3,4),*()()   

  1. 1) Editorial Office of Science & Technology Progress and Policy, Hubei Academy of Scientific and Technical Information, 2 Hongshan Road, Wuchang District, Wuhan 430071, China
    2) School of Computer Science and Artificial Intelligence, Wuhan University of Technology, 122 Luoshi Road, Hongshan District, Wuhan 430070, China
    3) New Media Department, Chinese Medical Association Publishing House, 69 Dongheyan Street, Xicheng District, Beijing 100052, China
    4) Key Laboratory of Knowledge Mining and Service for Medical Journals, National Press and Publication Administration, 69 Dongheyan Street, Xicheng District, Beijing 100052, China
  • Received:2024-03-15 Revised:2024-05-10 Online:2024-07-15 Published:2024-08-02
  • Contact: SHEN Xibin

摘要:

【目的】 探讨生成式人工智能给科技期刊业带来的影响与挑战,分析不同利益相关者的诉求与风险,提出科技期刊业应对生成式人工智能挑战的关键举措。【方法】 基于文献综述梳理生成式人工智能在科技期刊业应用的最新进展,构建“需求—风险”二维分析框架,对不同应用场景进行分类评估;采用利益相关者分析法,多维解构生成式人工智能对作者、编辑、审稿人、读者等主体的影响;借鉴国内外经验教训,从前瞻政策、技术创新、服务升级、人才培养、伦理治理等方面系统提出推进科技期刊业智能化转型的对策建议。【结果】 当前生成式人工智能已广泛应用于科技期刊选题策划、学术写作、同行评议、编辑出版、学术传播等环节,极大提升行业智能化水平,但也带来内容同质化、学术造假等问题隐患。不同利益相关者对生成式人工智能的诉求各异,既有效率提升、成本节约等普遍需求,也面临版权侵权、职业替代、伦理失范等风险挑战。【结论】 生成式人工智能正驱动科技期刊业态重塑,亟须统筹布局、多管齐下,在加快关键技术创新应用的同时,注重人才培养和伦理规范,促进人机协同,构建开放共享、合作共赢的融合发展新生态,推动行业创新发展。

关键词: 生成式人工智能, 科技期刊产业, 融合发展, 应用场景, 应对策略

Abstract:

[Purposes] This study aims to explore the impact and challenges brought by generative artificial intelligence (AI) on the scientific journal industry, analyze the demands and risks of different stakeholders, and propose strategies for the industry to address the challenges of generative AI. [Methods] Based on a literature review, we analyzed the latest progress in the application of generative AI in the scientific journal industry and constructed a two-dimensional analysis framework of "demand-risk" to classify and evaluate different application scenarios. Additionally, stakeholder analysis was conducted to deconstruct the multi-dimensional impact of generative AI on authors, editors, reviewers, readers, and other entities. Drawing on domestic and international experiences, we put forward systematic suggestions to promote the intelligent transformation of the scientific journal industry from several aspects: forward-looking policies, technological innovation, service upgrades, talent cultivation, and ethical governance. [Findings] At present, generative AI has been widely applied in various aspects of the scientific journal industry, including topic selection, academic writing, peer review, editing, and dissemination, greatly promoting the industry to be more intelligent. However, it has also brought problems such as content homogenization and academic misconduct. As for stakeholders, different stakeholders have different demands for generative AI. While they share common needs such as efficiency improvement and cost savings, they also face risks from copyright infringement, job replacement, and ethical misconduct. [Conclusions] As generative AI is reshaping the scientific journal industry, it is imperative to implement overall planning and multiple measures. While accelerating the innovative application of key technologies, the industry should pay attention to talent cultivation and ethical regulations to promote human-machine collaboration, building a new ecosystem of integrated development that is open, shared, and mutually beneficial, thereby promoting the innovative development of the industry.

Key words: Generative artificial intelligence, Scientific journal industry, Integrated development, Application scenario, Strategy