用53个学术网红视频分析出AI辅助论文生产的标准化流程
Generative Knowledge Production Pipeline Driven by Academic Influencers
- 基于5.3万观众的视频数据，提炼出人机协同的知识生产流程
- 发现生成式AI可自动化出版流程并提升学术参与门槛
- 适合关注AI科研伦理与流程优化的研究者和政策制定者
生成式AI正重塑知识生产、验证与传播方式，引发学术诚信与可信度问题。本研究分析了53个学术影响力视频，累计观看量达530万次，识别出一种新兴的、结构化且可落地的生成式知识生产流程，该流程在保持原创性、符合伦理规范的同时，实现了人机协作的平衡。研究发现，生成式AI有潜力自动化出版工作流，并推动知识生产民主化，同时挑战传统科学规范。学术网红成为这一范式转型的关键中介，将基层实践与机构政策连接，增强适应性。为此，研究提出一个生成式出版生产流程及配套政策框架，以支持人机共智的适应与可信标准强化。这些发现有助于学者、教育工作者与政策制定者理解AI的变革影响，倡导负责任且创新驱动的知识生产。此外，还揭示了自动化最佳实践、优化学术工作流及激发学术研究与发表创造力的路径。
原文摘要 · Abstract (English)
Generative AI transforms knowledge production, validation, and dissemination, raising academic integrity and credibility concerns. This study examines 53 academic influencer videos that reached 5.3 million viewers to identify an emerging, structured, implementation-ready pipeline balancing originality, ethical compliance, and human-AI collaboration despite the disruptive impacts. Findings highlight generative AI's potential to automate publication workflows and democratize participation in knowledge production while challenging traditional scientific norms. Academic influencers emerge as key intermediaries in this paradigm shift, connecting bottom-up practices with institutional policies to improve adaptability. Accordingly, the study proposes a generative publication production pipeline and a policy framework for co-intelligence adaptation and reinforcing credibility-centered standards in AI-powered research. These insights support scholars, educators, and policymakers in understanding AI's transformative impact by advocating responsible and innovation-driven knowledge production. Additionally, they reveal pathways for automating best practices, optimizing scholarly workflows, and fostering creativity in academic research and publication.
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