From Augmentation to Substitution: Governing Human–AI Boundaries in Generative Ecosystems

Engineering notes

Engineering notes will be added by the aipentium editorial team.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为大语言模型、生成式AI、ChatGPT相关技术、计算机视觉、深度学习等高价值论文补充中文说明。

Original abstract

The rapid diffusion of generative AI is creating "forensic opacity" from synthetic images, driving an accelerating integrity crisis in academic publishing. The widespread adoption of AI as a cocreator has outpaced the editorial review process's verification capacity. This emergent study uses the theoretical perspectives of the AI Diffusion Triad and Service-Dominant Logic to explore the demarcation between human-AI augmentation and fraudulent substitution. We argue that the AI-driven productivity shock overwhelms the capacity of the traditional peer-review process. Undisclosed AI displacement of cognitive labor also shifts the ecosystem from value co-creation to value co-destruction, leading to a convergence toward template-like research generation. This ERF proposes an acceptance boundary framework and an empirical research agenda to identify the acceptable human/AI boundary and help re-establish trust and accountability in scholarly content generation.

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