人–AI 协作的演化动力学 v0.1:交互风格作为 SEI v1.4 与 ORBIT v1.3 框架下的选择压力

本文提出了一个基于演化视角的人–AI协作研究方法,将用户的交互风格视作对 GPT 的选择压力,探讨其对协作效率、微观残差修正(RCS-µ)、宏观认知单元(CAf)及组织共振(ORBIT)稳定性的影响。 通过结合 SEI v1.4 与 ORBIT v1.3 框架,并借助进化生物学和信息论的类比,本研究提出交互风格—认知演化假说,并展示如何通过 IDS、IDA 等指标进行量化与实验验证。 研究结果有助于理解不同用户行为模式对人–AI长期共演和协作质量的潜在影响,同时为高认知密度任务的协作指南和组织设计提供理论与实验依据。 This paper proposes an evolutionary perspective on human–AI collaboration, conceptualizing user interaction styles as selective pressures acting on GPT. We examine their effects on collaboration efficiency, micro-level residual correction (RCS-µ), macro-level cognitive units (CAf), and organizational resonance (ORBIT) stability. By integrating SEI v1.4 and ORBIT v1.3 frameworks, and drawing analogies from evolutionary biology and information theory, we introduce the “interaction style–cognitive evolution” hypothesis and demonstrate how metrics such as IDS and IDA can quantify and experimentally validate these effects. Our study provides insights into how different user behaviors influence long-term co-evolution and collaboration quality, offering theoretical and practical guidance for high cognitive density tasks and organizational design.