认知涌现：人类与AI知识共创中的能动性、维度与动态机制

Cognitio Emergens: Agency, Dimensions, and Dynamics in Human-AI Knowledge Co-Creation

May 6, 2025

作者: Xule Lin

cs.AI

摘要

随着人类与AI系统从工具使用关系发展为协同进化的认知伙伴关系，科学知识创造正在发生根本性变革。当AlphaFold彻底改变蛋白质结构预测领域时，研究人员描述了他们如何与一个重塑其基础关系认知的认知伙伴进行互动。本文引入"涌现认知"(Cognitio Emergens, CE)框架，该框架针对现有模型的局限性，这些模型关注静态角色或狭隘指标，却未能捕捉科学理解如何通过递归的人机交互随时间涌现。CE整合了三个解决这些局限的组件：描述权威在人类与AI之间如何分配的"主体配置"(Directed, Contributory, Partnership)，其中伙伴关系在配置间动态振荡而非线性发展；捕捉通过协作在发现、整合和预测三个维度上涌现的六种具体能力的"认知维度"，形成指导发展的独特"能力特征"；以及识别塑造这些关系演变力量的"伙伴关系动力学"，特别是研究人员可能失去对其正式认可知识的解释控制权的"认知异化"风险。借鉴自创生理论、社会系统理论和组织模块化理论，CE揭示了知识共创如何通过角色、价值观和组织结构的持续协商而涌现。通过将人机科学协作重新概念化为根本上的协同进化，CE提供了一个平衡的视角，既不盲目颂扬也不过度担忧AI的演变角色，而是提供了培育伙伴关系的概念工具，在保持人类有意义参与的同时，实现变革性的科学突破。

English

Scientific knowledge creation is fundamentally transforming as humans and AI systems evolve beyond tool-user relationships into co-evolutionary epistemic partnerships. When AlphaFold revolutionized protein structure prediction, researchers described engaging with an epistemic partner that reshaped how they conceptualized fundamental relationships. This article introduces Cognitio Emergens (CE), a framework addressing critical limitations in existing models that focus on static roles or narrow metrics while failing to capture how scientific understanding emerges through recursive human-AI interaction over time. CE integrates three components addressing these limitations: Agency Configurations describing how authority distributes between humans and AI (Directed, Contributory, Partnership), with partnerships dynamically oscillating between configurations rather than following linear progression; Epistemic Dimensions capturing six specific capabilities emerging through collaboration across Discovery, Integration, and Projection axes, creating distinctive "capability signatures" that guide development; and Partnership Dynamics identifying forces shaping how these relationships evolve, particularly the risk of epistemic alienation where researchers lose interpretive control over knowledge they formally endorse. Drawing from autopoiesis theory, social systems theory, and organizational modularity, CE reveals how knowledge co-creation emerges through continuous negotiation of roles, values, and organizational structures. By reconceptualizing human-AI scientific collaboration as fundamentally co-evolutionary, CE offers a balanced perspective that neither uncritically celebrates nor unnecessarily fears AI's evolving role, instead providing conceptual tools for cultivating partnerships that maintain meaningful human participation while enabling transformative scientific breakthroughs.