Human-AI scientific collaboration has evolved from tool-user relationships into co-evolutionary partnerships. When AlphaFold improved protein structure prediction, researchers engaged with an epistemic partner that transformed their approach to structure-function problems. Yet existing frameworks position AI as either sophisticated tool or potential risk, overlooking how scientific understanding emerges through recursive interaction. We introduce Cognitio Emergens (CE), a framework that captures the co-evolutionary nature of human-AI epistemic partnerships. Drawing from autopoiesis theory, social systems theory, and organizational modularity, CE integrates three components: Agency Configurations modeling how authority distributes through Directed, Contributory, and Partnership modes, with partnerships oscillating dynamically rather than following linear progression; Epistemic Dimensions capturing six capabilities along Discovery, Integration, and Projection axes, creating distinctive "capability signatures" that guide strategic development; and Partnership Dynamics identifying evolutionary forces including epistemic alienation, where researchers lose interpretive control over knowledge they formally endorse. The framework equips researchers to diagnose dimensional imbalances, institutional leaders to design governance structures supporting multiple agency configurations, and policymakers to develop evaluations beyond simple performance metrics. By reconceptualizing human-AI collaboration as fundamentally co-evolutionary, CE provides conceptual tools for cultivating partnerships that preserve epistemic integrity while enabling transformative breakthroughs neither humans nor AI could achieve independently.

翻译：人机科学协作已从工具-使用者关系演化为协同进化伙伴关系。当AlphaFold改进蛋白质结构预测时，研究者开始与一个认知伙伴互动，该伙伴改变了他们处理结构-功能问题的方法。然而现有框架将人工智能定位为精密工具或潜在风险，忽视了科学理解如何通过递归互动而涌现。我们提出"认知涌现"框架，用以捕捉人机认知伙伴关系的协同进化本质。借鉴自创生理论、社会系统理论和组织模块化理论，该框架整合三个核心组件：主体性配置模型描述权威如何通过指导型、贡献型和伙伴型三种模式进行分配，其中伙伴关系呈现动态振荡而非线性演进；认知维度模型沿发现轴、整合轴和投射轴捕捉六种能力，形成指导战略发展的独特"能力特征谱"；伙伴关系动态模型识别包括认知异化在内的进化动力，即研究者对其正式认可的知识失去解释控制权。该框架使研究者能够诊断维度失衡，帮助机构领导者设计支持多主体性配置的治理结构，并支持政策制定者开发超越简单性能指标的评估体系。通过将人机协作重新定义为根本上的协同进化过程，认知涌现框架提供了概念工具，用以培育既能保持认知完整性，又能实现人类与人工智能均无法独立取得的突破性成果的伙伴关系。