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May 8, 2025
The generation of scientific knowledge is undergoing a fundamental transformation. Humans and AI are evolving beyond the pure tool-user relationship to become co-evolutionary, epistemic partners. Examples like AlphaFold in protein structure prediction illustrate how AI systems are changing the way researchers think and their understanding of fundamental relationships.
But how can this new form of collaboration be adequately described and understood? Existing models often focus on static role distributions or narrowly defined metrics. They thus miss the dynamics with which scientific understanding emerges over time through recursive human-AI interaction.
The "Cognitio Emergens" (CE) concept offers a new framework for capturing the complex interactions in human-AI collaboration. CE integrates three core components:
Agency Configurations: These describe the distribution of authority between humans and AI. Three configurations are distinguished: "Controlled" (human dominated), "Contributing" (AI supported), and "Partnership" (equal collaboration). Importantly, partnerships dynamically oscillate between these configurations and do not follow a linear progression.
Epistemic Dimensions: This captures six specific abilities that emerge through collaboration along the axes of "Discovery," "Integration," and "Projection." These abilities form characteristic "ability signatures" that guide the development of the partnership.
Partnership Dynamics: This component identifies the forces that shape the development of the human-AI relationship. A particular risk is "epistemic alienation," in which researchers lose interpretive control over the knowledge they formally generate.
CE draws on theories of autopoiesis, social systems, and organizational modularity. It shows how knowledge co-creation arises through continuous negotiation of roles, values, and organizational structures.
By viewing scientific collaboration between humans and AI as fundamentally co-evolutionary, CE offers a balanced perspective. Neither is the role of AI uncritically celebrated nor unnecessarily feared. Instead, CE provides conceptual tools for designing partnerships that ensure meaningful human participation while enabling transformative scientific breakthroughs.
The future of knowledge generation lies in the effective design of these human-AI partnerships. CE offers a valuable framework for understanding and leveraging the associated challenges and opportunities.
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