LLM × Human Cognition: Mapping the Frontiers of Artificial and Human Intelligence
Co-Cognition Lab is building a cognitive map that AI and humans can explore together — a panoramic survey of what we call the "truth universe": a systematic mapping of the terrain where human cognition and machine intelligence meet.
At its center is the Co-Cognition Map: What domains of knowledge remain siloed because their methodological paradigms are incompatible? Where can co-cognition provide unique epistemic value? This is a cross-disciplinary taxonomy and multi-dimensional scoring system, currently narrowing from 108 candidate domains.
LLM Intuition Research is the first anchor point on this map — four intuition subtypes, constitutive degradation, and the Human-First Protocol provide the theoretical foundation. Competition Landscape extends that framework into strategic analysis of the global LLM race — and doubles as a testable assertion, left for time to verify. The report contains 6 core theses, a degradation-risk ranking across 4 strategic trajectories, probability estimates for 8 future scenarios, and a dedicated China strategy analysis. If you only have 3 minutes, start with the theses and the scenario probability table.
While mapping the terrain, we identified a blind spot that cuts across all quadrants: human-AI cognitive collaboration under crisis and extreme conditions. The existing taxonomy didn't reach it — Crisis Cognition Collaboration exists to fill that gap.
One map, one anchor point, one field test, one gap filled — at every step, we return to the same question: In a world that increasingly relies on intelligent machines, where can human understanding still reach?
Preprint Available · OSF DOI: 10.17605/OSF.IO/XSY39 · CC BY 4.0
Our paper is now publicly available:
Co-Cognition Lab is a multi-project research collective investigating the interplay between large language models and human cognition. We build theoretical frameworks and practical tools to understand where human intuition augments AI capabilities—and where it remains irreplaceable.
Current research directions:
