Science and Artificial Science: From Human-AI Collaboration to Coupled Knowledge Dynamics
Abstract
Artificial intelligence is moving from an external tool of scientific research toward an internal participant in knowledge production. Mathematics is among the first disciplines in which this transition has become visible. In 2026, Terence Tao publicly described AI as a practically useful research tool in mathematics and theoretical physics; later, together with twenty-four other Fields Medalists, he signed “A Severe Misalignment of AI in Mathematics,” warning that an AI culture centered on rapid problem solving could weaken mathematical understanding, intellectual transmission, and the training of future mathematicians. He subsequently highlighted the Foundation for Science and AI Research (SAIR) and its effort to develop open scientific AI infrastructure. We interpret this sequence not as a contradiction, but as evidence that human science and artificial intelligence are moving from a tool relation toward a coupled relation.On this basis, the paper distinguishes three levels: science using AI, science jointly produced by humans and AI, and Artificial Science - the science of artificially constructed knowledge-generating systems. We then introduce Coupled Knowledge Dynamics as a framework for the co-evolution of human science and artificial science. Two conceptual quantities are proposed: cognitive position p, describing where artificial cognition is located within scientific practice, and cognitive momentum q, describing how artificial science drives changes in the…
Read the paper
Related studies
- Quantum dots: synthesis, bioapplications, and toxicity
- A Guide to In Silico Drug Design
- Quantum Computing for Healthcare: A Review
- Automated in Silico Design of Homogeneous Catalysts
- Identification of Novel 3-Hydroxy-pyran-4-One Derivatives as Potent HIV-1 Integrase Inhibitors Using in silico Structure-Based Combinatorial Library Design Approach
- In silico structural elucidation of RNA-dependent RNA polymerase towards the identification of potential Crimean-Congo Hemorrhagic Fever Virus inhibitors
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.