The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap

This paper argues that scientific knowledge represents a local optimum rather than global truth. Using machine learning analogies, researchers show how historical accidents, cognitive path-dependency, and institutional lock-in shape scientific frameworks across mathematics, physics, chemistry, and biology. Three interconnected mechanisms—cognitive, formal, and institutional—limit scientific discovery.