Cognitive Age: Observable Cognitive Independence in Human–System Interaction

This preprint introduces the concept of cognitive age, a theoretical framework for understanding and observing cognitive independence during human problem solving. Rather than treating cognition as a fixed individual trait, the paper defines cognitive age as a contextual and dynamic property of a person's interaction with a specific task. It reflects the degree to which an individual independently frames problems, engages with guidance, and progresses toward solutions. The framework distinguishes cognitive age from chronological age, intelligence quotient (IQ), and traditional educational assessment by focusing on observable patterns of reasoning rather than latent ability. It synthesizes insights from help-seeking behaviour, dynamic assessment, learning sciences, and developmental psychology to propose a set of interaction-based indicators that may support formative assessment without reducing cognition to a single score or diagnostic label. The paper argues that advances in generative AI make interaction-based measures of cognitive independence increasingly relevant for education, human–AI collaboration, and AI governance. It discusses how cognitive age could inform adaptive educational systems, AI-assisted learning environments, and future regulatory approaches while explicitly cautioning against its misuse as an institutional classification or replacement for existing measures of human capability. This work is intended as a conceptual foundation for future empirical research on cognitive development, human–AI interaction, educational technology, and responsible AI.