Cognitive Architectures and Human–AI Coevolution: Pathways, Dynamics, and Alignment

This document presents an original theoretical framework for understanding the coevolutionary dynamics between biological and artificial cognitive architectures. Authored by Faruk Alpay, the study proposes a systematic exploration of how cognitive systems—both human and AI—can evolve in tandem through structured interaction pathways, dynamic feedback loops, and emergent alignment mechanisms. The framework introduces conceptual models describing reciprocal influence patterns, adaptive learning convergence, and alignment stabilization over iterative cycles of coevolution. By formalizing these interaction dynamics, the study provides a foundational schema for designing future human–AI ecosystems that are mutually reinforcing, ethically sustainable, and strategically aligned with human development trajectories. Key contributions include:- A novel characterization of coevolutionary feedback processes between human cognition and artificial cognitive architectures.- The introduction of "alignment dynamics" as an emergent phenomenon rather than a static goal.- A proposed pathway-based model for recursive adaptation between biological and synthetic intelligence agents. This theoretical construction challenges static views of AI alignment by modeling it as a dynamic, co-evolving process rather than a one-time objective. It offers early structural proof that human and AI cognition can, under certain pathways and stability conditions, converge toward ethically aligned cooperative evolution. Note:The full document is currently under restricted access to ensure responsible dissemination. Only the descriptive metadata is publicly visible at this time. Unauthorized commercial use and derivative modifications are prohibited under the selected Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license. Publication Date: 2025-04-29Author: Faruk Alpay (ORCID: 0009-0009-2207-6528) Correspondence: [email protected]