Neuroplasticity in Human-AI Integration: A Contribution to Symbiotic Intelligence Theory

Document Type : Research Paper

Author

Visting Distinguised Professor, School of Education, Tsinghua University

10.22034/jpiut.2026.74244.4683

Abstract

The accelerating convergence of human cognition and artificial intelligence demands new conceptual frameworks that move beyond augmentation toward genuine integration. This paper positions neuroplasticity—the brain's lifelong capacity to reorganize neural structure and function through experience—as the central biological mechanism enabling deep human-AI symbiosis. The analysis argues that sustained, reciprocal interaction with advanced AI systems can induce targeted neuroplastic changes that allow human cognition to extend into artificial substrates, while AI architectures adapt in response to human neural patterns. Drawing on cognitive neuroscience, brain-computer interface research, extended mind theory, and postdigital philosophy, the paper develops a contribution to symbiotic intelligence theory. In this framework, symbiotic intelligence emerges as a hybrid, co-evolutionary system in which human and artificial intelligences mutually reshape one another through reciprocal plasticity, producing cognitive capabilities that exceed what either system can achieve alone. The analysis examines how intentional design of AI interfaces, feedback loops, and educational practices can harness neuroplasticity to support ethical and effective integration, while addressing risks of cognitive dependency, identity transformation, and epistemic inequity. The paper concludes by outlining implications for pedagogy, cognitive enhancement, and the governance of hybrid intelligence in the emerging era of artificial superintelligence.

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