The Architecture of Cognitive Amplification: Enhanced Cognitive Scaffolding as a Resolution to the Comfort-Growth Paradox in Human-AI Cognitive Integration
Giuseppe Riva

TL;DR
This paper proposes Enhanced Cognitive Scaffolding, a framework that transforms AI from a mere tool into a dynamic mentor, promoting ongoing cognitive growth and addressing the comfort-growth paradox in human-AI integration.
Contribution
It introduces a novel framework combining progressive autonomy, adaptive personalization, and cognitive load optimization to foster genuine cognitive development in human-AI systems.
Findings
Accelerated skill acquisition across domains
Improved self-regulation and higher-order thinking
Safeguards against dependency and bias
Abstract
AI systems now function as cognitive extensions, evolving from tools to active cognitive collaborators within human-AI integrated systems. While these systems can amplify cognition - enhancing problem-solving, learning, and creativity - they present a fundamental "comfort-growth paradox": AI's user-friendly nature may foster intellectual stagnation by minimizing cognitive friction necessary for development. As AI aligns with user preferences and provides frictionless assistance, it risks inducing cognitive complacency rather than promoting growth. We introduce Enhanced Cognitive Scaffolding to resolve this paradox - reconceptualizing AI from convenient assistant to dynamic mentor. Drawing from Vygotskian theories, educational scaffolding principles, and AI ethics, our framework integrates three dimensions: (1) Progressive Autonomy, where AI support gradually fades as user competence…
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