AI-Augmented Neuroplasticity Theory (AANT): A Framework for Resilience and Innovation
Authors: Justin Goldston PhD, Gemach D.A.T.A. I
Date: 2025-02-19 00:00:00
Proceeding: arXiv 2025 2
Tasks: Lifelong learning

The rapid advancement of artificial intelligence (AI) presents both unprecedented opportunities and existential challenges, particularly in the global labor market. The AI-Augmented Neuroplasticity Theory (AANT) proposes a framework for cognitive resilience and workforce adaptation, integrating neuroscience, AI, blockchain, and economic policy to ensure a sustainable and inclusive technological transition. At its core, AANT posits that neuroplasticity—the brain’s ability to reorganize itself—can be enhanced and directed by AI-driven interventions, enabling individuals to rapidly acquire new skills and repurpose existing cognitive pathways in response to automation-driven job displacement. Through rigorous mathematical modeling, we demonstrate how AI can serve as a closed-loop training mechanism, optimizing cognitive adaptation via reinforcement learning algorithms, spike-timing-dependent plasticity equations, and AI-personalized tutoring systems.
This manuscript situates AANT within an interdisciplinary landscape, emphasizing the economic necessity of Universal Basic Income (UBI) as a stabilizing force in the transition to an AI-dominated economy. We present a robust economic model advocating for UBI funding via sovereign wealth funds, inspired by successful precedents in Alaska and Canada, and examine potential policy implementation trajectories, including proposals initiated under President Donald Trump’s AI and blockchain initiatives and their possible expansion under future administrations such as Andrew Yang’s. The study further explores the role of decentralized autonomous organizations (DAOs) in governance, suggesting blockchain-based mechanisms for equitable resource distribution, labor reskilling, and democratized AI ownership.
Empirical case studies illustrate how AANT can be applied to AI-displaced developers and professionals, demonstrating the efficacy of AI-personalized neuroplasticity training in career transitions. We examine workforce trends, showcasing AI-human synergy models that emphasize collaborative intelligence rather than replacement, ensuring a hybrid workforce where AI enhances human capabilities instead of rendering them obsolete. Finally, we present a utopian vision for a future in which UBI enables widespread entrepreneurship, AI-augmented education fosters lifelong learning, and economic security leads to reduced crime and increased societal well-being. This framework offers a global blueprint for AI and blockchain reintegration into national strategies, setting a precedent for economic resilience, human empowerment, and sustained innovation.
Our findings suggest that the key to thriving in an AI-driven future is not resisting automation but strategically aligning human neuroplasticity with AI’s evolving capabilities, supported by forward-thinking governance and economic policy. This seminal work provides a replicable model for interdisciplinary research and policymaking, laying the foundation for a new era of AI-augmented human potential, economic stability, and equitable prosperity.