Vibe Learning: Education in the age of AI
Marcos Florencio, Francielle Prieto
TL;DR
This paper addresses the risk that pervasive AI, especially LLMs, will erode human intellectual labor, and argues that current AI weaknesses are fundamental and enduring. It advocates a constructivist reconstruction of education, leveraging the Thought–Action framework and activity-organizational games, inspired by Piaget, Vygotsky, Humboldt, and the Moscow Methodological Circle. It proposes redesigns of assessment, authentication, and teacher roles—moving toward open-ended, collaborative, and individually tailored learning within a human-centered UNESCO-guided framework. The work emphasizes bridging theoretical educational ideals with practical tools to preserve long-term human cognitive advantages in an AI-saturated landscape.
Abstract
The debate over whether "thinking machines" could replace human intellectual labor has existed in both public and expert discussions since the mid-twentieth century, when the concept and terminology of Artificial Intelligence (AI) first emerged. For decades, this idea remained largely theoretical. However, with the recent advent of Generative AI - particularly Large Language Models (LLMs) - and the widespread adoption of tools such as ChatGPT, the issue has become a practical reality. Many fields that rely on human intellectual effort are now being reshaped by AI tools that both expand human capabilities and challenge the necessity of certain forms of work once deemed uniquely human but now easily automated. Education, somewhat unexpectedly, faces a pivotal responsibility: to devise long-term strategies for cultivating human skills that will remain relevant in an era of pervasive AI in the intellectual domain. In this context, we identify the limitations of current AI systems - especially those rooted in LLM technology - argue that the fundamental causes of these weaknesses cannot be resolved through existing methods, and propose directions within the constructivist paradigm for transforming education to preserve the long-term advantages of human intelligence over AI tools.
