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Abstract

This chapter argues that contemporary debates about artificial intelligence in education have become trapped between technological hype and apocalyptic fear, obscuring a more productive understanding of the relationship between humans and machines. Rather than accepting “artificial intelligence” as a replication of human cognition, the chapter proposes the concept of “cybersocial learning,” emphasizing the fundamentally different but mutually entangled learning processes of humans and computational systems. This is the basis for a more productive “AI literacy.” Drawing on philosophical, historical, cognitive science, and educational research traditions, the chapter critiques the discourse of “cognitive offloading” and the assumption that AI necessarily diminishes human intellectual capacity. Instead, it reframes Generative AI as a writing technology and feedback mechanism whose educational value depends on pedagogical design and human mediation. The chapter develops this argument through an analysis of the historical evolution of AI systems, an empirical examination of the CyberScholar platform, and a concluding manifesto outlining five calamities of unmediated AI alongside seven affordances for cybersocial learning. Across these discussions, we argue that our responsibility in education task is not to resist AI with nostalgic return to legacy teaching practices nor surrender to automation uncritically, but to design learning ecologies in which human agency, dialogue, multimodal meaning-making, recursive feedback, collaborative intelligence, metacognition, and productive diversity are enhanced through carefully calibrated human-machine relations.

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Losing Our Minds? Towards CyberSocial Solutions for the Problem of #AI*