How AI is rewiring the human brain: the generational transformation of cognition and knowing

This Open Forum paper examines how artificial intelligence (AI) is transforming not only what humans know but how knowledge itself is constructed, remembered and valued. It argues that AI has evolved from a tool of efficiency into an epistemic infrastructure, a system that reframes cognition, morality and identity across generations. Using Rousseau’s concept of conscience, Heidegger’s enframing (Gestell), and Postman’s technopoly as lenses, the paper situates today’s cognitive transformation within a philosophical lineage from natural conscience to predictive cognition. It proposes that the rise of AI-mediated environments represents an epistemological rupture—a transition from embodied, effortful knowledge-making to instantaneous, machine-guided cognition. Tracing five generational cohorts from Baby Boomers to Generation Alpha, it identifies a widening gap between those who were relatively AI-independent to a generation that is developing interface-based cognition, with high dependence on AI learning environments. The implications are neurological as well as epistemological. Insights from neuroscience and cognitive psychology indicate that reliance on generative systems may weaken neural pathways linked to memory, reflection, and metacognitive control. The paper introduces the concept of epistemic sovereignty—the capacity to author knowledge independently—and argues that its erosion signals not diminished intelligence but diminished authorship. As analogue generations disappear, so too may the brains unshaped by algorithmic mediation. Preserving their epistemic virtues will require deliberate design and regulation of learning environments that restore friction, ambiguity and cognitive struggle as essential features of human development. The paper calls for an epistemology of resistance—an intentional re-authoring of the mind in the age of artificial cognition. As such, this paper develops a discussion framework for cognitive sovereignty in AI-saturated environments and outlines strategic implications for education, work and policy.