From Homo Faber to Homo Resonans: A Kinetic Grid Model of Cognitive Agency and Attention Sovereignty in the Era of AI

Contemporary societies are characterized by an asymmetrical expansion of functional capacity alongside a persistent erosion of existential coherence. While existing frameworks have examined either the scarcity of attention in information-rich environments (e.g., Simon, 1971) or the problem of existential meaning (e.g., Frankl, 1946; Rosa, 2019), few accounts provide an integrated model linking cognitive resource allocation with value-based evaluation. This paper introduces the Kinetic Grid Model, a theoretical framework conceptualizing the human subject as a dynamic architecture of Functional Nodes (operational processing units), Validation Nodes (evaluative structures with core value) and Global Observer (central executive regulator), operating under finite temporal and attentional constraints. Within this model, meaningful experience is formally defined as resonance: a state of structural alignment between functional outputs and the system's internal value-core. Crucially, this framework addresses the cognitive challenges of the Artificial Intelligence era, where AI functions as an extrinsic, high-capacity functional mesh devoid of intrinsic validation. We argue that while AI exponentially accelerates functional accumulation, it simultaneously exacerbates the risks of cognitive dissipation and algorithmic hijacking. Consequently, the paper proposes the figure of Homo Resonans—in contrast to Hannah Arendt’s (1958) Homo faber—as an ontological model of agency oriented toward vectorial coherence and the defense of attention sovereignty, rather than mere instrumental production. Finally, potential empirical pathways are outlined, including experience-sampling of real-time alignment, experimental manipulation of value congruence, and neurocognitive correlates of resonant states. This model seeks to provide a conceptual basis for exploring testable propositions regarding motivation, meaning, and cognitive autonomy in increasingly automated environments. This article is a conceptual/theoretical contribution and does not report original empirical data.