「Resonant Economics」:Orchestration, Pain, and Generative Value Beyond the Age of Computation
Abstract
This paper presents Resonant Economics, a life-oriented economic framework developed in response to the structural limits of computation-centered economics in the AI era. As artificial intelligence increasingly automates calculation, optimization, and coordination, the foundational assumptions shared by neoliberal, Marxian, and Keynesian economics—rational optimization, labor-centered value, and demand management—lose their explanatory and normative sufficiency. The present crisis is therefore understood not as cyclical or technological, but ontological: a breakdown in how economic value itself is conceptualized. Building on historical analysis from the Great Depression to the contemporary AI economy, this paper proposes a generative economic ontology grounded in resonance, redefined not as harmony or consensus but as orchestration—the dynamic composition of heterogeneous actors, values, and temporalities. Within this framework, pain (tension, friction, and discomfort) is reinterpreted as a signal of phase difference and a necessary condition for generative value creation, rather than a cost to be eliminated. Trust is reconceptualized as relational durability: the capacity of economic systems to endure difference and strain without collapse. Profit is reframed as Ecosystem Surplus, a non-linear emergent value generated through sustained resonance among firms, workers, communities, and natural systems. This work intentionally presents a fully integrated theoretical framework, rather than a minimized journal-oriented version, in order to preserve its generative and ontological coherence. It is offered as a long-horizon contribution to economic thought, inviting historical, philosophical, and practical engagement beyond conventional disciplinary boundaries.
Fields of Study & Subjects
Interdisciplinary Studies: Technology
Society
and Humanities
Innovation
Sustainability
Human-Machine Systems
Digital Education and Society
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 January 2026
- Document type
- Preprint