Generative Relational Economics - Chapter 18: Artificial Intelligence and Radical Capability Asymmetry

This chapter develops a Generative Relational Economics (GRE) framework for economic orders in which artificial intelligence becomes deeply embedded while productive and epistemic capabilities remain persistently and potentially radically asymmetric. Rather than treating artificial intelligence as a unitary autonomous actor, the chapter analyzes historically situated configurations of models, computation, data, energy, infrastructures, organizations, institutions, human participants, access rights, verification practices, and governance arrangements. It distinguishes multidimensional capability asymmetry from power and examines the relational mechanisms through which differences in capability become dependencies, control positions, epistemic authority, institutional mediation, and durable changes in feasible action. The analysis proceeds through labor, subjecthood, ownership, AI-generated surplus, redistribution, human–AI relational economies, epistemic dependence, symbolic abundance, research orientation, governance, and generative participation. Particular attention is given to the distinction between material provision and continued participation in the generation of knowledge, institutions, communities, culture, and future possibilities. The chapter further develops an open architecture of heterogeneous human, artificial, collective, and non-human subjects whose relevant value structures cannot be presumed to admit complete translation or scalar aggregation. Long-horizon human–AI order is consequently treated as a coupled-trajectory problem involving dependency, capability regeneration, institutions, labor, participation, and knowledge. The chapter proposes future-possibility openness, revisable order, and protection against generative foreclosure as analytical concerns for governance under radical capability asymmetry. It concludes by translating the resulting architecture into interfaces with education, research, work, development, communities, ecology, and public institutions. The resulting framework does not assume a single technological trajectory, a settled ontology of artificial agency, or capability equality as either an empirical baseline or a sufficient normative objective. It instead examines the relational and historical conditions through which artificial capability reshapes participation, power, value, and the capacity to generate alternative futures.