Can Technological Civilization Reproduce Itself? Artificial Intelligence, Human Knowledge, and the Reproductive Capacity of Civilization

Abstract

Modern civilization measures technological progress primarily by capability: what can be produced, computed, transported, cured, constructed, communicated, or automated. This paper argues that long-term technological resilience requires a second criterion: reproductive capacity — whether successive generations retain credible pathways for regenerating the knowledge, skilled people, tools, material and energy pathways, institutions, and teaching systems upon which essential technological capabilities depend. Existing scholarship separately examines automation-induced skill erosion, tacit knowledge, organizational forgetting, absorptive capacity, industrial commons, technological diffusion, and civilizational knowledge preservation. The present paper integrates these strands around a civilization-level question: Can technological civilization reproduce itself? The paper proposes Civilizational Technological Reproductive Capacity (CTRC) as the distributed capacity to regenerate essential technological capability across generations. Civilizational Knowledge Reproductive Capacity (CKRC) is treated as its knowledge-specific component. A Reproductive Gap distinguishes present operational capability from credible regenerative capability. A Civilizational Bootstrap Map (CBM) represents technical dependencies and recovery pathways. The revised framework adds a second dependency layer: advanced technologies also require a functioning civilizational substrate capable of sustaining specialization, institutions, education, health, logistics, and long-duration reconstruction. The paper therefore introduces the provisional concept of a Minimum Civilizational Support Threshold (MCST): the minimum combination of population, essential services, infrastructure, institutional coordination, resources, energy, and supporting capabilities required to sustain regeneration of a specified technology. This addition reveals a recursive problem. Advanced technologies support food systems, medicine, communications, logistics, energy, and institutional coordination; those systems in turn support the specialized people and organizations required to reproduce advanced technologies. Artificial intelligence can deepen such recursion if essential services become dependent on advanced compute, while also offering powerful tools for expert capture, simulation, teaching, and dependency mapping. A Technological Reproductive Resilience Profile (TRRP) is proposed as a multidimensional assessment framework, and a research agenda is offered for measuring both technological and civilizational support dependencies.