The Civilizational Epistemic Attractor: Artificial Intelligence, Authority Without Command, and the Formation of Humanity's Future

The long-run social significance of artificial intelligence may not depend on whether AI acquires consciousness, sovereignty, or the capacity to command human beings. A different possibility deserves attention. As AI systems become increasingly capable in the breadth of knowledge they can access, the speed with which they can retrieve it, the quality of their reasoning, and the scope of their cross-domain advice, individuals and institutions may voluntarily assign greater weight to AI judgments under uncertainty. AI may thereby migrate from tool to advisor, from advisor to epistemic authority, from authority to directional mediator, and, in the limiting case, contribute to the emergence of a civilizational-scale structure of cognitive attraction. This paper defines such a possible relational social structure as a \textbf{Civilizational Epistemic Attractor (CEA)}: an emergent configuration in which large numbers of decentralized individuals and institutions, through repeated and voluntary epistemic deference to a shared class of AI systems, become systematically more likely to organize their judgments about what is true, possible, plausible, and worth pursuing around correlated AI-mediated reference points, without centralized command or a formal transfer of sovereignty. The paper develops a five-level model of AI's social-role migration: instrument, epistemic advisor, epistemic authority, directional mediator, and civilizational epistemic attractor. It then introduces \textbf{authority without command} as the micro-level mechanism linking perceived epistemic superiority to voluntary deference; distinguishes formal decision rights from substantive epistemic influence; defines the \textbf{collective possibility space} to capture the set of futures a society is able to identify, articulate, seriously evaluate, and potentially actualize; and develops a dynamic chain from distributed deference to correlated judgment, collective direction formation, and recursive path dependence. The framework also emphasizes that epistemic convergence can coexist with personalized interpretive fragmentation, and that high-quality advice at the individual level need not aggregate into socially desirable outcomes. The paper does not claim that the fifth-level structure is inevitable, nor that AI will become an absolute authority. Its purpose is to provide a conceptually distinct and eventually testable framework for a possible civilizational-scale relational structure.